Authors: H. Tawfik, P. Liatsis
Addresses: Intelligent and Distributed Systems Laboratory, Deanery of Business and Computer Sciences, Liverpool Hope University, Hope Park, Liverpool L16 9JD, UK. ' Information and Biomedical Engineering Centre, School of Engineering and Mathematical Sciences City University, Northampton Square, London EC1V 0HB, UK
Abstract: This paper discusses a driving simulation framework, which focuses on the decision-making role performed at the tactical driving level. Our tactical driving technique using Genetic Algorithms (GAs), named GA-INTACT, accounts for the positions of a |subject| vehicle and those of other vehicles and their speed parameters in the surrounding traffic condition, and selects favourable speed change and lane transition actions for the |subject| vehicle, according to safety, speed and driving behaviour criteria. The use of GAs for obtaining near-optimum driving solutions eliminates the need for learning driving patterns, and handles the complex nature of modelling tactical driving. In particular, the proposed framework addresses the role of driving behaviour in influencing drivers| tactical decisions – a matter that is not treated systematically and sufficiently by other driving simulation methods.
Keywords: driver behaviour; genetic algorithms; GAs; intelligent systems framework; tactical driving; driving modelling; driving decision making; simulation; speed changes; lane transition; safety.
International Journal of Intelligent Systems Technologies and Applications, 2008 Vol.5 No.1/2, pp.20 - 48
Available online: 05 May 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article