Publications (7)
Stochastic Sampling Simulation for Pedestrian Trajectory Prediction
Cyrus Anderson, Xiaoxiao Du, Ram Vasudevan +1
Urban environments pose a significant challenge for autonomous vehicles (AVs) as they must safely navigate while in close proximity to many pedestrians. It is crucial for the AV to…
On-Demand Trajectory Predictions for Interaction Aware Highway Driving
Cyrus Anderson, Ram Vasudevan, Matthew Johnson-Roberson
Highway driving places significant demands on human drivers and autonomous vehicles (AVs) alike due to high speeds and the complex interactions in dense traffic. Merging onto the h…
A Kinematic Model for Trajectory Prediction in General Highway Scenarios
Cyrus Anderson, Ram Vasudevan, Matthew Johnson-Roberson
Highway driving invariably combines high speeds with the need to interact closely with other drivers. Prediction methods enable autonomous vehicles (AVs) to anticipate drivers' fut…
Flint Water Crisis: Data-Driven Risk Assessment Via Residential Water Testing
Jacob Abernethy, Cyrus Anderson, Chengyu Dai +10
Recovery from the Flint Water Crisis has been hindered by uncertainty in both the water testing process and the causes of contamination. In this work, we develop an ensemble of pre…
Off The Beaten Sidewalk: Pedestrian Prediction In Shared Spaces For Autonomous Vehicles
Cyrus Anderson, Ram Vasudevan, Matthew Johnson-Roberson
Pedestrians and drivers interact closely in a wide range of environments. Autonomous vehicles (AVs) correspondingly face the need to predict pedestrians' future trajectories in the…
Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars
Manikandasriram Srinivasan Ramanagopal, Cyrus Anderson, Ram Vasudevan +1
One of the major open challenges in self-driving cars is the ability to detect cars and pedestrians to safely navigate in the world. Deep learning-based object detector approaches…