scholarly journals Travel Time Reliability for Urban Networks: Modelling and Empirics

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Fangfang Zheng ◽  
Xiaobo Liu ◽  
Henk van Zuylen ◽  
Jie Li ◽  
Chao Lu

The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data collected by Automated Number Plate Recognition (ANPR) cameras. We further investigate the network-level travel time reliability by connecting the network reliability measures such as the weighted standard deviation of travel time rate and the weighted skewness of travel time rate distributions with network traffic characteristics (e.g., the network density). The weighting is done with respect to the number of signalized intersections on a trip. A clear linear relation between the weighted average travel time rate and the weighted standard deviation of travel time rate can be observed for different time periods with time-varying demand. Furthermore, both the weighted average travel time rate and the weighted standard deviation of travel time rate increase monotonically with network density. The empirical findings of the relation between network travel time reliability and network traffic characteristics can be possibly applied to assess traffic management and control measures to improve network travel time reliability.

2015 ◽  
Vol 6 (2) ◽  
pp. 87-109 ◽  
Author(s):  
Renato Redondi ◽  
Paolo Malighetti ◽  
Stefano Paleari

The objective of this work is to evaluate the accessibility of European municipalities by air transport. We focus on travels that typically require the use of air transport by computing the quickest paths between any pair of municipalities separated by more than 500 km. The total travel time includes three components: i) travel by car or High Speed Train to reach the origin airport, ii) travel by air from the origin airport to the destination airport, including waiting times when no direct flight is available and iii) travel by car or High Speed Train from the destination airport to the municipality of destination. For each territorial unit, we calculate the population-weighted average travel time to reach any other municipality in Europe.


2018 ◽  
Vol 10 (11) ◽  
pp. 3982 ◽  
Author(s):  
Shicheng Li ◽  
Jian Gong ◽  
Qinghai Deng ◽  
Tianyu Zhou

Constructing the Qinghai–Tibet Railway (QTR) was a landmark project and was beneficial to the sustainable development of the Third Pole. To understand the sustainable development of remote regions by the provision of railway, we studied the QTR’s impact on accessibilities and economic linkages for four cities in the Third Pole, Xining, Golmud, Nagqu, and Lhasa, and between these four cities and 29 capital cities in mid-eastern China. First, employing average shortest travel time (ASTT) and weighted average travel time (WATT) as indicators, we calculated the railway-based accessibilities for June 2006 and January 2013. Then, using a gravity model, railway-based economic linkages were determined. The results demonstrate that: (i) ASTT for Xining–Golmud decreased by 4.14 h from June 2006 to January 2013. Both ASTT and WATT indicated that the accessibilities of the four cities and between these four cities and 29 capital cities in mid-eastern China improved significantly, and the spatial disparity in accessibility for the four cities decreased, which increased the balance and sustainability of the transportation system; (ii) the average contribution rate of the QTR to improving economic linkages for six routes among the four cities was 25.29%, with the Xining–Nagqu and Nagqu–Lhasa linkages improving most significantly; (iii) the QTR strengthened economic linkages between the four cities and mid-eastern cities. Because of the QTR, the economic linkages between the four cities and 29 capital cities increased 27.58% on average. The spatial disparity in interurban economic linkages also decreased. Transporting products from Tibet should be promoted to strengthen the sustainability of economic growth.


2018 ◽  
Vol 232 ◽  
pp. 02055
Author(s):  
Xinyue Fan ◽  
Qi Shen ◽  
Qinglong He

Based on the big data collected by the video detection equipment, the network topology table of the city level video detection equipment is constructed by using the time relation and the spatial position relation of the data. By using the steepest descent method and adaptive method, the travel confidence time randomness model is constructed, which can describe whether a traveler can finish his travel time on time. It overcomes the shortcomings of the existing travel time reliability calculation model, which is difficult to combine with the actual use of video detection equipment data, then examples analysis are followed. The results show that, for the data collected by the video detection device, the travel confidence time randomness model is more accurate than the existing models. It can describe the probability of the traveler arriving at the destination in a given time more accurately, which can be used to identify illegal parking road and provide a reliable basis for traffic management departments in traffic planning, dividing road network status and traffic situation prediction.


2017 ◽  
Vol 2616 (1) ◽  
pp. 91-103 ◽  
Author(s):  
PilJin Chun ◽  
Michael D. Fontaine

In September 2015, the Virginia Department of Transportation instituted an active traffic management system on I-66 in Northern Virginia. I-66 is a major commuter route into Washington, D.C., that experiences significant recurring and nonrecurring congestion. The active traffic management system sought to manage existing capacity dynamically and more effectively with hard shoulder running, advisory variable speed limits, lane use control signs, and queue warning systems. An initial before-and-after analysis of the system’s operational effectiveness was performed with probe-based travel time data from the provider, INRIX, and used records from the active traffic management’s traffic operations center. On weekdays, statistically significant improvements were often observed during off-peak periods, but conditions did not improve during peak periods. Weekends showed the greatest improvements, with travel times and travel time reliability measures improving by 10% to 14%. Segment-level analysis revealed that most of the benefits were attained because of the use of hard shoulder running outside of the peak periods, which created additional capacity on I-66. Benefits due to advisory variable speed limits were inconclusive because of limited data.


Author(s):  
Xiaoqiang Kong ◽  
William L. Eisele ◽  
Yunlong Zhang ◽  
Daren B. H. Cline

This study represents the first research to investigate the impacts of two critical determinants—level of congestion and travel time reliability—on routing decisions with two groups of truck drivers having different levels of awareness of the real-time and the historical traffic conditions on available routes. The research analyzed 14,538 global positioning system devices recording trips on the I-495 crossing through Maryland, Virginia, and Washington, DC, and 2,166 trips in the Dallas area, to explore how truck drivers make routing decisions based on real-time travel time and reliability information by applying a binary logistic regression model. Researchers found that for truck drivers who are not familiar with the historical traffic and travel time conditions on available routes, real-time congestion information is a significant factor in their routing decision-making process, while travel time reliability is not a major consideration. For frequent truck drivers who are familiar with the historical traffic and travel time conditions on available routes, travel time reliability is a significant factor in their routing decision-making process, and traffic congestion information is not a significant factor. These results bring more accuracy to travel time prediction and provide valuable insights into traffic management and reliability performance measures. Moreover, this research provides statistical evidence proving the potential value of delivering travel time reliability information to drivers, traffic management agencies, and navigation map developers.


2021 ◽  
Author(s):  
Matheus Bernardino de Araújo ◽  
Matheus Monteiro Silveira ◽  
Rafael Lopes Gomes

Intelligent Transport Systems (ITS) arose as a modern solution to traffic jams and vehicle accidents in the urban environment. A key part of the ITS is Traffic Management (TM), which concerns the planning and route definition of the vehicle. Existing TM solution focuses specifically on urban traffic information, ignoring the issues related to the network infrastructure and the applications at the top of it. Within this context, this paper presents a vehicle routing and re-routing strategy, called DINO, that considers both travel time of vehicles on the roads and the active network flows in the network, aiming to dynamically bring a suitable balance between travel time and packet delivery through a heuristic. The experiments performed suggest that DINO improves the packet delivery of the applications while reduces the average travel time of vehicles.


2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Tangyi Guo ◽  
Jie Yang ◽  
Liu He ◽  
Kun Tang

The rapid development of bike sharing has posed some challenges to the traffic management on campus. The bike sharing on campus has problems such as messy parking, and some buildings in the peak hours have no bikes to borrow. Thus, alternative parking spots are proposed based on the layout principle of parking spots for bicycles. An optimization model of the layout of campus bike-sharing parking spots with travel time and construction cost as the optimization goal is established, and the branch and bound algorithm is used to solve the model. Finally, the study analysis is carried out by optimizing the layout of the bike-sharing parking spot of Nanjing University of Science and Technology. The results show that, after optimizing the layout of parking spots, the average travel time of users is reduced by 6.0%, and the total construction cost is reduced by 27.3%. While being convenient for campus bike-sharing users, it also provides scientific decision-making support for the campus traffic management.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qi Zhang ◽  
Hong Chen ◽  
Hongchao Liu ◽  
Wei Li ◽  
Yibin Zhang

Origin-destination- (O-D-) based travel time reliability (TTR) is fundamental to next-generation navigation tools aiming to provide both travel time and reliability information. While previous works are mostly focused on route-based TTR and use either ad hoc data or simulation in the analyses, this study uses open-source Uber Movement and Weather Underground data to systematically analyze the impact of rainfall intensity on O-D-based travel time reliability. The authors classified three years of travel time data in downtown Boston into one hundred origin-destination pairs and integrated them with the weather data (rain). A lognormal mixture model was applied to fit travel time distributions and calculate the buffer index. The median, trimmed mean, interquartile range, and one-way analysis of variance were used for quantification of the characteristics. The study found some results that tended to agree with the previous findings in the literature, such that, in general, rain reduces the O-D-based travel time reliability, and some seemed to be unique and worthy of discussion: firstly, although in general the reduction in travel time reliability gets larger as the intensity of rainfall increases, it appears that the change is more significant when rainfall intensity changes from light to moderate but becomes fairly marginal when it changes from normal to light or from moderate to extremely intensive; secondly, regardless of normal or rainy weather, the O-D-based travel time reliability and its consistency in different O-D pairs with similar average travel time always tend to improve along with the increase of average travel time. In addition to the technical findings, this study also contributes to the state of the art by promoting the application of real-world and publicly available data in TTR analyses.


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