Traveler's Route Choice Behavior Model And Simulation Analysis

In spite of the great development made in recent years, there are still traffic problems existing in our city, traffic congestion has become very serious. To solve the increasingly serious traffic problems, strengthening the construction of infrastructure, we should pay attention to enhancing the level of road operations unceasingly at the same time.As a sub-system of Intelligent Transportation System (ITS), Advanced Traveler Information System (ATIS) could improve the quality of travel by guiding the path selection of traveler. The paper employed agent-oriented approach under the environment of StarLogo to model the path selection behavior of traveler from two levels of tactics and strategy under ATIS. The results of experiment on the two-route network were showed that the impact on the traveler's trip planning, and the benefit of ATIS will improve with the growth of traffic flow in a certain extent. This gives good reference for the application of ATIS.The problem of traveler route choice has always been a hot issue in the field of transportation research. The accurate description of traveler route choice in a given traffic conditions can better induce people to travel and improve the efficiency of traveler. The actual travel behavior is better described by the descriptive model of decision based on Cumulative Prospect Theory (CPT) in risky traffic networks. Traveler is assumed know the probability distribution of the travel time before the departure in this paper, and then the traveler route choice model based on CPT in the condition of risky traffic networks is proposed. At last it is proofed that there is more advantage for CPT to depict the actual travel behavior of traveler.There are closely linked between optimal departure time choosing and traveler route choice, traveler route choice has a direct bearing on optimal departure time choosing. When the traveler complete a trip in accordance with the selected path, they can make a decision whether traveler will change optimal departure time next trip based on route's actual travel time. Based on the basal idea and decision-making framework of Cumulative prospect theory, by taking traveler's predicted arrival time as reference points, then establishes the value function and acquires a optimal departure time. By setting up an arrival time satisfying interval, to research whether traveler will change or how change optimal departure time next trip.