Crowdsensing based Real-time Traffic Condition Assessment Method

In this paper, we study a real-time traffic condition assessment method on the basis of taxi GPS data of Dongguan city by a new sensing form - crowdsensing. First, data preprocessing is used to clean invalid and noisy data. Second, we propose a road network extraction solution by mixing grid method and least square curve fitting. Third, we present a geometric matching based map matching solution. Finally, a velocity parameter estimation scheme based on self-adaptive traffic flow velocity is employed to assess traffic condition. A series of simulation experiments are carried out to verify the effectiveness of our proposed solutions.