Cooperative vehicle‐actuator system: a sequence‐based framework of cooperative intersections management

Wu, Jia; Perronnet, Florent; Abbas-Turki, Abdeljalil

doi:10.1049/iet-its.2013.0093

Cited by 46 publications

(16 citation statements)

References 34 publications

(40 reference statements)

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“…Ghaffarian et al [176] introduced a V2I-based traffic controller that utilized integer linear program (ILP) to calculate optimal and safe passing orders of the vehicles trajectories while ensuring maximal throughput. Researchers in [177]- [179] studied sequence-based protocols for safe TP in cooperative real intersection. Vehicles negotiated the right of way individually with the controller with regard to a passing sequence to increase the throughput.…”

Section: Safety and Efficiencymentioning

confidence: 99%

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Gholamhosseinian

Seitz

2022

IEEE Access

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Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy.INDEX TERMS Vehicular ad-hoc networks (VANETs), intersection management (IM), vehicle-tovehicle (V2V), vehicle-to-infrastructure (V2I), trajectory planning (TP), spatio-temporal (ST), connected autonomous vehicles (CAVs), vulnerable road users (VRUs), connected vehicles (CVs), autonomous vehicle (AVs). II. INTERSECTION MANAGEMENT (IM) FUNDAMENTALS A. ARCHITECTURE ALTERNATIVESASHKAN GHOLAMHOSSEINIAN (Graduate Student Member, IEEE) received the bachelor's degree in computer engineering-software in Iran, the M.Sc. degree in computer network engineering from Halmstad University, Sweden, and the Post master's degree in communications for intelligent transport systems from Eurecom, France. He is currently pursuing the Ph.D. degree in electrical engineering and information technology with the Communication Networks Group, Technische Universität Ilmenau, Germany. His research interests include vehicular networks, intelligent transport systems, computer networks, and wireless and mobile networks and communications. JOCHEN...

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Section: Safety and Efficiencymentioning

confidence: 99%

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Gholamhosseinian

Seitz

2022

IEEE Access

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“…Two-way communication is used to receive status information from approaching vehicles, such as current position, velocity, and destination, Cooperative Adaptive Cruise Control (CACC) has been explored to allow vehicles to coordinate their movements relative to each other in order to pass through an intersection efficiently, with reduced delay and fuel consumption [40]. The work in [41] studied simple rules for each vehicle to behave as it arrives at an intersection, taking into account whether it has right-of-way and its distance to other vehicles, yielding efficient and safe intersection crossings.…”

Section: A Vehicle-to-vehicle Cooperation and Reasoningmentioning

confidence: 99%

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Loke

2019

IEEE Trans. Intell. Veh.

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The connected automated vehicle has been often touted as a technology that will become pervasive in society in the near future. One can view an automated vehicle as having Artificial Intelligence (AI) capabilities, being able to self-drive, sense its surroundings, recognise objects in its vicinity, and perform reasoning and decision-making. Rather than being stand alone, we examine the need for automated vehicles to cooperate and interact within their socio-cyber-physical environments, including the problems cooperation will solve, but also the issues and challenges. We review current work in cooperation for automated vehicles, based on selected examples from the literature. We conclude noting the need for the ability to behave cooperatively as a form of social-AI capability for automated vehicles, beyond sensing the immediate environment and beyond the underlying networking technology.5 At https://www.sae.org/standardsdev/dsrc/ and in particular the message set dictionary SAE J2735 at https

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“…For the lateral control of a platoon, safety must be considered an important issue, which could include vehicle collision avoidance [17]. Hesham Rakha suggested that intersection management could be considered a collaborative optimisation problem [18], but it is much more difficult for each vehicle to independently implement path planning control.…”

Section: Platoon Control Strategymentioning

confidence: 99%

Lateral control system for vehicle platoon considering vehicle dynamic characteristics

Liu

Zong

Zhang

2019

IET Intelligent Transport Systems

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Cooperative vehicle‐actuator system: a sequence‐based framework of cooperative intersections management

Cited by 46 publications

References 34 publications

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

Lateral control system for vehicle platoon considering vehicle dynamic characteristics

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