A Rule-Based Cooperative Merging Strategy for Connected and Automated Vehicles

Ding, Jishiyu; Li, Zhiheng; Peng, Huei; Zhang, Yi

doi:10.1109/tits.2019.2928969

Cited by 116 publications

(59 citation statements)

References 21 publications

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“…Miculescu and Karaman [19] applied this method in a polling-system-based coordination in intersections with no traffic signals, which can reduce the delay time and is computationally efficient. Ding et al [20] formulates the scheduling process as a mixed integer linear programming problem and can generate a near-optimal merging sequence which can improve the traffic efficiency and reduce the computational cost.…”

Section: Related Workmentioning

confidence: 99%

Coordinated Control Algorithm at Non-Recurrent Freeway Bottlenecks for Intelligent and Connected Vehicles

Dongxin

et al. 2020

IEEE Access

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Intelligent and Connected Vehicle (ICV) technology is considered to be a solution to improve the traffic performance. Through the information exchange in real-time among the vehicles, the roadside infrastructures, and the cloud platform, the sensing of the vehicles can be enhanced. This also enables coordinated driving decisions, which can improve traffic operations, especially at bottleneck locations. This paper addresses the problem of coordinating the vehicles near the bottleneck locations to help the vehicles passing the area quickly and smoothly. A lane advisory algorithm is designed to reduce conflicts by encouraging early lane changes. A coordinated vehicle movement planning algorithm is proposed to achieve a smooth longitudinal reference speed profiles for vehicles in the subject area. The algorithm can open enough headway for vehicles to change the lane and continue their trips. The effectiveness of the algorithm is evaluated using SUMO (Simulation of Urban MObility) as the simulation tool with no communication between vehicles as the benchmark case as well as the case where the vehicular traffic follows the so-called First-in-First-Out (FIFO) principle. The results of the evaluation summarize and indicate that the Coordinated Control Algorithm (CCA) proposed in this paper can improve traffic performance in terms of the average speed, the waiting time, the total travel time, and the traffic flow rate under different levels of service. INDEX TERMS Coordinated control, coordinated movement planning, intelligent and connected vehicles, lane advisory, non-recurrent bottlenecks.

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Section: Related Workmentioning

confidence: 99%

Coordinated Control Algorithm at Non-Recurrent Freeway Bottlenecks for Intelligent and Connected Vehicles

Dongxin

et al. 2020

IEEE Access

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“…The objective is to coordinate all the vehicles passing the merging zone safely and efficiently and to mitigate the stop‐and‐go operations under mixed traffic conditions, where both CAVs and human‐driven vehicles (non‐CAVs) travel on the roads. We briefly review the model introduced in [7], where there are two legs, mainline and ramp road, illustrated in Fig. 2.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…In our previous approach [7], the proposed cooperative merging strategy computes a near‐optimal merging sequence in real time in terms of travel delay and safety, and the motion planning algorithm is designed for energy saving. The extended cooperative merging frameworks under mixed traffic scenario are presented in the following sections.…”

Section: Problem Descriptionmentioning

confidence: 99%

“…

M_{new}

and

R_{new}

in Fig. 3) are all CAVs, the assigned arrival time of newly detected CAVs can be determined through the merging sequence adjustment algorithm in [7], where the rule‐based cooperative merging strategy achieves a near‐optimal solution of the merging sequence. It should be noted that full coordination cases may only occur under high CAV penetration scenarios.…”

Section: Cooperative Merging Framework For Cavsmentioning

confidence: 99%

“…Our earlier work [7] has established a centralised cooperative merging framework for coordinating two strings of CAVs passing through the merging zone effectively and safely. In our approach, the rule‐based merging strategy computes a near‐optimal merging sequence in terms of travel delay and safety, and the motion planning algorithm is designed for energy‐saving.…”

Section: Introductionmentioning

confidence: 99%

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