On-trip Behavior of Truck Drivers on Freeways: New mathematical models and control methods

Congestion, a frequent problem on freeways, is often considered a major challenge for the operations of road freight transport. Trucks, the main choice for road freight, not only suffer from congestion but they also contribute to it. Consequently, billions of dollars are lost worldwide in trucking operations, which also impedes economic growth...

Route Choice Behaviour under Uncertainty in Public Transport Networks: Stated and Revealed Preference Analyses

Arguably, nearly all real-world decisions, including travel choices, are inherently associated with subjective uncertainty where decision-makers’ personal evaluations play a significant role. In public transport networks, uncertainty due to waiting time and, recently, the COVID-19 pandemic possibly induce the most frustration and anxiety....

Uncertainty Quantification and Predictability Analysis for Traffic Forecasting at Multiple Scales

Observing, modelling, predicting, and understanding the dynamics of traffic systems on different levels is one of the most critical topics in the transport and planning domain. At the macroscopic scale, traffic congestion is the central problem that impacts all aspects of society. Traffic congestion costs valuable travel time, extra fuel...

Data-Driven Modelling of Routing and Scheduling in Freight Transport

This dissertation includes initial steps towards introducing a data-driven integrated logistics and traffic modelling framework. The main objective is to unravel the complex interaction between freight transport and traffic systems and to incorporate this knowledge into measures for improving the performance of traffic and logistics operations....

Highway Traffic Congestion Patterns: Feature extraction and Pattern retrieval

Traffic congestion occurs daily, which can have negative effects on not only the quality of mobility, but also other important aspects of life like economic growth, health and environment. Both understanding and efficiently managing traffic are therefore crucially important tasks. Vast amounts of data are collected daily to gain insights into...

Multiscale Pattern Recognition of Transport Network Dynamics and its Applications: A bird’s eye view on transport

Cities are complex, dynamic and ever-evolving. We need to understand how these cities work in order to predict, control or optimize their operations. We have identified some open issues related to network and data complexity that need to be solved to build feasible methods for these purposes. To this end, we first build multiscale graphs...

Data-driven Analysis and Modeling of Passenger Flows and Service Networks for Public Transport Systems

Public transport (PT) plays an increasingly important role in solving mobility challenges, especially in densely populated metropolitan areas. Further improving PT systems requires more advanced planning and operations. Fortunately, the considerable amount of data that have become increasingly available for PT systems offer an opportunity to...

A Novel Design of the Transport Infrastructure for Traffic Simulation Models

Over the past decades, transport and traffic models have become powerful tools for transport and traffic practitioners and academics all over the world. Most of these commercial model packages provide proprietary and closed source software, which generally implies that users are not enabled to freely edit, modify and extend the code....

Development, Simulation and Evaluation of In-car Advice on Headway, Speed and Lane

With the use of Advanced Driver Assistance Systems (ADAS), traffic efficiency may be improved. This thesis presents an advisory system using advice on headway, speed and lane, in order to prevent potential problems 1-2km downstream. Current systems operate on smaller scale (e.g. Adaptive Cruise Control) or larger scale (e.g. route advice). With...

Dynamic OD demand estimation and prediction for dynamic traffic management

Dynamic origin-destination (OD) demand is important input to many simulation models applied within dynamic traffic management systems (DTMS) for predicting traffic states on the network. The inability to provide high-quality dynamic OD demand estimates makes prediction with simulation models simply impossible, irrespective of how well these...

Vehicle-class Specific Control of Freeway Traffic

The increase of mobility of the past decades has led to substantial congestion on the freeways. Traffic jams emerge both on a daily basis at the same location, as well as during accidents when a part of the freeways is temporarily blocked. In those cases, traffic management centers intervene into traffic in order to reduce or even dissolve...

Fusing Heterogeneous Traffic Data: Parsimonious Approaches using Data-Data Consistency

Reliable and accurate estimation of traffic states play an important role in traffic management and traffic theory development, which therefore has significant social and scientific relevance. Data for traffic estimation normally from different sources and have different types, characteristics, etc, so data fusion techniques are used. Traffic...