The Vehicle Driver

Driver scheduling based on "driver-friendly" vehicle schedules

In the area of optimization of public transportation there are several methods for modeling and solving vehicle and driver scheduling problems. We designed a sequential heuristic method for solving the combined (vehicle and driver scheduling) problem. Our model is based on a modification of the vehicle schedules to satisfy driver requirements. We introduced a driver friendly approach of the opt...

MANFIS Based Modeling and Prediction of the Driver-Vehicle Unit Behavior in Overtaking Scenarios

Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the fut...

Heavy Vehicle Driver Workload Assessment, Executive Summary

Modeling Driver Response to Lead Vehicle Decelerating

This paper presents a driver performance map of braking and steering in response to three driving scenarios that lead to rear-end crashes. This map encompasses low risk, conflict, near-crash, and crash imminent driving states that correspond to advisory warning, crash imminent warning, and crash mitigation functionalities for intelligent vehicle rear-end crash countermeasures. Specifically, thi...

Ambient Storytelling for Vehicle-Driver Interaction

This research initiative explores methods for augmenting and deepening the relationship between a vehicle and its driver(s) over the course of its ownership lifecycle. Using a variety of in-car and cloud-based computing technologies, the USC Mobile and Environmental Media Lab is developing a suite of integrated real-time applications that monitor and analyze the activities of both driver and ve...