On Thursday, November 20, I had the privilage to present highlights from my research to MIT transit group led by Prof. Nigel Wilson and thereafter had the opportunity to disucss ongoing research activities with group members.
The seminar was entitled: “Unraveling and modeling the dynamics of public transport systems: Theory and applications”, where I briefly presented the transit operations and assignment model, BusMezzo, and its applications to service reliability and control, congestion and evaluation of increased capacity as well as service disruptions and the value of real-time information provision.
For a reduced version of the presentation, click here: MIT seminar 20112014 v1
The hEART2014 conference – the 3rd Symposium of the European Association for Research in Transportation was concluded today after 3 days of presentations and discussions in Leeds, UK. I have attended all three hEART conferences that have been organized so far and they have all proven a good opportunity to discuss ongoing works within an interesting research community.
I had two contributions on this conference. The first one is concerned with the evaluation of capacity increase in public transport projects. Many public transport investments are motivated by the need to relief congestion. However, conventional static assignment models that are used for cost-benefit analysis are not suitable for assessingi congestion related benefits as most of the negative conogestion impacts arise from system dynamics (e.g. reliability, crowding and denied boarding) and are therefore not reflected in average volume over capacity levels. Together with Jens West and Jonas Eliasson, we applied a new appraisal scheme for a metro line in Stockholm which takes into consideration the dynamic congestion effects and their variations. The presentation slides are available here: Appraisal of increased pt capacity hEART2014.
The second contribution is an attmept to infer the urban structure based on transport flow data. The availability of pervasive data collection facilitates the analysis of spatial and temporal distribution of activities based on people movements rather than based on land-use density proxies (as is conventionally done in urban planning and trip generation models). Together with Qian Wang and Yu Zhao, we formulated a spatial analysis technique to identify urban clusters and then classify them based on their temporal profiles with respect to incoming and outgoing flows. We applied this technique to Stockholm metropolitan area using public transport flow data. The analysis provide insights on the discrepency between the planning policy and the observed urban structure. This technique might be most valuable for anlayzing urban forms in mega-cities in emerging economies which undergo rapid changes. The presentation slides are avialable here: Urban clusters