Risk Evaluation of Autonomous Vehicle Integration in Traffic Environments

The integration of Autonomous Vehicles (AV) into existing transportation systems presents significant challenges, including safety, infrastructure adaptation, and public acceptance. To address these issues, a structured risk assessment framework is essential for guiding decision-making processes. This paper studies the application of the Analytic Hierarchy Process (AHP) as a decision-support tool for evaluating the risk associated with AV integration. Focusing on three critical risk categories - hazard, vulnerability, and exposure - this study uses AHP to assess and prioritize risks. A case study based on the IN2CCAM European project is presented to evaluate the potential impact of AVs in both urban and extra-urban traffic environments. Key Performance Indicators are identified, and the relative weights of various risk factors are determined. The results indicate that the hazard category has the greatest impact on the integration of AVs, with the probability of accidents being the most critical factor. However, social acceptance, production costs and charging infrastructure limitations also play an important role in determining the feasibility of AV adoption.