Connected vehicles have the potential to revolutionise the cities we live in and the way we travel. Connectivity will enable traffic management systems to safely optimise traffic flow in real time, easing congestion, improving air quality and minimising impacts on the environment. This will positively impact users by improving journey time reliability and allowing users to make ‘on the move’ choices about their travel using real-time journey information.
The use of this technology will enable transport authorities to fully utilise road capacity. However, the deployment of connected vehicles will generate significant amounts of data. Therefore, it will be important to optimise the wireless transfer of data between vehicles and roadside infrastructure to cope with this increase in volume. To support this, FLOURISH explored how data can be transferred and utilised to maximise the potential benefits associated with connected and autonomous vehicles (CAVs).
During the FLOURISH car trials, the University of Bristol investigated the conditions required for the effective transfer of data and pioneered the application of fog-based computing to CAVs. This state-of-the-art technology is more immediate than cloud-based solutions and thus will enhance the benefits that can be delivered by CAVs, such as more efficient traffic flows. Moreover, this technology could benefit other road users – such as pedestrians and cyclists – by enabling connected vehicles to ‘see’ round blind-corners.
The car trials also involved testing the provision of a range of services, such as roadworks and accident warnings, using a central Cooperative Intelligent Transport System (C-ITS) developed by Dynniq. In future, these services will enable authorities to better manage the road network and will result in more informed journeys for users.
Benefits of Connectivity
To complement the live trials, FLOURISH used simulated environments to examine how CAVs will behave on the network. A traffic model of Bristol was developed by Aimsun with the capability to simulate vehicle-to-everything communications, and this was used by Atkins to develop a Rules Engine that models several CAV scenarios, such as vehicle platooning and speed harmonisation. These scenarios were tested at different levels of CAV penetration to understand the impact of CAVs on the road network. The results suggested that maximum benefits could be achieved with higher levels of CAV penetration. It is critical that the impact of vehicle connectivity continues to be explored to inform the planning of future transport infrastructure.
In relation to this, FLOURISH explored how Artificial Intelligence could be deployed in traffic management systems to create a responsive network of CAVs. Neural network technologies were developed and applied by React AI to understand how road traffic patterns and behaviours can be analysed and predicted; enabling better network decisions to be made and thus reducing congestion and minimising delays.
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