Abstract
Finding optimal path in a given network is an important content of intelligent transportation information service. Static shortest path has been studied widely and many efficient searching methods have been developed, for example Dijkstra’s algorithm, Floyd-Warshall, Bellman-Ford, A* et al. However, practical travel time is not a constant value but a stochastic value. How to take full use of the stochastic character to find the shortest path is a significant problem. In this paper, GPS floating car is used to detect road section’s travel time. The probability distribution of travel time is estimated according to Bayes estimation method. The combined probability distribution of a feasible route is calculated according to probability operation. The objective function is to find the route that has the biggest probability to arrive for desired time thresholds. Improved Genetic Algorithm is used to calculate the optimal path. The efficiency of the proposed method is illustrated with a practical example.
Highlights
Finding optimal paths in a given network is one of the most fundamental problems in network studies and has broad applications in the physical and social sciences and in engineering, in the fields of computer science, operations research, and transportation engineering [1]
After the travel time probability distribution being determined, how to find the optimal path based on stochastic distribution is a difficult problem
The travel time of the road section based on each floating car can be calculated according to above introduced method
Summary
Finding optimal paths in a given network is one of the most fundamental problems in network studies and has broad applications in the physical and social sciences and in engineering, in the fields of computer science, operations research, and transportation engineering [1]. Static shortest path has been studied widely and many efficient searching methods have been developed, for example Dijkstra’s algorithm, Floyd-Warshall, Bellman-Ford, A* et al Dijkstra’s algorithm is a graph search algorithm that solves the single-source shortest path problem for a graph with non-negative edge path costs, producing a shortest path tree [2,3]. This algorithm is often used in routing as a subroutine in other graph algorithms. After the travel time probability distribution being determined, how to find the optimal path based on stochastic distribution is a difficult problem. An example is analyzed to illustrate the efficiency of the proposed method
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