What should be the topic for your report? You can choose any project topic that is interesting to you that is related somehow to smarter mobility. We are very flexible, and we encourage you to be creative. Below is a list of possible topics that have been covered or suggested in previous years. You can revisit or extend any of these topics, but keep in mind that novelty is encouraged.
Risk survey of traffic injury in low-income countries
Risk analysis of transportation infrastructure in China
Risk analysis of transportation infrastructure in Brazil
Modeling traffic as a swarm of individual cars and drivers
Particle swarm optimisation
Environmental damage from road construction, maintenance and use
Geographically mapping environmental harm from road and air traffic
Better sensors for traffic flow
Accident rates of self-driving vehicles
Who pays? The insurance industry in the age of self-driving vehicles
Tweaking the algorithms within Google Maps
Economic costs of traffic jams
How to evaluate economic costs of traffic congestion
Customising TripAdvisor for personal psychological preferences
Feasibility of Pavegen and similar technologies in Liverpool
Comparison of Google Maps and Baidu (百度地图) in China
Has China solved the “last mile” problem with e-bikes?
Cross-cultural comparison of road safety risk tolerance
Optimising Uber routing for stochastic demand
Gender differences in transportation risk tolerance
Cross-cultural views on personal mobility: XJTLU versus UoL
Planning sensor placement for monitoring traffic flow
Comparing traffic loop detectors, sensors, still cameras and videography
Agent-based model of transportation at city scales
Regional modelling of transportation needs in low-income countries
Matatus
Comparisons of modelling software for planning local and regional roadways
What kind of report should you write? It is acceptable, and still common, to conduct a straightforward review of the literature that summarizes the current state of affairs. Such reviews, if they are scholarly and comprehensive, are very valuable. Typically these are expected to review the scientific and engineering literature typically held in archival journals. In theory, they could also review commercial literature, gray literature, and even on-line blogs, but it is often very difficult to arrive at reliable conclusions from such material. Although reviews are acceptable, we will likely look more favourably on a project that does more than simply review literature.
The first way to do more is to use your skills as an engineer to propose, analyse, or test possible engineering solutions to defined problems within smarter mobility. If you want to do this and you might require materials or lab equipment, let Scott know as soon as possible.
The second way to improve your report is to conduct quantitative or statistical analysis to develop numerical answers to defined problems within smarter mobility. Such a project might develop a computer simulations of some important project from which you can derive relevant quantitative conclusions.
A third way to make your project more than a simple review is to conduct a data analysis or a risk-analytic study that quantifies traffic or risk features from empirical data sets. This might include regressions that associate different variables, cluster analysis that recognises patterns in the individuals that make up a data set, descriptive or exploratory data analysis, or possibly hypothesis testing.
Input data can from lots of sources, including hard numbers from traffic institutions, governmental records, published archives, social media, or even narratives from YouTube comment sections. The data can be existing (such as data from Kaggle or government repositories). You can also collect some yourself, for instance, from the lab or from public surveys. If you intend to collect data on human subjects for this project, consult with Scott as soon as possible to be sure you don't run afoul of any data ethics rules or privacy restrictions. Data availability need never be a hindrance. If the data you need to conduct an interesting statistical or other quantitative analysis is not available, you are free to use hypothetical data generated by computer simulation as a placeholder. Talk with Scott if you think this might be a good approach for you.