Fully funded PhD studentship

The increasing automation of vehicle systems is enabling many new opportunities to improve transport safety, mobility and transport efficiency. Autonomous systems enable new functionalities to become available whether on land or in the air. With vehicle or infrastructure based sensing systems and distributed computing autonomous systems are already making an impact on transport safety, efficiency and mobility. Many challenges concerning sensing, communication and control systems exist but it is often said the greatest barrier to adoption will relate to human factors and legal requirements.

Loughborough University has launched a new cross-disciplinary research initiative to bring together all of the key skills and approaches that are needed to support future research studies in the field of autonomous vehicle systems. Six opportunities for PhD study are available based in four different Schools within the University.  Although based in separate Schools the PhD students will work as a virtual team and there will be regular liaison meetings to promote synergies. 

Automobile automation includes information provision, navigation support, cruise control, emergency braking, automated stopping, automated steering, automated parking and coordinated highway driving (platoons). One of the major functionalities of autonomous vehicles is to fully avoid traffic collisions. However, imprecise data on positions and velocities of surrounding traffic can compromise safety of autonomous vehicles as well as other vehicles. Furthermore, possible sensor or actuator failures and ambiguous motion planning (due to imperfect measurements under the conditions of uncertainty) may also pose a potential threat to the safe operation of autonomous vehicles. Traditional accident prediction models are normally segment- or area-based that largely ignore vehicle-based factors and interactions with other vehicles and / or objects (both static and dynamic). The development of a new accident model will therefore be challenging as internal factors (e.g. sensor failures, imprecise measurements, other conditions of uncertainty in motion planning) need to be integrated with external factors such as current and projected positions and velocities of other participating road users, level of traffic flow, traffic mix and density as well as road geometry (slope / gradient and curvatures) in all built environments (e.g. metropolitan, urban, suburban, rural, dual carriageway, single carriageway, junctions, roundabouts) and weather conditions. In this PhD project, new accident risk models will be developed by integrating internal factors (e.g. sensor failures, imprecise measurements, other conditions of uncertainty in motion planning) with external factors (e.g. current and projected positions and velocities of other participating road users, level of traffic flow, traffic mix and density as well as road geometry) in all built environments (e.g. metropolitan, urban, suburban, rural, dual carriageway, single carriageway, junctions, roundabouts) and weather conditions. 

Students must have a first or upper second class academic qualification in a relevant subject or a relevant Masters qualification. 

The studentship provides a tax free stipend of £13,726 per annum for a period of three years plus tuition fees at the UK/EU rate. Due to funding restrictions, the studentships are open to UK and EU applicants only. Non UK applicants must the minimum English language requirements, details available here: http://www.lboro.ac.uk/international/englang/index.htm

Applications are now invited for this studentship which is described in detail below. Please contact the relevant Staff member identified for this research topic for further information. Details about the application process can be found here: http://www.lboro.ac.uk/study/apply/research/

Deadline for applications: 7 May 2013.  

Please quote ref AV /CBE on the application. 

Contact: Mohammed Quddus m.a.quddus@lboro.ac.uk , 01509 228545