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Journal articles on the topic 'Bus travel'
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1
Li, X., W. Tu, S. Shen, Y. Yue, N. Luo, and Q. Li. "REVEALING SPATIAL VARIATION AND CORRELATION OF URBAN TRAVELS FROM BIG TRAJECTORY DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 12, 2017): 53–57. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-53-2017.
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With the development of information and communication technology, spatial-temporal data that contain rich human mobility information are growing rapidly. However, the consistency of multi-mode human travel behind multi-source spatial-temporal data is not clear. To this aim, we utilized a week of taxies’ and buses’ GPS trajectory data and smart card data in Shenzhen, China to extract city-wide travel information of taxi, bus and metro and tested the correlation of multi-mode travel characteristics. Both the global correlation and local correlation of typical travel indicator were examined. The results show that: (1) Significant differences exist in of urban multi-mode travels. The correlation between bus travels and taxi travels, metro travel and taxi travels are globally low but locally high. (2) There are spatial differences of the correlation relationship between bus, metro and taxi travel. These findings help us understanding urban travels deeply therefore facilitate both the transport policy making and human-space interaction research.
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Lang, Hong, Shiwen Zhang, Kexin Fang, Yingying Xing, and Qingwen Xue. "What Is the Impact of a Dockless Bike-Sharing System on Urban Public Transit Ridership: A View from Travel Distances." Sustainability 15, no. 14 (July 8, 2023): 10753. http://dx.doi.org/10.3390/su151410753.
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Recently, the rapid development of the bike-sharing system (BSS) has dramatically influenced passengers’ travel modes. However, whether the relationship between the BSS and public transit is competitive or complementary remains unclear. In this paper, a difference-in-differences (DID) model is proposed to figure out the impact of the dockless BSS (DBSS) on bus ridership. The data was collected from Shanghai, China, which includes data from automatic fare collection (AFC) systems, automatic vehicle location (AVL) systems, DBSS transaction data, and point-of-interest (POI) data. The research is based on the route-level, and the results indicate that shared bikes have a substitution impact on bus ridership. Regarding all the travel distance, each shared bike along the route leads to a 0.39 decrease in daily bus ridership on the weekdays, and a 0.17 decrease in daily bus ridership on the weekends, respectively, indicating that dockless shared bikes lead to a stronger decrease in bus ridership on weekends compared to weekdays. Additionally, the substitution effects of shared bikes on bus ridership gradually decays from 0.104 to 0.016 in daily bus ridership on weekends, respectively, with the increase in the travel distance within 0–3 km. This paper reveals that the travel distance of passengers greatly influences the relationship between the DBSS and public transit on the route level.
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Zhou, Fang, Jianhui Wu, Yan Xu, and Chi Yi. "Optimization Scheme of Tradable Credits and Bus Departure Quantity for Travelers’ Travel Mode Choice Guidance." Journal of Advanced Transportation 2020 (December 20, 2020): 1–8. http://dx.doi.org/10.1155/2020/6665161.
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To analyze the influence of tradable credits and bus departure quantity on travelers' travel mode choice, this study investigated car travel and bus travel as research objects and established a two-mode day-to-day travel mode choice model based on tradable credits and bus departure quantity. To improve the guiding effect of tradable credits and bus departure quantity, an optimization scheme of tradable credits and bus departure quantity was developed with the goal of minimizing the system total travel time of car travel and the system total comprehensive cost of bus travel. Taking a test transportation network as an example, the influence of no tradable credits scheme, tradable credits scheme, and tradable credits and bus departure quantity scheme on the travelers’ travel mode choice behavior was analyzed. The results showed that the tradable credits and bus departure quantity scheme could reduce the saturation of road traffic and improve bus service quality.
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Wu, Jianhui, Yuanfa Ji, Xiyan Sun, and Yan Xu. "Optimization Scheme of Fine Toll and Bus Departure Quantity for Bottleneck Congestion Management." Complexity 2021 (March 15, 2021): 1–10. http://dx.doi.org/10.1155/2021/5518502.
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This paper chooses car travel and bus travel as the research objects, establishes a dual-mode equilibrium model based on the bottleneck model, and compares the travel characteristics of the no-toll and fine-toll schemes. We find that the fine-toll scheme can eliminate the queuing time at the bottleneck, but it also increases the congestion risk cost of bus travel. In order to eliminate the queuing time at the bottleneck and reduce the congestion risk cost of bus travel without increasing the car travel cost and bus travel cost, we propose an optimization scheme of fine toll and bus departure quantity and analyze its travel characteristics theoretically. Through the numerical example, we calculate and analyze the equilibrium results of no-toll scheme, fine-toll scheme, and optimization scheme of fine toll and bus departure quantity. The results indicate that the optimization scheme of fine toll and bus departure quantity can help travelers to choose a reasonable travel mode and travel time to travel in the rush hour.
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Liu, Sha, Xiang Li, and Chuanni He. "STUDY ON DYNAMIC INFLUENCE OF PASSENGER FLOW ON INTELLIGENT BUS TRAVEL SERVICE MODEL." Transport 36, no. 1 (February 26, 2021): 25–37. http://dx.doi.org/10.3846/transport.2021.14343.
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To improve the service quality and convenience of bus travel services, this paper proposes the Intelligent Bus Travel Service Model (IBTSM). The IBTSM makes it possible to provide a travel strategy considering every aspect of bus travel, specifically, delay in the peak period arising from limited carrying-capacities of buses. A three-step approach was executed toward implementing the IBTSM. First, the bus travel-time was predicted using Long Short-Term Memory (LSTM). Next, the crowding level in the bus was evaluated using a fuzzy expert system, based on which a reasonable start-off time was planned, and the delay caused by large passenger flow was circumvented. The k-Nearest Neighbours (k-NN) algorithm was used to provide input data of passenger flow. In this study, the correlation between passenger flow variation and bus services was investigated to extend the provisions of the travel strategy to include start-off time scheduling and target bus selection, rather than only bus running-time estimation. The proposed model was evaluated using a bus in China as a case study, and its reliability and positive impact on promoting both the quality of bus services and development of intelligent travel were demonstrated.
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Liu, E. H., S. Tian, and Q. Chen. "Mechanism Research of Bus Dynamic Information Impact on the Commuter Travel Behavior." Applied Mechanics and Materials 743 (March 2015): 660–66. http://dx.doi.org/10.4028/www.scientific.net/amm.743.660.
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In this paper, according to the characteristics of the bus travel decision-making, the traffic behavior selection data in Nanjing were collected by designing traffic wishes questionnaires and a binary logit model was built on dynamic information service under the bus commuters travel route choice behavior of binary logit model. This paper analyses the effect by using the model parameter calibration including bus-taking time, bus congestion and personal information e.g. age and gender on the bus commuters travel route choice behavior. Studies have shown that public transport information are closely related to travel routes and travel activities, and bus commuters will make adjustments on travel route after obtaining travel information. Public transportation information can change the passengers’ state of participating in transportation and improve the level of the public transport system service in some ways.
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Xue, Lian, Dan Jie Zhao, and Gui Mei Liu. "Stochastic Simulation of Bus Traveling Time." Advanced Materials Research 186 (January 2011): 556–59. http://dx.doi.org/10.4028/www.scientific.net/amr.186.556.
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The development of the city's public transport system has an indispensable role to alleviate the pressure of urban roads. Bus travel time reliability is an important evaluation index of the bus operation service level. The simulation of bus travel time helps us understand the reliability of bus running time. In this paper, we use Monte Carlo stochastic simulation method to calculate the reliability of bus travel time. On this basis, we establish a model of the reliability of public transportation systems to research the reliability of bus travel time.
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Bai, Cong, Zhong-Ren Peng, Qing-Chang Lu, and Jian Sun. "Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes." Computational Intelligence and Neuroscience 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/432389.
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Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.
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Fitzpatrick, Kay, Karen Kuenzer, and Torsten Lienau. "Attitudes toward Intercity Bus Travel in Texas." Transportation Research Record: Journal of the Transportation Research Board 1557, no. 1 (January 1996): 64–71. http://dx.doi.org/10.1177/0361198196155700110.
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As required by the Intermodal Surface Transportation Efficiency Act of 1991, a percentage of each state's public transportation funds must be spent on intercity bus transportation development and support, unless the governor certifies intercity bus needs are being adequately met. A study was initiated to produce data necessary to define the current state of the intercity bus industry in Texas. To accomplish this objective, surveys were developed and distributed to the general population, bus riders, and bus companies in the state. A review of cities currently being served by the intercity bus industry was also made. General-population respondents indicated that they would be more likely to ride a bus if there were more express bus service, better station locations, and higher air and train fares. Bus riders indicated they would ride more often if there were improved security measures at stations and on buses, more leg room, more comfortable seats, adherence to schedules, and lower bus fares. Government-owned multimodal transportation facilities, operating subsidies for rural routes, and billboards and signs for advertising intercity service were suggested by bus companies as ways to aid the industry. The review of cities currently served by the intercity bus industry revealed that only 21 Texas cities with populations over 5,000 were further than 16.1 km (10 mi) from intercity bus service, and that most of these cities had access to transit service to an intercity bus stop.
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Chen, Qi, Yibo Yan, Xu Zhang, and Jian Chen. "Impact of Subjective and Objective Factors on Bus Travel Intention." Behavioral Sciences 12, no. 11 (November 19, 2022): 462. http://dx.doi.org/10.3390/bs12110462.
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Given the lack of quantitative descriptions on the interaction between psychological factors and the built environment in existing urban bus travel behavior, this study examines the simultaneous influences of the objective-built environment and subjective psychological factors on bus travel intentions. An empirical study on the influence path of bus travel intention was conducted using structural equation modeling. Then, personal attribute factors were introduced, and a linear regression model was used to explore the influence of behavioral intentions. This study uses 410 investigated samples from the residents in Zhengzhou, China. The findings proved that psychological factors play mediating roles between the travel environment and its impact on travel behaviors and confirms the validity of the description of the measurement variable with respect to the bus travel intentions proposed in the study. We also found that the retirement factor among the personal attribute factors could significantly affect bus travel intentions, which means that the retired group prefers to use buses for traveling. This study shows innovations in catching the intermediary effect of psychological factors between the built environment and travel behavior while also quantifying the effects of both subjective and objective factors when choosing bus travel.
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Zhang, Yanan, Hongke Xu, Qing-Chang Lu, and Xiaohui Fan. "Travel Time Reliability Analysis Considering Bus Bunching: A Case Study in Xi’an, China." Sustainability 14, no. 23 (November 23, 2022): 15583. http://dx.doi.org/10.3390/su142315583.
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Bus bunching occurring at stops has an unstable impact on bus travel time. In order to evaluate urban bus travel time effectively, the travel time reliability (TTR) addressing bus bunching is analyzed. This paper focuses on the delayed time caused by bus bunching in the dwelling process at bus stops and uses the coefficient of variation of time headway to evaluate the degree of bus bunching. Moreover, the travel time deviation (TTD) indicator and travel time on-time accuracy (OTA) model are proposed to evaluate the bus TTR. The proposed model is used to analyze 113 runs of a bus route in Xi’an city, China. Real-time GPS data are used to analyze the operation of each run from the origin to the destination stops. The results show that 74.34% of the runs are delayed. When the value of TTD is higher than |0.1|, 64.2% of runs are delayed with bus bunching. Based on the measuring of OTA in two situations, the value of TTR considering bus bunching is reduced by 20%. In addition, the number of stopping routes at peak periods has a significant impact on the occurrence of bus bunching. The research results would have practical implications for the operation and management of buses.
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Wu, Jianhui, Yuanfa Ji, Xiyan Sun, and Yan Xu. "Guidance Optimization of Travelers’ Travel Mode Choice Based on Fuel Tax Rate and Bus Departure Quantity in Two-Mode Transportation System." Journal of Advanced Transportation 2020 (January 12, 2020): 1–10. http://dx.doi.org/10.1155/2020/4190632.
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This aim of this study is to improve the guidance role of the fuel tax rate and bus departure quantity on travel mode choice. Car and bus travel are chosen as the research object, and a day-to-day evolution model of dual-mode network traffic flow (based on a stochastic user equilibrium model and the method of network tatonnement process) is established. Subsequently, a guidance optimization model of fuel tax rate and bus departure quantity is designed. This guidance optimization model is formulated to determine the comprehensive minimum value among system total travel time of car travel, system total comprehensive cost of bus travel, and the difference between the total operating cost of bus departure increment and the total amount of fuel tax levied on car travelers. Through numerical examples, the validity of this guidance optimization model is verified, and the influence of fuel tax rate and bus departure quantity on the traffic network is analyzed. The results show that a guidance optimization scheme based on fuel tax rate and bus departure quantity can help regulate the proportion of car travel and improve bus service quality.
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Zhang, Jianming, Jun Cai, Mengjia Wang, and Wansong Zhang. "An Estimation Method for Passenger Flow Volumes from and to Bus Stops Based on Land Use Elements: An Experimental Study." Land 13, no. 7 (July 2, 2024): 971. http://dx.doi.org/10.3390/land13070971.
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To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volumes from and to bus stops was constructed with land use elements between bus stop TAZs and the upstream and downstream collections of bus stop TAZs. Building upon this, the passenger flow volumes from and to 38 bus stops in the Xueyuan Square area of Dalian during weekday morning peak hours were taken as the experimental objects. The basic estimation models of two gravity sets corresponding to passenger flow volumes from and to bus stops were constructed using the bus travel generation based on the aggregation of area-based origin unit method and the bus travel distance impedance based on the probability density method. Finally, the reliability of the estimation method of passenger flow volumes from and to bus stops was verified by regression fitting between the surveyed values of passenger flow volume and the estimated values of the basic models. The results indicate that the fuzzy estimation and transformation of bus travel based on land use elements, which serves as a crucial lever for facilitating strategic alignment in transit-oriented development (TOD), can be effectively achieved by using the area-based origin unit method to aggregate bus travel generation and the probability density method to evaluate the bus travel distance impedance.
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Kurniawan, M. Rizki, Oky Dwi Nurhayati, and Kurniawan Teguh Martono. "Sistem Informasi Geografis Pencarian Lokasi Agen Bus dan Travel Terdekat di Kota Semarang Berbasis Mobile dengan Metode Dijkstra." Jurnal Teknologi dan Sistem Komputer 3, no. 2 (April 20, 2015): 302. http://dx.doi.org/10.14710/jtsiskom.3.2.2015.302-310.
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Nowadays, the mobility of people who travel to a place through road transportation is increasing, either private vehicle or public transportation services. By the high intensity of use the road transportation, especially the road transportation service in Semarang, in this cases are bus and travel, it makes the transportation service users often confused in determining transportation agency to be used, especially if user is in hurry. Therefore, transportation user need a mobile application that can provide bus or travel transportation agency locator services which nearby user location and provide destination route which is expected. The Bus and Travel agency – Based Applications Mobile Locator Using Dijkstra Method is the ultimate solution in the search of bus and travel agency in Semarang. The purpose of development this application is developing a search guidance system of bus and travel agency location which nearby user location that can provide an efficient route and save the time. The Bus and Travel agency – Based Applications Mobile Locator is implemented using ionic framework that runs on Android. Sqlite as the media storage of this, allows user to perform agency data management. In Addition, it is supported by the relevance of agency data which is obtained from Department of Transportation, Communication, and Information Central of Java and transportation magazine site. The use of Google Maps API supports search location using Dijkstra Method in search of bus and travel agency, that expected to facilitate the users find travel or bus agency as expected, and its information that’s already available.
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Yin, Zhenzhong, and Bin Zhang. "Bus Travel Time Prediction Based on the Similarity in Drivers’ Driving Styles." Future Internet 15, no. 7 (June 21, 2023): 222. http://dx.doi.org/10.3390/fi15070222.
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Providing accurate and real-time bus travel time information is crucial for both passengers and public transportation managers. However, in the traditional bus travel time prediction model, due to the lack of consideration of the influence of different bus drivers’ driving styles on the bus travel time, the prediction result is not ideal. In the traditional bus travel time prediction model, the historical travel data of all drivers in the entire bus line are usually used for training and prediction. Due to great differences in individual driving styles, the eigenvalues of drivers’ driving parameters are widely distributed. Therefore, the prediction accuracy of the model trained by this dataset is low. At the same time, the training time of the model is too long due to the large sample size, making it difficult to provide a timely prediction in practical applications. However, if only the historical dataset of a single driver is used for training and prediction, the amount of training data is too small, and it is also difficult to accurately predict travel time. To solve these problems, this paper proposes a method to predict bus travel times based on the similarity of drivers’ driving styles. Firstly, the historical travel time data of different drivers are clustered, and then the corresponding types of drivers’ historical data are used to predict the travel time, so as to improve the accuracy and speed of the travel time prediction. We evaluated our approach using a real-world bus trajectory dataset collected in Shenyang, China. The experimental results show that the accuracy of the proposed method is 13.4% higher than that of the traditional method.
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Lee, Gyeongjae, Sangho Choo, Sungtaek Choi, and Hyangsook Lee. "Does the Inclusion of Spatio-Temporal Features Improve Bus Travel Time Predictions? A Deep Learning-Based Modelling Approach." Sustainability 14, no. 12 (June 17, 2022): 7431. http://dx.doi.org/10.3390/su14127431.
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With the abundance of public transportation in highly urbanized areas, it is common for passengers to make inefficient or flawed transport decisions due to a lack of information. The exact arrival time of a bus is an example of such information that can aid passengers in making better decisions. The purpose of this study is to provide a method for predicting path-based bus travel time, thereby assisting accurate bus arrival and departure time predictions at each bus stop. Specifically, we develop a Geo-conv Long Short-term Memory (LSTM) model that (1) extracts subsequent spatial features through a 1D Convolution Neural Network (CNN) for the entire bus travel sequence and (2) captures the temporal dependencies between subsequences through the LSTM network. Additionally, this study utilizes additional variables that affect two components of bus travel time (dwelling time and transit time) to precisely predict travel time. The constructed model is then evaluated by the practical application to two bus lines operating in Seoul, Korea. The results show that our model outperforms three other baseline models. Two bus lines with different types of operation show different model performance patterns that are dependent on travel distance. Interestingly, we find that the variable related to the link of the stop location appears to play an important role in predicting bus travel time. We believe that these novel findings will contribute to the literature on transportation and, in particular, on deep learning-based travel time prediction.
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Yashiro, Ryosuke, and Hironori Kato. "Intermodal Connection of High-Speed Rail with Interregional Bus Services in Japan." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (September 10, 2020): 674–84. http://dx.doi.org/10.1177/0361198120949877.
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An intermodal transportation service consisting of high-speed rail (HSR) and an interregional bus service is one policy option for rural areas where interregional travel demand is too low to justify the construction of HSR. This study reviews current interregional bus services connecting with interregional rail, particularly HSR, in Japan, and analyzes the market potential for improving intermodal transportation by integrating HSR with an interregional bus service. It reviews the current interregional transportation network and related travel demand, including for air, rail, and bus. It also analyzes the connectivity of rail+bus intermodal transportation. The analysis showed poor connectivity of HSR and interregional bus services in Japan. Next, an interregional travel mode choice model is estimated with a nested-logit model using data from the Interregional Travel Survey 2010. Then, origin–destination pairs constituting the potential travel demand of the rail+bus option are identified using simple market analysis. This revealed that origin–destination pairs connecting prefectural cities along the Tohoku Shinkansen (HSR) with Kofu City could gain modal shift from other travel modes to rail+bus through improvement in the connection or introduction of a new interregional bus service connected with HSR. Expected changes in modal shares for rail+bus are estimated through a case study where a connection at the HSR station is hypothetically improved by a newly introduced interregional bus service. This suggests that improvements in connectivity at the HSR station could encourage the intermodal transportation service of rail+bus, even for areas not connected with the HSR network.
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Roza, Angelalia, Andy Mulya Rusli, and Mohamed Rehan Karim. "Analisis Reveal dan Stated Preference Terhadap Atribut Travel Time dan Travel Cost Pada Kompetisi Moda Bus dan Kereta Api: Studi Kasus Malaysia." Jurnal Rekayasa Sipil (JRS-Unand) 13, no. 1 (March 4, 2017): 13. http://dx.doi.org/10.25077/jrs.13.1.13-22.2017.
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Penelitian ini bertujuan untuk menganalisa kompetisi moda angkutan umum darat antarkota di negara berkembang seperti Malaysia, terkait atribut travel time dan travel cost. Kajian ini menjadi penting karena kebijakan infrastuktur di negara berkembang seperti realisasi double tracking project ETS di Malaysia, berpotensi menimbulkan persaingan moda khususnya bus dan kereta api, terkait dua atribut tersebut. Pendekatan analisis dilakukan menggunakan reveal preference method yang dipertajam dengan stated preference method. Tingginya kompetisi moda angkutan umum darat antarkota ini memungkinkan terjadinya mode shift, yang dapat diprediksi melalui preferensi dan persepsi pengguna moda. Preferensi dan persepsi pengguna moda bus antarkota dideskripsikan dengan memunculkan analisis sensitivitas terhadap 12.000 data set. Melalui analisis sensitivitas, dijumpai adanya perbedaan persepsi pengguna bus terhadap kebijakan penyedia jasa dalam perubahan nilai utilitas kedua moda tersebut. Temuan studi ini menarik, dimana reduksi travel time dan penurunan travel cost yang sama pada kedua moda, belum tentu menghasilkan persentase mode shift yang sama. Pengguna bus terlihat kurang begitu responsif terhadap pengurangan travel time maupun travel cost moda saingannya. Sebaliknya, pengguna bus antarkota lebih khawatir terhadap bertambahnya travel cost dan travel time moda mereka (bus). Diharapkan kajian ini menjadi pertimbangan bagi pembuat kebijakan agar pembangunan infrastruktur lebih tepat sasaran menuju terciptanya balance mode share. Terutama bagi kebijakan yang menimbulkan persaingan angkutan umum darat antarkota di masa depan.Kata kunci : Metoda stated preference, Reveal preference, Preferensi moda bus antarkota, Analisis sensitivitas.
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Yu, B., Z. Z. Yang, and J. Wang. "Bus travel-time prediction based on bus speed." Proceedings of the Institution of Civil Engineers - Transport 163, no. 1 (March 2010): 3–7. http://dx.doi.org/10.1680/tran.2010.163.1.3.
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Gong, Xiaolin, Xiucheng Guo, Xueping Dou, and Lili Lu. "Bus Travel Time Deviation Analysis Using Automatic Vehicle Location Data and Structural Equation Modeling." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/410234.
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To investigate the influences of causes of unreliability and bus schedule recovery phenomenon on microscopic segment-level travel time variance, this study adopts Structural Equation Modeling (SEM) to specify, estimate, and measure the theoretical proposed models. The SEM model establishes and verifies hypotheses for interrelationships among travel time deviations, departure delays, segment lengths, dwell times, and number of traffic signals and access connections. The finally accepted model demonstrates excellent fitness. Most of the hypotheses are supported by the sample dataset from bus Automatic Vehicle Location system. The SEM model confirms the bus schedule recovery phenomenon. The departure delays at bus terminals and upstream travel time deviations indeed have negative impacts on travel time fluctuation of buses en route. Meanwhile, the segment length directly and negatively impacts travel time variability and inversely positively contributes to the schedule recovery process; this exogenous variable also indirectly and positively influences travel times through the existence of signalized intersections and access connections. This study offers a rational approach to analyzing travel time deviation feature. The SEM model structure and estimation results facilitate the understanding of bus service performance characteristics and provide several implications for bus service planning, management, and operation.
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Zhao, Shuzhi, Chunxiu Lu, Shidong Liang, and Huasheng Liu. "A Self-Adjusting Method to Resist Bus Bunching Based on Boarding Limits." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/8950209.
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Bus bunching is one of the most serious problems of urban bus systems. Bus bunching increases waiting and travel time of passengers. Many bus systems use schedules to reach equal headways. Compared to the idea of schedules and the target headway introduced later, we propose a new method to improve the efficiency of a bus system and avoid bus bunching by boarding limits. Our solution can be effectively implemented when buses cannot travel as planned because of bad road conditions and dynamic demands at bus stops. Besides, using our method, bus headways reach the state with equal headways dynamically and spontaneously without drivers’ explicit intervention. Moreover, the method can improve the level of the bus service and reduce total travel time of passengers. We verify our method using an ideal bus route and a real bus route, both showing the success of the proposed method.
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Xin, Guangzhao, and Wei Wang. "Model Passengers’ Travel Time for Conventional Bus Stop." Journal of Applied Mathematics 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/986546.
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Limited number of berths can result in a subsequent bus stopping at the upstream of a bus stop when all berths are occupied. When this traffic phenomenon occurs, passengers waiting on the platform usually prefer walking to the stopped bus, which leads to additional walking time before boarding the bus. Therefore, passengers’ travel time consumed at a bus stop is divided into waiting time, additional walking time, and boarding time. This paper proposed a mathematical model for analyzing passengers’ travel time at conventional bus stop based on theory of stochastic service system. Field-measured and simulated data were designated to demonstrate the effectiveness of the proposed model. By analyzing the results, conclusion was conducted that short headway can reduce passengers’ waiting time at bus stop. Meanwhile, the theoretical analysis explained the inefficiency of bus stops with more than three berths from the perspective of passengers’ additional walking time. Additional walking time will increase in a large scale when the number of berths at a bus stop exceedsthe threshold of three.
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Green, Judith, Rebecca Steinbach, Alasdair Jones, Phil Edwards, Charlotte Kelly, John Nellthorp, Anna Goodman, Helen Roberts, Mark Petticrew, and Paul Wilkinson. "On the buses: a mixed-method evaluation of the impact of free bus travel for young people on the public health." Public Health Research 2, no. 1 (February 2014): 1–206. http://dx.doi.org/10.3310/phr02010.
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BackgroundIn September 2005 London introduced a policy granting young people aged < 17 years access to free bus and tram travel. A year later this policy was extended to people aged < 18 years in education, work or training. This intervention was part of a broader environmental strategy in London to reduce private car use, but its primary aim was to decrease ‘transport exclusion’, and ensure that access to goods, services, education and training opportunities were not denied to some young people because of transport poverty. However, there were also likely to be positive and negative health implications, which were difficult to assess in the absence of a robust evidence base on the impact of transport policies on health and well-being.ObjectivesTo evaluate the impact of free bus travel for young people in London on the public health. Specifically, to provide empirical evidence for the impact of this ‘natural experiment’ on health outcomes and behaviours (e.g. injuries, active travel) for young people; explore the effects on the determinants of health; identify the effects on older citizens of increased access to bus travel for young people and to identify whether or not the intervention represented value for money.DesignQuasi-experimental design, using secondary analysis of routine data, primary qualitative data and literature reviews.SettingLondon, UK.ParticipantsYoung people aged 12–17 years and older citizens aged ≥ 60 years.InterventionThe introduction of free bus travel for those aged < 17 years living in London in 2005, extended to those aged < 18 years in 2006.Main outcome measuresQuantitative: number of journeys to school or work; frequency and distance of active travel (i.e. walking and/or cycling), bus travel, car travel; incidence of road traffic injuries and assaults and socioeconomic gradients in travel patterns. Qualitative: how free bus travel affected young people and older citizens’ travel and well-being.MethodsQuantitative component: change-on-change analysis comparing pre–post change in the target age group (12–17 years) against that seen in ‘non-exposed’ groups [for travel mode, road traffic injury (RTI) and assaults]. Qualitative component: interviews analysed using both deductive and inductive methods. Economic evaluation: cost–benefit analysis (CBA).Data sourcesLondon Area Transport Survey (LATS) and London Travel Demand Survey (LTDS) (travel mode); STATS19 Road Accident data set (RTI); Hospital Episode Statistics (HES) (assaults); interviews with young people and older citizens; and cost data from providers and literature reviews.ResultsThe introduction of free bus travel for young people was associated with higher use of bus travel by adults and young people [31% increase, 95% confidence interval (CI) 19% to 42%; and 26% increase, 95% CI 13% to 41%, respectively], especially for short journeys, and lower car distances relative to adults (relative change 0.73, 95% CI 0.55 to 0.94); no significant overall reduction in ‘active travel’ [reduction in number of walking trips but no evidence of change in distance walked (relative change 0.99, 95% CI 0.92 to 1.07)]; significant reduction in cycling relative to adults (but from a very low base); a reduction in road traffic injuries for car occupants (relative change 0.89, 95% CI 0.84 to 0.95) and cyclists (relative change 0.60, 95% CI 0.55 to 0.66), but not pedestrians; an overall modest increase in journeys to work or school (relative change 1.09, 95% CI 1.06 to 1.14); equivocal evidence of impact on socioeconomic gradients in travel behaviour and no evidence of adverse impact on travel of older people aged > 60 years. An increase in assaults largely preceded the scheme. Qualitative data suggested that the scheme increased opportunities for independent travel, social inclusion, and a sense of belonging and that it ‘normalised’ bus travel. The monetised benefits of the scheme substantially outweighed the costs, providing what the Department for Transport (DfT) considers ‘high’ value for money.ConclusionThe free bus travel scheme for young people appears to have encouraged their greater use of bus transport for short trips without significant impact on their overall active travel. There was qualitative evidence for benefits on social determinants of health, such as normalisation of bus travel, greater social inclusion and opportunities for independent travel. In the context of a good bus service, universal free bus travel for young people appears to be a cost-effective contributor to social inclusion and, potentially, to increasing sustainable transport in the long term. Further research is needed on the effects of both active and other travel modes on the determinants of health; the factors that influence maintenance of travel mode change; travel as ‘social practice’; the impact of driving license changes on injury rates for young adults and the value of a statistical life for young people.FundingThe National Institute for Health Research Public Health Research programme.
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Gan, Albert, Huanyu Yue, Ike Ubaka, and Fang Zhao. "Development of Operational Performance and Decision Models for Arterial Bus Lanes." Transportation Research Record: Journal of the Transportation Research Board 1858, no. 1 (January 2003): 18–30. http://dx.doi.org/10.3141/1858-03.
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Bus lanes are a form of exclusive bus facility typically found along busy arterial streets. The use of bus lanes is justified because buses can carry more passengers than automobiles. However, a lane taken away from general-purpose traffic and designated as a bus-only lane can create congestion in other lanes, causing protests by motorists. An effort was undertaken to develop operational performance and decision models that can be used to justify and design bus lanes on arterial streets. The model considers the overall average person travel time under two treatments: with and without a bus-only lane. The CORSIM simulation model was used to estimate the bus and nonbus travel speeds under various scenarios of prevailing conditions, including bus volume, nonbus volume, right-turn volume, bus stop location, bus stop density, presence of bus bay, number of bus berths, mean dwell time, green ratio, cycle length, signal offset, and number of lanes. The simulated data were used as a substitute for field data in an empirical modeling of relationships between travel speeds and the prevailing conditions. The speed models allow person travel times to be estimated under different bus-lane designs and prevailing conditions. The models were found to produce speeds that closely approximate those reported in the literature for the given input conditions.
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Fatkhurrozi, M. i., D. K. Sudarsana, D. Yuniar, and A. Suraji. "Travel Time Behavior Study of Malang-Denpasar Intercity Bus Considering Sailing Time of Ketapang-Gilimanuk." JOURNAL OF SCIENCE AND APPLIED ENGINEERING 4, no. 2 (October 30, 2021): 63. http://dx.doi.org/10.31328/jsae.v4i2.3084.
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The study intends to acquire travel time behavior needed by Malang-Denpasar intercity bus (AKAP) considering sailing time of Ketapang-Gilimanuk. This research is a new thing to find out the inter-city bus travel time between islands. Where in this study the bus route connects the island of Java with the island of Bali. The interesting thing is that the travel time during the crossing at the port is part of the overall travel time identification. In addition, the presentation method using a trajectory table for inter-city bus travel routes is a more interesting presentation. Travel time of the bus is achieved by moving observer method (actual survey) where the surveyor is on the bus to track the travel. Interview is also conducted to get the experience of the respondents. The results are displayed in trajectory curve to present travel speed in each segment. In this study there are limitations that were carried out due to limited resources. This survey was only conducted in one round trip and 2 surveyors were mobilized. And what was noted during the survey was more about the travel time aspect. The results of this study provide an overview of travel time in outbound and inbound. In addition, the delay time that occurs during the trip is also identified. Actual survey shows that outbound journey is longer (13.9 hours) than inbound (11.13 hours). Delay time of outbound is 3.16 hours while that of inbound is 1.28 hours. Interview results longer travel time than that of actual survey. While sailing time of Ketapang and Gilimanuk harbour satisfies the minimum standard.
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Mohamed, Ahmed Hassan, Ibrhim A. I. Adwan, Abobaker G. F. Ahmeda, Hamza Hrtemih, and Haitham Al-MSari. "Identification of Affecting Factors on the Travel Time Reliability for Bus Transportation." Knowledge-Based Engineering and Sciences 2, no. 1 (May 2, 2021): 19–30. http://dx.doi.org/10.51526/kbes.2021.2.1.19-30.
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Public bus transit travel time is affected by many factors, including traffic signals and traffic condition. Transit agencies have implemented transit signal priority (TSP) strategies to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, these factors' collective impact and bus travel time strategies have not been studied at the stop-to-stop segment level. This research focuses on the factors affecting travel time reliability, emphasising the variability between operators and the policy implications of such differences. One-way analysis of variance (ANOVA) statistical methods have been used to assess the quality implications of public bus transportation time reliability. This research seeks to investigate the factors affecting the travel time (TT) reliability of bus transport. Studies were conducted along three bus routes serving different areas. Factors strongly related to TT reliability include route length, number of signalised intersections, day of the week, bus stops, departure delays, bus lane, passenger boarding and alighting, weather condition, and fare structure. Based on the proposed model factors affecting TT reliability, it was found that TT is strongly affected by the number of bus stoppings and also the length of the route. The reliability of all three routes during the weekday is low because of delays in departure. The number of signalised intersections along the route affects reliability. Meanwhile, more passengers boarding and paying cash increased the travel time reliability of buses.
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Czapla, Zbigniew, and Grzegorz Sierpiński. "Driving and Energy Profiles of Urban Bus Routes Predicted for Operation with Battery Electric Buses." Energies 16, no. 15 (July 31, 2023): 5706. http://dx.doi.org/10.3390/en16155706.
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Battery electric buses are used for operation on urban bus routes. The main disadvantage of battery electric buses is their limited range that depends on energy consumption. This paper presents a new approach to the estimation of energy consumption on urban bus routes based on driving and energy profiles. The energy consumption results from the travel parameters along the bus route. The travel parameters are described by driving profiles. The determination of driving profiles is based on GPS location data recorded by a receiver on a bus. Location data are recorded at consecutive track points at a constant frequency. For each track point, the distance to the preceding track point is determined using the location data, and then the speed and acceleration are calculated. The analyzed bus route is divided into sections. For each section, travel parameters consisting of travel time, speed parameters, and acceleration parameters are determined. Using travel parameters, the energy consumption is estimated for individual sections and the entire bus route. The estimated energy consumption is described by energy profiles. Experimental results have been obtained for the selected urban bus route under various traffic conditions. For the assumed model of energy consumption, the energy consumed on the entire bus route is 1.8 KWh/km at off-peak hours and 2.1 KWh/km at peak hours. The driving and energy profiles describe the urban bus routes well and allow evaluation of the suitability of the bus route for operation with battery electric buses.
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Li, Xiaowei, Jingkun Fan, Yao Wu, Jun Chen, and Xuefeng Deng. "Exploring Influencing Factors of Passenger Satisfaction toward Bus Transit in Small-Medium City in China." Discrete Dynamics in Nature and Society 2020 (November 23, 2020): 1–11. http://dx.doi.org/10.1155/2020/8872115.
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This paper aims to explore the factors influencing passengers’ satisfaction toward bus transit and develop the improvement strategy for the small-medium city. Data including individual attributes, travel activity attributes, and perceived service attributes were collected in the city of Weinan, China. The ordered logit (OL) model and ordered Probit (OP) model were employed to explore the significant factors associated with passengers’ satisfaction toward bus transit. The odds ratio (OR) was applied to quantitatively measure the effects of the significant factors. Improving strategies of bus transit service were proposed based on the model results using the three-factor theory. Results show that the OL model outperforms the OP model. The age, daily average waiting time, perceived waiting time, transferring convenience, the attitude of the driver, intelligent travel information service, hygienic environment inside the bus, ticket price, bus route setting, and bus stop setting significantly affect the passengers’ satisfaction. Among them, the ticket price, perceived waiting time, bus stop setting, intelligent travel information service, transferring convenience, and bus route setting were identified as exciting factors. It is recommended that optimization of bus route and bus stop setting, building bus dedicated lanes, optimizing dynamic charging system, and providing intelligent travel information service could be effective strategies to improve passengers’ satisfaction toward bus transit in Chinese small-medium cities.
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Deng, Lianbo, Wei Gao, Yanbing Fu, and Wenliang Zhou. "Optimal Design of the Feeder-Bus Network Based on the Transfer System." Discrete Dynamics in Nature and Society 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/483682.
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This paper studied the classic feeder-bus network design problem (FBNDP), which can be described as follows: for the passenger travel demand between rail stations and bus stops on a given urban transit network, it designs the optimal feeder bus routes and frequencies so as to minimize the passengers’ travel expense and the operator’s cost. We extended the demand pattern of M-to-1 in most existing researches to M-to-M. We comprehensively considered the passenger travel cost, which includes the waiting and riding cost on the bus, riding cost on rail, and transfer cost between these two transportation modes, and presented a new genetic algorithm that determines the optimal feeder-bus operating frequencies under strict constraint conditions. The numerical examples under different demand patterns have been experienced and analysed, which showed the robustness and efficiency of the presented algorithm. We also found that the distribution pattern of the travel demand has a significant influence on the feeder-bus network construction.
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Zhai, Zhikang, Ying Yang, Yu Shen, Yuxiong Ji, and Yuchuan Du. "Assessing the Impacts of Autonomous Bus-on-Demand Based on Agent-Based Simulation: A Case Study of Fuyang, Zhejiang, China." Journal of Advanced Transportation 2020 (November 23, 2020): 1–15. http://dx.doi.org/10.1155/2020/7981791.
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This paper envisions and assesses the performance of an autonomous bus-on-demand (ABoD) system. We take Fuyang, Zhejiang, China, as the study area to investigate the spatiotemporal distribution of bus travel demand during workdays, and we propose replacing inefficient bus routes with the ABoD system. Agent-based models with various bus dispatching and operation control strategies are constructed to evaluate the performance of the ABoD system. The behaviors and interactions of the agents, passengers, autonomous buses, and a control center are designed. After the verification of the simulated bus travel demand with real-world demand, a series of scenarios with various ABoD operation strategies are simulated. The simulation results show that, in comparison with both current fixed-schedule bus services and the optimized bus dispatching strategies, the ABoD system occupies fewer road resources and utilizes bus vehicles more efficiently. Besides, the system is adaptive to the sudden surge in bus travel demand and is economically sustainable.
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Glick, Travis B., and Miguel A. Figliozzi. "Measuring the Determinants of Bus Dwell Time: New Insights and Potential Biases." Transportation Research Record: Journal of the Transportation Research Board 2647, no. 1 (January 2017): 109–17. http://dx.doi.org/10.3141/2647-13.
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Dwell time is a major component of bus travel time and travel time variability. In turn, the distribution of bus travel times affects transit operators’ costs and customer satisfaction. Previous research used dwell time from bus stop–level data to understand the key factors that contribute to dwell time duration. However, bus stop–level data have significant shortcomings when bus stops are located near intersections or at time points. Regression results show that the use of only stop-level data can significantly bias estimation of boarding and alighting coefficients. This research complements bus stop data with bus GPS trajectory data around bus stops to prevent estimation bias and to measure better the key factors that determine dwell time. Regression results from individual and pooled bus stop models are compared to provide new insights into the impacts of traffic conditions, signalized intersections, bus bays, and time points on dwell times. The impacts of nearside, midblock, and farside bus stops are included in the analysis. The number of passengers boarding and alighting has a nonlinear effect with economies or efficiencies of scale.
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Wang, Jian, and Yang Cao. "Operating Time Division for a Bus Route Based on the Recovery of GPS Data." Journal of Sensors 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/1321237.
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Bus travel time is an important source of data for time of day partition of the bus route. However, in practice, a bus driver may deliberately speed up or slow down on route so as to follow the predetermined timetable. The raw GPS data collected by the GPS device equipped on the bus, as a result, cannot reflect its real operating conditions. To address this concern, this study first develops a method to identify whether there is deliberate speed-up or slow-down movement of a bus. Building upon the relationships between the intersection delay, link travel time, and traffic flow, a recovery method is established for calculating the real bus travel time. Using the dwell time at each stop and the recovered travel time between each of them as the division indexes, a sequential clustering-based time of day partition method is proposed. The effectiveness of the developed method is demonstrated using the data of bus route 63 in Harbin, China. Results show that the partition method can help bus enterprises to design reasonable time of day intervals and significantly improve their level of service.
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Deng, Yajuan, Xiaolei Ru, Ziqi Dou, and Guohua Liang. "Design of Bus Bridging Routes in Response to Disruption of Urban Rail Transit." Sustainability 10, no. 12 (November 27, 2018): 4427. http://dx.doi.org/10.3390/su10124427.
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Bus bridging has been widely used to connect stations affected by urban rail transit disruptions. This paper designs bus bridging routes for passengers in case of urban rail transit disruption. The types of urban rail transit disruption between Origin-Destination stations are summarized, and alternative bus bridging routes are listed. First, the feasible route generation method is established. Feasible routes for each pair of the disruption Origin-Destination stations include urban rail transit transfer, direct bus bridging, and indirect bus bridging. Then the feasible route generation model with the station capacity constraint is established. The k-short alternative routes are generated to form the bus bridging routes. Lastly, by considering the bus bridging resource constraints, the final bus bridging routes are obtained by merging and filtering the initial bridging routes. Numerical results of an illustrative network show that the bus bridging routes generated from the proposed model can significantly reduce travel delay of blocked passengers, and it is necessary to maintain the number of passengers in the urban rail transit below the station capacity threshold for ensuring a feasible routing design. One more important finding of this work is that the direct bridging route is preferred for short travel distances, while the indirect bridging route is preferred for longer travel distances. After the bridging bus routes are taken, the passenger’s total travel time is significantly lower than when no measures are taken. However, after the capacity constraint of a station is considered, the passenger’s total travel time will be increased by 3.49% compared with not considering a capacity constraint.
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Hasan, Md Abir, and Ashraf Uddin Fahim. "Measurement of Efficient Travel Time of a Highway Corridor Through Moving Observer Method: A Case Study on Savar-Manikganj Highway in Bangladesh." Journal of Engineering Science 13, no. 1 (July 5, 2022): 21–29. http://dx.doi.org/10.3329/jes.v13i1.60559.
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Travel time and its variability is one of the biggest controlling factors for trip planning, mode selection and forecasting trip duration. Travel time can be affected by various issues. Savar-Aricha highway is the gateway between south and south-western part of the country. Large variability on this corridor can cause great economic losses. To understand this routes travel time, running velocity and level of service moving observer method was conducted. The survey also includes travel time, stopped time and journey time for two types of public transport present on the corridor: ticket-based bus system and without ticket local bus system. The study found that, Ticket based bus system has lesser travel time and stopped time resulting is less travel time in comparison with local bus system. Speed analysis for both the route also supports this. In consideration of free flow speed, the level of service of this corridor was found A. Journal of Engineering Science 13(1), 2022, 21-29
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Liu, Shuozhi, Xia Luo, and Peter J. Jin. "Improving Bus Operations through Integrated Dynamic Holding Control and Schedule Optimization." Journal of Advanced Transportation 2018 (September 25, 2018): 1–18. http://dx.doi.org/10.1155/2018/9714046.
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Bus bunching can lead to unreliable bus services if not controlled properly. Passengers will suffer from the uncertainty of travel time and the excessive waiting time. Existing dynamic holding strategies to address bus bunching have two major limitations. First, existing models often rely on large slack time to ensure the validity of the underlying model. Such large slack time can significantly reduce the bus operation efficiency by increasing the overall route travel times. Second, the existing holding strategies rarely consider the impact on the schedule planning. Undesirable results such as bus overloading issues arise when the bus fleet size is limited. This paper explores analytically the relationship between the slack time and the effect of holding control. The optimal slack time determined based on the derived relationship is found to be ten times smaller than in previous models based on numerical simulation results. An optimization model is developed with passenger-orient objective function in terms of travel cost and constraints such as fleet size limit, layover time at terminals, and other schedule planning factors. The optimal choice of control stops, control parameters, and slack time can be achieved by solving the optimization. The proposed model is validated with a case study established based on field data collected from Chengdu, China. The numerical simulation uses the field passenger demand, bus average travel time, travel time variance of road segments, and signal timings. Results show that the proposed model significantly reduce passengers average travel time compared with existing methods.
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Wu, Fan, Xiaowei Hu, Shi An, and Duo Zhang. "Exploring Passengers’ Travel Behaviors Based on Elaboration Likelihood Model under the Impact of Intelligent Bus Information." Journal of Advanced Transportation 2019 (March 4, 2019): 1–12. http://dx.doi.org/10.1155/2019/9095279.
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The ubiquitous intelligent transportation infrastructure in metropolitan cities has enabled bus passengers to access comprehensive (even real-time) bus information. However, the impact of different types of information on passenger behavior is still insufficiently understood. Combining with the theory of information processing path, this study partially fills this gap by adopting an elaboration likelihood model (ELM) suitable for explaining how the various types of intelligent bus information influence passengers’ choice behavior. Six types of intelligent bus information (information of bus lines, estimated travel time, estimated time of arrival, congestion inside bus, road congestion, and bus fare) are used as six independent variables, and passengers’ departure time, travel routes, and travel modes as dependent variables. Valid questionnaire assessments were collected from 285 participants at 4 bus stops equipped with intelligent bus system in Harbin, providing quantitative data to verify each hypothesis. The results show that six types of intelligent bus information to different degrees (significant influence, slight influence, and no significant influence) affect three types of passengers’ choice behaviors; the information of estimated travel time and that of road congestion are both significantly effective in all three types of choice behavior while bus fare has no significant influence. Meanwhile, other types of information have a significant or slight effect on certain behavior. The results of this study can be used to design more reasonable intelligent bus information provision strategies to meet passengers’ requirements.
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Klein, Nicholas. "More than just a bus ride: The role of perceptions in travel behaviour." Urban Studies 54, no. 11 (May 24, 2016): 2490–503. http://dx.doi.org/10.1177/0042098016649324.
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The purpose of this article is to add another dimension to our understanding of travel behaviour by highlighting how individual decisions about travel are simultaneously influenced by both rational, calculable metrics of the transportation system but also by socially constructed, context-specific perceptions that travellers hold about the travel modes themselves. The context for this study is a rapid transformation of the market for intercity buses in the Northeast United States. In the past 15 years, new entrants have transformed a humdrum industry into a dynamic sector of the intercity travel market. The new entrants, curbside buses, have largely shunned traditional bus terminals in favour of picking up and dropping off bus passengers on city streets. Ridership has steadily increased, and these new bus companies have expanded operations throughout the country. Drawing on a series of focus groups with intercity bus passengers, I describe how two sets of factors drive intercity travellers’ choice to travel onboard the new intercity buses. First, the new companies offer operational and economic advantages. Second, and surprisingly, focus group participants have different perceptions of the new bus companies than the old – and these perceptions appear to be influencing their travel decisions.
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Nadimi, Navid, Aliakbar Zamzam, and Todd Litman. "University Bus Services: Responding to Students’ Travel Demands?" Sustainability 15, no. 11 (June 1, 2023): 8921. http://dx.doi.org/10.3390/su15118921.
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University bus services provide fixed-route public transport for students to and from large universities. They are relatively affordable and resource-efficient, but must compete against private cars and taxis which tend to be more convenient and flexible than University bus services. Many students, particularly those with lower incomes, depend on them. University administrators must understand how to improve University bus service in order to treat this group fairly. The main contribution of this paper is to examine how University bus service can help achieve social equity and sustainability goals. It investigates this by reporting the results of a survey of 303 students at Shahid Bahonar University of Kerman in Iran concerning their travel demands and University bus service utilization. Grounded theory and structural equation modeling is used to analyze the daily commute preferences of university students influenced by their characteristics, fleet condition, fares, station condition, and time factors. This study identifies various steps that the university administration can take to make University bus service more efficient and attractive, such as updating the bus fleet, improving stations, increasing security, and improving pedestrian access to stations. Survey respondents reported the highest satisfaction levels with fare levels, the security in buses, and waiting times. Women reported feeling discriminated against in their daily commutes. Poor-quality University bus service contributes to a negative feedback loop that increases automobile use and reduces university travel sustainability.
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Yin, Zhenzhong, and Bin Zhang. "Construction of Personalized Bus Travel Time Prediction Intervals Based on Hierarchical Clustering and the Bootstrap Method." Electronics 12, no. 8 (April 19, 2023): 1917. http://dx.doi.org/10.3390/electronics12081917.
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Providing accurate bus travel time information is very important to help passengers plan their trips and reduce waiting times. Due to the uncertainty of the bus travel time, the traditional prediction value of the travel time point cannot accurately describe the reliability of the prediction result, which is not conducive to passengers waiting for the bus according to the prediction result. At the same time, due to the large differences in the individual driving styles of the bus drivers, the travel time data fluctuate greatly, and the accuracy and reliability of the point prediction results are further reduced. To address this issue, this study develops a personalized bus travel time prediction intervals model for different drivers based on the bootstrap method. Personalized travel time prediction intervals were constructed for drivers with different driving styles. To further improve the quality of travel time prediction intervals, this study optimizes training data sets considering driving style factors. Then, this paper integrates hierarchical clustering, an artificial neural network, and the bootstrap method to construct another prediction intervals model for bus travel time based on driver driving style clustering and the bootstrap method. The real−world driving data sets of the No. 239 bus in Shenyang, China, were used for experimental verification. The results showed that the two models constructed in this paper can effectively quantify the uncertainty of the point prediction results, the PICP of each interval exceeding the confidence level set (80%). It was also found that the quality of the prediction intervals constructed by clustering the driving style data is better (MPIW values decreased by 23.33%, 54.24%, and 28.61 respectively, and the corresponding NMPIW values also decreased by 18.93%, 10.39%, and 14.19%, respectively), which can provide passengers with more reasonable suggestions for waiting time.
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Parolin, B. P. "Effects of Rationalization of Rural Passenger Services on Travel Activity Patterns." Transportation Research Record: Journal of the Transportation Research Board 1557, no. 1 (January 1996): 48–57. http://dx.doi.org/10.1177/0361198196155700108.
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One aspect of rationalization of rural passenger services in the state of New South Wales, Australia is examined: the travel and activity consequences for rural consumers of the substitution of longer-haul bus services for rail passenger services. Interview surveys of bus passengers in selected communities and town residents who previously used train services or presently use bus services were used to develop travel-activity profiles in the pre- and postrationalization period. The extent and nature of reorientation of travel-activity patterns were assessed to determine the effects of service substitution. Results indicate that most respondents were able to adjust their travel-activity patterns and benefit from the service substitution's greater number of travel choices, despite relatively low levels of mobility. The new bus services provide a higher level of service and are well patronized by respondents. Rural public transportation patronage in the study communities is now higher compared with that in the prerationalization period. Furthermore, no evidence was found of a link between rationalization and decline in services provision. The conclusion is drawn that new rural bus services have been overwhelmingly accepted and are well patronized in the study communities. They have also attracted many car users. Longer-haul bus services are now an integral part of the network of rural passenger services and of travel-activity patterns.
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Cui, Hongjun, Mingzhi Li, Minqing Zhu, and Xinwei Ma. "Investigating the Impacts of Urban–Rural Bus Service Quality on Rural Residents’ Travel Choices Using an SEM–MNL Integration Model." Sustainability 15, no. 15 (August 3, 2023): 11950. http://dx.doi.org/10.3390/su151511950.
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The high-quality development of urban–rural buses is an important way to narrow the gap between urban and rural areas. However, studies on the quality of bus services and its impact on bus travel-mode choice have mostly focused on urban buses, with less attention paid to urban–rural buses. This paper aims to explore how urban–rural bus service quality affects rural residents’ travel-mode-choice behavior based on survey data from rural residents in Henan Province, China. A structural equation model (SEM) is applied to examine the critical factors affecting rural residents’ satisfaction with urban–rural bus service quality and the heterogeneity of satisfaction among rural residents with different attributes. Furthermore, an integrated approach of SEM and the multinomial logit (MNL) model is proposed to identify the key factors that affect rural residents’ bus travel-mode choice. The results indicate that reliability and convenience are the key factors affecting satisfaction with urban–rural bus service quality. There are significant differences in rural residents’ satisfaction by gender, age, income, education level, occupation, and travel-mode attributes. Urban–rural bus service quality has a significant positive impact on rural residents’ bus travel-choice behavior, and its degree of influence is greater than all explicit variables except private car ownership. The findings of this study can help operators and governments formulate policies to improve the service quality of urban–rural buses and ultimately promote the use of buses.
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Szarata, Mateusz, Piotr Olszewski, and Lesław Bichajło. "Simulation Study of Dynamic Bus Lane Concept." Sustainability 13, no. 3 (January 27, 2021): 1302. http://dx.doi.org/10.3390/su13031302.
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Not many publications are available on using microsimulation models to analyze the feasibility of implementing the dynamic bus lane (DBL) concept. The paper presents the methodology and calibration process used for DBL modeling. For the selected four sites in Rzeszów (Poland), three options were analyzed: no bus lane, standard exclusive bus lane (XBL), and dynamic bus lane. The analyses were carried out using PTV Vissim software with an additional logic script to control the DBL activation. Simulation model parameters were calibrated using a genetic algorithm. The final assessment of individual options was based on the weighted average travel time for all transport modes. The results show that the dynamic bus lane could bring the same benefits to public transport and cause only a slight increase in travel times in private transport compared to XBL. The XBL solution, depending on the site, led to increasing the average travel time in private transport by 12% to 25%, while the dynamic bus lane increased by 1% to 12%. Weighted average travel time per person is proposed as the overall indicator of efficiency. Preliminary analyses show that the bus volume, bus occupancy, routing, and traffic conditions will affect the efficiency of the new solution.
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Bashar, Md Abul, Awal Ahmed Bappy, Md Foysal Ahmed Shobuj, Md Muktadir Sumon, and Md Aminur Islam. "Assessment of the satisfaction of Bus passengers in Dhaka, Bangladesh." INTERNATIONAL RESEARCH JOURNAL OF ENGINEERING & APPLIED SCIENCES 10, no. 2 (May 6, 2022): 01–08. http://dx.doi.org/10.55083/irjeas.2022.v10i02003.
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Increased population results in an increase in travel demand. Greater road length and construction of new roads result in faster and longer travels and increase car ownership, which contributes to increased traffic congestion and pollution. The bus form of travel is a critical component of resolving this issue. A bus can carry 30-40 passenger per trip on the other hand a private car carries 2-3 passengers per trip. So, bus transport could decrease the number of vehicles in road if it can provide better service quality in bus mode. In this experiment, the main objectives are to better understand overall passengers’ satisfaction in bus transport in Uttara-Gazipur route and predict the individual factors contributing to the comfort of the bus modes in this route. To evaluate this result, a questionnaire survey form was created with about 19 service quality parameters such as safe speed, temperature, noise, required time, waiting time for bus, station service, seat comfort service, cleanness, staff behaviour, payment system fare. In this experiment, opinions of 100 passengers were collected regarding the service quality. Data were analyzed using descriptive and multiple linear regression, analyzed by SPSS software. One main finding reported that passengers are not satisfied yet with bus service quality. This study revealed that 75% of feedback was poor or very poor, and 25% of feedback was positive or good regarding the level of satisfaction for bus mode. The regression analysis reported that the overall P-value is less than 0.05 and the regression coefficient, R2 is 0.64, which rejected the null hypothesis and makes the survey significant to assess the overall comfort of passengers traveling with bus in Uttara-Gazipur route. It was also found that three parameters: reliability (ẞ = 0.170, P=0.027), safe speed (ẞ = 0.240, P = 0.021) and travel time (ẞ = 0.320, P = 0.01) are individually contributing to overall satisfaction of passenger in Uttara-Gazipur route.
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Safitri, Asa Dina, Paksitya Purnama Putra, and Akhmad Hasanuddin. "MODE CHOICE ANALYSIS OF JEMBER-SURABAYA LAND TRANSPORTATION USING STATED PREFERENCE METHOD." Jurnal Rekayasa Sipil dan Lingkungan 4, no. 1 (October 31, 2020): 83. http://dx.doi.org/10.19184/jrsl.v4i1.12027.
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The launched of the new Probolinggo-Pasuruan toll road affected the Express Bus route from Jember to Surabaya. Taken from a third party application, the travel time for the Jember-Surabaya Express Bus route changes faster. The acceleration of travel time is 1 hour, from 4 hours 30 minutes to 3 hours 30 minutes. The initial hypothesis of this change is a change in public interest as users of the mode of transportation from the Train to the Express Bus. The Stated Preference method is used to determine people's preferences. Based on the analysis results, there are two utility model results obtained from the travel cost difference attribute and the travel time difference attribute with an R² value of 0.995. Based on the results of the sensitivity analysis, the greater the difference between the cost of travel and the difference in travel time, the probability of train passengers to move using the Express Bus will continue to increase.
Peresmian tol baru Probolinggo-Pasuruan mempengaruhi rute Bus Patas dari Jember ke Surabaya. Diambil dari aplikasi pihak ketiga, waktu tempuh rute Bus Patas Jember-Surabaya berubah lebih cepat. Percepatan waktu tempuh adalah sebesar 1 jam, dari 4 jam 30 menit menjadi 3 jam 30 menit. Hipotesis awal dari adanya perubahan tersebut adalah akan adanya perubahan minat masyarakat sebagai pengguna moda transportasi dari Kereta Api ke Bus Patas. Metode Stated Preference digunakan untuk menentukan preferensi orang. Berdasarkan hasil analisis terdapat dua hasil model utilitas yang diperoleh dari atribut perbedaan biaya perjalanan dan atribut perbedaan waktu tempuh dengan nilai R² sebesar 0,995. Berdasarkan hasil analisis sensitivitas, semakin besar selisih biaya perjalanan dengan selisih waktu tempuh maka probabilitas penumpang Kereta Api untuk berpindah menggunakan Bus Patas akan terus meningkat.
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Sularno, Sularno, Renita Astri, Putri Anggraini, Dio Prima Mulya, and Dwiki Mulya. "Geographical Information System of Bus and Travel Counter in Padang City Using BFS Method Based on Mobile Web." Scientific Journal of Informatics 8, no. 2 (November 30, 2021): 304–13. http://dx.doi.org/10.15294/sji.v8i2.33117.
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Purpose: One of the main objectives of the research is the BFS (Breadth-First Search) algorithm method in the search for nearby bus and travel counters using GPS found on each device used in the search process. Each smartphone produces a different coordinate point with an average distance difference of 30.2 meters to the hardware coordinate point. Each GPS embedded in the smartphone will process the data according to the location conditions of the user's point of existence. The methodology for system development is a standard process for a team of developers to connect all the steps needed in analyzing, designing, implementing, and maintaining information systems. Methods: The methodology becomes a guideline in system development activities in SDLC. The SDLC model used in this study is the WaterFall Model. Result: The results of this study are expected to facilitate the public in booking tickets and to find the nearest location from the bus and travel counters. Novelty: The novelty of this research is the development of GIS as a search for the location of bus and travel counters using the breadth-first search algorithm. This research can help the community find the location of the nearest bus and tourist counter in the city of Padang.
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Vanessa Damayanthi, Melati, Tri Basuki Joewono, and Patricia Hartieni. "PREFERENSI PEMILIHAN TUJUAN PERJALANAN BUS LISTRIK DI KAWASAN PERUMAHAN KOTA BANDUNG." Berkala Forum Studi Transportasi antar Perguruan Tinggi 2, no. 1 (April 30, 2024): 77–86. http://dx.doi.org/10.19184/berkalafstpt.v2i1.903.
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This study emphasizes the significance of advancing the utilization of electric buses as an eco-friendlytransportation alternative. Addressing the environmental and energy challenges conventional motor vehiclespose, the study focuses on electric bus modeling while integrating travel destination preferences. The researchenhances a greener and more efficient electric bus system by linking travel purposes with behavior patterns.This work aids sustainable transportation infrastructure development, concentrating on route selection inresidential areas. The study was conducted in Kota Baru Parahyangan, Summarecon Bandung, and TamanKopo Indah, employing purposive and snowball sampling. The discriminant analysis classification methodassessed travel destinations based on activity-based travel types, revealing 74 respondents favoringdiskresioner travel, 91 opting for mandatory travel, and 95 selecting both for electric bus usage withinresidential localities. This research offers insights for fostering sustainable transportation solutions tailored tocommunity needs. ABSTRAK Penggunaan bus listrik sebagai moda transportasi alternatif penting untuk dikembangkan lebih lanjut untukmengurangi produksi kendaraan bermotor berbahan bakar konvensional yang dapat menyebabkanpermasalahan lingkungan dan energi. Pemodelan bus listrik memerlukan aspek pemilihan rute yang berkaitanpada tujuan perjalanan. Memahami tujuan perjalanan terhadap pola perjalanan memungkinkan pengembangansistem transportasi bus listrik yang lebih efisien dan ramah lingkungan. Dengan demikian, penelitian ini dapatmemberikan kontribusi dalam mendukung pengembangan dan peningkatan infrastruktur transportasi yangberkelanjutan dan memfokuskan pada kebutuhan masyarakat di kawasan perumahan dalam hal pemilihan rute.Penelitian dilaksanakan di Kota Baru Parahyangan, Summarecon Bandung, dan Taman Kopo Indah denganmetode purposive sampling dan snowball sampling. Analisis tujuan perjalanan berdasarkan jenis perjalananberbasis aktivitas menggunakan metode klasifikasi analisis diskriminan sehingga diperoleh hasilpengelompokan adalah sebanyak 74 responden memilih perjalanan diskresioner, 91 responden memilihperjalanan wajib dan 95 responden memilih keduanya saat menggunakan bus listrik di kawasan perumahan.
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Dou, Xueping, and Tongfei Li. "Multi-Objective Bus Timetable Coordination Considering Travel Time Uncertainty." Processes 11, no. 2 (February 13, 2023): 574. http://dx.doi.org/10.3390/pr11020574.
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This paper proposes a timetable coordination method for transfer problems in a bus transit system. With a given bus network, a stochastic mixed-integer linear programming (MILP) model has been formulated to obtain coordinated bus timetables with the objective of minimizing a weighted sum of the average value of total waiting time and its average absolute deviation value, allowing for random bus travel time. The vital decision variable is the terminal departure offset time of each target bus trip within a certain off-peak period. The robust MILP model can also be used to solve the first-bus transfer problem with the introduction of several new linear constraints. A solution method based on the Monte Carlo simulation has been developed to solve the MILP model. Numerical experiments have been conducted for different scenarios. The results indicate that bus timetables coordinated by the developed model are capable of substantially reducing waiting time for transfer and non-transfer passengers. In addition, the feasibility of simplifying a common sub-route into a single transfer stop in a timetable coordination problem has been explored based on numerical experiments.
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Liu, Yi, Yuanhua Jia, Xuesong Feng, and Jiang Wu. "Bus Route Design with a Bayesian Network Analysis of Bus Service Revenues." Mathematical Problems in Engineering 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/5176920.
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A Bayesian network is used to estimate revenues of bus services in consideration of the effect of bus travel demands, passenger transport distances, and so on. In this research, the area X in Beijing has been selected as the study area because of its relatively high bus travel demand and, on the contrary, unsatisfactory bus services. It is suggested that the proposed Bayesian network approach is able to rationally predict the probabilities of different revenues of various route services, from the perspectives of both satisfying passenger demand and decreasing bus operation cost. This way, the existing bus routes in the studied area can be optimized for their most probable high revenues.
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Ma, Zhen-Liang, Luis Ferreira, Mahmoud Mesbah, and Ahmad Tavassoli Hojati. "Modeling Bus Travel Time Reliability with Supply and Demand Data from Automatic Vehicle Location and Smart Card Systems." Transportation Research Record: Journal of the Transportation Research Board 2533, no. 1 (January 2015): 17–27. http://dx.doi.org/10.3141/2533-03.
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Travel time reliability is an important aspect of bus service quality. Despite a significant body of research on private vehicle reliability, little attention has been paid to bus travel time reliability at the stop-to-stop link level on different types of roads. This study aims to identify and quantify the underlying determinants of bus travel time reliability on links of different road types with the use of supply and demand data from automatic vehicle location and smart card systems collected in Brisbane, Australia. Three general bus-related models were developed with respect to the main concerns of travelers and planners: average travel time, buffer time, and coefficient of variation of travel time. Five groups of alternative models were developed to account for variations caused by different road types, including arterial road, motorway, busway, and central business district. Seemingly unrelated regression equations estimation were applied to account for cross-equation correlations across regression models in each group. Three main categories of unreliability contributory factors were identified and tested in this study, namely, planning, operational, and environmental. Model results provided insights into these factors that affect bus travel time and its variability. The most important predictors were found to be the recurrent congestion index, traffic signals, and passenger demand at stops. Results could be used to target specific strategies aimed at reducing unreliability on different types of roads.
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Li, Xiaowei, Lanxin Shi, Haotian Li, Qian Liu, and Jun Chen. "What Affects Bus Passengers’ Travel Time? A View from the Built Environment and Weather Condition." Journal of Advanced Transportation 2023 (October 9, 2023): 1–17. http://dx.doi.org/10.1155/2023/6629507.
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The study aims to examine the impact of the built environment and weather conditions on travel time for bus passengers in Weinan, China. Various sources of data, including smart card data, bus GPS data, bus station data, road information data, and smart card swiping time, were integrated and analyzed. The study employed the light gradient boosting machine (LightGBM) model and SHapley Additive exPlanations (SHAP) value to assess the feature importance and nonlinear effects of different types of POI density, weather conditions, and time series on bus passengers’ travel time. The study findings indicate that several factors are associated with bus passengers’ travel time, including destination residential density, destination diversity, destination life service density, origin science and education density, origin residential density, origin diversity, humidity, visibility, boarding time between 7 and 8 a.m., and precipitation. This study also reveals nonlinear threshold effects. The study findings provide valuable insights that can be utilized to optimize the bus network and develop low-carbon-oriented land-use planning.