作者单位: |
1Ph.D. Student, School of Transportation, Southeast Univ., Nanjing 210096, China (corresponding author).
2Ph.D. Student, Jiangsu Key Laboratory of Urban ITS, Southeast Univ., Nanjing 210096, China.
3Professor, Joint Research Institute on Internet of Mobility, Southeast Univ. and Univ. of Wisconsin-Madison, Nanjing 210096, China.
4Lecturer, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast Univ., Nanjing 210096, China.
5Lecturer, Jiangsu Province Collaborative Innovation Center for Technology and Application of Internet of Things, Southeast Univ., Nanjing 210096, China. |
摘要: |
As traffic demands increase rapidly on highways, effective merging strategies are necessary to cooperate with intelligent vehicles and improve traffic operations. Existing merging algorithms for connected vehicles rarely consider the inflow from on-ramps. Also, the merging order of vehicles is generally generated based on very simple rules. In this paper, a cooperative merging strategy is developed for vehicles wirelessly connected to other vehicles and roadside infrastructure. The cooperative merging is formulated as an optimization problem, which takes as objectives the minimization of travel time of mainline vehicles and maximization of the number of merging vehicles. This problem is solved by a genetic algorithm. The effectiveness of this strategy is verified in MATLAB with various simulation scenarios. By comparing the simulation results with a platoon-velocity-based merging strategy, the cooperative merging scheme proves to improve traffic performance in terms of traffic efficiency and fuel consumption. Significant improvements are obtained, especially when mainline and on-ramp demand are both particularly high. To conclude, the proposed strategy is applicable to cooperative merging operations under saturated traffic conditions. |