Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles

Piyush Dhawankar, Prashant Agrawal, Bilal Abderezzak, Omprakash Kaiwartya, Krishna Busawon and Maria Simona Raboacă
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Piyush Dhawankar: Department of Computer Science, University of York, York YO10 5GH, UK
Prashant Agrawal: Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK
Bilal Abderezzak: Laboratoire de l’Énergie et des Systèmes Intelligent (LESI), University of Khemis Miliana, Road of Theniet El Had, Khemis Miliana 44225, Algeria
Omprakash Kaiwartya: School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, UK
Krishna Busawon: Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle Upon Tyne NE1 8ST, UK
Maria Simona Raboacă: Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, 720229 Suceava, Romania

Mathematics, 2021, vol. 9, issue 14, 1-24

Abstract: This paper is concerned with designing and numerically implementing a V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) control system architecture for a platoon of autonomous vehicles. The V2X control architecture integrates the well-known Intelligent Driver Model (IDM) for a platoon of Autonomous Driving Vehicles (ADVs) with Vehicle-to-Infrastructure (V2I) Communication. The main aim is to address practical implementation issues of such a system as well as the safety and security concerns for traffic environments. To this end, we first investigated a channel estimation model for V2I communication. We employed the IEEE 802.11p vehicular standard and calculated path loss, Packet Error Rate (PER), Signal-to-Noise Ratio (SNR), and throughput between transmitter and receiver end. Next, we carried out several case studies to evaluate the performance of the proposed control system with respect to its response to: (i) the communication infrastructure; (ii) its sensitivity to an emergency, inter-vehicular gap, and significant perturbation; and (iii) its performance under the loss of communication and changing driving environment. Simulation results show the effectiveness of the proposed control model. The model is collision-free for an infinite length of platoon string on a single lane road-driving environment. It also shows that it can work during a lack of communication, where the platoon vehicles can make their decision with the help of their own sensors. V2X Enabled Intelligent Driver Model (VX-IDM) performance is assessed and compared with the state-of-the-art models considering standard parameter settings and metrics.

Keywords: autonomous driving vehicles; vehicular communication; intelligent driver model; data-driven control model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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