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Modelling Car-Sharing Choice Using Extreme Value Theory

PGR-P-726

Key facts

Type of research degree
PhD
Application deadline
Ongoing deadline
Country eligibility
International (open to all nationalities, including the UK)
Funding
Competition funded
Supervisors
Dr Leonid Bogachev and Dr Haibo Chen
Schools
Institute for Transport Studies, School of Mathematics
Research groups/institutes
Statistics
<h2 class="heading hide-accessible">Summary</h2>

The proposed PhD project will focus on the development and application of extreme value theory (EVT) to model users' choice behaviour which involves choosing multiple vehicle types simultaneously and allocating continuous amounts of budget to the chosen vehicles. EVT model estimates the impacts of a set of socio-demographic attributes (e.g. user age, income level, driving license country, insurance plan, membership plan, and origin location) on user&rsquo;s vehicle choice and capture the satiation effect with increasing the consumption for each vehicle type. The project will also address how the theoretical outputs can be used by operators when determining the most efficient allocation of resources within sharing services.

<h2 class="heading hide-accessible">Full description</h2>

<p>Increasing traffic congestion and the resultant greenhouse gas emissions and local air pollution are a major public policy concern, and have stimulated a substantial body of research aimed at developing sustainable forms of people mobility and freight distribution. Travellers&rsquo; behaviour is currently undergoing a shift from owning vehicles to using and sharing services. This provides an opportunity to acquaint users with electrified L-category vehicles (EL-Vs) which are smaller, lighter and more specialised than other vehicles, and could produce economic savings in terms of time gained, energy consumption and space required for moving and parking. These issues are being addressed in the ELVITEN project which is funded by the Horizon 2020 programme (<a href="https://www.elviten-project.eu/en/">https://www.elviten-project.eu/en</a>). ELVITEN will carry out one-year long demonstrations with hundreds of EL-Vs of all categories in six European cities (Genoa, Rome, Bari, Malaga, Berlin and Trikala) and collect a big data bank of trip data and users&#39; experiences and opinions after the trips. Such data can be used to accurately predict users&rsquo; preferences on different vehicle types and their vehicle usage.</p> <p>This project will be supervised jointly by the Institute for Transport Studies and the Department of Statistics at Leeds, and will also involve strong research collaboration with an industrial partner called S3Transportation (Smart, Safe &amp; Sustainable Transportation, <a href="https://www.s3transportation.com/">www.s3transportation.com</a>).&nbsp;S3Transportation is an international consulting group specialised in Transport Engineering &amp; Economics and Transport Innovation (with 6 offices in Europe &amp; South America, incl. London). It is a major partner in the aforementioned ELVITEN project responsible for the Rome demonstration, mobility data analysis, and demand modelling. S3Transportation will be involved in both co-supervision and providing placement to the successful student. Thus, the project will offer ample opportunities to develop and enhance skills through a close interaction with industry, together with in-depth learning, training and research in modern extreme value statistics with diverse applications.</p> <ul> <li>Asljung, D., Nilsson, J. and Fredriksson, J.Comparing collision threat measures for verification of autonomous vehicles using extreme value theory. <em>IFAC-PapersOnLine</em>,<strong>49</strong> (2016), no. 15, 57&ndash;62, <a aria-label="Persistent link using digital object identifier" class="doi" href="https://doi.org/10.1016/j.ifacol.2016.07.709" rel="noreferrer noopener" target="_blank" title="Persistent link using digital object identifier">doi:10.1016/j.ifacol.2016.07.709</a>.</li> <li>Asljung, D., Nilsson, J. and Fredriksson, J. Using extreme value theory for vehicle level safety validation and implications for autonomous vehicles. <em>IEEE Transactions on Intelligent Vehicles</em>, <strong>2</strong> (2017), 288&ndash;297, <a _ngcontent-c10="" append-to-href="?src=document" href="https://doi.org/10.1109/TIV.2017.2768219" target="_blank">doi:10.1109/TIV.2017.2768219</a>.</li> <li>Davison, A.C. and Smith, R.L. Models for exceedances over high thresholds.<em> Journal of the Royal Statistical Society, Ser. B </em><strong>52</strong> (1990), 393&ndash;442, <a href="http://www.jstor.org/stable/2345667">http://www.jstor.org/stable/2345667</a></li> <li>Gyarmati-Szabo, J., Bogachev, L.V. and Chen, H. Nonstationary POT modelling of air pollution concentrations: Statistical analysis of the traffic and meteorological impact<em>. Environmetrics </em><strong>28</strong> (2017), no. 5, Paper e2449, 15 pp, <a href="https://doi.org/10.1002/env.2449">doi:10.1002/env.2449</a>.</li> <li>Zheng, L. and Sayed, T. Application of extreme value theory for before-after road safety analysis. <em>Transportation Research Record</em>, <strong>2673</strong> (2019),1001&ndash;1010, <a href="https://doi.org/10.1177/0361198119841555">doi:10.1177/0361198119841555.</a></li> </ul>

<h2 class="heading">How to apply</h2>

<p>Formal applications for research degree study should be made online through the <a href="https://environment.leeds.ac.uk/transport-research-degrees/doc/apply-2">ITS website</a>. Please state clearly in the research information section&nbsp;that the research project you wish to be considered for is &lsquo;Modelling Car-Sharing Choice Using Extreme Value Theory&rsquo;, as well as <a href="https://environment.leeds.ac.uk/transport/staff/923/dr-haibo-chen">Dr Haibo Chen</a> as your main supervisor.and&nbsp;<a href="https://physicalsciences.leeds.ac.uk/staff/8/dr-leonid-bogachev">Dr Leonid Bogachev</a>&nbsp;as co-supervisor.</p> <p><em>Informal enqueries about the project</em>: Dr Haibo Chen (<a href="mailto:H.Chen@its.leeds.ac.uk">H.Chen@its.leeds.ac.uk</a>) and Dr Leonid Bogachev (<a href="mailto:L.V.Bogachev@leeds.ac.uk">L.V.Bogachev@leeds.ac.uk</a>)</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p><em>We welcome applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.</em></p>

<h2 class="heading heading--sm">Entry requirements</h2>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<h2 class="heading">Contact details</h2>

<p>For further information please contact the Graduate School Office<br /> email:&nbsp;<a href="mailto:env-pgr@leeds.ac.uk">env-pgr@leeds.ac.uk</a>, tel: +44 (0)113 343 5326.</p>


<h3 class="heading heading--sm">Linked funding opportunities</h3>
<h3 class="heading heading--sm">Linked research areas</h3>