Готові списки джерел за темами / Travel time (Traffic engineering) Simulation

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Добірка наукової літератури з теми "Travel time (Traffic engineering) Simulation"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 19 липня 2025

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Статті в журналах з теми "Travel time (Traffic engineering) Simulation"

Chien, Steven I. J., Xiaobo Liu, and Kaan Ozbay. "Predicting Travel Times for the South Jersey Real-Time Motorist Information System." Transportation Research Record: Journal of the Transportation Research Board 1855, no. 1 (2003): 32–40. http://dx.doi.org/10.3141/1855-04.

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A dynamic travel-time prediction model was developed for the South Jersey (southern New Jersey) motorist real-time information system. During development and evaluation of the model, the integration of traffic flow theory, measurement and application of collected data, and traffic simulation were considered. Reliable prediction results can be generated with limited historical real-time traffic data. In the study, acoustic sensors were installed at potential congested places to monitor traffic congestion. A developed simulation model was calibrated with the data collected from the sensors, and this was applied to emulate traffic operations and evaluate the proposed prediction model under time-varying traffic conditions. With emulated real–time information (travel times) generated by the simulation model, an algorithm based on Kalman filtering was developed and applied to forecast travel times for specific origin-destination pairs over different periods. Prediction accuracy was evaluated by the simulation model. Results show that the developed travel-time predictive model demonstrates satisfactory performance.

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De Palma, André, Fabrice Marchal, and Yurii Nesterov. "METROPOLIS: Modular System for Dynamic Traffic Simulation." Transportation Research Record: Journal of the Transportation Research Board 1607, no. 1 (1997): 178–84. http://dx.doi.org/10.3141/1607-24.

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METROPOLIS proposes an interactive environment that simulates automobile traffic in large urban areas. The core of the system is a dynamic simulator that integrates commuters’ departure time and route choice behaviors over large networks: Drivers are assumed to minimize a generalized travel cost function that depends on travel time and schedule delay. This simulator is based on a behavioral driver information process. It allows real-time and off-line simulations. The system also includes a scenario builder and a graphical results viewer. The main ideas underlying METROPOLIS are presented, and preliminary computer simulation experiments are discussed for Geneva, Switzerland.

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Liu, Zhiguang, Tomio Miwa, Weiliang Zeng, Michael G. H. Bell, and Takayuki Morikawa. "Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information." Journal of Advanced Transportation 2018 (August 8, 2018): 1–13. http://dx.doi.org/10.1155/2018/8919721.

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Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.

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Thomas, Natacha, and Bader Hafeez. "Simulation of an Arterial Incident Environment with Probe Reporting Capability." Transportation Research Record: Journal of the Transportation Research Board 1644, no. 1 (1998): 116–23. http://dx.doi.org/10.3141/1644-12.

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Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.

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Kühne, Reinhart D., Karin Langbein-Euchner, Martin Hilliges, and Norbert Koch. "Evaluation of Compliance Rates and Travel Time Calculation for Automatic Alternative Route Guidance Systems on Freeways." Transportation Research Record: Journal of the Transportation Research Board 1554, no. 1 (1996): 153–61. http://dx.doi.org/10.1177/0361198196155400119.

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This study outlines the concept of extending an available simulation model for evaluation of freeway route guidance systems using the compliance rates of drivers with alternative route recommendations based on measurements from the freeway subnetwork near Munich, Germany. The system works with variable direction signs that automatically display routing instructions to prevent congestion on the main road. The effectiveness of the system is assessed by calculating the travel times with and without an alternative route guidance system in operation. The result is a decrease in individual travel times on the main road and overall travel time savings for all traffic participants of the system. The simulation indicates a high sensitivity of diverting portions of traffic that allows an exact validation. The diverted traffic affects not only travel time and the congested area but also the destinations, which permits the use of the compliance rate as an accurate fit parameter for exact description of traffic patterns from measurement data.

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Zhang, Kuilin, Hani S. Mahmassani, and Chung-Cheng Lu. "Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (2008): 86–94. http://dx.doi.org/10.3141/2085-10.

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This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.

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Kwon, Jaimyoung, Benjamin Coifman, and Peter Bickel. "Day-to-Day Travel-Time Trends and Travel-Time Prediction from Loop-Detector Data." Transportation Research Record: Journal of the Transportation Research Board 1717, no. 1 (2000): 120–29. http://dx.doi.org/10.3141/1717-15.

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An approach is presented for estimating future travel times on a freeway using flow and occupancy data from single-loop detectors and historical travel-time information. Linear regression, with the stepwise-variable-selection method and more advanced tree-based methods, is used. The analysis considers forecasts ranging from a few minutes into the future up to an hour ahead. Leave-a-day-out cross-validation was used to evaluate the prediction errors without underestimation. The current traffic state proved to be a good predictor for the near future, up to 20 min, whereas historical data are more informative for longer-range predictions. Tree-based methods and linear regression both performed satisfactorily, showing slightly different qualitative behaviors for each condition examined in this analysis. Unlike preceding works that rely on simulation, real traffic data were used. Although the current implementation uses measured travel times from probe vehicles, the ultimate goal is an autonomous system that relies strictly on detector data. In the course of presenting the prediction system, the manner in which travel times change from day to day was examined, and several metrics to quantify these changes were developed. The metrics can be used as input for travel-time prediction, but they also should be beneficial for other applications, such as calibrating traffic models and planning models.

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Wu, Zifeng, Laurence R. Rilett, and Yifeng Chen. "Evaluating the Impact of Highway-Railway Grade Crossings on Travel Time Reliability on a Highway Network Level." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 10 (2018): 1–11. http://dx.doi.org/10.1177/0361198118792756.

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Highway-rail grade crossings (HRGCs) have a range of safety and operational impacts on highway traffic networks. This paper illustrates a methodology for evaluating travel-time reliability for the routes and networks affected by trains traveling through HRGCs. A sub-area network including three HRGCs is used as the study network, and a simulation model calibrated to local traffic conditions and signal preemption strategies using field data is used as the platform to generate travel time data for analysis. Time-dependent reliability intervals for route travel time are generated based on route travel-time means and standard deviations. OD level reliability is calculated using a generic reliability engineering approach for parallel and series systems. The route travel time reliability results can be provided as real-time traffic information to assist drivers’ route-choice decisions. The OD level reliability is a way to quantify the impact of HRGCs on highway network operation. This effort fills the gap of reliability research for HRGCs on the route and sub-area network level, and contributes to improving the efficiency of decision-making for both traffic engineers and drivers.

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Ma, Zhengfeng, Darong Huang, Changguang Li, and Jianhua Guo. "Travel Time Reliability-Based Signal Timing Optimization for Urban Road Traffic Network Control." Mathematical Problems in Engineering 2020 (December 1, 2020): 1–11. http://dx.doi.org/10.1155/2020/8898062.

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Due to increasing traffic demand, many metropolitan areas are experiencing extensive traffic congestion, which demands for efficient traffic signal timing and optimization. However, conventional efficiency measure-based signal optimization cannot handle the ubiquitous uncertainty in the road networks, demanding for the incorporation of reliability measures into signal optimization, which is still in its early stage. Therefore, targeting this issue, based on the recent studies on recognizing travel time reliability (TRR) as an important reliability measure of road networks, a travel time reliability-based urban road traffic network signal timing optimization model is proposed in this paper, with the objective function to optimize a TTR measure, i.e., buffer time index. The proposed optimization model is solved using the heuristic particle swarm optimization approach. A case study is conducted using microscopic traffic simulation for a road network in the City of Nanjing, China. Results demonstrate that the proposed optimization model can improve travel time reliability of the road traffic network and the efficiency of the road traffic network as well. Future studies are recommended to expand the integration of travel time reliability into traffic signal timing optimization.

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Jayan, Akhilesh, and Sasidharan Premakumari Anusha. "Travel Time Prediction under Mixed Traffic Conditions Using RFID and Bluetooth Sensors." Periodica Polytechnica Transportation Engineering 48, no. 3 (2019): 276–89. http://dx.doi.org/10.3311/pptr.13779.

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Travel time information is an integral part in various ITS applications such as Advanced Traveler Information System, Advanced Traffic Management Systems etc. Travel time data can be collected manually or by using advanced sensors. In this study, suitability of Bluetooth and RFID (Radio Frequency Identifier) sensors for data collection under mixed traffic conditions as prevailing in India is explored. Reliability analysis was carried out using Cumulative Frequency Diagrams (CFDs) and buffer time index along with evaluation of penetration rate and match rate of RFID and Bluetooth sensors. Further, travel time of cars for a subsequent week was predicted using the travel time data obtained from RFID sensors for the present week as input in ARIMA modeling method. For predicting the travel time of different vehicle categories, relationships were framed between travel time of different vehicle categories and travel time of cars determined from RFID sensors. The stream travel time was then determined considering the travel time of all vehicle categories. The R-Square and MAPE values were used as performance measure for checking the accuracy of the developed models and were closer to one and lower respectively, indicating the suitability of the RFID sensors for travel time prediction under mixed traffic conditions. The developed estimation schemes can be used as part of travel time information applications in real time Intelligent Transportation System (ITS) implementations.

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Дисертації з теми "Travel time (Traffic engineering) Simulation"

Lu, Chenxi. "Improving Analytical Travel Time Estimation for Transportation Planning Models." FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/237.

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This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.

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Henclewood, Dwayne Anthony. "Real-time estimation of arterial performance measures using a data-driven microscopic traffic simulation technique." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44792.

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Traffic congestion is a one hundred billion dollar problem in the US. The cost of congestion has been trending upward over the last few decades, but has experienced slight decreases in recent years partly due to the impact of congestion reduction strategies. The impact of these strategies is however largely experienced on freeways and not arterials. This discrepancy in impact is partially linked to the lack of real-time, arterial traffic information. Toward this end, this research effort seeks to address the lack of arterial traffic information. To address this dearth of information, this effort developed a methodology to provide accurate estimates of arterial performance measures to transportation facility managers and travelers in real-time. This methodology employs transmitted point sensor data to drive an online, microscopic traffic simulation model. The feasibility of this methodology was examined through a series of experiments that were built upon the successes of the previous, while addressing the necessary limitations. The results from each experiment were encouraging. They successfully demonstrated the method's likely feasibility, and the accuracy with which field estimates of performance measures may be obtained. In addition, the method's results support the viability of a "real-world" implementation of the method. An advanced calibration process was also developed as a means of improving the method's accuracy. This process will in turn serve to inform future calibration efforts as the need for more robust and accurate traffic simulation models are needed. The success of this method provides a template for real-time traffic simulation modeling which is capable of adequately addressing the lack of available arterial traffic information. In providing such information, it is hoped that transportation facility managers and travelers will make more informed decisions regarding more efficient management and usage of the nation's transportation network.

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Hodges, Fiona. "Travel time budgets in an urban area /." Connect to thesis, 1994. http://eprints.unimelb.edu.au/archive/00000227.

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Chan, Ping-ching Winnie. "The value of travel time savings in Hong Kong." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23425003.

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Wu, Seung Kook. "Adaptive traffic control effect on arterial travel time charateristics." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31839.

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Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2010. Committee Chair: Hunter, Michael; Committee Member: Guensler, Randall; Committee Member: Leonard, John; Committee Member: Rodgers, Michael; Committee Member: Roshan J. Vengazhiyil. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Misra, Rajul. "Toward a comprehensive representation and analysis framework for non-worker activity-travel pattern modeling /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Li, Lok-man Jennifer. "Schedule delay of work trips in Hong Kong an empirical analysis /." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B40988041.

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Choy, Wing-pong. "A review of the value of travel time in Hong Kong." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31937068.

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Chan, Ping-ching Winnie, and 陳冰淸. "The value of travel time savings in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31954789.

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Adams, David Lewis. "Integrating travel time reliability into management of highways." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 52 p, 2008. http://proquest.umi.com/pqdweb?did=1459913561&sid=3&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Книги з теми "Travel time (Traffic engineering) Simulation"

Rakha, Hesham. Transit signal priority project, phase II: Field and simulation evaluation results. Virginia Transportation Research Council, 2006.

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Kittelson & Associates. Evaluating alternative operations strategies to improve travel time reliability. Transportation Research Board, 2013.

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Shawn, Turner, United States. Federal Highway Administration. Office of Highway Information Management., and Texas Transportation Institute, eds. Travel time data collection handbook. Office of Highway Information Management, Federal Highway Administration, U.S. Dept. of Transportation, 1998.

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Second Strategic Highway Research Program (U.S.), Kimley-Horn and Associates, and Parsons Brinckerhoff, eds. Guide to integrating business processes to improve travel time reliability. Transportation Research Board, 2011.

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Small, Kenneth A. Valuation of travel-time savings and predictability in congested conditions for highway user-cost estimation. National Academy Press, 1999.

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Hyŏn, Pak. Yebi tʻadangsŏng chosa chaengchŏm yŏnʼgu. Hanʼguk Kaebal Yŏnʼguwŏn, 2006.

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Arnold, E. D. Changes in travel in the Shirley Highway corridor, 1983-1986. Virginia Transportation Research Council, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1987.

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North, American Travel Monitoring Exhibition and Conference (2000 Middleton Wis ). North American Travel Monitoring Exhibition and Conference, TRB Data Committee's mid-year meetings, August 27-31, 2000, Middleton, WI. Wisconsin Dept. of Transportation, 2000.

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Dowling, Richard G. Incorporating travel-time reliability into the congestion management process: A primer. United States Department of Transportation, Federal Highway Administration, 2015.

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Kralich, Susana. Accesibilidad hogar-trabajo en el Gran Buenos Aires: Un estudio de caso en el partido de La Matanza. Instituto de Geografía, Universidad de Buenos Aires, Facultad de Filosofia y Letras, 1993.

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Частини книг з теми "Travel time (Traffic engineering) Simulation"

Amrutsamanvar, Rushikesh, Gaurang Joshi, Shriniwas S. Arkatkar, and Ravi Sekhar Chalumuri. "Empirical Travel Time Reliability Assessment of Indian Urban Roads." In Recent Advances in Traffic Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_11.

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Prajapati, N. I., A. K. Sutariya, and H. R. Varia. "Travel Time Delay Study on Congested Urban Road Links of Ahmedabad City." In Recent Advances in Traffic Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_8.

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Zhuang, Zhihan, Ying Wang, Junjie Wei, Junru Cai, and Xueyun Ling. "Traffic Scheduling Simulation System for Time-Sensitive Networking." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4229-8_30.

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Nguyen, Tuan Nam, and Gerhard Reinelt. "On Travel Time Functions for Mixed Traffic Systems Dominated by Motorcycles." In Modeling, Simulation and Optimization of Complex Processes HPSC 2015. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67168-0_12.

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Saw, Krishna, Bhimaji K. Katti, and Gaurang J. Joshi. "Fuzzy Rule-Based Travel Time Estimation Modelling: A Case Study of Surat City Traffic Corridor." In Recent Advances in Traffic Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_12.

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Bari, Chintaman Santosh, Parth Jhaveri, Satyendra Kumar Sharma, Shubham Gupta, and Ashish Dhamaniya. "Use of Toll Transaction Data for Travel Time Prediction on National Highways Under Mixed Traffic Conditions." In Recent Advances in Traffic Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4464-4_36.

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Sen, Saptarshi, and Sudip Kumar Roy. "Quantifying Travel Time Reliability of Air-Conditioned Public Buses in Urban Area: A Case Study of Kolkata." In Recent Advances in Traffic Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_25.

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Park, Chulsun, Juho Lee, Tianye Tan, and Sungkown Park. "Simulation of Scheduled Traffic for the IEEE 802.1 Time Sensitive Networking." In Lecture Notes in Electrical Engineering. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0557-2_8.

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Deb Nath, Rudra Pratap, Hyun-Jo Lee, Nihad Karim Chowdhury, and Jae-Woo Chang. "Modified K-Means Clustering for Travel Time Prediction Based on Historical Traffic Data." In Knowledge-Based and Intelligent Information and Engineering Systems. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15387-7_55.

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Haberl, Michael, Felix Hofinger, and Martin Fellendorf. "Effects of Traffic Signal Coordination on Traffic- and Emission-Related Evaluation Parameters." In Lecture Notes in Mobility. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-89444-2_38.

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Abstract A good coordination of traffic signals can reduce waiting times, the number of stops and accelerations, and thus increase travel speeds, which can lead to a reduction in fuel consumption and air pollutant emissions. To investigate the effects of traffic signal coordination on traffic and emission parameters, simulation studies are advantageous over time-consuming field tests to quantify and evaluate quickly, safely and cost-effectively a large number of different input variables, such as intersection distances, traffic volumes and different signal control configurations. This paper describes the findings of an extensive simulation study in which a microscopic traffic flow simulation model was coupled with an emission model. Through the simulation of a range of scenarios, the model is used to investigate the influence of inter alia traffic volume, signal coordination schemes and signal parameters on carbon dioxide, nitrogen oxides and particulate matter emissions along an arterial road equipped with a series of traffic lights. Results showed that shorter distances between the signalized intersections led to about 20% higher emission values. Furthermore, different cycle times and their effects on emissions were investigated, whereby higher cycle times led to lower values of about 14% less emissions.

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Тези доповідей конференцій з теми "Travel time (Traffic engineering) Simulation"

Bao, Chun, Feixing Fan, Yang Tang, et al. "Travel time characteristics of subway passenger flow and short-time passenger flow forecast." In Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), edited by Xiantao Xiao and Jia Yao. SPIE, 2024. https://doi.org/10.1117/12.3054827.

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Agüero Barrantes, Pablo, and Richard Christenson. "Real-Time Hybrid Simulation of Damped Transportation Structures." In IABSE Congress, San José 2024: Beyond Structural Engineering in a Changing World. International Association for Bridge and Structural Engineering (IABSE), 2024. https://doi.org/10.2749/sanjose.2024.0268.

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Support structures for traffic signs, luminaires, and traffic signals often rely on flexible elements with low damping. These elements are susceptible to wind-induced vibrations, leading to fatigue and potential failure, which can impact traffic flow and mobility. Current designs involve large structural components and connections, proving inefficient and costly for owners and managers. An economical solution is the use of passive dampers to reduce the size of these structural elements. However, testing such dampers faces limitations in both laboratory settings and open field-testing facilities. This paper presents the outcomes of applying Real-Time Hybrid Simulation to ancillary structures, incorporating a Stockbridge-type passive damper as a viable option for comprehensive testing. Noteworthy advantages include reduced installation effort and time, along with the capability to test a predetermined and broad range of structures.

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Ishibashi, Hiroki, Takuya Hashimoto, Haruhisa Ishigami, Ichiro Iwaki, and Nobuhiro Jinnai. "Social Impact Assessment of Bridges Based on Detour Simulation Using Virtual Person Trip Data." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.3094.

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This paper proposes a methodology for assessing the potential social impact of bridge closures using privacy-protected virtual person trip data. The increases in travel distance and time and CO2 emissions due to detours of individual agents are calculated by performing a path search for each trip using the Dijkstra algorithm on the road network modeled with graph theory assuming the closure of the analyzed bridges. The potential social impact of bridges is quantified as the economic loss estimated based on the increases in travel distance and time and CO2 emissions. As an illustrative example, the potential social impacts of the bridges located in the Tohoku region of Japan are evaluated. The estimation results demonstrate that even bridges with relatively low traffic volume can cause significant economic loss when closed to traffic. The proposed methodology contributes to the prioritization of bridge management strategies.

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Constantinescu, Augustin, Mario Trotea, and Ionuţ Daniel Geonea. "Optimizing a Route of Public Passenger Transportation in the Area Drobeta Turnu Severin Municipality." In Advances in Engineering and Management. Trans Tech Publications Ltd, 2025. https://doi.org/10.4028/p-b5lko9.

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In the present paper, an optimization method is presented for a route (a line) for public transport of people within the radius of the Municipality of Drobeta Turnu Severin. The current conditions regarding the public transport of people were presented, measurements were made on the route and trips were surveyed, these data being necessary to establish the input values for optimization. The most important result of this optimization is the establishment of an optimal distance between the stations on the analyzed route, a distance that ensures a minimum travel time for passengers, at an acceptable commercial speed and imposed by the traffic conditions specific to the Municipality of Drobeta Turnu Severin.

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Kim, Minjung, and Hwan-Sik Yoon. "Model Predictive Optimal Traffic Signal Control Using Neural Network Based on Real-Time Measured Traffic Information." In ASME 2024 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2024. https://doi.org/10.1115/imece2024-146048.

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Abstract Optimal traffic signal control can improve network-wide fuel efficiency as well as alleviate traffic congestion. Traditionally, traffic signals have been controlled using limited vehicle detection sensors; however, the recent advent of advanced traffic detection technologies, such as the sensor fusion approach that combines multimodal data from cameras and radars, enables the real-time collection of rich traffic information. The real-time traffic data can be used to predict future traffic flow and control traffic signals for optimization targets such as traffic throughput, total travel time, and network-wide fuel consumption. This paper proposes a Model Predictive Control (MPC) algorithm for optimal traffic signal control at real-world traffic intersections. The proposed traffic signal MPC method employs a Neural Network-based future traffic volume prediction model to minimize network-wide fuel consumption and unnecessary vehicle waiting time. Genetic Algorithm (GA) is used as a global optimization method to determine optimal control parameters including the prediction time horizon, optimal weights for road preference and waiting time of vehicles. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in SUMO, a high-fidelity traffic simulation environment. The traffic simulation model is based on a real-world traffic network incorporating the real vehicle detection range of a state-of-the-art sensor technology within the network. The incoming traffic flow in the model is simulated using actually measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed traffic signal MPC method can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control method. Additionally, incorporating truck priority in the control algorithm leads to further improvements in fuel consumption reduction.

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Solomon, J. H., P. Gonzalez-Mohino, F. Amirouche, and D. Zavattero. "Feasibility Analysis and Computer Simulation of an Automated Bus Route." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33186.

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Traffic congestion in major cities is a major problem which is growing steadily every year. It is clear that something must be done to curb this trend. Several different concepts are being investigated which can be used to minimize congestion and improve the traffic flow. Automation of the bus system represents one of those methods, and is the focus of this paper. Currently, public opinion of the quality of bus services is generally not perceived as adequate. Buses generally travel about 60% of the speed of other vehicles, and more often than not adherence to schedule is difficult to achieve. The consequence is that people choose to take personal transportation instead, causing increased congestion. Automation seeks to address this issue by offering decreased travel times, increased schedule adherence, and greater overall convenience compared to the current bus systems. The concept of automation is based on expanding upon the ideas of Bus Rapid Transit (BRT) and making the system as efficient as possible.

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V, Vishnuvardhan, Geethanjali A, Ramesh SB, Vamsi M, Jeevitha M, and Aravind SM. "Enhancing Secure Communication in VANETs with Blockchain and Privacy using PSOACO Algorithm." In Sri Venkatesa Perumal College of Engineering and Technology. International Journal of Advanced Trends in Engineering and Management, 2024. http://dx.doi.org/10.59544/hlww7128/svpcet24p19.

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This study explores the optimization of shortest paths in intelligent transportation systems using a hybrid Particle Swarm Optimization and Ant Colony Optimization (PSOACO) algorithm. The study focuses on improving traffic flow efficiency and minimizing travel time by finding the most optimal routes for vehicles. Utilizing simulations and algorithmic analysis, the PSOACO algorithm is evaluated for its effectiveness in guiding vehicles through complex traffic networks. The results demonstrate significant improvements in route planning and traffic coordination, showcasing the potential of hybrid optimization techniques in enhancing intelligent transportation systems’ performance. This study contributes to the advancement of efficient routing strategies, critical for managing traffic congestion and improving overall transportation system efficiency.

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K, Kavitha A., Jijin A, and Munavar Fairooz C. "Review on Factors Influencing Passenger Behavior on Vehicle Sharing." In 6th International Conference on Modeling and Simulation in Civil Engineering. AIJR Publisher, 2023. http://dx.doi.org/10.21467/proceedings.156.5.

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Transportation experts are attempting to promote a variety of sustainable travel alternatives in order to mitigate the negative effects of private vehicle use and traffic congestion. One of the widely accepted solutions is to endorse the public transit system. The vehicle share system introduced in recent times is proving to be another way by which the same can be achieved without compromising people’s utility and convenience as in the case of public transit. The purpose of this review paper was to convey the necessity of a thorough study of the elements that influence vehicle share demand. Several studies have focused on relevant factors that influence traveler’s mode selection, as well as their attitudes and traits about choosing various vehicle-sharing systems. This paper reviews recent studies in the literature on non-motorized (bicycle) bike-sharing, motorized (bike-taxi) bike-sharing, and car-sharing.

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Torres-Cruz, Alberto, Dirk F. de Lange, and Hugo I. Medellín-Castillo. "Development of a Virtual Platform to Evaluate the Performance of an Electrical Vehicle." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-52408.

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Virtual simulations of electrical vehicle performance help to optimize vehicle design, by studying and predicting the effects of parameter variations on the vehicle performance, in order to find an optimum balance between the cost and benefit of design decisions. In this work, the development of a virtual platform to evaluate the performance of an electrical vehicle is presented and applied to the study of public urban transportation. The aim is to analyze the requirements and optimize specifications for a light weight, energy efficient, autonomous vehicle without energy supply along the trajectory, except in the stations. Virtual platforms for vehicle performance have been developed before, and in many cases characteristic velocity profiles are used as a reference, according to the traffic environment in which the vehicle will operate. Vehicle analysis and design is focused on feasibility of the vehicle to be able to follow the prescribed velocity profile. In the present study, the evaluation is instead based on the cost/benefit relationship for an urban transport vehicle on traffic-free trajectories, enabling to adjust and optimize the velocity profiles in order to optimize the energy use while minimizing travel time. Therefore, the virtual platform is focused on the calculation of the net energy usage, the travel time and the system cost corresponding to an electrical vehicle with different battery and ultra-capacitor energy storage capacities, regeneration and storage of brake energy and an automatic governor for autonomous vehicle control. The influence of design parameters, such as the installed motor power, energy storage capacity, vehicle weight, passenger load and vehicle control strategy on the time schedule and energy efficiency is studied. However, the effort does not aim for a straight forward optimization of efficiency or minimization of travel time. In fact, energy optimization often conflicts with the travel time optimization. Therefore, both are analyzed simultaneously in order to assist in the search for an optimum compromise. In addition, the results are interpreted in terms of the overall obtained benefits of travel time reduction or optimization of the energy use, in contrast with the corresponding increment of the investment cost of the vehicle related to the implementation of the studied parameter variation. Specific trajectory profiles, including height profiles can be defined for optimization of the vehicle system for application in specific locations with specific geographic conditions.

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Hu, Ta-Yin, and Wei-Ming Ho. "Simulation-based travel time prediction model for traffic corridors." In 2009 12th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, 2009. http://dx.doi.org/10.1109/itsc.2009.5309719.

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Звіти організацій з теми "Travel time (Traffic engineering) Simulation"

Arhin, Stephen, Babin Manandhar, Kevin Obike, and Melissa Anderson. Impact of Dedicated Bus Lanes on Intersection Operations and Travel Time Model Development. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2040.

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Over the years, public transit agencies have been trying to improve their operations by continuously evaluating best practices to better serve patrons. Washington Metropolitan Area Transit Authority (WMATA) oversees the transit bus operations in the Washington Metropolitan Area (District of Columbia, some parts of Maryland and Virginia). One practice attempted by WMATA to improve bus travel time and transit reliability has been the implementation of designated bus lanes (DBLs). The District Department of Transportation (DDOT) implemented a bus priority program on selected corridors in the District of Columbia leading to the installation of red-painted DBLs on corridors of H Street, NW, and I Street, NW. This study evaluates the impacts on the performance of transit buses along with the general traffic performance at intersections on corridors with DBLs installed in Washington, DC by using a “before” and “after” approach. The team utilized non-intrusive video data to perform vehicular turning movement counts to assess the traffic flow and delays (measures of effectiveness) with a traffic simulation software. Furthermore, the team analyzed the Automatic Vehicle Locator (AVL) data provided by WMATA for buses operating on the study segments to evaluate bus travel time. The statistical analysis showed that the vehicles traveling on H Street and I Street (NW) experienced significantly lower delays during both AM (7:00–9:30 AM) and PM (4:00–6:30 PM) peak hours after the installation of bus lanes. The approximation error metrics (normalized squared errors) for the testing dataset was 0.97, indicating that the model was predicting bus travel times based on unknown data with great accuracy. WMATA can apply this research to other segments with busy bus schedules and multiple routes to evaluate the need for DBLs. Neural network models can also be used to approximate bus travel times on segments by simulating scenarios with DBLs to obtain accurate bus travel times. Such implementation could not only improve WMATA’s bus service and reliability but also alleviate general traffic delays.

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Kodupuganti, Swapneel R., Sonu Mathew, and Srinivas S. Pulugurtha. Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.1802.

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The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.

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Pulugurtha, Srinivas S., Abimbola Ogungbire, and Chirag Akbari. Modeling and Evaluating Alternatives to Enhance Access to an Airport and Meet Future Expansion Needs. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2120.

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The continued growth of air travel calls for the incessant construction effort at many airports and their surroundings. Thus, there is a need to determine how airports can better manage existing infrastructure to accommodate this growth. This study, therefore, focuses on (1) investigating how changes in transportation infrastructure have affected travel time reliability (TTR) of the surrounding road network within the airport vicinity over time, and, (2) exploring selected unconventional intersection designs and proposing new inbound/outbound access routes from the nearby major roads to the airport. The efficiency of road networks that surrounds large airports is discussed using Charlotte Douglas International Airport (CLT) as the case study. Firstly, an assessment of how transportation projects impact link-level travel time reliability (TTR) was performed using historical data. Secondly, an assessment of how future transportation projects would affect the traffic in the airport vicinity was performed. A simulation network was developed using the Vissim software, where the peak-hour turning movement counts were used with the existing signal design to replicate and calibrate the base scenario. Unconventional intersection designs such as continuous flow intersections (CFI), mini-roundabouts, and restricted crossing U-turn (RCUT) intersections were considered along with selected bridge design options to determine the impact on TTR. The results were compared with the conventional signalized intersection design. The connectivity projects led to an increase in TTR measures at most of the links within its vicinity after the project’s completion of the project. Similarly, parking areas exhibited the same characteristics, including those used by ridesharing companies. The simulation model showed that unconventional designs like RCUT and direct entry-exit ramps effectively reduced delay as well as the number of stops, increasing our understanding of how expansion projects affect TTR and potentially improving infrastructure optimization.

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