Taxi drivers drive on the roads every day and become very knowledgeable of the spatiotemporal traffic patterns in a city.It therefore is reasonable to assume that the routes chosen by taxi drivers often work out bette...Taxi drivers drive on the roads every day and become very knowledgeable of the spatiotemporal traffic patterns in a city.It therefore is reasonable to assume that the routes chosen by taxi drivers often work out better than those selected by other drivers.Since dynamic navigation assistance based on real-time traffic information faces limitations such as the spatial coverage of real-time data collection sites,performance of real-time data processing and communications,and accuracy of short-term traffic forecasts in a large urban area,experiences gained by taxi drivers can be a valuable data source for improving the quality of vehicle navigation guidance.This paper develops a vehicle navigation guidance system based on taxis drivers’ knowledge derived from floating car data collected over an extended time period.We then classify road segments based on the spatiotemporal characteristics of taxi tracking data.A case study using taxi tracking data collected in Wuhan,China is presented in this paper to demonstrate the performance of this vehicle navigation system based on taxi tracking data.展开更多
This paper describes a cooperative decentralized architecture for reactive real-time route guidance. The architecture is cooperative in the sense that it allows adjacent local controllers to exchange information regar...This paper describes a cooperative decentralized architecture for reactive real-time route guidance. The architecture is cooperative in the sense that it allows adjacent local controllers to exchange information regarding the traffic conditions in their territories. A set of local decision rules and associated heuristic functions to support the cooperative architecture are specified. A protocol governing the knowledge exchange among local adjacent controllers is developed. A simulation-assignment modeling framework is used for assessing the effectiveness of this cooperative architecture under various levels of controller knowledge and network traffic congestion. The cooperative decentralized system is tested under various scenarios of knowledge and cooperation and network traffic demand levels. The cooperative system is compared against the shortest path algorithm as a benchmark.展开更多
基金supported by the National Natural Science Foundation of China (Grant Nos.40801155,40830530,60872132,50808146)the National Science & Technology Pillar Program (Grant No.2008BAK49B02)+1 种基金the National Hi-Tech Research and Development Program of China ("863" Project) (Grant Nos.2009AA11Z213,2009AA11Z218)the projects funding of LIESMARS
文摘Taxi drivers drive on the roads every day and become very knowledgeable of the spatiotemporal traffic patterns in a city.It therefore is reasonable to assume that the routes chosen by taxi drivers often work out better than those selected by other drivers.Since dynamic navigation assistance based on real-time traffic information faces limitations such as the spatial coverage of real-time data collection sites,performance of real-time data processing and communications,and accuracy of short-term traffic forecasts in a large urban area,experiences gained by taxi drivers can be a valuable data source for improving the quality of vehicle navigation guidance.This paper develops a vehicle navigation guidance system based on taxis drivers’ knowledge derived from floating car data collected over an extended time period.We then classify road segments based on the spatiotemporal characteristics of taxi tracking data.A case study using taxi tracking data collected in Wuhan,China is presented in this paper to demonstrate the performance of this vehicle navigation system based on taxi tracking data.
文摘This paper describes a cooperative decentralized architecture for reactive real-time route guidance. The architecture is cooperative in the sense that it allows adjacent local controllers to exchange information regarding the traffic conditions in their territories. A set of local decision rules and associated heuristic functions to support the cooperative architecture are specified. A protocol governing the knowledge exchange among local adjacent controllers is developed. A simulation-assignment modeling framework is used for assessing the effectiveness of this cooperative architecture under various levels of controller knowledge and network traffic congestion. The cooperative decentralized system is tested under various scenarios of knowledge and cooperation and network traffic demand levels. The cooperative system is compared against the shortest path algorithm as a benchmark.
