00803792

Component

https://doi.org/10.3141/1725-09

http://scholar.google.com...mura&publication_year=2000

In this study drivers are assumed to reason and learn inductively based on the theory of cognitive psychology. The model system is basically a production system, a compilation of if-then rules in which the rules are revised by applying genetic algorithms. The behavior of drivers and network flow through Monte Carlo simulation using the model system is examined. The intention of this research is to shed light on the behavior of a driver-network system from a new standpoint, one different from that of equilibrium analysis. This research views drivers' behaviors as psychological and heterogeneous rather than economical and homogeneous. The results of the numerical experiments can be summarized as follows: (1) network flow does not necessarily converge to the user equilibrium; (2) drivers form a delusion, an extremely biased perception of travel time as a result of experiencing excessive travel times on early parts of the simulation in which little experience had been gained; (3) the delusion is dissolved by switching routes capriciously; and (4) without caprice drivers continue to travel on the same route because of their delusions and develop the habit of choosing the same route, thus freezing their behaviors. These results indicate that system behavior is much more complex and dynamic than implied by equilibrium analysis.

This paper appears in Transportation Research Record No. 1725, Freight Travel Behavior, Route Choice Behavior, and Advanced Traveler Information Systems.

English

p. 63-70

2000

Transportation Research Record

0309067286

Figures (5) ; References (18) ; Tables (1)

Cognition; Genetic algorithms; Mathematical models; Monte Carlo method; Perception; Route choice; Simulation; Travel behavior; Travel time

Caprice automobile

Delusions; Habits; Inductive learning

Highways; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Dec 4 2001 12:00AM

• AGGREGATE- AND DISAGGREGATE-BASED TRAVEL TIME ESTIMATIONS: COMPARISON OF APPLICATIONS TO SUSTAINABILITY ANALYSIS AND ADVANCED TRAVELER INFORMATION SYSTEMS
• ANALYSIS OF TIME ALLOCATION, DEPARTURE TIME, AND ROUTE CHOICE BEHAVIOR UNDER CONGESTION PRICING
• ANTICIPATED TRAVEL TIME, INFORMATION ACQUISITION, AND ACTUAL EXPERIENCE
• ANTICIPATORY OPTIMIZATION OF TRAFFIC CONTROL
• BICRITERION TRAFFIC EQUILIBRIUM: T2 MODEL, ALGORITHM, AND SOFTWARE OVERVIEW
• CONTENT OF VARIABLE MESSAGE SIGNS AND ON-LINE DRIVER BEHAVIOR
• FRAMEWORK FOR THE ANALYSIS OF GROCERY TELESHOPPING
• FREIGHT TRAVEL DEMAND MODELING: SYNTHESIS OF APPROACHES AND DEVELOPMENT OF A FRAMEWORK
• MODELING BEHAVIORAL ASPECTS OF URBAN FREIGHT MOVEMENT IN SUPPLY CHAINS
• MODELING INERTIA AND COMPLIANCE MECHANISMS IN ROUTE CHOICE BEHAVIOR UNDER REAL-TIME INFORMATION
• PERCEIVED VALUE OF TIME FOR TRUCK OPERATORS
• ROUTE AND SCHEDULING CHOICE UNDER TRAVEL TIME UNCERTAINTY
• TRAVELER RESPONSES TO ADVANCED TRAVELER INFORMATION SYSTEMS FOR SHOPPING TRIPS: INTERACTIVE SURVEY APPROACH
• USING GLOBAL POSITIONING SYSTEM DATA TO UNDERSTAND VARIATIONS IN PATH CHOICE
• VALUE OF TIME IN FREIGHT TRANSPORT IN FINLAND