Toward an Intelligent Driving Behavior Adjustment Based on Legal Personalized Policies Within the Context of Connected Vehicles - Outay, Fatma; Jabeur, Nafaa; Haddad, Hedi; Bouyahia, Zied; Gharrad, Hana (Frontiers in Built Environment, 2021)
The advent of Connected Vehicles (CVs) is creating new opportunities within the transportation sector. It is, indeed, expected to improve road traffic safety, enhance mobility, reduce fuel consumption and gas emissions, as well as foster economic growth via investments and jobs. However, to motivate the deployment of CVs and maximize their related benefits, policymakers must create appropriate neutral legal frameworks. These frameworks should promote the innovation of current road infrastructures, support cooperation and interoperability between transportation systems, and encourage fair competition between companies while upholding consumer privacy as well as data protection. We argue that policymakers should also support innovative mobility services toward a better accommodation of individual drivers and vehicles. Within this scope, we are proposing in this paper an intelligent approach that promotes the implementation of personalized road policies based on driving behaviors, driving performance, and the ongoing road traffic situation. These policies, which are dynamic in space and time, ultimately aim to increase drivers’ awareness by encouraging behavioral self-regulation. To meet our goals, we are using software agents that autonomously manage the driving behaviors according to well-defined transitions between driving states while enabling appropriate message exchanges between CVs. We run software simulations as well as field tests and obtained promising results that would reflect the relevance of implementing our vision of personalized policies.