Drisk.Ai Ltd

Autonomous Vehicle (AV) pilot studies have demonstrated that AVs can handle "normal" driving; 99% of our day-to-day driving experience. However it is proving harder than expected to train AVs to deal with the multitudinous unusual events that can happen on the road, known as edge-cases. When an AV fails to understand an edge-case, driving behaviour become...

The Greater Cambridge region has achieved growth and success on an international scale, but high commuter demand has led to issues of congestion and poor air quality. The Cambridge Autonomous Vehicle strategy details opportunities to use AVs to tackle these problems. The Cambridge Connector will undertake an at-scale trial of on-demand self-driving vehicl...

To make self-driving vehicle operations commercially viable, and offset current technology and driver costs, they must operate as efficiently as possible. This project therefore proposes a multi-area, multi-application self-driving operation, underpinned by a 5G-based, central, Remote Monitoring Teleoperation (RMTO) system. We will operate a mixed fleet o...

By now, everyone knows about the need to "flatten the curve," i.e. slow COVID-19 enough to spread out healthcare utilisation over a longer timescale and prevent a catastrophic capacity overrun. We realise that our best hope to flatten the curve is to engage in social distancing, but how effective are our efforts, how long will we need them, and will we be...

"**Need.** Simulation will be a vital component in the Connected Autonomous Vehicle (CAV) safety-case, enabling the validation and certification of autonomous Vehicle Control Systems (VCS). This is essential in cities where the density and diversity of other agents, including road-users, pedestrians, infrastructure and signage, as well as intermodal-conne...