LEARNING DRIVING PATTERNS TO SUPPORT NAVIGATION DECISION MAKING: PRELIMINARY RESULTS

Navigation is a science and technology of finding the position, course, and distance traveled by a ship, plane or other types of vehicles. The navigation task is a decision-making procedure, where at least one of the input or output parameters has spatial properties, and is related to current or future vehicle position or attitude. In recent years research in car navigation systems and driver support systems achieved exciting results but there are still some outstanding problems. This paper presents a novel approach to providing driver support for guidance navigation tasks. Although driving is a very complex process, there are a number of regularities, and signals from navigation sensors contain a large number of patterns that could be better exploited to support navigation guidance tasks. A system based on artificial intelligence techniques could learn common sequences of driving events (driving patterns) by comparing previous experience (pattern history) and current events (context). The system could predict future events and detect differences between predicted and actual signals. A detected difference could serve as the basis for providing support for guidance navigation tasks. This paper presents preliminary research results. (a) For the covering entry of this conference, please see IRRD abstract no. E200232.