A Systematic Cooperation Method for In-Car Navigation Based on Future Time Windows

  • Peiqun Lin School of Civil Engineering and Transportation, South China University of Technology
  • Chuhao Zhou School of Civil Engineering and Transportation, South China University of Technology
  • Yang Cheng Wisconsin Traffic Operations and Safety Laboratory, University of Wisconsin Madison
Keywords: navigation, greedy algorithm, future time windows, dynamic traffic assignment, simulation


Traffic congestion has become a severe problem, af-fecting travellers both mentally and economically. To al-leviate traffic congestion, this paper proposes a method using a concept of future time windows to estimate the future state of the road network for navigation. Through our method, we can estimate the travel time not only based on the current traffic state, but the state that ve-hicles will arrive in the future. To test our method, we conduct experiments based on Simulation of Urban MO-bility (SUMO). The experimental results show that the proposed method can significantly reduce the overall travel time of all vehicles, compared to the benchmark Dijkstra algorithm. We also compared our method to the Dynamic User Equilibrium (DUE) provided by SUMO. The experimental results show that the performance of our method is a little better than the DUE. In practice, the proposed method takes less time for computation and is insensitive to low driver compliance: with as low as 40% compliance rate, our method can significantly im-prove the efficiency of the unsignalised road network. We also verify the effectiveness of our method in a signalised road network. It also demonstrates that our method can assign traffic efficiently.


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How to Cite
Lin P, Zhou C, Cheng Y. A Systematic Cooperation Method for In-Car Navigation Based on Future Time Windows. Promet [Internet]. 2022May31 [cited 2022Nov.29];34(3):381-96. Available from: https://traffic.fpz.hr/index.php/PROMTT/article/view/3946