Travel route safety estimation based on conflict simulation.

With the aim of providing travelers information about the safety levels of selectable routes, it is necessary to develop a method that can properly estimate the safety of alternative travel routes. This paper proposes a conflict-based approach for travel route safety estimation (TRSE). It is developed on the basis of the classical safety evaluation model where both the amount of exposure to safety risk and the risk under unit exposure are measured to estimate the route safety. A combination of a set of dynamic and static factors related to traffic flow characteristics and roadway features are selected to estimate conflict exposure and potential conflict risk. A route-based method is employed where two parallel estimations of conflict are conducted for both the component segments links and intersection turning links. Three machine learning models (i.e., random forest, k-nearest neighbor, and support vector machine) are tested in conflict risk estimation. A fuzzy reasoning process based on the fuzzy logic algorithm is employed to conduct the route safety estimation. The proposed TRSE is tested on a four-horizontal and six-vertical network extracted from a real road network in China. Conflict simulation results were obtained by Vissim and SSAM tools. The results illustrate the practicability and effectiveness of the proposed TRSE approach.