The benefits of Autonomous MaaS
Autonomous MaaS has the potential to overcome many of the limitations of current transport systems that favour privately owned, manually operated cars and vans. It also offers a solution to the “last mile” problem enabling cost effective and timely access to transport hubs. Autonomous vehicles remove driver costs, whether taxi drivers or light freight such as parcels and deliveries. Vehicle utilisation can be significantly increased, reducing waste and draw on resources, while the bespoke door-to-door and private ride potential with autonomous pods means MaaS can overcome the limitations of existing forms of public transport.
How to Make Autonomous MaaS Happen
Despite much talk around the future of autonomy, progression is hindered by key considerations.
Most important is ensuring that driverless vehicles are not only safe for passengers, other road users and pedestrian, but also energy efficient and environment friendly. Connected autonomous driving technologies like this, can optimise traffic flow and reduce overall energy requirements, all of which could support in meeting the UK’s ambitious emission reduction goals.
Secondly, is deciding who is responsible for deciding whether an autonomous car is safe to be rolled out on public roads. And finally, if there is an accident involving an autonomous vehicle, who is responsible?
To solve these issues, rigorous testing of vehicles, their subsystems and connectivity is vital. However, to test every potential circumstance the vehicle may encounter when on public roads demands a significant amount of testing mileage across numerous environments, something that is not efficient or cost-effective.
One of the most significant solutions to this is scenario-based testing, where it is possible to evaluate a vehicle, or vehicle subsystems, using realistic scenarios that car may face without the need for high-levels of mileage and time. These scenarios can be delivered/executed either on the proving ground with real-life vehicles, in simulation, or using a mixture of both, otherwise known as mixed reality testing.