Penetration effect of connected and automated vehicles on cooperative on‐ramp merging

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

doi:10.1049/iet-its.2019.0488

Cited by 37 publications

(15 citation statements)

References 29 publications

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“…Similarly, Rios-Torres and Malikopoulos (2018) applied the motion planner developed in Rios-Torres and Malikopoulos (2017a) to an environment where CAV and HDV coexisted to investigate how the increasing percentage of CAVs may influence the energy use at on-ramp merging. Nevertheless, these studies (Rios-Torres and Malikopoulos, 2018; Ding et al , 2019) were more focused on assessing the impacts of CAV penetration under the existing control framework rather than designing a specific CAV control strategy for the mixed traffic conditions.…”

Section: Merging Control For Single-lane Freeways With Mixed Trafficmentioning

confidence: 99%

“…The problem assumed different driving rules for CAVs and HDVs and considered the benefits of a series of upstream vehicles on the main road. Ding et al (2019) applied their previous strategy (Ding et al , 2020) to the mixed CAV-HDV condition. They discussed the impacts of CAV penetration on throughput, traffic efficiency, fuel use and emission.…”

Section: Merging Control For Single-lane Freeways With Mixed Trafficmentioning

confidence: 99%

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Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review

Zhu

Easa

Gao

2022

JICV

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Purpose On-ramp merging areas are typical bottlenecks in the freeway network since merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and lead to various negative impacts on traffic efficiency and safety. The connected and autonomous vehicles (CAVs), with their capabilities of real-time communication and precise motion control, hold a great potential to facilitate ramp merging operation through enhanced coordination strategies. This paper aims to present a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field. Design/methodology/approach The review comprehensively covers 44 papers recently published in leading transportation journals. Based on the application context, control strategies are categorized into three categories: merging into sing-lane freeways with total CAVs, merging into sing-lane freeways with mixed traffic flows and merging into multilane freeways. Findings Relevant literature is reviewed regarding the required technologies, control decision level, applied methods and impacts on traffic performance. More importantly, the authors identify the existing research gaps and provide insightful discussions on the potential and promising directions for future research based on the review, which facilitates further advancement in this research topic. Originality/value Many strategies based on the communication and automation capabilities of CAVs have been developed over the past decades, devoted to facilitating the merging/lane-changing maneuvers at freeway on-ramps. Despite the significant progress made, an up-to-date review covering these latest developments is missing to the authors’ best knowledge. This paper conducts a thorough review of the cooperation/coordination strategies that facilitate freeway on-ramp merging using CAVs, focusing on the latest developments in this field. Based on the review, the authors identify the existing research gaps in CAV ramp merging and discuss the potential and promising future research directions to address the gaps.

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Section: Merging Control For Single-lane Freeways With Mixed Trafficmentioning

confidence: 99%

Section: Merging Control For Single-lane Freeways With Mixed Trafficmentioning

confidence: 99%

Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review

Zhu

Easa

Gao

2022

JICV

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“…To address the lane merging issues for CAVs, the centralized control approach has been widely studied by many researchers [9]- [11]. A centralized controller is proposed to control and manage the vehicles within the certain controlled area [12].…”

Section: B Related Workmentioning

confidence: 99%

Cooperative Decision Making of Connected Automated Vehicles at Multi-lane Merging Zone: A Coalitional Game Approach

Hang

Huang

et al. 2021

Preprint

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To address the safety and efficiency issues of vehicles at multi-lane merging zones, a cooperative decision-making framework is designed for connected automated vehicles (CAVs) using a coalitional game approach. Firstly, a motion prediction module is established based on the simplified single-track vehicle model for enhancing the accuracy and reliability of the decisionmaking algorithm. Then, the cost function and constraints of the decision making are designed considering multiple performance indexes, i.e. the safety, comfort and efficiency. Besides, in order to realize human-like and personalized smart mobility, different driving characteristics are considered and embedded in the modeling process. Furthermore, four typical coalition models are defined for CAVS at the scenario of a multi-lane merging zone. Then, the coalitional game approach is formulated with model predictive control (MPC) to deal with decision making of CAVs at the defined scenario. Finally, testings are carried out in two cases considering different driving characteristics to evaluate the performance of the developed approach. The testing results show that the proposed coalitional game based method is able to make reasonable decisions and adapt to different driving characteristics for CAVs at the multi-lane merging zone. It guarantees the safety and efficiency of CAVs at the complex dynamic traffic condition, and simultaneously accommodates the objectives of individual vehicles, demonstrating the feasibility and effectiveness of the proposed approach.

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“…Although these research efforts [24] aim at enhancing our understanding of improving the efficiency through coordination of CAVs in a mixed traffic environment, deriving a tractable solution to the problem of CAV coordination at merging or roundabout scenario still remains challenging. Several approaches reported in the literature implemented well-known car-following models, which emulate the human-driving behavior [25], [26], to derive a deterministic quantification of the vehicle trajectory [27], [28]. Other approaches have used carfollowing models [29] or learning algorithms [30], [31] for CAV coordination in mixed traffic environment.…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Optimally Coordinated Connected and Automated Vehicles in a Mixed Traffic Environment

Valencia¹,

Mahbub²,

Malikopoulos³

2022

Preprint

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Trajectory planning of connected and automated vehicles (CAVs) poses significant challenges in a mixed traffic environment due to the presence of human-driven vehicles (HDVs). In this paper, we apply a framework that allows optimal coordination of CAVs and HDVs traveling through a traffic corridor consisting of an on-ramp merging, a speed reduction zone, and a roundabout. We study the impact of different penetration rates of CAVs and traffic volumes on the efficiency of the corridor. We provide extensive simulation results and report on the benefits in terms of total travel time and fuel economy.

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Penetration effect of connected and automated vehicles on cooperative on‐ramp merging

Cited by 37 publications

References 29 publications

Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review

Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review

Cooperative Decision Making of Connected Automated Vehicles at Multi-lane Merging Zone: A Coalitional Game Approach

Performance Analysis of Optimally Coordinated Connected and Automated Vehicles in a Mixed Traffic Environment

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