AAC 2022 Paper Abstract

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Paper TuBT3.3

Khan, Rahan (OHIO State University), Hanif, Athar (The Ohio State University), Ahmed, Qadeer (The Ohio State University)

Cooperative Navigation Strategy for Connected Autonomous Vehicle Operating at Smart Intersection

Scheduled for presentation during the Regular Session "Position, Navigation, and Timing Security in Highly Automated Vehicles" (TuBT3), Tuesday, August 30, 2022, 15:40−16:00, Ballroom

10th IFAC International Symposium on Advances in Automotive Control, August 28-31, 2022, Columbus, Ohio, USA

This information is tentative and subject to change. Compiled on March 29, 2024

Keywords Position, navigation and timing safety and security in automotive systems, Safety of the intended functionality, Control, guidance and navigation of autonomous vehicles

Abstract

This paper focuses on the cooperative navigation strategy for connected autonomous vehicles operating at smart intersections. The goal of this work is a cooperative navigation system to achieve cooperative collision avoidance for enhancing the safety and capacity of the intersection. This work considers cooperative connected autonomous vehicles operating simultaneously with non-cooperative autonomous vehicles. This work uses beyond visual range scenarios to reduce vulnerable situations. Beyond visual range, information is implemented by using the data from the roadside units, autonomous intersection management system, smart traffic lights, and onboard units. The efficacy of this work is validated in MATLAB/Simulink environment. The simulation results show the separation time within the set upper and lower bounds. That ensures that the ego vehicle does not collide with others at the intersection. The cooperative collision avoidance algorithm guides the ego vehicle as soon as the ego vehicle comes in the range of the intersection service area, which increases the safety and capacity of the intersection. This strategy is comfortably used for both an unsignalized and signalized intersection. In an unsignalized intersection scenario, the ego vehicle uses an onboard unit. In signalized intersection scenario, the ego vehicle uses a roadside unit, onboard unit, autonomous intersection management system, and smart traffic lights. As no such framework is found in the literature. The proposed framework is the near-future requirement where the connected autonomous vehicle utilizes the information from smart infrastructure devices.

 

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