Optimum agent-based modelling with impact to engineering practice

Why people move the way they do when crossing a bridge? Why they evacuate (e.g., in a fire or earthquake scenario) buildings creating certain outflow patterns? Why they get in step or out of step when just walking side by side or the one behind the other? Why stampede (or crowd crush) tragedies still happen and finally how much behaviour between pedestrians approaches behaviour between car drivers?<br /> <br /> Agent based, or crowd dynamics, simulations try to capture the underlying mechanisms of all the above, yet not always accurately. There are a number of validation studies towards trying to make such simulations more realistic but these tend to refer to quite limited scenarios with little impact to our everyday lives. The current PhD project would aim to:<br /> <br /> i) Optimise current agent based simulation approaches using latest numerical (e.g., machine learning) techniques for establishing the interaction component the individual receives when moving inside a crowd. As a starting point, validation would take place in real-world crowd scenarios, such of this of people crossing a bridge.<br /> ii) Blend the optimised tool(s) reproducing more realistic crowd motion and interactions between individuals, with standard design software. How good are the structural design approaches currently practiced, and what differences emerge from this blending operation are the novel research question targets.<br /> iii) Expand the above agent based simulation approaches to topics like traffic routing (micro-simulation models in SUMO) and designing for more efficient transport infrastructure or more compatible with future trends like that of autonomous driving.<br /> <br /> The research would be a joint effort between the School of Civil Engineering (Dr Nikolaos Nikitas) and the School of Computing (Dr Evangelos Pournaras) and would have a hybrid numerical and physical testing aspect. Off-the-shelve software like Oasys MassMotion would be used in this research and there will be close interaction with practicing engineers using agent based simulations and design software.<br /> <br /> Candidate specifics:<br /> Beyond the standard requirements for PhD entry in an Engineering School the candidate should have excellent programming skills and statistics knowledge and experience. Previous work with agent based simulations is not necessary but would be a strong feature for interested candidates.<br />

<p><strong><a href="https://core.ac.uk/outputs/34999583">BasiGo project&nbsp;</a></strong></p>

<p>Formal applications for research degree study should be made online through the&nbsp;<a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University&#39;s website</a>. Please state clearly in the Planned Course of Study section that you are applying for <em><strong>PHD Civil Engineering</strong></em> and in the research information section&nbsp;that the research degree you wish to be considered for is <em><strong>Optimum agent-based modelling with impact to engineering practice</strong></em> as well as&nbsp;<a href="https://eps.leeds.ac.uk/civil-engineering/staff/600/dr-nikolaos-nikitas">Dr Nikolaos Nikitas</a> as your proposed supervisor.</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>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p> <p class="MsoNoSpacing">Applications will be considered on an ongoing basis. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents in support of your application by the closing date of 3 April 2023:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> <li>Funding information:&nbsp;EPSRC Doctoral Training Studentship</li> </ul>

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.

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.

<p class="MsoNoSpacing">A highly competitive EPSRC Doctoral Training Partnership Studentship consisting of the award of fees with a maintenance grant (currently &pound;17,668 for session 2022/23) for 3.5 years.&nbsp; An additional Top-Up of &pound;3,000 per year for 3.5 years is available to previous University of Leeds graduates.<br /> <br /> This opportunity is open to UK applicants only.&nbsp; All candidates will be placed into the EPSRC Doctoral Training Partnership Studentship Competition and selection is based on academic merit.</p> <p>Please refer to the&nbsp;<a href="https://www.ukcisa.org.uk/">UKCISA</a>&nbsp;website for&nbsp;information regarding Fee Status for Non-UK Nationals.</p>

<p>For further information about this project, please contact Dr Nikolaos Nikitas<br /> e:&nbsp;<a href="mailto:n.nikitas@leeds.ac.uk">n.nikitas@leeds.ac.uk</a></p> <p>For further information about your application, please contact Doctoral College Admissions<br /> e: <a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a></p>