GRIDS: Personalized Guideline Recommendations while Driving Through a New City

Abstract

Drive tourism has become increasingly popular in the last decade; however, driving through a new city is challenging as the road, and traffic environments vary significantly across cities. A driver habitual to driving in one city may face severe difficulty adapting to a different driving environment, leading to road fatalities. This paper develops GRIDS , an Explainable Model for Guidelines Recommendation for Inter-Domain Driving Safety , which learns the driving rules behind the changing environment and recommends the necessary personalized guidelines to a driver while driving through a new city. We develop an explainable domain adaptation model to provide customized recommendations in terms of driving guidelines, broadly categorized into four major feature categories of a driving environment. A thorough evaluation over the Carla driving simulator shows that the recommendations generated through GRIDS can help in improving driving safety.