Assessing the Impact of Intelligent Mobility (IM) on Traffic Performance

Application details:
Reference: ABCE19/MQHE1
Studentship start date: 1 July 2019
Advert closing date: 2 June 2019
Interview date: Early June 2019

Loughborough University
Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Find out more: www.lboro.ac.uk/study/postgraduate/supporting-you/research/

Highways England is the UK government-owned company responsible for planning, enhancing, operating and maintaining England’s Strategic Road Network (SRN), which comprises over 4,400 miles of motorways and major A-roads. While delivering roadbuilding and improvement schemes on the network, they are operating and maintaining the network in real time, providing information services through on-road technology, and the traffic officer service to manage incidents.

Find out more: https://highwaysengland.co.uk/

Full project detail
The aim of this PhD project is to develop, apply and verify various statistical and artificial intelligence techniques and algorithms to make predictions, take optimal decisions, perform classical and Bayesian inferences and actions that are rigorous and scientific in the face of uncertainties. The output will be valuable to design and implement suitable real-time traffic prediction focusing at enhancing overall traffic conditions, reducing delays and traffic collisions.

Intended objectives:
1) Explore a set of Intelligent Mobility services and examine their potential impact on Highways England’s Strategic Road Network (SRN);
2) Construct an integrated simulation platform (e.g. VISSIM and VSimRTI) in order to implement and test various mobility services and scenarios;
3) Develop traffic estimation models that are able to replicate traffic conditions in the presence of mobility services, also involving fleets of connected and autonomous vehicles (CAVs);
4) Design and implement real-time traffic estimation targeting network level decisions.

Further details are available on request.

Find out more:
The successful candidate will be based at the School of Architecture, Building and Civil Engineering: www.lboro.ac.uk/departments/abce/.

Entry requirements
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in a relevant discipline. Applicants having a background in subjects relating to engineering, computing, mathematics or statistics are particularly welcomed. A relevant master’s degree and/or employment experience will be an advantage.

Funding information:
The 3.5-year (42-month) studentship, jointly funded by Loughborough University and Highways England, will start in July 2019 and provide a tax-free stipend of £14,777 a year (stipend will rise in line with the level set by the Research Council) for the duration of the studentship plus tuition fees at the UK/EU rate. Highways England will also provide a tax-free stipend top-up of £4,000 a year and a generous training/development allowance. International students may apply but will need to fund the difference between UK/EU and international tuition fees.

Contact details
For information about the project, please contact:

Prof. Mohammed Quddus (Loughborough University)
[Email Address Removed]
+44 (0)1509 228545

Dr Vivi Michalaki (Highways England)
[Email Address Removed]
+44 (0)7702 151815

For information about the application process, please contact:

Mr Berkeley Young
[Email Address Removed]
+44 (0)1509 222611

How to apply
All applications should be made online at www.lboro.ac.uk/study/apply/research/ and must include a research proposal. Under programme name, please select Civil and Building Engineering.

Please quote reference number: ABCE19/MQHE1