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.

Trust strategy simulation of corporation–NPO cross alliance using evolutionary game theory

Kybernetes ◽  
2017 ◽  
Vol 46 (3) ◽  
pp. 450-465 ◽  
Author(s):  
Yidan Chen ◽  
Lanying Sun
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Nonprofit Organizations ◽  
Bounded Rationality ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Stable State ◽  
Evolutionary Strategies ◽  
Content Type ◽  
Trust Relationships

Purpose The purpose of this paper is to investigate the dynamics and evolution of trust in organizational cross alliances. Design/methodology/approach In alliances between corporations and nonprofit organizations, trust in decision-making is a dynamic process. Using the replicated dynamics model of evolutionary game theory, this paper provides a trust decision model and analyzes four scenarios under different parameters. A numerical simulation is developed to present an intuitive interpretation of the dynamic development of trust decisions and the effects of incentive and punishment mechanisms. Findings Under different parameters, bounded rationality and utilities result in different but stable evolutionary strategies; the initial probability of adopting a trust strategy leads directly to whether participants adopt the strategy when the system reaches stability after continued games; and incentive and punishment mechanisms can significantly reduce the initial probability of adopting a trust strategy where the system evolves to meet stable state needs. Practical implications The establishment of trust relationships is an important influence on the stable and coordinated development of an alliance. The proposed model can help the alliance build closer trust relationships and provide a theoretical basis for the design of the trust mechanism. Originality/value Incentive and punishment bound by some degree of trust are introduced to address the problems of trust decisions and their dynamics; the model created reflects the bounded rationality and utility of each game stage. Useful evolutionary stable strategies using different variables are proposed to address the decision-making problems of trust in cross alliances.

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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