Relevant bibliographies by topics / TRAVEL / Road Travel

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'TRAVEL / Road Travel'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 January 2023

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Journal articles on the topic "TRAVEL / Road Travel"

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Mindell, Jennifer S. "Road travel casualties." Journal of Transport & Health 6 (September 2017): 7–9. http://dx.doi.org/10.1016/j.jth.2017.08.004.

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Yusra, Cut liliiza, Muhammad Isya, and Renni Anggraini. "ANALISIS PENGARUH KERUSAKAN JALAN TERHADAP KECEPATAN PERJALANAN." Jurnal Arsip Rekayasa Sipil dan Perencanaan 1, no. 3 (September 11, 2018): 46–55. http://dx.doi.org/10.24815/jarsp.v1i3.11761.

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Road damage that occurs in some road segments that cause huge losses, especially for road users. It is worth noting that there is no decrease in road quality due to road surface damage. The purpose of this study is to analyze the effect of the rate of damage with the speed of travel. This research took place on Lueng Mane - Tadu Raya Road segment, Kuala Tadu Sub-District, Nagan Raya District over 2000 meters divided into 20 segments with a segment length of 100 meters. Primary data were collected by actual field survey that is road geometric data, extensive damage to roads and travel speed. The results show that road damage is very influential to the speed of travel, as seen in segment 11 with the value of 18 very ugly road conditions with travel speed reached 28,324 km/h, while in segment 6 PCI value of 100 perfect road conditions (Excellent) travel speed reaches 59,90 km/h, so the equation Y = 0,3202x + 21,264. This shows that the higher the level of damage the lower the speed of travel, the lower the level of damage the higher the speed of travel.
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Chen, Peng, Rui Tong, Guangquan Lu, and Yunpeng Wang. "Exploring Travel Time Distribution and Variability Patterns Using Probe Vehicle Data: Case Study in Beijing." Journal of Advanced Transportation 2018 (2018): 1–13. http://dx.doi.org/10.1155/2018/3747632.

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Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network.
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Roni, T. S., M. I. Ramli, and S. A. Adisasmitha. "Selection Model of Use of the Elevated Toll Road Route in Makassar City." IOP Conference Series: Earth and Environmental Science 1117, no. 1 (December 1, 2022): 012076. http://dx.doi.org/10.1088/1755-1315/1117/1/012076.

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Abstract This study aims to analyze the selection of the A.P. Pettarani Elevated Toll Road route. Data collection was carried out by distributing questionnaires and reviewing respondents to describe the travel characteristics of A.P. Pettarani Elevated Toll Road respondents using Ms. Excel to process the data. The results showed that in the selection of A.P. Pettarani elevated toll road to the airport, and the dominant respondents entered the toll road through the Bakti road where the traveler was aged 50-59 years old, with the last education being a bachelor’s degree, working as an officer, with an income of IDR 4.5M-5.5M. The travel costs incurred are IDR20-30K, travel distance of 7-11 km, travel time of 10-20 minutes, and travel frequency of 15-20 times a month to travel for work/business. In the selection of travel routes using the A.P. Pettarani elevated toll road to the port, the dominant respondents entered the overpass toll road through the Rappocini road, where the traveler was aged 20-29 years old, with the last education being a bachelor’s degree, working as an officer, with an income of IDR 4.5M-5.5M. The travel costs incurred are IDR20-30K, travel distance of 7-11 km, travel time of 20-30 minutes, and travel frequency of 15-20 times to travel for work/business.
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Koryagin, Mark, and Vladimir Katargin. "OPTIMIZATION OF AN URBAN TRANSPORT SYSTEM ON THE CONDITION OF DIFFERENT GOALS OF MUNICIPAL AUTHORITIES, OPERATORS AND PASSENGERS." TRANSPORT 31, no. 1 (March 22, 2016): 63–69. http://dx.doi.org/10.3846/16484142.2016.1125946.

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A control system of urban passenger transport is considered. The system participants are a passenger flow, a transport operator and municipal authorities. The participants’ strategies include a travel mode choice, a frequency of public transport service, and a road capacity. Objective functions are transport costs, public transport profit, road costs, and travel time. The passenger flow heterogeneity is based on the value of time that has an exponential distribution. The total costs of passenger flow depend on the probability of the travel mode choice. The dependence between travel time, roads capacity, and traffic is based on Greenshields model. The authorities’ objective consists of travel time and road costs, which can be changed by the road capacity. The game theoretic approach is applied to describe the control system. The existence of Nash equilibrium for coalition-free games for two (the passenger flow and the authorities and three (with addition of public transport) players is proved. The characteristics of urban passenger transport were studied based on a numerical example.
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Nyaki, Prosper S., Hannibal Bwire, and Nurdin K. Mushule. "Travel Time Reliability of Bus Operation in Heterogeneous Traffic Conditions of Dar es Salaam City, Tanzania." LOGI – Scientific Journal on Transport and Logistics 11, no. 2 (November 1, 2020): 44–55. http://dx.doi.org/10.2478/logi-2020-0014.

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AbstractThe assessment of travel time reliability enables precise prediction of travel times, better activity scheduling and decisions for all users of the road network. Furthermore, it helps to monitor traffic flow as a crucial strategy for reducing traffic congestion and ensuring high-quality service in urban roads. Travel time reliability is a useful reference tool for evaluating transport service quality, operating costs and system efficiency. However, many analyses of travel time reliability do not provide true travel variation under heterogeneous traffic flow conditions where traffic flow is a mixture of motorized and non-motorized transport. This study analysed travel time reliability under heterogeneous traffic conditions. The travel reliabilities focused on passenger waiting time at bus stops, in-vehicle travel time, and delay time at intersections which were analysed using buffer time, standard deviation, coefficient of variation, and planning time. The data used were obtained from five main bus routes in Dar es Salaam. The results indicate low service reliability in the outbound directions compared to inbound directions. They also intend to raise awareness of policy-makers about the situation and to make them shift from expanding road networks towards optimising road operations.
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Nian, Guangyue, Jian Sun, and Jianyun Huang. "Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model." ISPRS International Journal of Geo-Information 10, no. 12 (December 10, 2021): 829. http://dx.doi.org/10.3390/ijgi10120829.

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Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.
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Intiruk, Narong, Sukree Sinthupinyo, and Wasan Pattara-Atikom. "Travel Time Estimation on a Link without Real-Time Data by Correlated Links." Advanced Materials Research 931-932 (May 2014): 531–35. http://dx.doi.org/10.4028/www.scientific.net/amr.931-932.531.

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This paper presents a novel method to estimate travel time on a road segment using information from other road segments. This method is useful especially in the case that real-time traffic on such road segment is not available. The proposed method is based on the correlation between the road segment itself and the most related road segment. We measure the relation between road segments by dynamic time warping algorithm and apply the K-Nearest-Neighbor algorithm to select the best neighbor segment to estimate the travel time on the target road segment. We found that the best attributes set that can measure the correlation between road sections consists of location of the road segments, day of the week, and current time. The link correlation results can be used as reference data to determine the travel time on the roads that are related.
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Zong, Ping, Yao Han, and Chenbo Xu. "Research on Optimal Route Planning for Self-Driving Tour Based on Road Network Structure." Security and Communication Networks 2022 (September 29, 2022): 1–11. http://dx.doi.org/10.1155/2022/6588288.

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Today’s social and economic development continues to improve people’s quality of life, and private cars are widely popularized, and self-driving tours have developed. The rapid development of self-driving travel has played an important role in the development of the national economy, and self-driving travel has become popular. Because the development of self-driving tours has caused some problems, the road network structure has become more and more complex, and the roads have become very congested. Especially during the holidays, there are more private cars in tourist attractions and the roads are more congested. How to use the information of roads and attractions and then choose the optimal travel route becomes particularly important. In response to this problem, we first analyze the topology of the road network, then analyze the accessibility of scenic spots and related factors that affect self-driving travel, and use the A∗ algorithm, Dijkstra algorithm, and other calculation methods to calculate the optimal path. The experiment found that there are many influencing factors of self-driving travel, and the road network structure has the greatest influence on it. The A∗ algorithm has obvious advantages over the Dijkstra algorithm.
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Roddis, S. M., A. J. Richardson, and C. D. Mcpherson. "Obtaining Travel Intensity Profiles from Household Travel Survey Data." Transportation Research Record: Journal of the Transportation Research Board 1625, no. 1 (January 1998): 95–101. http://dx.doi.org/10.3141/1625-12.

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Innovative ways to examine the spatiotemporal variations in road traffic, by using data from the Victorian Activity and Travel Survey (VATS), are presented. The approach is shown to offer significant advantages over traditional methods of analysis, such as observational surveys or roadside traffic counts. By linking the complete vehicle travel paths reported in VATS with the detailed demographic data of the respondents, a comprehensive understanding of travel and driver behavior is developed. The general methodology described is shown to be applicable to any travel data obtained from household travel surveys, especially where the origins and destinations of the recorded trips have been geocoded and stored in a geographic information system.
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Dissertations / Theses on the topic "TRAVEL / Road Travel"

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Sigakova, Ksenia. "Road Freight Transport Travel Time Prediction." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3031.

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Road freight transport travel time estimation is an important task in fleet management and traffic planning. Goods often must be delivered in a predefined time window and any deviation may lead to serious consequences. It is possible to improve travel time estimation by considering more factors that may affect it. In this thesis work we identify factors that may affect travel time, find possible sources of information about them, propose a model for estimating travel time of heavy goods vehicles, and verify this model on real data. As results, the experiments showed that considering time related and weather related factors, it is possible to improve accuracy of travel time estimation. Also, it was shown that the influence of a particular factor on travel time depended on the considered road segment. Furthermore, it was shown that different data mining algorithms should be applied for different road segments in order to get the best estimation.
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Atkins, S. T. "Travel behaviour : responses to direct road user charges." Thesis, University of Southampton, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370514.

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Alvarez, Patricio A. "A Methodology to Estimate Time Varying User Responses to Travel Time and Travel Time Reliability in a Road Pricing Environment." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/631.

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Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.
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Turner, Mark. "Motion sickness occurrence in public road transport." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326821.

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LeSage, Bernard C. "Optimization of vehicle suspension systems in off-road travel." Thesis, McGill University, 1989. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=55619.

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Meistre, Brent Arthur. "Road culture : an investigation of the road as a means of mental and physical exploration." Thesis, Rhodes University, 2000. http://eprints.ru.ac.za/2324/1/MEISTRE-MA-TR00-78.pdf.

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Chapter one considers various manifestations of the concept of ‘journey’ and how they have changed over history. The Odyssean journey that the hero undertakes to reach a point of self-realisation is investigated. This leads to a other discussion of types of journeys such as pilgrimages, as well as ‘wandering’. These are contrasted with the twentieth century perceptions of journey. Questions of travel are then dealt with: how the nature of the traveller's path has changed over the centuries, various points of travel and gender, and how in the last century solitary travel has been transformed into mass tourism. The second chapter deals specifically with the motorcar, the mobility it enables and how it has led to the rise of a roadside culture. Different factors that influenced the rise of the motorcar are looked at. The motorcar as a cell and eroticism and the car are also investigated. The twentieth century city, it's restructuring, as well as the highway systems is discussed. In Chapter Three, the sense of freedom that the motorcar created is considered in particular reference to escape, aimlessness, and road weariness, as well as the landscape as a symbol of freedom. This leads to a discussion on the notion of speed, the sense of power and the romanticisation of death in car crashes. Chapter Four investigates masculinity and the road. The frontier as a place in the psyche of the male is also dealt with. The road as a means of testing and regaining masculinity in the mid-twentieth century is considered. Issues of the male domination of the land and the feminine are discussed, with the chapter ending with a brief examination of the woman as traveller. Lastly the masters’ submission exhibition, entitled RODE is discussed with direct reference to the theories investigated in the previous chapters. Individual works as well as the methodology are looked at closely.
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Brunnemer, Kristin Carol. "Rewriting the road (auto)mobility and the road narratives of American writers of color /." Diss., UC access only, 2009. http://proquest.umi.com/pqdweb?index=135&did=1874459661&SrchMode=1&sid=1&Fmt=7&retrieveGroup=0&VType=PQD&VInst=PROD&RQT=309&VName=PQD&TS=1270492729&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.
Includes abstract. Includes bibliographical references (leaves 224-238). Issued in print and online. Available via ProQuest Digital Dissertations.
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Moyo, Norbert. "The potential network effects of travellers' responses to travel demand management measures." Thesis, University of Southampton, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274449.

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Safour, Aziza Ali. "Analysis of road user charging impacts on activity travel patterns in Libya." Thesis, University of Salford, 2011. http://usir.salford.ac.uk/26888/.

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In Libya, studies state that there is an increase in car ownership and this increase in traffic movement causes congestion which affects and can increase travelling time in large Libyan cities, particularly in Tripoli and Benghazi. Because of this the Government are requesting the establishment of a new policy that could be effective in reducing traffic problems at the present time and avoiding the amplification of traffic problems in the future. Currently, road user charging policy (RUC) is considered as a suitable tool for tackling urban traffic problems. Because of the reasons stated above, RUC can be applied in the urban areas of large Libyan cities in order to reduce traffic congestion problems. This study attempts to ascertain and document the perceived impacts of road user charging on an individual's daily activity travel patterns in urban areas by using one of the large Libyan cities (Benghazi) as the case study. The research methodology has been designed with the aim of identifying the existing transport conditions and the characteristics of activity travel patterns in Benghazi; establishing the views of transport policymakers and consultants toward RUC, and establishing and documenting the perceived impacts of road user charging on individuals' daily activity travel patterns. A triangulation method was employed to collect data, a survey of a road user charging experiment in Benghazi was conducted with the road users in the central business district (CBD) and semi-structured interviews have been carried out with transport policymakers. The findings indicate that RUC policy can have a positive impact in reducing traffic congestion with a reduction in car trips crossing the restricted areas during the peak period by around 35.5%. However the road users had different choices to make; they could decide to pay the toll and continue with their current travel pattern, pay the toll for some days, or not pay at all. Around 68% of drivers chose to pay the toll for all days or for some days. On the other hand, 32% of the drivers did not pay the toll at all and avoided the payment by choosing other alternatives. The majority of drivers who decided to avoid the toll chose to change their travel time, to before the restricted period. Furthermore, the analysis of travel durations during the field study proved that the lognormal distribution is the best suited distribution for the data of the durations of travel. Regarding the attitudes toward RUC, the study concluded that 70% of the transport policymakers, consultants and academics thought that RUC may greatly assist in the reduction of traffic congestion. However, more than a quarter of respondents (27%) stated that they did not have enough information or knowledge on how RUC could impact on the travel patterns of road users. In addition, the study concluded that the main reasons for non-implementation of a road user charging policy are a lack of public transport, a lack of knowledge on RUC policy and the culture of the community. It has been stated that although the Ministry of Transport in Libya has established a number of projects aiming to improve the road conditions and public transport services, the condition of roads still needs to be improved. Despite these limitations, there are a number of benefits which can be obtained from the implementation of RUC in large Libyan cities, particularly in Tripoli and Benghazi. To implement the road user charging scheme successfully from the beginning the transport policymakers could use the guidelines that have been developed in this study to identify the main issues, requirements and needs of road user charging before the process begins and these guidelines will be the first step in the implementation of road user charging in Libya.
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Al, Adaileh Mohammad Ali. "A Travel Time Estimation Model for Facility Location on Real Road Networks." Ohio University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1557421387196019.

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Books on the topic "TRAVEL / Road Travel"

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Royston, Angela. Road travel. London: Macdonald Educational, 1986.

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Wood, Tim. Road travel. New York: Thomson Learning, 1993.

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Clymer, Theodore. A road to travel. Lexington, Mass: Silver, Burdett & Ginn Inc., 1987.

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Pollard, Michael. Travel by road and rail. Basingstoke: Macmillan, 1986.

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Shanghai Hengshan Road travel guide. Shanghai: Shanghai People's Fine Arts Pub., 2005.

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Organisation for Economic Co-operation and Development., ed. Road travel demand: Meeting the challenge. Paris: Organisation for Economic Co-operation and Development, 2002.

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Feleo, Anita B. Two for the road: Travel tales. Pasig City, Philippines: Published and exclusively distributed by Anvil Pub., 1998.

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Strawberry road. Tokyo: Kodansha International, 1991.

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Pybus, Cassandra. Raven road. St Lucia, Qld: University of Queensland Press, 2001.

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Road magic. Woodward, OK: S. Foss, 1993.

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Book chapters on the topic "TRAVEL / Road Travel"

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Barton, Susan. "Road Travel." In Travel and Tourism in Britain, 1700–1914, 1–4. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003112976-1.

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Wilkie, Fiona. "‘Motorvating’: Road Travel." In Performance, Transport and Mobility, 83–119. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137476890_4.

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Mogridge, Martin J. H. "Road Building." In Travel in Towns, 274–81. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-11798-7_10.

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Mogridge, Martin J. H. "Road Speeds." In Travel in Towns, 15–42. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-11798-7_2.

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Mogridge, Martin J. H. "Road Pricing." In Travel in Towns, 148–80. London: Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-11798-7_6.

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Gershwin, M. Eric, and Edwin L. Klingelhofer. "Travel, School, and on the Road." In Living Allergy Free, 225–35. Totowa, NJ: Humana Press, 1992. http://dx.doi.org/10.1007/978-1-4612-0399-5_15.

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Penha, James. "The Privilege of the Open Road." In Philosophy, Travel, and Place, 223–26. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98225-0_14.

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Lerin, Pablo Martinez, Daisuke Yamamoto, and Naohisa Takahashi. "Encoding Travel Traces by Using Road Networks and Routing Algorithms." In Intelligent Interactive Multimedia: Systems and Services, 233–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29934-6_23.

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Rubin, Jonathan. "Connected Autonomous Vehicles: Travel Behavior and Energy Use." In Road Vehicle Automation 3, 151–62. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40503-2_12.

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Li, Lei, Xiaofang Zhou, and Kevin Zheng. "Finding Least On-Road Travel Time on Road Network." In Lecture Notes in Computer Science, 137–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46922-5_11.

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Conference papers on the topic "TRAVEL / Road Travel"

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Wells, I. "Travel information highway." In Eleventh International Conference on Road Transport Information and Control. IEE, 2002. http://dx.doi.org/10.1049/cp:20020204.

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Yearworth, M. "Travel information highway." In Tenth International Conference on Road Transport Information and Control. IEE, 2000. http://dx.doi.org/10.1049/cp:20000101.

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Morton, S. "Automated Travel Time Estimation." In EAGE Winter Symposium - Reservoir Geophysics, the Road Ahead. European Association of Geoscientists & Engineers, 1996. http://dx.doi.org/10.3997/2214-4609.201406832.

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Ravish, Roopa, Prajwal Nadagouda, Kiran Hombal, Lavanya Ramkumar, Priya Nayak, Preet Shah, Rakshith Jayakumar, Pragnya Suresh, and Shanta Rangaswamy. "IoT Based Road Travel Time Detection." In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2018. http://dx.doi.org/10.1109/icacci.2018.8554804.

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Šimunović, Ljupko, Mario Ćosić, Dino Šojat, and Julijan Jurak. "Population synthesis in activity-based travel demand." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1150.

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A Synthetic Population is first part of creating travel demand model by using activity-based approach. Population synthesis is application of algorithms that expanded representative samples of people or household with characterises (such as gender, car ownership, age or ethnicity etc.) to entire area of researching. Because of complexity of people decisions before or during travel, one attribute is not enough to fully describe what factors have impact on them. Population synthesis iterate a set of attributes for each person in the sample and after expansion and assigning weights create simulated people or household with their characteristic. Basic components are marginal distribution targets of household and person attributes, household and person samples and algorithm for selecting the sample records into a synthetic population such that the attributes of that population match the marginal targets. Goal of this paper is to present population synthesis and her importance for activity-based approach in travel demand modelling. The paper will consist of introduction, literature overview, presenting benefits and complexity of population synthesis, discussion and conclusion.
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Pfoser, Dieter, Sotiris Brakatsoulas, Petra Brosch, Martina Umlauft, Nektaria Tryfona, and Giorgos Tsironis. "Dynamic travel time provision for road networks." In the 16th ACM SIGSPATIAL international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1463434.1463513.

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Oda, T. "Travel time measurement using infrared vehicle detectors." In Eighth International Conference on Road Traffic Monitoring and Control. IEE, 1996. http://dx.doi.org/10.1049/cp:19960314.

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de Ruiter, J. C. C. "Automation of travel times calculation in the Netherlands." In Eleventh International Conference on Road Transport Information and Control. IEE, 2002. http://dx.doi.org/10.1049/cp:20020232.

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Li, Lun, Dong Wang, Zhu Xiao, and Xiaohong Li. "Urban Road Travel Time Prediction based on ELM." In 2016 5th International Conference on Advanced Materials and Computer Science (ICAMCS 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icamcs-16.2016.83.

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Sunderrajan, Abhinav, Jagannadan Varadarajan, and Kong Wei Lye. "Road Speed Profiling for Upfront Travel Time Estimation." In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018. http://dx.doi.org/10.1109/icdmw.2018.00100.

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Reports on the topic "TRAVEL / Road Travel"

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Kulwicki, Allison, and Vicki Gelfeld. AARP Travel Research: Road Trips. AARP Research, June 2015. http://dx.doi.org/10.26419/res.00106.001.

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Mathew, Sonu, and Srinivas S. Pulugurtha. Effect of Weather Events on Travel Time Reliability and Crash Occurrence. Mineta Transportation Institute, November 2022. http://dx.doi.org/10.31979/mti.2022.2035.

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The magnitude of the effect of adverse weather conditions on road operational performance varies with the type of weather condition and the road characteristics of the road links and adjacent links. Therefore, the relationship between weather and traffic is always a concern to traffic engineers and planners, and they have extensively explored ways to integrate weather information into transportation systems. Understanding the influence of weather on operational performance and safety helps traffic engineers and planners to proactively plan and manage transportation systems. The main objective of this research is to evaluate the effect of adverse weather conditions on travel time reliability and crash occurrence, by severity, using weather data, road data, travel time data, and crash data for North Carolina. The methodology and results from this research are useful for transportation system managers and planners to manage the traffic and improve safety under different weather conditions. They also help improve the functionality of weather-responsive management strategies like variable signs to indicate the change in reliability and safety under rainfall and low visibility conditions.
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Freitas, Carlos Otávio, Felipe de F. Silva, and Mateus C. R. Neves. A Stochastic Frontier Approach Applied to Farms to Selected Andean Countries. Inter-American Development Bank, September 2021. http://dx.doi.org/10.18235/0003660.

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In this paper, we estimate a stochastic production function for Bolivia, Ecuador, Colombia, and Peru to investigate whether road infrastructure affects farm technical inefficiency. We use agricultural censuses of Colombia and Bolivia in 2013 and 2014, respectively; national agricultural surveys in 2017 of both Ecuador and Peru; and data on the road network and travel time to the nearest town with 50,000 inhabitants or more. Our main findings are that irrigation increases the value of production and road network decreases farm technical inefficiency, that is, road density (travel time) increases (decreases) farm technical efficiency.
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Edwards, Frances, Joseph Szyliowicz, Dan Goodrich, William Medigovich, Liz Lange, and Autumn Anderton. Surface Transportation Supply Chain Security: Creating a Blueprint for Future Research. Mineta Transportation Institute, April 2021. http://dx.doi.org/10.31979/mti.2021.1937.

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Ninety percent of the world’s trade goods travel by surface transportation, using maritime, road and rail assets. The security of the goods in transit, the infrastructure supporting the movement, and the vehicles, are required to ensure that international commerce proceeds successfully. Much has been written about the surface supply chain itself, but little has focused on the security of these components. This report provides a guide for those wanting an increased understanding of the security issues that supply chain surface transportation systems confront and a blueprint to guide their future research.
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Agrawal, Asha Weinstein, Hilary Nixon, and Cameron Simmons. Investing in California’s Transportation Future: Public Opinion on Critical Needs. Mineta Transportation Institute, December 2020. http://dx.doi.org/10.31979/mti.2020.1861.

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In 2017, the State of California adopted landmark legislation to increase the funds available for transportation in the state: Senate Bill 1 (SB1), the Road Repair and Accountability Act of 2017. Through a combination of higher gas and diesel motor fuel taxes, SB1 raises revenue for four critical transportation needs in the state: road maintenance and rehabilitation, relief from congestion, improvements to trade corridors, and improving transit and rail services. To help state leaders identify the most important projects and programs to fund within those four topical areas, we conducted an online survey that asked a sample of 3,574 adult Californians their thoughts on how the state can achieve the SB1 objectives. The survey was administered from April to August 2019 with a survey platform and panel of respondents managed by Qualtrics. Quota sampling ensured that the final sample closely reflects California adults in terms of key socio-demographic characteristics and geographic distribution. Key findings included very strong support for improving all transportation modes, reducing air pollution and greenhouse gas emissions from transportation, and more convenient options to travel without driving. Respondents placed particular value on better maintenance for both local streets and roads, as well as highways. Finally, the majority of respondents assessed all types of transportation infrastructure in their communities as somewhat or very good.
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Liu, Hongrui, and Rahul Ramachandra Shetty. Analytical Models for Traffic Congestion and Accident Analysis. Mineta Transportation Institute, November 2021. http://dx.doi.org/10.31979/mti.2021.2102.

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In the US, over 38,000 people die in road crashes each year, and 2.35 million are injured or disabled, according to the statistics report from the Association for Safe International Road Travel (ASIRT) in 2020. In addition, traffic congestion keeping Americans stuck on the road wastes millions of hours and billions of dollars each year. Using statistical techniques and machine learning algorithms, this research developed accurate predictive models for traffic congestion and road accidents to increase understanding of the complex causes of these challenging issues. The research used US Accidents data consisting of 49 variables describing 4.2 million accident records from February 2016 to December 2020, as well as logistic regression, tree-based techniques such as Decision Tree Classifier and Random Forest Classifier (RF), and Extreme Gradient boosting (XG-boost) to process and train the models. These models will assist people in making smart real-time transportation decisions to improve mobility and reduce accidents.
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Mahlberg, Justin, Yaguang Zhang, Sneha Jha, Jijo K. Mathew, Howell Li, Jairaj Desai, Woosung Kim, et al. Development of an Intelligent Snowplow Truck that Integrates Telematics Technology, Roadway Sensors, and Connected Vehicle. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317355.

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The Indiana Department of Transportation (INDOT) manages and maintains over 28,000 miles of roadways. Maintenance of the roadways includes pavement repair in the summer as well as snow removal and de-icing in the winter. The prioritization of assets during winter storm events is crucial and impacts travel and safety. The objective of this project was to identify and develop tools INDOT could provide its operators to effectively perform winter operation de-icing activities. This project examined application methods and data to provide analytics and make data-driven decisions for state-wide deployment and operations. Discovery of calibration metrics partnered with fleetwide telematics enabled the development of analytic dashboards that allowed real-time evaluations and adjustments to be made during winter operation activities. These tools will allow the agency to better treat and enhance safety for road users.
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Nafakh, Abdullah Jalal, Franklin Vargas Davila, Yunchang Zhang, Jon D. Fricker, and Dulcy M. Abraham. Safety and Mobility Analysis of Rolling Slowdown for Work Zones: Comparison with Full Closure. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317380.

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There are times when the traffic lanes through a work zone must be kept clear for activities such as placing overhead beams, erecting overhead signs, and installing power lines, and other temporary roadway work activities. As an alternative to a full road closure, a rolling slowdown can typically provide up to 30 minutes to complete such activities without bringing approaching traffic to a complete halt. Using data from recent rolling slowdowns and full closures carried on the Indiana interstate network and a simulation approach, this study compares rolling slowdowns to full closures from safety and mobility standpoints. The study suggests that while rolling slowdowns are more impactful in terms of travel times, they are a safer option than full closures as they often form a forward moving shockwave causing, lower hard braking rates, and consequently a lower probability of causing a crash.
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Albrecht, Jochen, Andreas Petutschnig, Laxmi Ramasubramanian, Bernd Resch, and Aleisha Wright. Comparing Twitter and LODES Data for Detecting Commuter Mobility Patterns. Mineta Transportation Institute, May 2021. http://dx.doi.org/10.31979/mti.2021.2037.

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Local and regional planners struggle to keep up with rapid changes in mobility patterns. This exploratory research is framed with the overarching goal of asking if and how geo-social network data (GSND), in this case, Twitter data, can be used to understand and explain commuting and non-commuting travel patterns. The research project set out to determine whether GSND may be used to augment US Census LODES data beyond commuting trips and whether it may serve as a short-term substitute for commuting trips. It turns out that the reverse is true and the common practice of employing LODES data to extrapolate to overall traffic demand is indeed justified. This means that expensive and rarely comprehensive surveys are now only needed to capture trip purposes. Regardless of trip purpose (e.g., shopping, regular recreational activities, dropping kids at school), the LODES data is an excellent predictor of overall road segment loads.
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Speroni, Samuel, Asha Weinstein Speroni, Michael Manville, and Brian D. Taylor. Charging Drivers by the Gallon vs. the Mile: An Equity Analysis by Geography and Income in California. Mineta Transportation Institute, September 2022. http://dx.doi.org/10.31979/mti.2022.2238.

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This study used data from the 2017 National Household Travel Survey California Add-On sample to explore how replacing the current state vehicle fuel tax with a flat-per-mile-rate road-user charge (RUC) would affect costs for different kinds of households. We first estimated how household vehicle fuel efficiency, mileage, and fuel tax expenditures vary by geography (rural vs. urban) and by income. These findings were then used to estimate how much different types of households pay in the current per-gallon state fuel tax, what they would pay if the state were to replace fuel taxes with a flat-rate road-usage charge (RUC) that would generate revenues similar to the current state fuel tax (2.52¢ per mile driven), and the difference in household expenditures between the fuel tax and RUC. We find that rural households tend to drive more miles and own less fuel-efficient vehicles than urban ones, so they pay comparatively more in fuel tax and would pay more with the RUC as well. However, this rural/urban variation is less for the RUC than the fuel tax, so moving to a flat-rate RUC would redistribute some of the overall tax burden from rural households (that drive more miles in fuel-thirsty vehicles) to urban households (that drive fewer miles in more fuel-efficient vehicles). Transitioning from the fuel tax to RUC would also generally shift the fuel tax burden from lower-income to higher-income households, with one exception: expenditures would rise for low-income urban households. However, the variation in the tax incidence between the gas tax and RUC is quite modest, amounting to less than one dollar per week for both urban and rural households at all income levels.
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