A Dual-Step Approach for Implementing Smart AVS in Cars
Received: 15 May 2024 | Revised: 3 June 2024 | Accepted: 6 June 2024 | Online: 2 August 2024
Corresponding author: Bachu Poornima
Abstract
The Smart Autonomous Vehicular System (AVS) is designed to combine technologies such as sensors, cameras, radars, and machine learning algorithms in cars. The implementation of Smart AVS in smart cars has the potential to revolutionize the automotive industry and transform the way we think about transportation. In this paper, the implementation of Smart AVS in smart cars includes two steps. Firstly, the architecture is designed using Microsoft Threat Modelling tool. Secondly, with the use of Engineering Software, smart cars are constructed and simulated to verify and validate algorithms related to autonomous driving, path planning, and other intelligent functionalities. Simulating these algorithms in a controlled virtual environment helps to identify and address issues before implementation on physical vehicles. The main advantages of using the proposed model are early detection of vulnerabilities, realistic simulation of sensor inputs, communication protocol testing, cloud integration validation, user interface, and consumer experience, and validation of compliance with security standards.
Keywords:
GPS, IoT devices, Temperature sensors, engine control module, Microsoft Threat Modelling, sensors, smart Autonomous Vehicular System (AVS)Downloads
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