scholarly journals A Dynamic Day-To-Day Departure Time and Route Choice Model for Bounded-Rational Individuals

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Lingjuan Chen ◽  
Yu Wang ◽  
Dongfang Ma
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Navigation Systems ◽  
Dynamic Learning ◽  
Traffic State ◽  
Departure Time ◽  
Navigation Information

Accurate prediction of travellers’ day-to-day departure time and route choice is critical in advanced traffic management systems. There have been several related works about route choice with the assumption that the departure time for individual travellers is known beforehand. With real-time traffic state information provided by navigation systems and previous historical experience, travellers will dynamically update their departure time, which is neglected in existing works. In this study, we aim to describe travellers’ spatial-temporary choice behaviour taking navigation information into account and propose a bounded-rational day-to-day dynamic learning and adjustment model. The new model contains three steps. First, the real-time navigation guidance on each discrete day is obtained, and the self-learned experience of travellers’ choices with navigation information is presented; then, the day-to-day revision process of the choices is derived to maximize departure and route choice prospect; next, by aggregating each individual’s behaviour and calculating route choice probability, a bounded-rational continuous day-to-day dynamic model is provided. Numerical experiments suggest that the proposed model converges to a spatial-temporal oscillating equilibrium not a fixed-point stable status, and the final equilibrium trend is different from classical user equilibrium. The findings of the study are helpful to improve the prediction accuracy of traffic state in urban street networks.

Solving the Overlapping Problem in Route Choice with Paired Combinatorial Logit Model

2003 ◽  
Vol 1857 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Anthony Chen ◽  
Panatda Kasikitwiwat ◽  
Zhaowang Ji
Keyword(s):  
Mathematical Programming ◽  
Logit Model ◽  
Choice Model ◽  
Route Choice ◽  
Similarity Index ◽  
User Equilibrium ◽  
Transportation Systems ◽  
Programming Formulation ◽  
Stochastic User Equilibrium ◽  
Mathematical Programming Formulation

Recently, there has been renewed interest in improving the logit-based route choice model because of the importance of the route choice model in intelligent transportation systems applications, particularly the applications of advanced traveler information systems. The paired combinatorial logit (PCL) model and its equivalent mathematical programming formulation for the route choice problem have been studied. An algorithm based on the partial linearization method is presented for solving the PCL stochastic user equilibrium problem. Detailed examples are provided to explain how this hierarchical logit model resolves the overlapping problem through the similarity index while still accounting for both congestion and stochastic effects in the mathematical programming formulation.

Dynamic Model Research of Departure Time and Route Choice Based on Prospect Theory

2011 ◽  
Vol 243-249 ◽  
pp. 4418-4421
Author(s):  
Zhi Yong Yang ◽  
Gui Yun Yan
Keyword(s):  
Prospect Theory ◽  
Choice Model ◽  
Weighting Function ◽  
Route Choice ◽  
Traffic Information ◽  
Traveler Information ◽  
Travel Choice ◽  
Traveler Information Systems ◽  
Model Research ◽  
Departure Time

This paper takes commuters’ daily travel as research object to build model of travel choice which contains departure time and travel route based on Prospect Theory. Choosing the time of arriving destination as reference point, commuter will choose the time at which he/she can obtain the maximum value as departure time, then establishes choice model of departure time. Using Bayesian Theory to update and adjust route’s forecasting travel time in light of traffic information provided by Advanced Traveler Information Systems (ATIS) and travelers’ previous experience information. Gets decision weighting function after having analyzed traveler’s individual subjective probability which is about the possible result for route choice, then obtains the expression of travel route’s prospect value and gets route choice model. Finally, by designing a network to analyze the dynamic choice model, and achieves expected effect.

Is it Necessary to Relax the IID Assumptions in the Logsum-Based Accessibility Analysis?

2019 ◽  
Vol 2673 (4) ◽  
pp. 84-96
Author(s):  
Yongnan Yan ◽  
Xiangdong Xu ◽  
Anthony Chen
Keyword(s):  
Choice Model ◽  
Route Choice ◽  
User Equilibrium ◽  
Stochastic User Equilibrium ◽  
Independence Assumption ◽  
Accessibility Analysis ◽  
Project Appraisal ◽  
Transit Accessibility ◽  
Accessibility Evaluation ◽  
The Difference

Accessibility is an important link between transportation and land use. As a typical measure of accessibility, logsum or a utility-based measure has been widely used in project appraisal, urban transit accessibility evaluation, destination choice, and network vulnerability analysis. Since the logsum term is the log of the denominator of the choice probability expression, it inherits the independently and identically distributed (IID) assumptions of the classical multinomial logit (MNL) route choice model. This paper aims to explore whether the IID assumptions have a significant effect on the logsum-based accessibility analysis, given that accessibility analysis focuses at the origin-destination (O-D) level and zonal level (aggregate analysis) rather than at the route level (disaggregate analysis). We derive two new logsum terms for two representative extended logit stochastic user equilibrium (SUE) models, that is, the C-logit model for relaxing the independence assumption and the MNL model with scaling effect (MNLs) for relaxing the identically distributed assumption. The case analysis of a real network in Winnipeg, Canada shows that: (1) there does exist a difference in accessibility evaluation among the three logsum terms using the three route choice models; (2) relaxing the identically distributed assumption is more important than the independence assumption since the difference in accessibility evaluation between MNLs-logsum and MNL-logsum is larger than that between C-logit-logsum and MNL-logsum; (3) the difference in accessibility evaluation at the zonal level is smaller than that at the O-D level; and (4) the difference increases with the dispersion parameter.

Analysis of Time Allocation, Departure Time, and Route Choice Behavior Under Congestion Pricing

2000 ◽  
Vol 1725 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Toshiyuki Yamamoto ◽  
Satoshi Fujii ◽  
Ryuichi Kitamura ◽  
Hiroshi Yoshida
Keyword(s):  
Time Allocation ◽  
Choice Model ◽  
Stated Preference ◽  
Congestion Pricing ◽  
Route Choice ◽  
Multinomial Logit Model ◽  
Allocation Model ◽  
Departure Time ◽  
Departure Time Choice ◽  
Pricing Schemes

Driver behavior under congestion pricing is analyzed to evaluate the effects of alternative congestion pricing schemes. The analysis, which is based on stated preference survey results, focuses on time allocation, departure time choice, and route choice when a congestion pricing scheme is implemented on toll roads in Japan. A unique feature of the model system of this study is that departure time choice and route choice are analyzed in conjunction with the activities before and after the trip. A time allocation model is developed to describe departure time choice, and a route and departure time choice model is developed as a multinomial logit model with alternatives representing the choice between freeways and surface streets and, for departure time, the choice from among before, during, or after the period when congestion pricing is in effect. The results of the empirical analysis suggest that departing during the congestion pricing period tends to have higher utilities and that a worker and a nonworker have quite different utility functions. The comparative analysis of different congestion pricing schemes is carried out based on the estimated parameters. The results suggest that the probability of choosing each alternative is stable even if the length of the congestion pricing period changes, but a higher congestion price causes more drivers to change the departure time to before the congestion pricing period.

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.

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