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

Dhawankar, Piyush, Agrawal, Prashant, Abderezzak, Bilal, Kaiwartya, Omprakash, Busawon, Krishna and Raboacă, Maria Simona (2021) Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles. Mathematics, 9 (14). p. 1696. ISSN 2227-7390

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Official URL: https://doi.org/10.3390/math9141696

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.

Item Type: Article
Additional Information: Funding information: This work was supported by a grant from the Romanian Ministry of Research and Innovation, CCCDI—UEFISCDI, project number PN‐III‐P1‐1.2‐PCCDI‐2017‐0776/No. 36 PCCDI/15.03.2018, within PNCDI III and project number PN‐III‐P1‐1.2‐PCCDI‐2017‐0194/25 PCCDI within PNCDI III.
Uncontrolled Keywords: autonomous driving vehicles; vehicular communication; intelligent driver model; data-driven control model
Subjects: G400 Computer Science
G600 Software Engineering
H300 Mechanical Engineering
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 19 Jul 2021 16:04
Last Modified: 31 Jul 2021 10:06
URI: http://nrl.northumbria.ac.uk/id/eprint/46710

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