PhD Studentship - Pro-active Traffic Management through Short-term, Long Range State Estimation

University of Sheffield - Civil & Structural Engineering/Automatic Controls and Systems Engineering

The University of Sheffield, in collaboration with A*STAR’s Institute of High Performance Computing (IHPC) in Singapore invite applications from outstanding candidates for this PhD scholarship opportunity.

This unique opportunity will involve spending two years in Sheffield and two years at the IHPC in Singapore researching in an exciting globally important field.

The Project:

This project leverages the traffic data from the Motorway Incident Detection and Automatic Signalling (MIDAS) and the combined expertise of IHPC, the ACSE and CIV departments at The University of Sheffield to:

  1. Produce a model able to predict the long-range evolution of traffic flows in a short time horizon;
  2. Define a control strategy to manage traffic flows and the algorithm to implement it.

In the UK, the motorway network is constantly monitored by the MIDAS system with sensors spaced less than 500m apart relaying information on the traffic state and reacting to queue formations. There is a clear scope to adopting a proactive, rather than reactive, behaviour based on the short-term prediction of traffic behaviour anticipating the formation of queues wherever possible by acting on the wider network, including the nearby junctions, rather than just on the same road segment.

Modelling driver behaviours is instrumental to predict congestion likelihood and, to achieve this, it is fundamental that the model faithfully reproduces the available data.

The University of Sheffield has access to the MIDAS data though industrial collaborators and has established track records in modelling and analysis of dynamical systems.

The IHPC have research track records on the transportation system in Singapore through microscopic models including the traveller’s behaviour, as well as network based analysis.

A graph-theoretical study of the motorway network as well as in depth traffic data analysis will shape the model. This will feature a representation of the motorway network with the reconstruction of the origin-destination (OD) matrix and its traffic dynamics. The model should look at large portions, if not the whole network to capture long-range effects and reveal globally optimal traffic management strategies.

Following validation, the model will provide a simulation platform to define intervention strategies. These will be informed by the identification of the network control nodes, the emerging local dynamics and performance indexes, including the Highways England traffic-flow targets.

Funding Details

Whilst in Sheffield, students receive fees and stipend (at the RCUK rate, £14,777 in 2018/19)

A monthly stipend of 2500 Singapore Dollars (~£1360) whilst in Singapore.

  • A one-off "settling-in allowance" of one thousand Singapore dollars (~£545).
  • A one-time airfare allowance of one thousand five hundred Singapore dollars (~£820).
  • Consumables and Bench Fees incurred by students when based at A*STAR in Singapore.
  • Cost of medical insurance while the student is based at A*STAR.

In addition, students will be able to claim up to £500 from Sheffield towards the costs of an airfare back to the UK whilst they are in Singapore in order to make a home visit. This will normally be available for students who meet the normal expectations of spending approximately half of the programme in Singapore.

Funding  Currency

GBP-British Pound while in UK. Singapore Dollars while in Singapore.

Locations

12 months in Sheffield, 24 months in Singapore, 12 months in Sheffield

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Type / Role:

PhD

Location(s):

Northern England