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Spatial Modelling and Dynamics

PGR-RA-157

Expertise of research area
accessibility; autonomous driving; cities; cloud computing; connected vehicle; decarbonisation; driver behaviour variability; human behaviour modelling and simulation; Low-emission oriented driving; policy; portable emissions measuring systems (PEMS); Smart objects and interaction design; sustainability; transport & mobility


<h2 class="heading hide-accessible">Summary</h2>

We develop and validate mathematical and statistical models and simulation tools for the representation, analysis and optimisation of traffic and transportation systems with a particular focus on the use of big data in new modelling approaches.

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

<p>Research in&nbsp;<a href="https://environment.leeds.ac.uk/transport-spatial-modelling-dynamics">Spatial Modelling and Dynamics</a> is divided into five different areas:</p> <ul> <li><strong>Connected transport with the Internet of Things (IoT)</strong> &ndash;&nbsp;addresses how the Internet of Things solutions can be used in connected transport and automated driving to increase safety, provide more comfort and create many new business opportunities for mobility services. We will carry out the multi-criteria evaluations (Technical, user, business, legal) of the IoT impact on pushing the level of autonomous driving, using data from real-world pilots.</li> <li><strong>User acceptance of connected and autonomous vehicles &ndash;&nbsp;</strong>addresses all issues raised by the majority (if not all) of the general public that hinder the wide market uptake of Connected and Autonomous Vehicles (CAV). We not only focus on the interaction of the &ldquo;users&rdquo; in or near CAV, but also assess the impact of connected transport on people&rsquo;s well-being, quality of life, and equity. We aim to capture the public&rsquo;s acceptance, attitude and concerns, model/simulate scenarios for hand-on practices and validate the innovation in real-world trials.</li> <li><strong>Optimal fuel consumption with predictive vehicle control &ndash;&nbsp;</strong>aims to bring together the most advanced technologies from powertrain control and intelligent transport systems to achieve a global optimum for fuel consumption. It works towards the creation of a global optimiser which consists of a set of dynamic, intelligent control and prediction components designed for effective powertrain management, utilizing real-time environment data, road topography, traffic and weather conditions. It also studies key societal challenges such as social equity.</li> <li><strong>Low-emission driving, management and assistance &ndash;&nbsp;</strong>addresses a major policy concern about the impact of road traffic on local air quality and assesses innovations for improving underlying vehicle and fuel technologies, traffic management and enforcement. It aims to develop solutions to substantially reduce vehicle emissions from not only powertrain but also brake wear and tyre wear. It will provide evidence to guide the derivation of effective driving practices and training courses for different user groups.</li> <li><strong>Modelling of innovative urban mobility management and policy</strong> &ndash; addresses urban public administration and innovational services development with respect to innovative urban mobility management, development and implementation. It encompasses modelling approaches and experiments to be developed for and carried out in various cities Europe and beyond, notably projects involving the use of innovative instruments, e.g. automatic/electric Driving, shared mobility, and stakeholders coordination mechanisms.</li> </ul> <p>We currently&nbsp;have opportunities for prospective postgraduate researchers.&nbsp; Previous topics have included:</p> <ul> <li>Train timetable rescheduling</li> <li>Tools for participation in transport planning</li> <li>International transport policy in case of landlocked countries</li> <li>Airport-driven development, transport planning and sustainable mobility</li> <li>Towards comprehensive measures of performance and reliability for London&rsquo;s multi-modal public transport networks</li> </ul> <p>In addition to research study associated with a specific project, prospective students can also suggest their own topic. In this case, we ask prospective students to contact us for an informal discussion, before submitting a research proposal. Search <a href="https://phd.leeds.ac.uk/search?clive=leeds-pgr-web-supervisors&amp;query=&amp;f.school%7Cschools%5B%5D=Institute+for+Transport+Studies">PhD supervisors</a> in the Institute for Transport Studies.</p> <p><iframe frameborder="0" height="315" src="https://www.youtube.com/embed/jHQtI8AT-x8?loop=1&amp;playlist=https://www.youtube.com/watch?v=uqV3H9IKkDw&amp;list=PLPooB6Qr1ayESV1E-FWY6ZafMCeOtqCOg&amp;index=12" width="560"></iframe></p> <h3>Useful links and further reading:</h3> <ul> <li><a href="https://environment.leeds.ac.uk/transport-research-degrees">Research degrees within the Institute of Transport Studies</a></li> <li><a href="https://environment.leeds.ac.uk/transport-spatial-modelling-dynamics">Spatial Modelling and Dynamics</a></li> <li><a href="https://environment.leeds.ac.uk/transport-research">Institute of Transport Studies,&nbsp;Research&nbsp;and Innovation</a></li> </ul> <h3>Leeds Doctoral College</h3> <p>Our <a href="https://www.leeds.ac.uk/info/130558/leeds_doctoral_college">Doctoral College</a> supports you throughout your postgraduate research journey. It brings together all the support services and opportunities to enhance your research, your development, and your overall experience.</p>

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

<p>Formal applications for research degree study should be made online through the <a href="http://www.leeds.ac.uk/info/130206/applying/91/applying_for_research_degrees">University&#39;s website</a>.</p>

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

<p>For general enquiries and details regarding the application process, please contact the Graduate School Office:<br /> e:&nbsp;<a href="mailto:env-pgr@leeds.ac.uk">env-pgr@leeds.ac.uk</a>, t: +44 (0)113 343 5326.</p>


<h2 class="heading heading--sm">Linked funding opportunities</h2>