Source of Publication
Procedia Computer Science
In recent years, autonomous vehicles (AVs), connected vehicles (CVs) and all relative technology have been in the spotlight, being intensively researched and developed. There is high anticipation on the benefits of automation and the overall reform it will bring to the transport sector, with some optimistic estimates considering it as a reality within the next few years. Evidently, AVs and CVs are attracting considerable attention and are developed very rapidly, cultivating great expectations for traffic safety improvements. While their potential is enormous and undeniable, benefits are not automatically guaranteed as there are parameters that currently appear unforeseen. This paper investigates the ways that monitoring and enforcement of autonomous vehicles can be improved and serious problems such as tailgating and crashes can be mitigated. This paper's result could provide useful conclusions about human factor, the effectiveness of existing monitoring and enforcing systems and possible future systems regarding enforcement and monitoring of autonomous vehicles (AVs).
AVs, Safety of AVs, Tailgating, Monitoring, Enforcement
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Zavantis, Dimitrios; Outay, Fatma; El-Hansali, Youssef; Yasar, Ansar; Shakshuki, Elhadi; and Malik, Haroon, "Autonomous Driving and Connected Mobility Modeling: Smart Dynamic Traffic Monitoring and Enforcement System for Connected and Autonomous Mobility" (2022). All Works. 5300.
Indexed in Scopus
Open Access Type
Gold: This publication is openly available in an open access journal/series