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.

scholarly journals User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network

2020 ◽  
Vol 12 (17) ◽  
pp. 6706
Author(s):  
Qinghui Xu ◽  
Xiangfeng Ji
Keyword(s):  
High Probability ◽  
Choice Behavior ◽  
Route Choice ◽  
User Equilibrium ◽  
Equilibrium Analysis ◽  
Risk Averse ◽  
Risk Seeking ◽  
Route Choice Behavior ◽  
Risk Neutral ◽  
Context Dependent

This paper studies travelers’ context-dependent route choice behavior in a risky trafficnetwork from a long-term perspective, focusing on the effect of travelers’ salience characteristics. In particular, a flow-dependent salience theory is proposed for this analysis, where the flow denotes the traffic flow on the risky route. In the proposed model, travelers’ attention is drawn to the salient travel utility, and the objective probabilities of the state of the world are replaced by the decision weights distorted in favor of this salient travel utility. A long-run user equilibrium will be achieved when no traveler can improve his or her salient travel utility by unilaterally changing routes, termed salient user equilibrium, which extends the scope of the Wardropian user equilibrium. Furthermore, we prove the existence and uniqueness of this salient user equilibrium. Finally, numerical studies demonstrate our theoretical findings. The equilibrium results show non-intuitive insights into travelers’ route choice behavior. (1) Travelers can be risk-seeking (the travel utility of a risky route is small with a relatively high probability), risk-neutral (in special situations), or risk-averse (the travel utility of a risky route is large with a relatively high probability), which depends on the salient state. (2) The extent of travelers’ risk-seeking or risk-averse behavior depends on their extent of salience bias, while the risk-neutral behavior is irrelative to this salience bias.

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.

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 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.

Comprehending the roles of traveler perception of travel time reliability on route choice behavior

2019 ◽  
Vol 16 ◽  
pp. 13-22 ◽  
Author(s):  
Zohreh Rashidi Moghaddam ◽  
Mansoureh Jeihani ◽  
Srinivas Peeta ◽  
Snehanshu Banerjee
Keyword(s):  
Travel Time ◽  
Choice Behavior ◽  
Route Choice ◽  
Travel Time Reliability ◽  
Route Choice Behavior

Rail Transit Travel Time Reliability and Estimation of Passenger Route Choice Behavior

2012 ◽  
Vol 2275 (1) ◽  
pp. 58-67 ◽  
Author(s):  
Yanshuo Sun ◽  
Ruihua Xu
Keyword(s):  
Travel Time ◽  
Choice Behavior ◽  
Route Choice ◽  
Service Reliability ◽  
Travel Time Reliability ◽  
Elapsed Time ◽  
Route Choice Behavior ◽  
Collection Data ◽  
Passenger Flow Assignment ◽  
Transfer Stations

Applications of automatic fare collection data were investigated, with a focus on analysis of travel time reliability and estimation of passenger route choice behavior. Beijing Metro was used as a case study. A rail journey was decomposed, and each component was studied with regard to the uncertainties involved. Methods were then designed and validated to infer platform elapsed time (PET) for through stations and platform elapsed time–transfer (PET-Trans) for transfer stations by using smart card transactional data, train schedules, and complementary manual surveys. With this information, the journey time distribution of any path can be established, and methods were proposed for inferring route choice proportions. After data preparation, the methods were applied to two typical origins and destinations from the Beijing Metro. Key values concerning travel time reliability, such as PET, PET-Trans, travelers left behind (unable to board), and path coefficients, were obtained and interpreted in detail. The outcome of this research could facilitate analysis of transit service reliability and passenger flow assignment in daily operations.

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