scholarly journals Target-Oriented User Equilibrium Considering Travel Time, Late Arrival Penalty, and Travel Cost on the Stochastic Tolled Traffic Network

2021 ◽  
Vol 13 (17) ◽  
pp. 9992
Author(s):  
Xinming Zang ◽  
Zhenqi Guo ◽  
Jingai Ma ◽  
Yongguang Zhong ◽  
Xiangfeng Ji
Keyword(s):  
Travel Time ◽  
Policy Design ◽  
Route Choice ◽  
Travel Cost ◽  
User Equilibrium ◽  
Traffic Network ◽  
Utility Model ◽  
Late Arrival ◽  
Choice Decision ◽  
New Perspective

In this paper, we employ a target-oriented approach to analyze the multi-attribute route choice decision of travelers in the stochastic tolled traffic network, considering the influence of three attributes, which are (stochastic) travel time, (stochastic) late arrival penalty, and (deterministic) travel cost. We introduce a target-oriented multi-attribute travel utility model for this analysis, where each attribute is assigned a target by travelers, and travelers’ objective is to maximize their travel utility that is determined by the achieved targets. Moreover, the interaction between targets is interpreted as complementarity relationship between them, which can further affect their travel utility. In addition, based on this travel utility model, a target-oriented multi-attribute user equilibrium model is proposed, which is formulated as a variational inequality problem and solved with the method of successive average. Target for travel time is determined via travelers’ on-time arrival probability, while targets for late arrival penalty and travel cost are given exogenously. Lastly, we apply the proposed model on the Braess and Nguyen–Dupuis traffic networks, and conduct sensitivity analysis of the parameters, including these three targets and the target interaction between them. The study in this paper can provide a new perspective for travelers’ multi-attribute route choice decision, which can further show some implications for the policy design.

scholarly journals A Traffic Restriction Scheme for Enhancing Carpooling

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Dong Ding ◽  
Bin Shuai
Keyword(s):  
Genetic Algorithm ◽  
Traffic Congestion ◽  
Route Choice ◽  
Travel Cost ◽  
User Equilibrium ◽  
Bilevel Program ◽  
Traffic System ◽  
Factors Influencing ◽  
Simple Network

For the purpose of alleviating traffic congestion, this paper proposes a scheme to encourage travelers to carpool by traffic restriction. By a variational inequity we describe travelers’ mode (solo driving and carpooling) and route choice under user equilibrium principle in the context of fixed demand and detect the performance of a simple network with various restriction links, restriction proportions, and carpooling costs. Then the optimal traffic restriction scheme aiming at minimal total travel cost is designed through a bilevel program and applied to a Sioux Fall network example with genetic algorithm. According to various requirements, optimal restriction regions and proportions for restricted automobiles are captured. From the results it is found that traffic restriction scheme is possible to enhance carpooling and alleviate congestion. However, higher carpooling demand is not always helpful to the whole network. The topology of network, OD demand, and carpooling cost are included in the factors influencing the performance of the traffic system.

scholarly journals A Two-Class Stochastic Network Equilibrium Model under Adverse Weather Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chenming Jiang ◽  
Linjun Lu ◽  
Junliang He ◽  
Caimao Tan
Keyword(s):  
Travel Time ◽  
Equilibrium Model ◽  
Route Choice ◽  
Weather Condition ◽  
Weather Conditions ◽  
User Equilibrium ◽  
Network Equilibrium ◽  
Adverse Weather Conditions ◽  
Adverse Weather Condition ◽  
Adverse Weather

Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes a novel stochastic traffic network equilibrium model considering impacts of adverse weather conditions on roadway capacity and route choice criteria of two-class mixed roadway travellers on demand modes, in which the two-class route choice criteria root in travelers’ different network information levels (NILs). The actual route travel time (ARTT) and perceived route travel time (PRTT) are considered as the route choice criteria of travelers with perfect information (TPI) and travelers with bounded information (TBI) under adverse weather conditions, respectively. We then formulate the user equilibrium (UE) traffic assignment model in a variational inequality problem and propose a solution algorithm. Numerical examples including a small triangle network and the Sioux Falls network are presented to testify the validity of the model and to clarify the inner mechanism of the two-class UE model under adverse weather conditions. Managerial implications and applications are also proposed based on our findings to improve the operation efficiency of urban roadway network under adverse weather conditions.

Stochastic Traffic Assignment Model Based on Travel Time Reliability

2011 ◽  
Vol 130-134 ◽  
pp. 3716-3720
Author(s):  
Yi Ran Cheng ◽  
Yin Han ◽  
Xin Kai Jiang ◽  
Jia Lei Gu
Keyword(s):  
Travel Time ◽  
Equilibrium Model ◽  
Choice Behavior ◽  
Transportation Networks ◽  
Route Choice ◽  
User Equilibrium ◽  
Travel Time Reliability ◽  
Stochastic User Equilibrium ◽  
Model Based ◽  
Route Choice Behavior

Considering the un-deterministic transportation networks, the paper proposes the change of the route choice decisions under the stochastic transportation networks. The route choice behavior is described as a choice for a time shortest route which is subject to a time-reliability level. The paper also considered this new route choice behavior in the stochastic user equilibrium model, and proposed stochastic user equilibrium model based on the optimized reliability travel time route choice behavior in the stochastic networks. The equivalence and uniqueness of the solution of the model are demonstrated. Numerical results of a small network show that the proposed model can reflect the real traveler’s route choice behavior in stochastic transportation networks.

scholarly journals A Reliability-Based Network Equilibrium Model with Adaptive Risk-Averse Travelers

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Lei Zhao ◽  
Hongzhi Guan ◽  
Junze Zhu ◽  
Yunfeng Wei
Keyword(s):  
Travel Time ◽  
Time Distribution ◽  
Choice Behavior ◽  
Route Choice ◽  
Great Influence ◽  
User Equilibrium ◽  
Probability Density Distribution ◽  
Risk Averse ◽  
Route Choice Behavior ◽  
Travel Time Distribution

In this paper, route free-flow travel time is taken as the lower bound of route travel time to examine its impacts on budget time and reliability for degradable transportation networks. A truncated probability density distribution with respect to route travel time is proposed and the corresponding travel time budget (TTB) model is derived. The budget time and reliability are compared between TTB models with and without truncated travel time distribution. Under truncated travel time distribution, the risk-averse levels of travelers are adaptive, which are affected by the characteristics of the used routes besides the confidence level of travelers. Then, a TTB-based stochastic user equilibrium (SUE) is developed to model travelers’ route choice behavior. Moreover, its equivalent variational inequality (VI) problem is formulated and a route-based algorithm is used to solve the proposed model. Numerical results indicate that route travel time boundary produces a great influence on decision cost and route choice behavior of travelers.

The Impact of Traffic Information on Drivers’ Day-to-Day Route Choice Behavior

2011 ◽  
Vol 97-98 ◽  
pp. 925-930
Author(s):  
Shi Xu Liu ◽  
Hong Zhi Guan
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Choice Behavior ◽  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Statistical Characteristics ◽  
Traffic Information ◽  
Route Choice Behavior ◽  
The Impact

The influence of different traffic information on drivers’ day-to-day route choice behavior based on microscopic simulation is investigated. Firstly, it is assumed that drivers select routes in terms of drivers’ perceived travel time on routes. Consequently, the route choice model is developed. Then, updating the drivers’ perceived travel time on routes is modeled in three kinds of traffic information conditions respectively, which no information, releasing historical information and releasing predictive information. Finally, by setting a simple road network with two parallel paths, the drivers’ day-to-day route choice is simulated. The statistical characteristics of drivers’ behavior are computed. Considering user equilibrium as a yardstick, the effects of three kinds of traffic information are compared. The results show that the impacts of traffic information on drivers are related to the random level of driver’s route choice and reliance on the information. In addition, the road network cannot reach user equilibrium in three kinds of information. This research results can provide a useful reference for the application of traffic information system.

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 Route Choice Model Considering Generalized Travel Cost Based on Game Theory

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Feng Yu-qin ◽  
Leng Jun-qiang ◽  
Xie Zhong-Yu ◽  
Zhang Gui-e ◽  
He Yi
Keyword(s):  
Game Theory ◽  
Travel Time ◽  
Road Network ◽  
Choice Model ◽  
Route Choice ◽  
Weight Coefficient ◽  
Travel Cost ◽  
Emission Factors ◽  
Relational Model ◽  
The Cost

This paper aims at testing the influence of emission factors on travelers’ behavior of route choice. The generalized travel cost is defined as the linear weighted sum of emission factors, travel time, and travel time reliability. The relational model of exhaust volume and traffic volume is established using the BPR (Bureau of Public Road) function to calculate the cost of travel regarding emission. The BPR function is used to measure the road segment travel time, while the reliability is used to quantify the cost of travel time fluctuation. At last, the route choice model considering the generalized travel cost is established based on the game theory. The calculating and analyzing of results under a miniature road network show that the weight coefficient of travel cost influences the travelers’ behavior of route choice remarkably and the route choice model which takes emission into account can reduce the exhaust of road network effectively, approximately 11.4% in this case.

scholarly journals Experimental Study of Day-to-Day Route-Choice Behavior: Evaluating the Effect of ATIS Market Penetration

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Shixu Liu ◽  
Lidan Guo ◽  
Said M. Easa ◽  
Hao Yan ◽  
Heng Wei ◽  
...  
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Choice Behavior ◽  
Route Choice ◽  
User Equilibrium ◽  
Traffic Information ◽  
Market Penetration ◽  
Network Information ◽  
Route Choice Behavior ◽  
Average Travel Time

This paper examines the travelers’ day-to-day route-choice behavior with Advanced Traveler Information Systems (ATIS) through laboratory-like experimental method. Five groups of route-choice behavior experiments are designed to simulate actual daily behavior of travelers. In the experiment, subjects are provided with different levels of the complete road network information to simulate the proportion of subjects equipped with ATIS equipment (i.e., ATIS market penetration) and choose the routes repeatedly. The subject’s route-choice behavior under different proportions of complete road network information is analyzed, and the strategy of releasing such complete information is determined when the performance of road network system is the best. The Braess network which consists of three routes was used in the experiment and analysis. The results show that the fluctuation of traffic flow runs through the entire experiments, but it tends to converge to user equilibrium. When the market penetration is 75%, both the fluctuation of traffic flow and the tendency of subjects to change routes are the smallest, so the road network system is the most stable. This interesting result indicates that releasing traffic information to all travelers is not the best. Other results show that the travel times of the three routes in the five groups of experiments tend to converge to and finally fluctuate around user-equilibrium travel time. With the increase in ATIS market penetration, the average travel time of subjects in each round tends to increase. The overall trend of the five groups of experiments is that as the number of route switches increases, the average travel time increases. The results also indicate that releasing traffic information to all travelers cannot weaken the Braess Paradox. On the contrary, the more travelers are provided with traffic information, the less likely it will weaken the Braess Paradox.

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