The following studies which I have been involved in together with students and colleagues will be presented at TRB this year:
The Potential of Demand Responsive Transport as a Complement to Public Transport: An Assessment Framework and an Empirical Evaluation. (Session 293, Monday10:15 AM-12:00 PM Convention Center, 147A) Alonso-Gonzalez M., Liu T., Cats O., van Oort N. and Hoogendoorn S.
Individual, Travel and Bus Stop Characteristics Influencing Traverlers’ Safety Perceptions. (Session 556, Tuesday10:15 AM-12:00 PM Convention Center, 143B) Abenoza R.F., Ceccato V., Susilo Y. and Cats O.
Constructing Spatiotemporal Load Profiles of Transit Vehicles with Multiple Data Sources. (Session 649, Tuesday1:30 PM- 3:15 PM Convention Center, Hall E) Lou D., Bonnetain L., Cats O. and van Lint H.
Strategic Planning and Prospects of Rail-bound Demand Responsive Transit. (Session 660, Tuesday1:30 PM- 3:15 PM Convention Center, Hall E) Cats O. and Haverkamp J.
Demand-anticipatory Flexible Public Transport Service. (Session 784, Tuesday 8:00 AM- 9:45 PM Convention Center, Hall E) van Engelen M., Cats O., Post H. and Aardal K.
In addition, will be presiding:
Poster session 650 on Transit Service Disruptions: Impacts and Mitigation Measures (Tuesday 1:30 PM- 3:15 PM, Convention Center, Hall E)
Poster session 651 on Economic and Optimization Models for Integrated Service Planning (Tuesday 1:30 PM- 3:15 PM, Convention Center, Hall E)
In conjunction with the TRB conference, Jaime Soza Parra and I meet with Washington Metropolitan Area Transit Authority on Jan 11 to present and discuss the preliminary results of our evaluation of their headway-control experiment.
One common limitation to all of these studies was the lack of information on the probabilities associated with disruptions. This prevented a complete risk analysis and assessing the (e.g. annual) costs and benefits associated with disruptions and mitigation measures.
Together with Menno Yap and Niels van Oort, the frequency and duration of various disruption types on each public transport mode (train, metro, tram and bus) were estimated based on a unique dataset. We also identify which is the primary predictor of each variable to allow researchers and professionals in other contexts to estimate disruption probabilities in the lack of local data.
We propose a method for embedding link exposure into the identification and evaluation of critical links and perform a risk analysis for the multi-modal public transport network of the Rotterdam The Hague Metropolitan Area. By comparing the results with the conventional measures, we demonstrate that disregarding exposure risks prioritizing heavily utilized links instead of those which are actually the weakest.