99 citations · 117 across the 18 of their papers we have counts for
16 papers · 1 filter
Performance Assessment of Lidar Odometry Frameworks: A Case Study at the Australian Botanic Garden Mount Annan
Mohamed Mourad Ouazghire, Julie Stephany Berrio, Mao Shan +1
Autonomous vehicles are being tested in diverse environments worldwide. However, a notable gap exists in evaluating datasets representing natural, unstructured environments such as…
A Novel Probabilistic V2X Data Fusion Framework for Cooperative Perception
Mao Shan, Karan Narula, Stewart Worrall +4
The paper addresses the vehicle-to-X (V2X) data fusion for cooperative or collective perception (CP). This emerging and promising intelligent transportation systems (ITS) technolog…
Automatic lane change scenario extraction and generation of scenarios in OpenX format from real-world data
Dhanoop Karunakaran, Julie Stephany Berrio, Stewart Worrall +1
Autonomous Vehicles (AV)'s wide-scale deployment appears imminent despite many safety challenges yet to be resolved. The modern autonomous vehicles will undoubtedly include machine…
What is the appropriate speed for an autonomous vehicle? Designing a Pedestrian Aware Contextual Speed Controller
Daniel Jiang, Stewart Worrall, Mao Shan
Social acceptance is a major hurdle for autonomous vehicle technology, central to which is ensuring both passengers and nearby pedestrians feel safe. This idea of `feeling safe' an…
A Persistent and Context-aware Behavior Tree Framework for Multi Sensor Localization in Autonomous Driving
Siqi Yi, Stewart Worrall, Eduardo Nebot
Robust and persistent localisation is essential for ensuring the safe operation of autonomous vehicles. When operating in large and diverse urban driving environments, autonomous v…
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…