A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory
Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/2529856 |
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| _version_ | 1832547342829486080 |
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| author | Haigen Min Yukun Fang Runmin Wang Xiaochi Li Zhigang Xu Xiangmo Zhao |
| author_facet | Haigen Min Yukun Fang Runmin Wang Xiaochi Li Zhigang Xu Xiangmo Zhao |
| author_sort | Haigen Min |
| collection | DOAJ |
| description | Connected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. In this paper, we focused on the scenario of on-ramp merging of CAVs, proposed a centralized approach based on game theory to control the process of on-ramp merging for all agents without any collisions, and optimized the overall fuel consumption and total travel time. For the framework of the game, benefit, loss, and rules are three basic components, and in our model, benefit is the priority of passing the merging point, represented via the merging sequence (MS), loss is the cost of fuel consumption and the total travel time, and the game rules are designed in accordance with traffic density, fairness, and wholeness. Each rule has a different degree of importance, and to get the optimal weight of each rule, we formulate the problem as a double-objective optimization problem and obtain the results by searching the feasible Pareto solutions. As to the assignment of merging sequence, we evaluate each competitor from three aspects by giving scores and multiplying the corresponding weight and the agent with the higher score gets comparatively smaller MS, i.e., the priority of passing the intersection. The simulations and comparisons are conducted to demonstrate the effectiveness of the proposed method. Moreover, the proposed method improved the fuel economy and saved the travel time. |
| format | Article |
| id | doaj-art-2117ebace1b14893971241c0223d98f6 |
| 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-2117ebace1b14893971241c0223d98f62025-02-03T06:44:57ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/25298562529856A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game TheoryHaigen Min0Yukun Fang1Runmin Wang2Xiaochi Li3Zhigang Xu4Xiangmo Zhao5School of Information & Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information & Engineering, Chang’an University, Xi’an 710064, ChinaThe Joint Laboratory for Internet of Vehicles, Ministry of Education, China Mobile Communications Corporation, Chang’an University, Xi’an 710064, ChinaHenan Transport Investment Group Co., Ltd., Zhengzhou 450016, ChinaSchool of Information & Engineering, Chang’an University, Xi’an 710064, ChinaSchool of Information & Engineering, Chang’an University, Xi’an 710064, ChinaConnected and automated vehicles (CAVs) have attracted much attention of researchers because of its potential to improve both transportation network efficiency and safety through control algorithms and reduce fuel consumption. However, vehicle merging at intersection is one of the main factors that lead to congestion and extra fuel consumption. In this paper, we focused on the scenario of on-ramp merging of CAVs, proposed a centralized approach based on game theory to control the process of on-ramp merging for all agents without any collisions, and optimized the overall fuel consumption and total travel time. For the framework of the game, benefit, loss, and rules are three basic components, and in our model, benefit is the priority of passing the merging point, represented via the merging sequence (MS), loss is the cost of fuel consumption and the total travel time, and the game rules are designed in accordance with traffic density, fairness, and wholeness. Each rule has a different degree of importance, and to get the optimal weight of each rule, we formulate the problem as a double-objective optimization problem and obtain the results by searching the feasible Pareto solutions. As to the assignment of merging sequence, we evaluate each competitor from three aspects by giving scores and multiplying the corresponding weight and the agent with the higher score gets comparatively smaller MS, i.e., the priority of passing the intersection. The simulations and comparisons are conducted to demonstrate the effectiveness of the proposed method. Moreover, the proposed method improved the fuel economy and saved the travel time.http://dx.doi.org/10.1155/2020/2529856 |
| spellingShingle | Haigen Min Yukun Fang Runmin Wang Xiaochi Li Zhigang Xu Xiangmo Zhao A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory Journal of Advanced Transportation |
| title | A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory |
| title_full | A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory |
| title_fullStr | A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory |
| title_full_unstemmed | A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory |
| title_short | A Novel On-Ramp Merging Strategy for Connected and Automated Vehicles Based on Game Theory |
| title_sort | novel on ramp merging strategy for connected and automated vehicles based on game theory |
| url | http://dx.doi.org/10.1155/2020/2529856 |
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