Towards Energy Efficient Autonomous Vehicles via Cloud-Aided Learning

Lead Research Organisation: Loughborough University
Department Name: Aeronautical and Automotive Engineering

Abstract

There are two ongoing revolutions in modern automotive industry. The first is the development of autonomous transportation systems which is leading to greatly improved safety, traffic economy, environment and passenger comfort. The second on is the development of advanced propulsion systems, envisaging reduced fuel consumption and exhaust emissions. The intersection of the autonomous transportation systems and advanced propulsion systems is the future trend, which has been revealed in the strategic partnerships between automakers and IT companies. However, there is a big challenge that the environment information collected by autonomous vehicles is poorly used in propulsion systems, especially when vehicles run in fast changing conditions. Only few examples of using environment data to optimise energy efficiency can be found, although the potential benefits in fuel reduction and mission flexibility are great.

This project aims to tackle this challenge by developing a cloud-aided learning framework to merge the two themes as integrity. To establish awareness of the environment, the onboard sensors of autonomous vehicles including cameras, light detecting and ranging (LiDAR), ultrasonic, and radar are used to perceive the environment over short distances. The GPS and intelligent transportation systems are used to perceive the environment at a further distance. The combined information enables the autonomous vehicle to establish a comprehensive model of the external environment. Using advanced machine learning algorithms (e.g., dynamic Bayesian network), the environment information can be used to update the propulsion system model in real time. Combining the real-time updated model with dynamic optimisation methods (e.g., adaptive model predictive control), the optimal actions of the propulsion system can be obtained in s systematic way. Employing high performance computing resources on cloud, the computational intensive modelling and optimisation tasks can be cost-effectively addressed.

Aligning with the EPSRC Innovation Fellowship priority area of "Robotics and Artificial Intelligence Systems" through its focus on efficient transport, a cloud-in-the-loop testing platform will be built. This framework focuses on sensing, modelling, control, optimisation and computing of energy efficient autonomous vehicles. In a long term vision, the framework can be generalised from a single vehicle to connected and autonomous for further economic benefits.

Planned Impact

This research will address several fundamental problems in developing future vehicle architecture, from both theoretical and application aspects. Finding a way to successfully utilise external information will break down a wall that currently exists between research in autonomous driving and engine control and, therefore, an energy efficient autonomous vehicle can be delivered. This research has considerable potential economic benefit. It embraces the driverless technology market worth up to £50 billion to the UK economy by 2035. Also, it anticipates the government's clean energy policy on low carbon vehicles up to 2040. Future developments in the UK automotive industry, including technical innovations and competitive advantages, will be greatly aided by this research that will provide a bridge between laboratory models and production vehicles. To make this happen, I will focus on the following dissemination and impact activities.

Advisory board meetings composed by both academia and industry will be organised to engage with partners from the start, ensuring a close and fruitful collaboration. The advisory board will lead to two-way conversations between academia and industry, allowing me to will act as an ambassador for research and innovation across interfaces.

A website hosted by LU will be established to increase visibility. Links to the publications, testing videos, tutorial example and a part of algorithm codes would be made available. Similar information would also be published on my homepage. LinkedIn and ResearchGate will also be used to disseminate the research outcomes.

The research outcomes will be presented in industrial workshops and exhibitions including the Future Powertrain Exhibitions and the Consumer Electronics Show. The attendance will attract the interest of many suppliers from decision-making industry and data industry. Also they are ideal opportunities to ensure the technology being generalised.

Working with the host organisation and industrial partners, I will apply for international patents throughout the project.

I will give free webinars through the platform provided by IEEE and Mathworks. The latest research findings would be presented to public through the "IEEE Tech Insider Webinars" and the "Matlab and Simulink Webinars for Academia". Public lectures will be given at Open Days and Student Visits at LU. I will also become a STEM ambassador to disseminate ideas by initiating an activity through the STEM ambassador hubs.

High quality papers will be published in top tier IEEE journals. The research outcomes be also submitted to the most prestigious conferences including IEEE Conference on Decision and Control and International Conference on Robotics and Automation and SAE Congress. The publications will be made open access and shared via the open LU Publications Information Login (LUPIN) system.

Prototype testing will be given in Smart Mobility Living Lab facility, London and the engagement with common end users and media will be emphasised.

I will give consultations to Department for Transportation (DfT) of UK for the policy making of vehicles manufacturing transportation infrastructure in the future. I will work closely with Prof Ricardo Martinez-Botas, a science advisory council member of DfT, to offer the technical support.

AI will organise a workshop to disseminate the results to representatives from industrial partners in LU. I will invite established partners with whom I have connections and potential partners to join the industrial workshop. By successful demos, this pioneering work can build the confidence of automakers and attract more industrial partners.

Publications

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First Year Of Impact 2021
 
Description Capital Equipment Funding of Department of Aeronautical and Automotive Engineering, Loughborough University
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Organisation Loughborough University 
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Description PhD studentship on low carbon autonomous vehicles
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Description Travel award for the 2018 Workshop on the Electrification of Road Transport
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Collaborator Contribution Information and testing data.
Impact A joint proposal was submitted to the EPSRC Trustworthy Autonomous Systems Hub. This is a multi-disciplinary research across control engineering and automotive engineering.
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Description Collaboration with the company UbiPOS 
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PI Contribution Guidance algorithm design.
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Description Collaborative research on connected vehicles with scholars from Sun Yat-sen University, China 
Organisation Sun Yat-Sen University
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Sector Academic/University 
PI Contribution Designing algorithms for the collaborative research.
Collaborator Contribution Providing test data.
Impact Four journal papers have been finished together and are being reviewed.
Start Year 2018
 
Description Collaborative research on eco-driving of autonomous vehicles with scholars from Tsinghua University, China 
Organisation Tsinghua University China
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Sector Academic/University 
PI Contribution The development of eco-driving algorithms.
Collaborator Contribution Experimental facilities.
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Description Collaborative research on interactive decision making and safe control for autonomous vehicles with Loughborough University 
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Description Collaborative research on the optimisation of low carbon autonomous vehicles with University of Birmingham 
Organisation University of Birmingham
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Sector Academic/University 
PI Contribution Algorithm design.
Collaborator Contribution Algorithm verification.
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Start Year 2019
 
Description Collaborative with Cranfield University 
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Sector Academic/University 
PI Contribution Algorithm design.
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Description Invited talk given at the Research Zoomposium at College of Science and Engineering, University of Glasgow 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Professional Practitioners
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Year(s) Of Engagement Activity 2021
 
Description Keynote talk given at the Workshop of Electrification and Road Transport 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact I gave keynotes at the workshop on fellowship application and energy efficient autonomous vehicles. Collaborations with researchers from Sun Yat-Sen University are secured for joint publications.
Year(s) Of Engagement Activity 2018
 
Description My current research is reported by the Low Carbon Vehicle magazine 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
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Description Participation of the Low Carbon Vehicle Event 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
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Year(s) Of Engagement Activity 2018
 
Description Reported as the "Research Story of the Month" at Loughborough University in June 2018 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Undergraduate students
Results and Impact The research being done in my My EPSRC Innovation Fellowship was reported by the University Press. I was interviewed by the Vice Chancellor of Loughborough University. The report motivated many researchers to seek collaborations with me.
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Description Research story published by the host institution 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
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Year(s) Of Engagement Activity 2020
 
Description Won the 1st place of the Best Poster Award at the Future Powertrain Conference 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact My poster won the highest prize in the poster competition. It helps me to secure collaborations with researchers from University of Birmingham. We have worked together on grant proposals and publications.
Year(s) Of Engagement Activity 2018
 
Description Won the 2nd place of the Best Poster Award at the Future Powertrain Conference 2019 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
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