A Neurofuzzy Approach to Modeling Longitudinal Driving Behavior and Driving Task Complexity

Integrated Driving Behavior Modeling

A framework for integrated driving behavior modeling, based on the concepts of short-term goal and short-term plan is proposed. Drivers are assumed to conceive and perform short-term plans in order to accomplish short-term goals. This behavioral framework captures drivers' planning capabilities and allows decisions to be based on anticipated future conditions. An integrated driving behavior mod...

Longitudinal Driving Behavior: Theory and Empirics

Modeling and Prediction of Driving Behavior

Driving assistance systems that adapt to an individual driver are essential for avoiding traffic accidents because there are individual differences in the way of driving. To realize such systems, it is necessary to take account of not only observable physical quantities, but also information inferred from observation. For example, a collision avoidance system warns a driver according to an esti...

A Scenario-Adaptive Driving Behavior Prediction Approach to Urban Autonomous Driving

Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles’ driving behaviors plays a crucial role in autonomous vehicles. Most traditional driving behavior prediction models work only for a specific traffic scenario and cannot be adapted to different scenarios. In addition, priori...

Comparing Expert and Novice Driving Behavior in a Driving Simulator

This paper presents a study focused on comparing driving behavior of expert and novice drivers in a mid-range driving simulator with the intention of evaluating the validity of driving simulators for driver training. For the investigation, measurements of performance, psychophysiological measurements, and self-reported user experience under different conditions of driving tracks and driving ses...