Optimal merging into a high-speed lane dedicated to connected autonomous vehicles

Davis, L.C.

doi:10.1016/j.physa.2020.124743

Cited by 16 publications

(2 citation statements)

References 31 publications

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“…Obviously, the stationary merging position fails to make full advantage of the space resource of the merging section, bringing the potential negative effects of congestion when expanded to some other traffic rates. (2) Second, existing studies usually concentrate on the complete connected environment [26][27][28][29]. Scholte et al proposed a control strategy for the merging of a single vehicle into a cooperative platoon [30].…”

Section: Introductionmentioning

confidence: 99%

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Liu

Cen

Yao

et al. 2022

Journal of Advanced Transportation

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Freeway on-ramp merging area is deemed to be typical bottlenecks section, which leads to low traffic efficiency, congestions, and frequent accidents. Most existing studies on merging for the connected and automated vehicles focus on merging at a single fixed merging point. However, the problem of coordination between merging vehicle and arterial traffic flow in the acceleration lane is ignored in the existing studies. is study proposes a merging model, which combined safety and coordination of CAVs with featuring optimal merging positions. e proposed model has two stages: one is analysis of merging velocity of the insertable gap and the other one is determining constraint condition of cooperative merging. e outputs of first stage are interval of merging speed and the mergeable range. e outputs of second stage are optional insertable gap and the corresponding driving scheme.en, a traffic simulation experiment is designed to evaluate the proposed model. e simulation results show that the proposed model can effectively guarantee driving safety and make the merging process smoother with 28.7% reduction in travel time for the CAV merging. Furthermore, the proposed model does not sacrifice the interests of surrounding traffic to assist in CAV merging.e results indicate the promising potential of using the proposed methods can approximately get a fair use of road resources for each CAV.

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Section: Introductionmentioning

confidence: 99%

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Liu

Cen

Yao

et al. 2022

Journal of Advanced Transportation

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show abstract

“…An autonomous vehicle (AV, i.e., automated or self-driving vehicle) equipped with advanced technologies assists a human driver or to control the vehicle independently, where human interference may not be required [1,2]. e control decisions, such as accelerating, deaccelerating, changing lanes, and parking, can be made by a human driver or an autonomous system, depending on the automated levels of the vehicle and the perception results of the surrounding environment (e.g., pedestrians, cyclists, other vehicles, traffic signals, and school zones) [2][3][4][5]. Vehicle automation can be divided into several levels, e.g., no automation, partial automation, high automation, or full automation according to the involvement of a human driver or automated system in monitoring the surrounding environment and control the vehicle.…”

Section: Introductionmentioning

confidence: 99%

Safety of Autonomous Vehicles

Wang

Zhang

Huang

et al. 2020

Journal of Advanced Transportation

100

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Autonomous vehicle (AV) is regarded as the ultimate solution to future automotive engineering; however, safety still remains the key challenge for the development and commercialization of the AVs. Therefore, a comprehensive understanding of the development status of AVs and reported accidents is becoming urgent. In this article, the levels of automation are reviewed according to the role of the automated system in the autonomous driving process, which will affect the frequency of the disengagements and accidents when driving in autonomous modes. Additionally, the public on-road AV accident reports are statistically analyzed. The results show that over 3.7 million miles have been tested for AVs by various manufacturers from 2014 to 2018. The AVs are frequently taken over by drivers if they deem necessary, and the disengagement frequency varies significantly from 2 × 10−4 to 3 disengagements per mile for different manufacturers. In addition, 128 accidents in 2014–2018 are studied, and about 63% of the total accidents are caused in autonomous mode. A small fraction of the total accidents (∼6%) is directly related to the AVs, while 94% of the accidents are passively initiated by the other parties, including pedestrians, cyclists, motorcycles, and conventional vehicles. These safety risks identified during on-road testing, represented by disengagements and actual accidents, indicate that the passive accidents which are caused by other road users are the majority. The capability of AVs to alert and avoid safety risks caused by the other parties and to make safe decisions to prevent possible fatal accidents would significantly improve the safety of AVs. Practical applications. This literature review summarizes the safety-related issues for AVs by theoretical analysis of the AV systems and statistical investigation of the disengagement and accident reports for on-road testing, and the findings will help inform future research efforts for AV developments.

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Discussion and Outlook

Kerner

2021

Understanding Real Traffic

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Optimal merging into a high-speed lane dedicated to connected autonomous vehicles

Cited by 16 publications

References 31 publications

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Safety of Autonomous Vehicles

Discussion and Outlook

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