Recognition of Vehicle Travel Path Based on Comprehensive Scoring Method with Driving Habits
Under the background of big data,the key technology to provide OD data for traffic planning analysis is to identify the travel paths of urban vehicles based on electronic police.First,the vehicle passing information in the road network and the real-time road condition information provided by the Internet platform are obtained,and multiple iterative calculations are performed to obtain the path close to the real travel time,so as to determine the optimal travel path set of the vehicle;then,the path is analyzed and designed.Travel time,number of path turns and path node cycle length are used as a normalized calculation method for the three factors affecting driving habits;finally,a comprehensive scoring method is used to determine the maximum possible driving path between adjacent detection points of vehicles.In this paper,the case verification method is used to obtain the optimal path set of the vehicle,the weight of the in-fluencing factors of the path is obtained by the questionnaire,the scoring matrix of different paths is obtained by normalization,and then the maximum possible path between adjacent detection points and the vehicle are selected by comprehensive scoring.The actual driving path is the same.The results demonstrate the usability of the method.
NETL
NSTL
万方数据
