A decision-making rule for modeling travelers’ route choice behavior based on cumulative prospect theory

2011 ◽  
Vol 19 (2) ◽  
pp. 218-228 ◽  
Author(s):  
Hongli Xu ◽  
Jing Zhou ◽  
Wei Xu
Keyword(s):  
Decision Making ◽  
Prospect Theory ◽  
Choice Behavior ◽  
Route Choice ◽  
Cumulative Prospect Theory ◽  
Route Choice Behavior ◽  
Behavior Based ◽  
Decision Making Rule

Drivers’ Route Choice Behavior Analysis Based on Cumulative Prospect Theory

2014 ◽  
Vol 1030-1032 ◽  
pp. 2231-2234
Author(s):  
Wei Yan Zong ◽  
En Jian Yao ◽  
Yang Yang
Keyword(s):  
Prospect Theory ◽  
Choice Behavior ◽  
Route Choice ◽  
Expected Utility Theory ◽  
Cumulative Prospect Theory ◽  
Route Choice Behavior ◽  
Route Network ◽  
Behavior Characteristics ◽  
Study Designs ◽  
Different Levels

Due to different travel experiences, travel attitude varies from people of different levels of familiarity with urban route network. Expected utility theory (EUT) is usually used to describe travelers’ route choice behavior. But there is huge discrepancy between reality and the results under the condition with network uncertainty when the cumulative prospect theory (CPT) is more attractive to describe the travelers’ route choice behavior. Based on CPT this study designs scenarios at different levels of familiarity with urban road network, analyzes route choice behavior in all scenarios and conclude travelers’ behavior characteristics compared with reality investigation results. It shows that CPT is really more powerful to describe the travelers’ behavior under risk and people of high familiarity level are more relied on constraint time and tend to take a risk for more gain.

scholarly journals A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaowei Jiang ◽  
Yanjie Ji ◽  
Muqing Du ◽  
Wei Deng
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Evolutionary Game Theory ◽  
Choice Behavior ◽  
Evolutionary Game ◽  
Route Choice ◽  
Cumulative Prospect Theory ◽  
Traffic Information ◽  
Analytic Method ◽  
Route Choice Behavior

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers’ route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver’s route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver’s route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

scholarly journals Sequential Route Choice Modeling Based on Dynamic Reference Points and Its Empirical Study

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xueqin Long ◽  
Chenxi Hou ◽  
Shanshan Liu ◽  
Yuejiao Wang
Keyword(s):  
Prospect Theory ◽  
Travel Time ◽  
Real Time ◽  
Route Choice ◽  
Cumulative Prospect Theory ◽  
Time Travel ◽  
Reference Points ◽  
Travel Time Prediction ◽  
Route Choice Behavior ◽  
Types Of Information

Aiming at the influence of information, we investigate and analyze the sequential route choice behavior under dynamic reference points based on cumulative prospect theory in this paper. An experiment platform collecting the sequential route choices based on C/S structure is designed and four types of information are released to participants, respectively. Real-time travel time prediction methods are then proposed for travelers’ decision-making. Using nonlinear regression method, the parameters of the value function and weight function of cumulative prospect theory are estimated under different types of information, respectively. It is found that travelers’ behavior showed obvious characteristic of risk pursuit under the circumstance where real-time travel time information is released. Instead, when they have access to descriptive information, they tend to be more conservative.

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