Public transportation systems of different degrees and complexity are widely employed in cities around the world. Well-organised and efficient public transportation reduces traffic and the time spent commuting to work. In addition, more people choosing public transport rather than personal cars has a positive impact on reducing the number of vehicles on city roads: lessening their effect on climate change, improving air quality, and reducing noise pollution. Modelling and simulation of urban transportation systems is one way of analysing the influence that a variety of factors have on the overall functioning of the system. In this paper we present a Collective Adaptive Systems (CAS) model of an urban transportation system. We compare aspects of real data collected from a city bus system in the city of Edinburgh, UK, with the results of simulations of the CAS model constructed in the carma language. The simulations show results which are in good agreement with the real-world data, leading us to believe that the model could have useful predictive powers and thus provide an environment for experimentation with possible changes to the design of the system.
|Name||Lecture Notes in Computer Science|
|Name||Theoretical Computer Science and General Issues|
|Conference||8th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation|
|Abbreviated title||ISoLA 2018|
|Period||30/10/18 → 13/11/18|