5 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
Sub-Goal Social Force Model for Collective Pedestrian Motion Under Vehicle Influence
Dongfang Yang, Fatema T. Johora, Keith A. Redmill +2
In mixed traffic scenarios, a certain number of pedestrians might coexist in a small area while interacting with vehicles. In this situation, every pedestrian must simultaneously r…
Optical Flow based Visual Potential Field for Autonomous Driving
Linda Capito, Keith Redmill, Umit Ozguner
Monocular vision-based navigation for automated driving is a challenging task due to the lack of enough information to compute temporal relationships among objects on the road. Opt…
A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios
Dongfang Yang, Keith Redmill, Umit Ozguner
Vehicle-pedestrian interaction (VPI) is one of the most challenging tasks for automated driving systems. The design of driving strategies for such systems usually starts with verif…
An Online Evolving Framework for Modeling the Safe Autonomous Vehicle Control System via Online Recognition of Latent Risks
Teawon Han, Dimitar Filev, Umit Ozguner
An online evolving framework is proposed to support modeling the safe Automated Vehicle (AV) control system by making the controller able to recognize unexpected situations and rea…
Driving Intention Recognition and Lane Change Prediction on the Highway
Teawon Han, Junbo Jing, Umit Ozguner
This paper proposes a framework to recognize driving intentions and to predict driving behaviors of lane changing on the highway by using externally sensable traffic data from the…
Model predictive trajectory optimization and tracking for on-road autonomous vehicles
Peng Liu, Brian Paden, Umit Ozguner
Motion planning for autonomous vehicles requires spatio-temporal motion plans (i.e. state trajectories) to account for dynamic obstacles. This requires a trajectory tracking contro…