Optimizing Vehicle Approach Strategies for Connected Signalized Intersections

Günther, Hendrik-Jörn; Kumar, Vivek; Hussain, Shah; Sommerwerk, Kay; Bondarenko, Dennis

doi:10.1109/vnc48660.2019.9062810

Cited by 4 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Safe cooperation and collaboration among multiple vehicles is one of the prospective applications for road safety, when conflicts arise on shared road segments, such as stationary intersections [5]- [8] and dynamic intersections [9], including merge points, single-track lanes, and construction zones [10], [11]. Under these cooperative protocols, each CAV uses Vehicle-to-Infrastructure (V2I) Communications and/or Vehicle-to-Vehicle (V2V) Communications for inter-vehicle interaction and negotiation to avoid vehicle collisions and deadlocks.…”

Section: Introductionmentioning

confidence: 99%

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Aoki¹,

Ragunathan²,

Rajkumar³

2022

Preprint

View full text Add to dashboard Cite

Connected and Automated Vehicles (CAVs) are highly expected to improve traffic throughput and safety at road intersections, single-track lanes, and construction zones. However, multiple CAVs can block each other and create a mutual deadlock around these road segments (i) when vehicle systems have a failure, such as a communication failure, control failure, or localization failure and/or (ii) when vehicles use a long shared road segment. In this paper, we present an Autonomous Deadlock Detection and Recovery Protocol at Intersections for Automated Vehicles named A-DRIVE that is a decentralized and timesensitive technique to improve traffic throughput and shorten worst-case recovery time. To enable the deadlock recovery with automated vehicles and with human-driven vehicles, A-DRIVE includes two components: V2V communication-based A-DRIVE and Local perception-based A-DRIVE. V2V communication-based A-DRIVE is designed for homogeneous traffic environments in which all the vehicles are connected and automated. Local perception-based A-DRIVE is for mixed traffic, where CAVs, non-connected automated vehicles, and human-driven vehicles co-exist and cooperate with one another. Since these two components are not exclusive, CAVs inclusively and seamlessly use them in practice. Finally, our simulation results show that A-DRIVE improves traffic throughput compared to a baseline protocol.

show abstract

Section: Introductionmentioning

confidence: 99%

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Aoki¹,

Ragunathan²,

Rajkumar³

2022

Preprint

View full text Add to dashboard Cite

show abstract

A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System

et al. 2023

View full text Add to dashboard Cite

With the application of mobile communication technology in the automotive industry, intelligent connected vehicles equipped with communication and sensing devices have been rapidly promoted. The road and traffic information perceived by intelligent vehicles has important potential application value, especially for improving the energy-saving and safe-driving of vehicles as well as the efficient operation of traffic. Therefore, a type of vehicle control technology called predictive cruise control (PCC) has become a hot research topic. It fully taps the perceived or predicted environmental information to carry out predictive cruise control of vehicles and improves the comprehensive performance of the vehicle-road system. Most existing reviews focus on the economical driving of vehicles, but few scholars have conducted a comprehensive survey of PCC from theory to the status quo. In this paper, the methods and advances of PCC technologies are reviewed comprehensively by investigating the global literature, and typical applications under a cloud control system (CCS) are proposed. Firstly, the methodology of PCC is generally introduced. Then according to typical scenarios, the PCC-related research is deeply surveyed, including freeway and urban traffic scenarios involving traditional vehicles, new energy vehicles, intelligent vehicles, and multi-vehicle platoons. Finally, the general architecture and three typical applications of the cloud control system (CCS) on PCC are briefly introduced, and the prospect and future trends of PCC are proposed.

show abstract

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Aoki¹,

Ragunathan²,

Rajkumar³

2022

2022 IEEE Intelligent Vehicles Symposium (IV)

View full text Add to dashboard Cite

Optimizing Vehicle Approach Strategies for Connected Signalized Intersections

Cited by 4 publications

References 11 publications

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

A Review and Outlook on Predictive Cruise Control of Vehicles and Typical Applications Under Cloud Control System

A-DRIVE: Autonomous Deadlock Detection and Recovery at Road Intersections for Connected and Automated Vehicles

Contact Info

Product

Resources

About