Husnain Malik

Fuzzy Logic to Evaluate Driving Maneuvers: An Integrated Approach to Improve Training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us from building better training programs. Currently, there is a need to develop and evaluate advanced driving assistance systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel intelligent driver training system that analyzes crash risks for a given driving situation, providing avenues for the improvement and personalization of driver training programs. The analysis takes into account numerous variables synchronously acquired from the driver, the vehicle, and the environment. The system then segments out the maneuvers within a drive. This paper further presents the fuzzy set theory to develop the safety inference rules for each maneuver executed during the drive, and presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving maneuvers and then provides a comprehensive analysis of the drive used to give feedback to novice drivers.

How Consistent Are Drivers In Their Driving?A Driver Training Perspective

This paper describes how the value and effectiveness of driver training as a means of improving driver behavior and road safety continues to fuel research and societal debates. Knowledge about what are the characteristics of safe driving that need to be learned is extensive. Research has shown that young drivers are over represented in crash statistics. The encouraging fact is that novice drivers have shown improvement in road scanning pattern after training. This paper presents a driver behavior study conducted on a closed circuit track. A group of experienced and novice drivers performed repeated multiple maneuvers (i.e. turn, overtake and lane change) under identical conditions. Variables related to the driver, vehicle and environment were recorded in a research vehicle equipped with multiple in vehicle sensors such as global positioning system (GPS) accelerometers, vision processing, eye tracker and laser scanner. Each group consistently exhibited a set of driving pattern characterizing a particular group. Behavior such as the indicator usage before lane change, following distance while performing a maneuver were among the consistent observed behavior differentiating novice from experienced drivers. This paper highlights the results of the study and emphasizes the need for effective driver training programs that focuses on young and novice drivers.