Towards efficient urban road transport using multimodal traffic management

Abstract

As travel demand and urbanization increase, they cause road congestion. This results in lost productivity, reduced accessibility, and negative effects on the environment. Solutions to reduce congestion in the transport network include urban traffic management. It could for example be regulating signal control, variable speed limit, and ramp metering, or distributing traveler information about traveltimes and congestion through radio broadcasts, variable message signs, or navigation apps. A multimodal traffic management system utilizes several transportation modes within an integrated system to improve network performance and robustness. Large-scale mobility data from both the public transport network and private vehicles enable a better understanding of multimodal travel patterns. Traffic data can also be used to estimate reliable traffic models that can support evaluation and prioritization of traffic management measures. The aim of the thesis is to identify synergies and challenges of multimodal traffic management. The aim includes analyzing, developing, and evaluating dynamic route choice models that can support multimodal traffic management decisions, using large-scale passive mobility data. First, recent trends are explored in the transition to more efficient road transport, emphasizing the role of monitoring and modeling traffic. Second, related literature is surveyed to identify the potential synergies and challenges of multimodal traffic management. Requirements of data and models in a decision support system that can help to prioritize between multimodal traffic management measures are also identified. Based on these requirements, route choice in the road network is analyzed using GPS trajectory data. This provides insights into how data-driven route choice models can be a component in multimodal traffic management. The thesis contributes to the understanding of how a decision support system for multimodal traffic management can be developed, how route choice modeling can be used in such a tool, and how multimodal traffic management is needed in the transition towards more efficient road transport.