Completed Engineering Computing & AI

TASCC: Secure Cloud-based Distributed Control (SCDC) Systems for Connected Autonomous Cars

In plain English

AI plain-English summary

A single Google self-driving car costs roughly £100,000 just for its sensing equipment—this project aims to bring that price down by moving the computing power to the cloud. Road accidents claim 1.3 million lives and cause 7 million injuries each year, while traffic jams cost drivers and passengers 90 billion lost hours annually. Transportation also produces 26% of human-caused greenhouse gas emissions. Current autonomous cars are too expensive for commercial use, and connected cars that talk to each other and roadside infrastructure offer limited benefits unless integrated with smart autonomous features. This project brings together world-class universities and industrial partners, including Jaguar Land Rover, to combine connected-vehicle technology with autonomous systems using cloud computing. By sharing expensive computing resources across vehicles, the framework could slash per-car costs while giving each car access to information only available on the cloud. If successful, the research could enable affordable driver-less cars in the long term. In the short term, it will demonstrate specific autonomous features in a test environment. The project also addresses security threats that could cause public harm or reputational damage to manufacturers if such systems were commercialised without safeguards.

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Automotive industry and the consumers are eager for smart features on new cars and more efficient vehicles. Modern cars are not considered as mere means for travelling from point A to B anymore, but rather smart systems that offer personalised services and have the capability to adapt to the user's preferences and needs. They are expected to become intelligent agents that learn from their environments and exploit various sources of information to become increasingly autonomous systems that relieve the driver from tedious tasks, such as parking, and improve safety, efficiency, and desirability of the future cars. From a wider angle, today's land transportation systems claim about 1.3 million lives and 7 million injuries in road accidents, according to a recent report by CISCO. The increasing number of cars results in traffic jams costing about 90 billion of lost hours for the drivers and the passengers. In addition, transportation accounts for about 26% of the total greenhouse gas emission from human activities. While public transport can help, cars remain to be the desired means of transport according to a recent report by the Department of Transport in 2014. These market forces in addition to the environmental, economic and social impacts of transport systems demand a timely and transformative research to rethink the automotive control systems and revolutionise vehicle design for future cars. There have been two trends towards this objective in the past decade: in the one hand the research in autonomous systems, inspired by unmanned space vehicles, gave birth to driver-less concept cars such as Google robotic car; on the other hand, modern wireless communications enabled cars to talk to each other and the roadside infrastructures, resulting in the concept of connected cars. However, driver-less cars remain to be too expensive for commercial vehicles (Google's cars cost about £100,000 only for sensing equipment) and connected vehicles can offer little if not properly integrated into smart and autonomous features. This ambitious research is defined by a number of world-class academic institutions and leading industrial partners to work with Jaguar Land Rover, a market leader in high end cars, to design and validate a framework that combines the power of connected vehicles concept with the notion of autonomous systems and build a novel platform for cost-effective deployment of autonomous features and ultimately realisation of connected and fully autonomous cars. This can be made possible thanks to modern wireless technologies and the power of cloud computing that allows sharing expensive computing resources (hence, reducing costs per vehicle) and provides access to information that are only available on the cloud. To realise the ambition of the project, a number of key challenges in the areas of ultra-low-latency wireless technologies, cloud computing, distributed control systems, and human interaction issues will be addressed in this project. In addition, potential security threats will be identified and analysed to assess the potential risks for the public and reputational damage for car manufacturers should such technologies be commercialised. At the end of the project, the technical solutions will be integrated into a single framework and will be validated by example applications, characterising technical and service-level performance of the framework, and providing a basis for the future direction of enhanced automated services. While the objective here is to ultimately enable affordable driver-less cars, in the short term, this project aims to enable a number of demonstrable autonomous features in a test environment.

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Researchers

Alan Stevens (Co-Investigator)Aldo Sorniotti (Co-Investigator)Alexander Wolf (Co-Investigator)Carsten Maple (Co-Investigator)Jolyon Carroll (Co-Investigator)Lee Gillam (Co-Investigator)Mehrdad Dianati (Principal Investigator)Paul Krause (Co-Investigator)Rahim Tafazolli (Co-Investigator)Saber Fallah (Co-Investigator)Tim Watson (Co-Investigator)

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Original classification

Research Grant

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