Delay-Aware Design, Analysis and Verification of Intelligent Intersection Management

Zheng, Bowen; Lin, Chung-Wei; Liang, Hengyi; Shiraishi, Shinichi; Li, Wenchao; Zhu, Qi

doi:10.1109/smartcomp.2017.7946999

Cited by 28 publications

(10 citation statements)

References 14 publications

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“…Importantly, it still not clear if and under which circumstances intelligent intersections can provide significant benefits. For example, [73] find that introducing only 10% human drivers into scenarios with AUVs can render intelligent intersections as useful as traffic lights, and [81] show that communication delays can severely impact performance. Therefore, the key question is whether a tradeoff in privacy is worthwhile.…”

Section: G Intelligent Intersectionsmentioning

confidence: 99%

Privacy and Trust in the Internet of Vehicles

Zavvos

Gerding

Yazdanpanah

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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The Internet of Vehicles aims to fundamentally improve transportation by connecting vehicles, drivers, passengers, and service providers together. Several new services such as parking space identification, platooning and intersection control-to name just a few-are expected to improve traffic congestion, reduce pollution, and improve the efficiency, safety and logistics of transportation. Proposed end-user services, however, make extensive use of private information with little consideration for the impact on users and third parties (those individuals whose information is indirectly involved). This article provides the first comprehensive overview of privacy and trust issues in the Internet of Vehicles at the service level. Various concerns over privacy are formalised into four basic categories: privacy of personal information, trust, consent to provide information, and multi-party privacy. To help analyse services and to facilitate future research, the main relevant end-user services are taxonomised according to voluntary and involuntary information they require and produce. Finally, this work identifies several open research problems and highlights general approaches to address them. These especially relate to measuring the tradeoff between privacy and service functionality, automated consent negotiation, trust towards the IoV and its individual services, and identifying and resolving multi-party privacy conflicts.

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Section: G Intelligent Intersectionsmentioning

confidence: 99%

Privacy and Trust in the Internet of Vehicles

Zavvos

Gerding

Yazdanpanah

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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“…Furthermore, to elevate cooperation and efficiency in particular zones, they presented market mechanisms. In a different approach, Zheng et al [221] proposed a delay-tolerant IM protocol in terms of communication. Besides, a framework was devised for safety, performance and liveliness analysis of the protocol and showed that the system was collision free and decreased delay compared to the traffic lights.…”

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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“…We then apply the cross-layer methodology to the design and verification of centralized autonomous intersections in [6]. In this application, vehicles approaching an intersection exchange information with an intersection manager via V2I messages, and the intersection manager decides the order for vehicles to pass the intersection.…”

Section: Cross-layer Design For Connected Vehiclesmentioning

confidence: 99%

Cross-Layer Design of Automotive Systems

et al. 2021

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With growing system complexity and closer cyberphysical interaction, there are increasingly stronger dependencies between different function and architecture layers in automotive systems. This paper first introduces several cross-layer approaches we developed in the past for holistically addressing multiple system layers in the design of individual vehicles and of connected vehicle applications; and then presents a new methodology based on the weakly-hard paradigm for leveraging the scheduling flexibility in architecture layer to improve the system performance at function layer. The results of these works demonstrate the importance and effectiveness of cross-layer design for automotive systems.

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Delay-Aware Design, Analysis and Verification of Intelligent Intersection Management

Cited by 28 publications

References 14 publications

Privacy and Trust in the Internet of Vehicles

Privacy and Trust in the Internet of Vehicles

A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles

Cross-Layer Design of Automotive Systems

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