Modeling And Calculation Of Driver's Route Choice Behavior

With the development of society and economic,the ownership of car is constantly increasing.At the same time,the urban road load is more and more serious,which lead to many traffic problems,such as traffic congestion,traffic accidents and so on.Urban road transport system is a random,dynamic and complex system,which is composed of human,vehicle,road and environment.As a complicate individual with ability of thinking,summarizing the experience and refining subjectivity,driver is the dominant factor of the system.It is very important to study driver's route choice for the urban road transport system research.Not only is the shortest distance path concerned from the current location to the destination,but also all kinds of factors should be concerned to get the best road.Research on route choice behavior under random dynamic conditions integrating all kinds of factors can provide a theoretical basis to solve the question of resource shortages and traffic congestion.The cognitive activity chain of driver's route choice is analyzed in the paper based on the driver cognitive psychology.Then the factors of route choice are studied by analytic hierarchy process(AHP)method based on integrated calculation of human-vehicle-road-environment pre-trip.Route choice behavior is modeled separately by static and dynamic Bayesian networks pre-trip and after trip.Research on route choice behavior of singe-destination,multi-destination and unexpected-destination trip under random dynamic conditions are the main contents of the paper.The relationship among the destinations and the impact of it on route-choice behavior are studied from the point of trip destination.A new inferring method is proposed by using radiation field and discrete dynamic Bayesian network based on complex network simplified.These studies are of great significance to alleviate congestion and reduce energy consumption.