Recent examples of severe natural hazards across the globe (e.g., wildfires in California, US and Attica, Greece in 2018; hurricanes Irma, Harvey and Florence in 2017 and 2018; Indonesian earthquake and tsunami in 2018) have highlighted the role of effective emergency response systems towards mitigating societal and economic impact. Such systems are especially important in densely populated urban settings, in which an excessively large number of people needs to move within a short time interval. Recent advances in information and communication technology have paved the way for more rapid, yet efficient, emergency response strategies. In this context, the anticipated emergence of shared, connected, and autonomous mobility services may enhance the available infrastructure resources for addressing the complex trip generation patterns during, or immediately after, the occurrence of a severe natural hazard. How could the use of shared, connected and autonomous vehicles facilitate and expedite the transportation-related emergency response in cities? Which policy actions could be put in place at a planning stage, in order to transform the shared, connected, and autonomous vehicle fleet into an optimal emergency response fleet? Which population groups would be the primary beneficiaries of such a transformation?
It is expected that the student will answer these and/or other relevant questions by means of traffic simulations, surveys, spatial analyses and statistical modelling, but other approaches will also be considered. A successful project will pave the way for a digital platform (app or a geoinformatics platform) that can illustrate the assignment of shared, connected, and autonomous vehicles across various emergency response activities in real-time.
Qualified applicants are encouraged to contact the supervisors informally to discuss their application. The position will remain open until filled.
Academic qualifications A first degree (at least a 2.1) ideally in Transport/Civil Engineering, Geography, Operation Research, Computer Science, Geoinformatics, Cognitive Sciences (other degrees will be considered if the applicant can show the relevance to the project) with a good fundamental knowledge of transport planning and/or human behaviour and modelling and/or geoinformatics.
English language requirement IELTS score must be at least 6.5 (with no less than 6.0 in each of the four components). Other, equivalent, qualifications will be accepted. Full details of the University’s policy are available online. https://www.napier.ac.uk/research-and-innovation/research-degrees/application-process
Essential attributes: • Experience of fundamentals of transport planning and/or human behaviour and modelling and/or geoinformatics • Competent in Matlab and/or Python and/or C++ and/or SAS/SPSS/R • Knowledge of traffic assignment models and/or statistical and econometric modelling and/or spatial econometrics • Good written and oral communication skills • Strong motivation, with evidence of independent research skills, relevant to the project • Good time management
Desirable attributes: • Experience with research
No funding available at the moment: self funded students only.
Murray-Tuite, P. & Wolshon, B. (2013) Evacuation transportation modeling: An overview of research, development, and practice. Transportation Research Part C: Emerging Technologies, 27, pp.25-45
Waugh, W.L. (2015) Living with Hazards, Dealing with Disasters: An Introduction to Emergency Management. Routledge: London
Fagnant, D.J. and Kockelman, K.M. (2014) The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C: Emerging Technologies, 40, pp.1-13