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An extended smart driver model considering electronic throttle angle changes with memory |
| Congzhi Wu(武聪智)1,2,3, Hongxia Ge(葛红霞)1,2,3,†, and Rongjun Cheng(程荣军)1,2,3 |
1 Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China;
2 Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing 210096, China;
3 National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-centre, Ningbo 315211, China |
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Abstract Based on the fact that the electronic throttle angle effect performs well in the traditional car following model, this paper attempts to introduce the electronic throttle angle into the smart driver model (SDM) as an acceleration feedback control term, and establish an extended smart driver model considering electronic throttle angle changes with memory (ETSDM). In order to show the practicability of the extended model, the next generation simulation (NGSIM) data was used to calibrate and evaluate the extended model and the smart driver model. The calibration results show that, compared with SDM, the simulation value based on the ETSDM is better fitted with the measured data, that is, the extended model can describe the actual traffic situation more accurately. Then, the linear stability analysis of ETSDM was carried out theoretically, and the stability condition was derived. In addition, numerical simulations were explored to show the influence of the electronic throttle angle changes with memory and the driver sensitivity on the stability of traffic flow. The numerical results show that the feedback control term of electronic throttle angle changes with memory can enhance the stability of traffic flow, which shows the feasibility and superiority of the proposed model to a certain extent.
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Received: 26 March 2021
Revised: 06 June 2021
Accepted manuscript online: 28 June 2021
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PACS:
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05.60.-k
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(Transport processes)
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45.70.Vn
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(Granular models of complex systems; traffic flow)
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| Fund: Project supported by the Natural Science Foundation of Zhejiang Province, China (Grant No. LY20G010004) and the the Program of Humanities and Social Science of Education Ministry of China (Grant No. 20YJA630008), and the K. C. Wong Magna Fund in Ningbo University, China. |
Corresponding Authors:
Hongxia Ge
E-mail: gehongxia@nbu.edu.cn
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Cite this article:
Congzhi Wu(武聪智), Hongxia Ge(葛红霞), and Rongjun Cheng(程荣军) An extended smart driver model considering electronic throttle angle changes with memory 2022 Chin. Phys. B 31 010504
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