Microscopic modelling of interactions of active mode traffic

Samenvatting

The goal of Prof. Samer Hamdar’s research to be conducted during his sabbatical leave is to explore the relationship between vehicular and non-vehicular (i.e. pedestrians and bicyclists) traffic mobility (i.e. congestion levels and travel time reliability) as an emerging property of individual operational behavior. Pedestrians move in 2 directions, whereas car traffic is mainly lane bound and can be modelled as moving in one direction (forward). There are situations in-between, like multi-lane car traffic or cyclists, which move mainly in one direction, but can deviate from their path. This project will aim at modelling this range of movements, including interactions between the different modalities (note that “mode” or “modality” means a way of transport, i.e. walking, cycling, car etc.), as well as coming up with methods (and data) to calibrate and validate the models.
At the individual microscopic level of movement, different traffic models exist. They include prospect theory and hazard-based models are translated to individual acceleration, gap acceptance, avoidance and merging models. These newly suggested traffic models are compared to existing microscopic models (social force, IDM, Cellular Automata and psycho-physical models). It will be checked to which extent they reproduce the characteristics at a network scale, in terms of mobility, i.e. what are the levels of traffic congestion, and traffic dynamics, for instance queue growing. Especially important is that the new models (from prof. Hamdar) will be linked with data collected in the Allegro project and available at the TU Delft. This requires working with the host TU Delft institution given their access to a wealth of microscopic and macroscopic traffic data including trajectory data. Note that “trajectory data” are high-detailed data on location and speed of individual travellers (one car, or one pedestrian). These are typically recorded with high-resolution video cameras, after which the images are analysed to find the path of individual travellers.
The different research findings would be ultimately used to find behavioral patterns od travellers, which in the end can be used to design (a) a more efficient surface transportation system and (b) creating a prototype simulation model for proper calibration and validation.

Kenmerken

Projectnummer

040.11.695

Hoofdaanvrager

Dr. V.L. Knoop

Verbonden aan

Technische Universiteit Delft, Faculteit Civiele Techniek en Geowetenschappen, Transport & Planning

Looptijd

01/04/2019 tot 31/07/2019