Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect
The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/9181836 |
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| _version_ | 1832556360091303936 |
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| author | Tenglong Li Fei Hui Ce Liu Xiangmo Zhao Asad J. Khattak |
| author_facet | Tenglong Li Fei Hui Ce Liu Xiangmo Zhao Asad J. Khattak |
| author_sort | Tenglong Li |
| collection | DOAJ |
| description | The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and active vehicle-to-vehicle (V2V) communications based on field experimental data. Data mining results show that the correlation between the jerk effect and the driving behavior increases by 50.6% on average when V2V messages are received. In light of the data analysis results, a new car-following model is proposed to explore the jerk effect in a connected environment. The model parameters are calibrated, and the results show that the standard deviation between the new model simulation data and the observed data decreases by 38.2% compared to that of the full velocity difference (FVD) model. Linear and nonlinear analyses of the calibrated model are then carried out to evaluate the connected traffic flow stability. Finally, the theoretical analysis is verified by simulation experiments. Both the theoretical and simulation results show that the headway amplitude and velocity fluctuations are reduced when considering the jerk effect in a connected environment, and the traffic flow stability is improved. |
| format | Article |
| id | doaj-art-c87113a0bf094378bcb70c4d6e8e9232 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-c87113a0bf094378bcb70c4d6e8e92322025-02-03T05:45:45ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/91818369181836Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk EffectTenglong Li0Fei Hui1Ce Liu2Xiangmo Zhao3Asad J. Khattak4School of Information Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information Engineering, Chang’an University, Xi’an 710064, ChinaThe existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the change in the traffic jerk effect between inactive and active vehicle-to-vehicle (V2V) communications based on field experimental data. Data mining results show that the correlation between the jerk effect and the driving behavior increases by 50.6% on average when V2V messages are received. In light of the data analysis results, a new car-following model is proposed to explore the jerk effect in a connected environment. The model parameters are calibrated, and the results show that the standard deviation between the new model simulation data and the observed data decreases by 38.2% compared to that of the full velocity difference (FVD) model. Linear and nonlinear analyses of the calibrated model are then carried out to evaluate the connected traffic flow stability. Finally, the theoretical analysis is verified by simulation experiments. Both the theoretical and simulation results show that the headway amplitude and velocity fluctuations are reduced when considering the jerk effect in a connected environment, and the traffic flow stability is improved.http://dx.doi.org/10.1155/2020/9181836 |
| spellingShingle | Tenglong Li Fei Hui Ce Liu Xiangmo Zhao Asad J. Khattak Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect Journal of Advanced Transportation |
| title | Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect |
| title_full | Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect |
| title_fullStr | Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect |
| title_full_unstemmed | Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect |
| title_short | Analysis of V2V Messages for Car-Following Behavior with the Traffic Jerk Effect |
| title_sort | analysis of v2v messages for car following behavior with the traffic jerk effect |
| url | http://dx.doi.org/10.1155/2020/9181836 |
| work_keys_str_mv | AT tenglongli analysisofv2vmessagesforcarfollowingbehaviorwiththetrafficjerkeffect AT feihui analysisofv2vmessagesforcarfollowingbehaviorwiththetrafficjerkeffect AT celiu analysisofv2vmessagesforcarfollowingbehaviorwiththetrafficjerkeffect AT xiangmozhao analysisofv2vmessagesforcarfollowingbehaviorwiththetrafficjerkeffect AT asadjkhattak analysisofv2vmessagesforcarfollowingbehaviorwiththetrafficjerkeffect |