Institution: University College London
Dept/School/Faculty: Department of Civil, Environmental & Geomatic Engineering
PhD Supervisor: Dr E Buldakov
Application Deadline: 09 August 2013
Funding Availability: Funded PhD Project (European/UK Students Only)
Duration of Studentship: 4 years (MPhil, then PhD)
Stipend: £15,7426 per annum
Vacancy Information
The UCL Department of Civil, Environmental and Geomatic Engineering invites applications for a four year (one year MPhil and three year PhD) studentship to work on an Engineering and Physical Sciences Research Council (EPSRC), UK funded project.
The UCL Department of Civil, Environmental and Geomatic Engineering invites applications for a four year (one year MPhil and three year PhD) studentship to work on an Engineering and Physical Sciences Research Council (EPSRC), UK funded project.
Studentship Description
Traffic congestion is the problem affecting all modern cities. It has a negative impact on the quality of life as well as on environment and economy. There are few cities in the world where the problem is being successfully solved and London is a notable example. London has an efficient transport system which allows if not to completely remove the congestion problem, but substantially improve traffic situation. A tempting approach for solving transport problems is applying such best practices. However, each city has specific features affecting traffic conditions. These could include different climatic conditions, different quality of roads, different speed limits and other particulars of traffic codes, different traffic control strategies, different types of vehicles, etc. Would solutions proved efficient in London be as efficient under new conditions? This is the principal question to be answered by the project and a rational answer for this question not possible without implementing a model of an urban transport system which would allow investigating effects of implementing various traffic management solutions by adjusting model parameters.
Traffic congestion is the problem affecting all modern cities. It has a negative impact on the quality of life as well as on environment and economy. There are few cities in the world where the problem is being successfully solved and London is a notable example. London has an efficient transport system which allows if not to completely remove the congestion problem, but substantially improve traffic situation. A tempting approach for solving transport problems is applying such best practices. However, each city has specific features affecting traffic conditions. These could include different climatic conditions, different quality of roads, different speed limits and other particulars of traffic codes, different traffic control strategies, different types of vehicles, etc. Would solutions proved efficient in London be as efficient under new conditions? This is the principal question to be answered by the project and a rational answer for this question not possible without implementing a model of an urban transport system which would allow investigating effects of implementing various traffic management solutions by adjusting model parameters.
The project will therefore develop a large-scale traffic system model combining two considerably different approaches: an artificial neural network model and a fluid-like continuous traffic flow model. A multi-fluid model of traffic flows will be developed, which represents the overall traffic flow as a mixture of fluids with different properties representing different types of vehicles. Construction, calibration and verification of the model will require considerable amount of real data of various types including traffic flow data trough main roads, concentration of vehicles through a modelled area at different times, positions of concentrated vehicle sources, such as bus depots, etc.
As a case study the model will be applied to assess applicability of London traffic solutions to improving traffic situation in Nizhniy Novgorod, a large industrial city in Russia. The project will be carried out in collaboration with Automobile Institute and Research Laboratory of Intelligent Transport Systems at Nizhniy Novgorod State Technical University.
Person Specification
Suitable candidates should have a good honours degree (1st Class or 2.1 minimum) in Mathematics, Physics or Engineering. A relevant Masters degree will be considered as an advantage. Candidates should have excellent written and oral communication skills. It would also be advantageous if they had programming ability, experience in numerical and analytical modelling and basic understanding of traffic flows.
Suitable candidates should have a good honours degree (1st Class or 2.1 minimum) in Mathematics, Physics or Engineering. A relevant Masters degree will be considered as an advantage. Candidates should have excellent written and oral communication skills. It would also be advantageous if they had programming ability, experience in numerical and analytical modelling and basic understanding of traffic flows.
Eligibility
Applications are invited from UK and EU members, residing in the UK. Applicants must meet the EPSRC eligibility requirements which can be found here
Applications are invited from UK and EU members, residing in the UK. Applicants must meet the EPSRC eligibility requirements which can be found here
Start Date
23rd September 2013 or as soon as possible thereafter
23rd September 2013 or as soon as possible thereafter
Application Procedure
Applicants should send a covering letter and CV indicating how you meet the criteria and demonstrating your passion for the research to Dr Eugeny Buldakov ( e.buldakov@ucl.ac.uk )
The successful applicant will then have to apply online to UCL by submitting the PhD application form, available from http://www.cege.ucl.ac.uk/Research/Pages/default.aspx and clicking on the Apply now button. Please name Dr Eugeny Buldakov as the proposed supervisor.
Applicants should send a covering letter and CV indicating how you meet the criteria and demonstrating your passion for the research to Dr Eugeny Buldakov ( e.buldakov@ucl.ac.uk )
The successful applicant will then have to apply online to UCL by submitting the PhD application form, available from http://www.cege.ucl.ac.uk/Research/Pages/default.aspx and clicking on the Apply now button. Please name Dr Eugeny Buldakov as the proposed supervisor.
Contact name: Eugeny Buldakov
Contact details: e.buldakov@ucl.ac.uk
Closing Date: 9 August 2013
Interview date: 15 August 2013
Studentship Start Date: 23 September 2013
Contact details: e.buldakov@ucl.ac.uk
Closing Date: 9 August 2013
Interview date: 15 August 2013
Studentship Start Date: 23 September 2013
Πηγή: www.ses.gr
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου