A Systematic Methodology to Study Driving Adaptation Effects under Flooding Conditions

Flooding events not only cause physical damage to the road infrastructure and roadside systems, yet they potentially lead to significant traffic disruptions over the network which have a large impact on the sustainability of urban cities. According to several climate change scenarios, flooding events as a result of intense precipitation are...

An Improved Optimization Method to Increase the Truck Planning Efficiency of Landside Air Cargo

Congestion in the landside air cargo supply chain occurs for different concurring reasons. Lack of coordination between freight forwarders, as example, might create truck congestion on the ground handler side. Horizontal collaboration between forwarders can be introduced and modeled via mathematical programming to mitigate congestion. Resulting...

Car-Following Model using Machine Learning Techniques: Approach at Urban Signalized Intersections with Traffic Radar Detection

This master thesis aims to gain new empirical insights into longitudinal driving behavior by means of the enumeration of a new hybrid car-following (CF) model which combines parametric and non parametric formulation. On one hand, the model, which predicts the drivers acceleration given a set of variables, benefits from innovative machine...

How to calibrate a pedestrian simulation model: An investigation into how the choices of scenarios and metrics influence the calibration

This research investigates the question how the choice of scenarios and metrics influences the calibration of pedestrian simulation models. By calibrating a pedestrian model using different combinations of scenarios and metrics and comparing the results it was concluded that it matters what scenarios and metrics are included during the...