Understanding the Shortest Route Selection Behavior for Private Cars Using Trajectory Data and Navigation Information

Abstract

Traffic information and driving preference play critical roles in the route selection of drivers and further impact transport management in practice. Some studies have explored the difference between actual and shortest paths for private cars during route selection. However, the quantification of the difference and deviation as well as the impacts of the date on route selection is still seldom investigated. The study proposed a method to quantify the deviation between actual and shortest paths based on big trajectory data and the digital map. Firstly, the rules of private car travel are determined according to the definition of a trip, and the travel trajectory is divided based on these rules to attain many trips. Then, the trip routes and their attributes are generated by geographical information methods. Baidu Map’s path planning collects the shortest routes with the optimal distance and time, and the deviation between actual and recommended paths is compared. Finally, the results of 2860 private car trips of nearly 400 drivers in Chongqing, China, reveal that only about 67% of the actual trips match well with the shortest path, which was significantly higher compared to existing studies. However, the deviation between the actual and shortest paths is limited to 9 minutes or 2 kilometers. There was no significant difference between the weekday and weekend in the proportion. Compared with the weekday, the indicators of the weekend are more deviated. Path selection and the deviation vary in travel modes, OD types, drivers’ preferences, travel time intervals, and distance intervals.

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

“…After plotting the survival and hazard function curves of pedestrians impacted by each risk factor, based on the application of the COX proportional-hazards model, we further analyzed the degree of risk of pedestrian violations affected by the combination of different risk factors during the waiting period. In other words, the purpose of the COX model is to simultaneously evaluate the effect of several factors on survival [ 11 , 48 ]. It can quantify how specified factors influence the hazard rate of pedestrian violations at a particular intersection in a time slot.…”