Transport is an important application domain for RAS and it will reshape many aspects of how we transport people and goods in the coming decades, from personal transportation systems, intelligent highways to autonomous public transportation systems. It also holds the potential for enabling entirely new capabilities in environments where direct human control is not physically possible. In transport, 20% of CO2 emissions on the road are due to inappropriate accelerations and traffic congestion increases CO2 emissions by 300%. These cost drivers more than $100 billion annually in wasted fuel and lost time. Whilst smart cars equipped with powerful computers and sensors have given drivers a better idea of their environment and car performance, robotics technology is already appearing in the form of advanced driver assistance, automatic parking and collision avoidance, providing drivers with greater situational awareness and safety. As the pilot schemes of driverless cars mature, unmanned transportation systems and solutions are set to expand from constrained environments such as airports to public transport, urban centers and other general-purpose environments. With the demographic shift associated with the ageing population, robotics will also transform transport solutions for the elderly and those with limited mobility, allowing them and wheelchair users to independently access their own vehicles and public transport systems.
Key focus research areas within the Network:
- machine vision and perception,
- large-scale navigation,
- spatial linguistics and exploration and planning,
- scene understanding,
- control and verification, and
- high-fidelity scalable simulation environments.
Transport theme leads within the Network:
- University of Oxford, Oxford Mobile Robotics Group
- University of Warwick, RAS Simulator for Smart and Connected Vehicles