Automated driving desires better performance on tasks like motion planning and interacting
with pedestrians in mixed-traffic environments. Deep learning algorithms can achieve high …

The application of naturalistic driving data (NDD) has the potential to answer critical
research questions in the area of driving behavior assessment, as well as the impact of …

Aerial cinematography is revolutionizing industries that require live and dynamic camera
viewpoints such as entertainment, sports, and security. However, safely piloting a drone …

Road traffic accidents involving collisions between vehicles and pedestrians are a major
cause of death and injury globally. With recent technological progress in the field of …

Prediction of pedestrian behavior is critical for fully autonomous vehicles to drive in busy city
streets safely and efficiently. The future autonomous cars need to fit into mixed conditions …

Over 20% of global crash fatalities involve pedestrians, but pedestrian crash causation and
pedestrian protection systems have not been thoroughly developed or reliably tested. To …

Objective: In 2012 in the United States, pedestrian injuries accounted for 3.3% of all traffic
injuries but, disproportionately, pedestrian fatalities accounted for roughly 14% of traffic …

This report summarizes the variety of methods used to estimate and evaluate exposure to
risk in pedestrian and bicyclist safety analyses. In the literature, the most common definition …

Driving video is available from in-car camera for road detection and collision avoidance.
However, consecutive video frames in a large volume have redundant scene coverage …

To prevent vehicles running off road, road edge detection is a fundamental function. Current
work on road edge detection has not exhaustively tackled all weather and illumination …