An Agent-oriented Simulating Approach To Study The Driver’s Behavior Under Real-time Traffic Information

As an important subsystem of Intelligent Transportation System (ITS),Advanced Traveler Information System (ATIS) is designed to provide real-timeinformation on traffic conditions to affect driver’s travel decision-makingbehaviors, in further to improve the performance of the whole transportationnetwork. Therefore, analyzing driver’s behaviors under ATIS environment is theimportant theoretical basis of both implementing effective service strategy for theATIS service providers and determining the corresponding market scales.Considering the inherent dynamic, discrete, complex and uncertain nature,transportation system under ATIS is difficult to model by traditionalmathematical methods. However, the modeling and simulating methods based onMulti-Agent provide a suitable and practical way for describing the drivers’behaviors under ATIS. Through developing travel individual behavior Agentmodel (mainly for driver-vehicle unit), and limiting the ATIS traffic environmentfor Agent “survival”, the paper use the Agent-Oriented simulation technology toreproduce a complex and orderly formation process of the system in thecompetition, cooperation, interaction among Agents. Moreover by changing theAgents survival environment (mainly changing the information environment), itinfluences the decision-making process of Agent, thereby fully understands theformation mechanism of the system to achieve the effective control of system.Firstly, an Agent model based on two-layer Agent architecture is presentedto describe the driver-vehicle unit under ATIS. The two-layer model includes thestrategic layer and tactical layer behavior models. The former is responsible forthe “head” of the decision-making behaviors, such as departure time choice,route choice and other behaviors under real-time information; while the latter isresponsible for the actual vehicle running in accelerating, decelerating, followingand lane-changing. This paper introduces the Agent-based BDI model to describethe internal reasoning logic of driver’s decision-making process. Meanwhile, forthe tactical layer, the paper develops the car-following model based on “desireedgap” and lane changing model based on reactive Agent technology.Secondly, the paper uses the driver behavior model established in tactical layer develop a interactive simulator DPIS (Delphi-Paramics InteractiveSimulator), based on the scalable programming interface of microscopic trafficsimulation software “Paramics” and the general developing environment“Delphi” developed by Borland. DPIS can simulate road network traffic andATIS information environment through servers by using the C/S (Client/Server)architecture. Respondents in the client point could make behavior decisionsunder real-time information according to the simulated environment, so as toachieve the driver behavioral data collection and analysis under real-timeinformation.Thirdly, in order to instantiate the BDI strategic layer behavior modelestablished above, the paper collectes the behavior data of several commuters byusing DPIS. Based on the data, the paper builds the behavior analysis frameworkby introducing “bounded rationality” theory and builds the statistical analysismodel based on Multinomial Probit Model (MNP) to analyze the departure timeswitching and route switching behaviors of commuters under ATIS. At the sametime, by combining the method of the discrete choice model and fuzzy logictheory, the paper characterizes the driver’s “obedience” behavior under real-timeinformation, so as to achieve the instantiation expression of driver-vehicle unitAgent strategic behavior model.Finally, based on the DPIS simulator developed and driver-vehicle unitAgent model built above (inluding strategic layer behavior model and tacticallayer behavior model), the paper discusses the application of driver behaviormodel under real-time information and several ATIS design and evaluationscenarios, maily focuses on the design of ATIS information supplying ratio andthe day-to-day dynamic evaluation of road network travel performance under acertain ATIS information supply strategies. In this way, the paper instructs thespecific application of driver behavior models built above under real-timeinformation in the implementation and evaluation of ATIS projects.The results provide theoretical basis for decision-making of ATIS operatorsin operation and management, meanwhile enrich the theories and methods ofdriver behavior analysis under ATIS environment, and provide a new train ofthought for future theoretical research and practical exploration.