Improving Incident Detection Effectiveness in Vehicular Networks: Methodology and Evaluation

In this paper a comprehensive and efficient incident detection approach is proposed, that uses probabilistic network and processing methodologies to exploit spatial and temporal correlations and dependencies in vehicular networks. The proposed approach, based on principal component analysis, provides an integrated way of effectively processing and organizing accumulated spatiotemporal information from a variety of different locations, vehicles and sources, and therefore allows for the development of enhanced and efficient transportation systems. The performance and operational effectiveness of our proposed incident detection methodology is achieved via modelling and simulation under various scenarios.