Design of Driving Behavior Pattern Measurements Using Smartphone Global Positioning System Data

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Design of Driving Behavior Pattern Measurements Using Smartphone Global Positioning System Data

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Xiaoyu Zhu / Xianbiao Hu / Yi-Chang Chiu

The emergence of new technologies such as GPS, cellphone, Bluetooth device, etc. offers opportunities for collecting high-fidelity temporal-spatial travel data in a cost-effective manner. With the vehicle trajectory data achieved from a smartphone app Metropia, this study targets on exploring the trajectory data and designing the measurements of the driving pattern. Metropia is a recently available mobile traffic app that uses prediction and coordinating technology combined with user rewards to incentivize drivers to cooperate, balance traffic load on the network, and reduce traffic congestion. Speed and celeration (acceleration and deceleration) are obtained from the Metropia platform directly and parameterized as individual and system measurements related to traffic, spatial and temporal conditions. A case study is provided in this paper to demonstrate the feasibility of this approach utilizing the trajectory data from the actual app usage. The driving behaviors at both individual and system levels are quantified from the microscopic speed and celeration records. The results from this study reveal distinct driving behavior pattern and shed lights for further opportunities to identify behavior characteristics beyond safety and environmental considerations.