104 citations · 382 across the 38 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…
Camera-Lidar Integration: Probabilistic sensor fusion for semantic mapping
Julie Stephany Berrio, Mao Shan, Stewart Worrall +1
An automated vehicle operating in an urban environment must be able to perceive and recognise object/obstacles in a three-dimensional world while navigating in a constantly changin…
Probabilistic Egocentric Motion Correction of Lidar Point Cloud and Projection to Camera Images for Moving Platforms
Mao Shan, Julie Stephany Berrio, Stewart Worrall +1
The fusion of sensor data from heterogeneous sensors is crucial for robust perception in various robotics applications that involve moving platforms, for instance, autonomous vehic…
Efficient statistical validation with edge cases to evaluate Highly Automated Vehicles
Dhanoop Karunakaran, Stewart Worrall, Eduardo Nebot
The widescale deployment of Autonomous Vehicles (AV) seems to be imminent despite many safety challenges that are yet to be resolved. It is well known that there are no universally…
Semantic sensor fusion: from camera to sparse lidar information
Julie Stephany Berrio, Mao Shan, Stewart Worrall +2
To navigate through urban roads, an automated vehicle must be able to perceive and recognize objects in a three-dimensional environment. A high-level contextual understanding of th…