Scheduling tasks in real-time systems using evolutionary strategies
WPDRTS '95 Proceedings of the 3rd Workshop on Parallel and Distributed Real-Time Systems
Active guided evolution strategies for large-scale vehicle routing problems with time windows
Computers and Operations Research
Car Navigation System Based on Hybrid Genetic Algorithm
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 05
IEEE Transactions on Intelligent Transportation Systems
MASCOTS '11 Proceedings of the 2011 IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems
Expert Systems with Applications: An International Journal
VEACON: A Vehicular Accident Ontology designed to improve safety on the roads
Journal of Network and Computer Applications
Computer Simulations of VANETs Using Realistic City Topologies
Wireless Personal Communications: An International Journal
Hi-index | 12.05 |
Nowadays, traffic jams in urban areas have become a problem that keeps growing every year since the number of vehicles in our cities is continuously increasing. One of the most common causes producing traffic jams are vehicle accidents. Moreover, the arrival time of the emergency services could be raised due to traffic congestion. Intelligent Transportation Systems (ITS) have a key role in order to reduce or mitigate this problem. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, thereby reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on the Dijkstra algorithm, and two approaches based on Evolution Strategies. Notice that, when an accident occurs, time is a critical issue, and the strategies here proposed contribute to find the optimal solution within a short time period.