The effect of pervasive computing and driver’s memory on connected and autonomous vehicles
Pervasive computing techniques provides application guidance and support for intelligent transportation systems. On the basis of connected autonomous vehicles, a extended model has been proposed. This paper focuses on studying the effects of the electronic throttle and driver's memory. In order...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/169639 |
| _version_ | 1811693132666896384 |
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| author | Chen, Can Du, Zhigang |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Chen, Can Du, Zhigang |
| author_sort | Chen, Can |
| collection | NTU |
| description | Pervasive computing techniques provides application guidance and support for intelligent transportation systems. On the basis of connected autonomous vehicles, a extended model has been proposed. This paper focuses on studying the effects of the electronic throttle and driver's memory. In order to show the influence of these two factors on the model, the extended model is studied by theoretical analysis and numerical methods. Stability conditions are obtained by adding perturbation to the linear analysis, the TDGL equation and mKdV equation are derived by nonlinear analysis, which shows that the phase change behavior of traffic jams can be described by both of them. The numerical simulation results show the correctness of the analysis results. Numerical results show that the effects of driver's memory and electronic throttle play an key role in the stability of traffic flow, which is consistent with the theoretical analysis results. |
| first_indexed | 2024-10-01T06:46:49Z |
| format | Journal Article |
| id | ntu-10356/169639 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:46:49Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1696392023-07-28T15:33:13Z The effect of pervasive computing and driver’s memory on connected and autonomous vehicles Chen, Can Du, Zhigang School of Civil and Environmental Engineering Engineering::Civil engineering Driver's Memory Electronic Throttle Pervasive computing techniques provides application guidance and support for intelligent transportation systems. On the basis of connected autonomous vehicles, a extended model has been proposed. This paper focuses on studying the effects of the electronic throttle and driver's memory. In order to show the influence of these two factors on the model, the extended model is studied by theoretical analysis and numerical methods. Stability conditions are obtained by adding perturbation to the linear analysis, the TDGL equation and mKdV equation are derived by nonlinear analysis, which shows that the phase change behavior of traffic jams can be described by both of them. The numerical simulation results show the correctness of the analysis results. Numerical results show that the effects of driver's memory and electronic throttle play an key role in the stability of traffic flow, which is consistent with the theoretical analysis results. Published version This work was supported by the National Natural Science Foundation of China under Grant 52072291. 2023-07-27T06:19:23Z 2023-07-27T06:19:23Z 2023 Journal Article Chen, C. & Du, Z. (2023). The effect of pervasive computing and driver’s memory on connected and autonomous vehicles. IEEE Access, 11, 45774-45781. https://dx.doi.org/10.1109/ACCESS.2023.3269958 2169-3536 https://hdl.handle.net/10356/169639 10.1109/ACCESS.2023.3269958 2-s2.0-85159646764 11 45774 45781 en IEEE Access © 2023 The Author(s). Published by IEEE. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf |
| spellingShingle | Engineering::Civil engineering Driver's Memory Electronic Throttle Chen, Can Du, Zhigang The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title | The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title_full | The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title_fullStr | The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title_full_unstemmed | The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title_short | The effect of pervasive computing and driver’s memory on connected and autonomous vehicles |
| title_sort | effect of pervasive computing and driver s memory on connected and autonomous vehicles |
| topic | Engineering::Civil engineering Driver's Memory Electronic Throttle |
| url | https://hdl.handle.net/10356/169639 |
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