Abstract

The increasing need for mobility has brought about significant changes in transportation infrastructures. Inefficiencies cause enormous losses of time, decrease in the level of safety for both vehicles and pedestrians, high pollution, degradation of quality of life, and huge waste of nonrenewable fossil energy.The scope of this article is to introduce novel functionality for providing knowledge to vehicles, thus jointly managing traffic and safety. This will be achieved through the design of the proposed functionality, which, at a high level, will comprise (1) sensor networks formed by vehicles of a certain vicinity that exchange traffic-related information, (2) cognitive management functionality placed inside the vehicles for inferring knowledge and experience, and (3) cognitive management functionality in the overall transportation infrastructure. The goal of the aforementioned three main components shall be to issue directives to the drivers and the overall transportation infrastructure valuable in context handling.

Abstract

The occurrence of an incident is one of the main causes of traffic congestion and delay on urban freeways. Currently, the development of an efficient traffic incident management process is an emerging issue in intelligent transport systems. The focus of this study is to develop an incident response model for use in an incident management program designed to reduce incident related traffic congestion and delays. Establishing a fuzzy control system based on a real operation process of incident response would help decrease the workload of operators who are constantly making essential decisions, and would be helpful in developing a more reliable operation procedure. Traffic incident data obtained from traffic detectors and information systems on freeways should be considered in order to determine the best form of operation. In this study, a fuzzy incident response model is formulated in terms of incident, type of vehicle, type of incident vehicle, location of incident vehicle, and incident service time. In order to analyze the reliability of the proposed model, the application of the model is made using the actual incident data collected on the freeway in the Los Angeles area. The application of the model shows that the fuzzy incident response system is very effective in describing the actual judgment of the incident operators in terms of incident service time. Document type: Article

Abstract

This paper presents the results of the assessment phase of the project PRIMA (Pro-Active Incident Management), where the benefits, costs and risks of novel traffic incident management techniques are investigated. The project targets the enhancement of current state-of-the-art measures for handling incidents, i.e. road accidents, breakdowns and congestion, by recommending proactive techniques. To this end, modern technologies such as eCall, C2X or xFCD are assessed in terms of their potential to optimize the overall incident duration and response. Results are derived from a scenario-based assessment methodology involving macroscopic traffic simulations, traffic performance calculations and cost-benefit analysis. The work presented in this paper is being followed up by the development of practical guidelines and recommendations for traffic managers of motorways and primary roads.