PhD Studentship: Novel Approach for Characterisation of Residual Risk in Connected Autonomous Vehicle (CAV) Test Programmes

Coventry University (CU) is inviting applications from suitably qualified graduates for a fully funded PhD studentship. The successful candidate will join this cutting-edge research project ‘Novel approach for characterisation of residual risk in Connected Autonomous Vehicle (CAV) test programmes’. 

This research project is a collaboration between Coventry University and HORIBA MIRA. The successful candidate will have the opportunity to conduct their research project closely working with HORIBA MIRA. 

The adoption of autonomous vehicle technology promises to deliver a wide range of social, economic, and environmental benefits. The magnitude of these benefits is in turn dependent on how we assess vehicle behaviour. Scenario based testing aims to assess the behaviour of automated vehicles using realistic and often complex test scenarios that the vehicle might encounter on public roads. Each scenario is defined by a vast number of parameters making the exploration of the scenario parameter space challenging. Assessing vehicle behaviour, where the full extent of the scenario space cannot be fully exploited, is therefore challenging and leads to risk that parts of the parameter space critical to evaluation of a vehicle’s performance remain unexplored. An alternative to an extension of the test effort and complete coverage of the parameter space, this PhD project seeks to establish the residual risk associated i.e., the likelihood that parts of the parameter space critical to vehicle performance remain unexplored. If residual risk can be measured and an acceptable value identified, this will accelerate development and realisation of the benefits of autonomous vehicle technology, without the cost and time penalties of an extended test programme.

Entry criteria for applicants to PhD  

• A bachelor’s (honours) degree in a Mathematics/Statistics, Engineering, Automotive, Computer Science or a related discipline with a minimum classification of 2:1 and a minimum mark of 60% in the project element (or equivalent), or an equivalent award from an overseas institution. 

Plus 

• the potential to engage in innovative research and to complete the PhD within 3.5 years 
• An adequate proficiency in English must be demonstrated by applicants whose first language is not English.  The general requirement is a minimum overall IELTS Academic score of 7.0 with a minimum of 6.5 in each of the four sections, or the TOEFL iBT test with a minimum overall score of 95 with a minimum of 21 in each of the four sections 

Additional requirements 

• Competent programming skills (in Matlab, Python, C++) and experienced in mathematics/statistics and numerical analysis;  
• Interest in mathematical modelling or statistical inference, and enthusiastic to work on an inter-disciplinary research project.

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