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Calibrating car-following models on urban expressways for Chinese drivers using naturalistic driving data

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Car-following models are the core component of microscopic traffic simulation, intelligent transportation systems and advanced driver assistance systems. The performance of these models applied to Chinese drivers has never been investigated with real-word driving data. To address this need, five representative car-following models were calibrated and validated with 2,100 urban-expressway car-following periods extracted from the 161,055 km of driving data collected in the Shanghai Naturalistic Driving Study (SH-NDS). The models were evaluated based on their estimation and prediction capabilities. The best performing models were applied to compare the car-following behavior of Shanghai and US drivers on urban expressways. The results showed that 1) the full velocity difference model, with a validation error of 24%, performed best in modeling Chinese drivers’ behavior; 2) according to the Intelligent Driver Model (IDM), drivers from the SH-NDS adopted a desired time headway which is only a third of that adopted by drivers from the VTTI 100-Car Study in the US; 3) based on the fundamental diagrams of the IDM model, Chinese drivers adopted shorter following gaps than US drivers, which leads to a higher expressway capacity. These results indicate that Chinese drivers are more aggressive which may indicate that they have a lower perception of risk in car-following situation than US drivers. The presented study assists understanding of the differences in driving behavior between China and the US. The results indicate that simulation models and components of intelligent vehicles must be calibrated to Chinese conditions before they can be successfully used in China.

Meixin Zhu, Xuesong Wang*, Tarko A. Calibrating Car-Following Models on Urban Expressways for Chinese Drivers Using Naturalistic Driving Data, Transportation Research Board 96th Annual Meeting, Washington D.C., USA, 2017. 1.8-12.

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