An affective intelligent driving agent: driver's trajectory and activities prediction.

Abstract

The traditional relationship between the car, driver, and city can be described as waypoint navigation with additional traffic and maintenance information. The car can receive and store waypoint information, find the shortest route to these waypoints, integrate traffic information, find points-of-interest, and alert the driver of a pre-programmed set of maintenance issues related to the car. Here, we propose a new route system that is multi-goal-centric rather than waypoint-centric. Instead of focusing on determining the route to a specified waypoint, as done in commercially available navigation systems, the system will analyze the driver's behavior in order to extract the potential set(s) of goals that the driver would like to achieve. The system must also understand the city on a number of levels: physical, social, and commercial. This provides the foundation for a social and intelligent driving assistant, that helps the driver achieve his goals and helps the city perform better through interaction between both entities.