Study Of Driving Behavior Based On Integrated Cognitive Activity And Decision-Making Optimization Method

With the development of transportation, the problems of traffic jams, environmental pollution and traffic accident are getting more and more serious. The development of Intelligent Transportation Systems (ITS) is an important measure for relieving above transportation problems. Intelligent Transportation Systems is an dynamics, random, complicate and open huge system, which is composed of human, vehicle, road and environment (namely, four elements in transportation, FET). As a complicate individual with ability of thinking, summarizing the experience and refining subjectivity, driver is the core of ITS. The driver can control the vehicle through handling it. During the whole process, perception, understanding, judgment and performance can be performed by driver. Driver plays an important role in coordinating and controlling FET and decides parts functions of system. Following the advance of traffic science, driving behavior has been becoming the key of ITS, and the theory basis of microscopic traffic flow simulation. So researching on the traffic system should be focused on the driving behavior, and FET also should be considered as a whole system.According to the demands of microscopic traffic flow simulation modeling and ITS, and based on the driver cognitive psychology, the driving behavior based on integrated cognitive and optimized decision-making mechanism has been studied. The main contents are as follows: desired speed model based on integrated calculation of human-vehicle-road-environment; the car-following model based on the projection pursuit regression and the validation methods of microscopic traffic simulation models; lane-changing decision-making model based on AHP method; driving decision-making optimization model based on precision clocked scan; modeling and simulation for driving behavior in mix-traffic environment. There are very important theoretical value and practical significance for improving the management efficiency of traffic systems, relieving traffic jams, reducing the pollution and resources depletion, cultivating the future new industry.