Stochastic User Equilibrium Model with Implicit Travel Time Budget Constraint

2008 ◽  
Vol 2085 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Tony E. Smith ◽  
Chao-Che Hsu ◽  
Yueh-Ling Hsu
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Time Budget ◽  
User Equilibrium ◽  
Time Constraints ◽  
Stochastic User Equilibrium ◽  
Trade Offs ◽  
Travel Time Budget ◽  
Travel Decisions ◽  
The Impact

Although time constraints on travel behavior have been widely recognized, little effort has been made to incorporate such constraints into the traditional stochastic user equilibrium (SUE) framework. The major objective of this research is to fill this gap by incorporating travel time constraints into the SUE model by means of a nonlinear perceived travel time function. This modified model, designated the travel time budget model, focuses primarily on discretionary travel behavior (such as shopping trips) and hence also allows the possibility of deferring travel decisions by incorporating an additional choice alternative designated the shop-less-frequently alternative. This model is compared with the traditional SUE model by using a simulated travel scenario on a test network designed to reflect a practical planning situation. The simulation shows that when attractiveness levels are increased by the introduction of a new shopping opportunity, the presence of travel time constraints can lead to significantly smaller predicted travel volumes than those of the traditional SUE model. More important, it shows that the overall pattern of travel can be quite different. In particular, travel to the shopping destination with enhanced attractiveness can actually decrease for some origin locations. The findings suggest that when an attempt is made to evaluate the impact of planning alternatives on future traffic patterns, it is vital to consider not only the cost of time itself but also the time trade-offs between travel and other human activities.

scholarly journals Parking Pricing and Model Split under Uncertainty

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Chengjuan Zhu ◽  
Bin Jia ◽  
Linghui Han ◽  
Ziyou Gao
Keyword(s):  
Travel Time ◽  
Confidence Level ◽  
Time Budget ◽  
Route Choice ◽  
Analytic Solutions ◽  
User Equilibrium ◽  
Travel Times ◽  
Modal Split ◽  
Parking Pricing ◽  
The Impact

In order to investigate different route choice criteria in a competitive highway/park-and-ride (P&R) network with uncertain travel times on the road, a bilevel programming model for solving the problem of determining parking fees and modal split is presented. In the face of travel time uncertainty, travelers plan their trips with a prespecified on-time arrival probability. The impact of three route choice criteria: the mean travel time, the travel time budget, and mean-excess travel time, is compared for parking pricing and modal split. The model at user equilibrium is described as a minimization model. And the analytic solutions are given. Analytic solutions show that both flow and travel time at equilibrium are independent of the price difference of travel expense on money. The main findings from the numerical results are elaborated. While given a confidence level, the flow on the highway changed significantly with the criteria, although the differences of the travel times are small. Travelers can be guided to choose their modes coordinately by improving the quality of the transit service. The optimal parking fees can be affected markedly by the confidence level. Finally, the influence of the log-normal distribution parameters is tested and analyzed.

scholarly journals Stochastic Congestion Pricing among Multiple Regions: Competition and Cooperation

2013 ◽  
Vol 2013 ◽  
pp. 1-11
Author(s):  
Hua Wang ◽  
Wei Mao ◽  
Hu Shao
Keyword(s):  
Social Welfare ◽  
Travel Time ◽  
Demand Uncertainty ◽  
Transportation Network ◽  
Congestion Pricing ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Stochastic User Equilibrium ◽  
Multiple Regions ◽  
The Impact

Previous studies of road congestion pricing problem assume that transportation networks are managed by a central administrative authority with an objective of improving the performance of the whole network. In practice, a transportation network may be comprised of multiple independent local regions with relative independent objectives. In this paper, we investigate the cooperative and competitive behaviors among multiple regions in congestion pricing considering stochastic conditions; especially demand uncertainty is taken into account in transportation modelling. The corresponding congestion pricing models are formulated as a bilevel programming problem. In the upper level, congestion pricing model either aims to maximize the regional social welfare in competitive schemes or attempts to maximize the total social welfare of multiple regions in cooperative schemes. In the lower level, travellers are assumed to follow a reliability-based stochastic user equilibrium principle considering risks of late arrival under uncertain conditions. Numerical examples are carried out to compare the effects of different pricing schemes and to analyze the impact of travel time reliability. It is found that cooperative pricing strategy performs better than competitive strategy in improving network performance, and the pricing effects of both schemes are quite sensitive to travel time reliability.

scholarly journals Impact of Travel Time Constraints on Taste Heterogeneity and Non-Linearity in Simple Time–Cost Trade-Offs

2018 ◽  
Vol 2672 (49) ◽  
pp. 135-145
Author(s):  
Jeff Tjiong ◽  
Stephane Hess ◽  
Thijs Dekker ◽  
Manuel Ojeda Cabral
Keyword(s):  
Travel Time ◽  
Time Budget ◽  
Discrete Choice Models ◽  
Time Constraints ◽  
Preference Heterogeneity ◽  
Choice Data ◽  
Effective Measure ◽  
Trade Offs ◽  
Opt Out ◽  
Functional Forms

Discrete choice models are a key technique for estimating the value of travel time (VTT). Often, stated choice data are used in which respondents are presented with trade-offs between travel time and travel cost and possibly additional attributes. There is a clear possibility that some respondents experience time constraints, leaving some of the presented options unfeasible. A model not incorporating information on these constraints would explain choices for faster and more expensive options as an indication that those respondents have a higher VTT when in reality they may be forced to select the more expensive option as a result of their personal constraints. This paper puts forward the hypothesis that this can have major impacts on findings in terms of heterogeneity in VTT measures. This paper examines via simulation the bias in VTT estimates and especially preference heterogeneity when such constraints are (not) accounted for. Empirical evidence is provided that preference heterogeneity is confounded with the travel budget impact on the availabilities of alternatives, and it is shown that there is a risk of producing biased estimates for appraisal VTT if studies do not explicitly model choice set formation. The inclusion of an opt-out alternative could be an effective measure to reduce the bias. This paper also explores the potential use of non-linear functional forms to capture the time budget impacts.

scholarly journals Design of Signal Timing Plan for Urban Signalized Networks including Left Turn Prohibition

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Qinrui Tang ◽  
Bernhard Friedrich
Keyword(s):  
Travel Time ◽  
Treatment Options ◽  
User Equilibrium ◽  
Signal Timing ◽  
Stochastic User Equilibrium ◽  
Left Turn ◽  
Traffic Demand ◽  
Total Travel Time ◽  
Left Turns ◽  
Demand Patterns

Urban road networks may benefit from left turn prohibition at signalized intersections regarding capacity, for particular traffic demand patterns. The objective of this paper is to propose a method for minimizing the total travel time by prohibiting left turns at intersections. With the flows obtained from the stochastic user equilibrium model, we were able to derive the stage generation, stage sequence, cycle length, and the green durations using a stage-based method which can handle the case that stages are sharing movements. The final output is a list of the prohibited left turns in the network and a new signal timing plan for every intersection. The optimal list of prohibited left turns was found using a genetic algorithm, and a combination of several algorithms was employed for the signal timing plan. The results show that left turn prohibition may lead to travel time reduction. Therefore, when designing a signal timing plan, left turn prohibition should be considered on a par with other left turn treatment options.

Quantifying the Impact of the COVID-19 Pandemic on Passenger Vehicle Drivers’ Willingness to Pay for Travel Time Savings and Reliability

2021 ◽  
pp. 036119812110388
Author(s):  
Tristan Cherry ◽  
Mark Fowler ◽  
Claire Goldhammer ◽  
Jeong Yun Kweun ◽  
Thomas Sherman ◽  
...  
Keyword(s):  
Willingness To Pay ◽  
Travel Time ◽  
Travel Behavior ◽  
Local Governments ◽  
Consumer Preferences ◽  
Stated Preference ◽  
Travel Time Reliability ◽  
Travel Time Savings ◽  
Time Savings ◽  
The Impact

The COVID-19 pandemic has fundamentally disrupted travel behavior and consumer preferences. To slow the spread of the virus, public health officials and state and local governments issued stay-at-home orders and, among other actions, closed nonessential businesses and educational facilities. The resulting recessionary effects have been particularly acute for U.S. toll roads, with an observed year-over-year decline in traffic and revenue of 50% to 90% in April and May 2020. These disruptions have also led to changes in the types of trip that travelers make and their frequency, their choice of travel mode, and their willingness to pay tolls for travel time savings and travel time reliability. This paper describes the results of travel behavior research conducted on behalf of the Virginia Department of Transportation before and during the COVID-19 pandemic in the National Capital Region of Washington, D.C., Maryland, and Northern Virginia. The research included a stated preference survey to estimate travelers’ willingness to pay for travel time savings and travel time reliability, to support forecasts of traffic and revenue for existing and proposed toll corridors. The survey collected data between December 2019 and June 2020. A comparison of the data collected before and during the pandemic shows widespread changes in travel behavior and a reduction in willingness to pay for travel time savings and travel time reliability across all traveler types, particularly for drivers making trips to or from work. These findings have significant implications for the return of travelers to toll corridors in the region and future forecasts of traffic and revenue.

Privacy Implication of Location-Based Service: Multi-Class Stochastic User Equilibrium and Incentive Mechanism

2019 ◽  
Vol 2673 (12) ◽  
pp. 256-265
Author(s):  
Haitao Hu ◽  
Zhanbo Sun ◽  
Runzhe Liu ◽  
Xia Yang
Keyword(s):  
Travel Time ◽  
Incentive Mechanism ◽  
Time Estimation ◽  
User Equilibrium ◽  
Travel Time Estimation ◽  
Stochastic User Equilibrium ◽  
Location Based Service ◽  
Modeling Framework ◽  
Privacy Concerns ◽  
Traffic Guidance

As a tool to assist traffic guidance and improve service quality, location-based service (LBS) platforms such as route navigation apps rely heavily on the collection and analysis of users’ location/trajectory information, which may evoke privacy concerns. Because of such privacy concerns, users may choose not to provide their information. In certain cases, this may lead to the problem of insufficient data for LBS applications (e.g., travel time estimation). To address this issue, the paper develops a modeling framework to quantify the levels of privacy for mixed user groups and proposes an incentive mechanism to encourage users to provide their location/trajectory information. It is assumed that LBS users have smaller travel time perception error but experience some extra privacy costs compared with the non-LBS users. A bi-level optimal incentive model with stochastic user equilibrium and elastic demand is developed to capture the mixed behavior of multi-class network users. The problem is solved using a meta-heuristic approach combined of genetic algorithm, successive average algorithm, and multiple behavior equilibrium assignment algorithm. The results reveal that the modeling framework can capture the mixed behavior of groups with different privacy levels. The proposed incentive mechanism is able to ensure sufficient data, and simultaneously minimize the required incentive.

Drone Security

2021 ◽  
pp. 352-384
Author(s):  
Marc Lacoste ◽  
David Armand ◽  
Fanny Parzysz ◽  
Loïc Ferreira ◽  
Ghada Arfaoui ◽  
...  
Keyword(s):  
Supply Chain ◽  
Network Connectivity ◽  
Time Constraints ◽  
Security Market ◽  
Technical Design ◽  
Market Growth ◽  
Resource Limitations ◽  
Trade Offs ◽  
Security Challenges ◽  
The Impact

This chapter explores the security challenges of the drone ecosystem. Drones raise significant security and safety concerns, both design-time and run-time (e.g., supply-chain, technical design, standardization). Two broad classes of threats are considered, on drones and using drones (e.g., to attack critical infrastructures or vehicles). They involve both professional and non-professional drones and lead to various types of attacks (e.g., IoT-type vulnerabilities, GPS spoofing, spying, kinetic attacks). Trade-offs involving hardware and software solutions to meet efficiency, resource limitations, and real-time constraints are notably hard to find. So far, protection solutions remain elementary compared to the impact of attacks. Advances in technologies, new use cases (e.g., enhancing network connectivity), and a regulatory framework to overcome existing barriers are decisive factors for sustainable drone security market growth.

scholarly journals Simulation of the Daily Activity Plans of Travelers Using the Park-and-Ride System and Autonomous Vehicles: Work and Shopping Trip Purposes

2020 ◽  
Vol 10 (8) ◽  
pp. 2912 ◽  
Author(s):  
Jairo Ortega ◽  
Jamil Hamadneh ◽  
Domokos Esztergár-Kiss ◽  
János Tóth
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Transport Mode ◽  
Park And Ride ◽  
Activity Chain ◽  
Private Car ◽  
Transport Modes ◽  
The Impact

The preferences of travelers determines the utility of daily activity plans. Decision-makers can affect the preference of travelers when they force private car users to use park-and-ride (P&R) facilities as a way of decreasing traffic in city centers. The P&R system has been shown to be effective in reducing uninterrupted increases in traffic congestion, especially in city centers. Therefore, the impacts of P&R on travel behavior and the daily activity plans of both worker and shopper travelers were studied in this paper. Moreover, autonomous vehicles (AVs) are a promising technology for the coming decade. A simulation of the AV as part of a multimodal system, when the P&R system was integrated in the daily activity plans, was carried out to determine the required AV fleet size needed to fulfill a certain demand and to study the impacts of AVs on the behavior of travelers (trip time and distance). Specifically, a group of travelers, who use private cars as their transport mode, was studied, and certain modifications to their daily activity plans, including P&R facilities and changing their transport mode, were introduced. Using the MATSim open-source tool, four scenarios were simulated based on the mentioned modifications. The four scenarios included (1) a simulation of the existing transport modes of the travelers, (2) a simulation of their daily activity plans when their transport modes were changed to AVs, (3) a simulation of the travelers, when P&R facilities were included in their activity chain plans, and (4) a simulation of their daily activity plans, when both P&R and AVs were included in their activity chain plans. The result showed that using the P&R system increased overall travel time, compared with using a private car. The results also demonstrated that using AVs as a replacement for conventional cars reduced travel time. In conclusion, the impact of P&R and AVs on the travel behavior of certain travelers was evaluated in this paper.

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