Chapter
Aug 12, 2020

Using Maneuver Transition Probabilities to Estimation of Driving Transition Pattern in Traditional Vehicle Environment and Connected Vehicle Environment

Publication: CICTP 2020

ABSTRACT

Considering the developments in intelligent transportation technology, accurately estimating the driving maneuver transition in the connected vehicle (CV) environment is crucial to design driver assistance systems. In this study, driving data were collected using a driving simulator. Thirty six test subjects participated in the experiment and the length of the road was about 20 km. Two types of test vehicle were used: equipped with a driver assistance system and not equipped with a driver assistance system. Driving behavior in this study was categorized into nine maneuver states. The experimental road was divided into nine zones. A comparative analysis was conducted to compare the changes in speed performance and driving maneuver transition between the connected vehicle (CV) environment and the traditional vehicle (TV) environment. The experiment used maneuver transition probabilities to represent the driving behavior. The results show that connected vehicle can help drivers in adjusting vehicle speed to ensure driving safety and comfort.

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Go to CICTP 2020
CICTP 2020
Pages: 2263 - 2270

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Published online: Aug 12, 2020

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Gonghao Sun [email protected]
1Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing Univ. of Technology, Beijing 100124, PR China. Email: [email protected]
2Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing Univ. of Technology, Beijing 100124, PR China. Email: [email protected]
3Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing Univ. of Technology, Beijing 100124, PR China. Email: [email protected]
4Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing Univ. of Technology, Beijing 100124, PR China. Email: [email protected]
Chenjing Zhou [email protected]
5Beijing Key Laboratory of Traffic Engineering, College of Metropolitan Transportation, Beijing Univ. of Technology, Beijing 100124, P.R. China. Email: [email protected]

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