104 citations · 325 across the 28 of their papers we have counts for
10 papers · 1 filter
Socially Aware Crowd Navigation with Multimodal Pedestrian Trajectory Prediction for Autonomous Vehicles
Kunming Li, Mao Shan, Karan Narula +2
Seamlessly operating an autonomous vehicle in a crowded pedestrian environment is a very challenging task. This is because human movement and interactions are very hard to predict…
Attentional-GCNN: Adaptive Pedestrian Trajectory Prediction towards Generic Autonomous Vehicle Use Cases
Kunming Li, Stuart Eiffert, Mao Shan +3
Autonomous vehicle navigation in shared pedestrian environments requires the ability to predict future crowd motion both accurately and with minimal delay. Understanding the uncert…
Efficient falsification approach for autonomous vehicle validation using a parameter optimisation technique based on reinforcement learning
Dhanoop Karunakaran, Stewart Worrall, Eduardo Nebot
The widescale deployment of Autonomous Vehicles (AV) appears to be imminent despite many safety challenges that are yet to be resolved. It is well-known that there are no universal…
Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations
Mao Shan, Karan Narula, Yung Fei Wong +4
Cooperative perception, or collective perception (CP) is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to sha…
Long-term map maintenance pipeline for autonomous vehicles
Julie Stephany Berrio, Stewart Worrall, Mao Shan +1
For autonomous vehicles to operate persistently in a typical urban environment, it is essential to have high accuracy position information. This requires a mapping and localisation…
Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
Stuart Eiffert, Kunming Li, Mao Shan +3
Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds. This problem becomes increasingly complex…