Urban mobility pricing with heterogeneous users

Efficient allocation of transport supply and demand is a key element of any well-functioning modern city. Use of mobility pricing as a transport demand management tool can assist to achieve this goal by helping to provide for an economically and socially optimal use of the available infrastructure. However, pricing of public goods can affect equity and have unintended redistribution effects, making its application challenging and unpopular with the public. This is primarily due to the complexity of optimal pricing problem and the limitations of travel behaviour and transport demand allocation models. Modelling and predicting impact of pricing policies requires capturing user?s heterogeneity, understanding the distribution of diverse transport needs and assessing the available alternatives, in all of their dimensions and interdependencies. This thesis applies an activity- and agent based simulation framework (MATSim) to study the effects of optimal congestion and public transport pricing on social and consumer welfare in a multi-modal context and in the presence of user heterogeneity in travel time valuations and trip characteristics. Here, MATSim?s ability to model interaction between public and private transport, including congestion delays and boarding denials due to capacity constraints, proves to be essential. In presenting a new approach for the inclusion of value of time and schedule delay heterogeneity as well as values of in-vehicle crowding into the MATSim framework, this thesis focuses on two major aspects: the impact of the degree of heterogeneity on the benefits from congestion and dynamic public transport pricing policies and the impact of availability of alternative modes of transport on equity. Using multi-modal Corridor and extended Sioux Falls scenarios, the results of this study confirm the potential for dynamic mobility pricing schemes based on internalisation of external costs, to create significant gains in social and consumer welfare. The scale of these gains depends on the scale of road congestion, public transport crowding and demand distribution between the available modes; however, all of these factors are affected by the degree of user heterogeneity. Increasing heterogeneity in the presence of multiple modes with different travel costs can lead to self-organization effects, thereby diminishing the gains of congestion pricing policies. Furthermore, effects on consumer welfare for individuals with low values of time are highly dependent on the availability and service level of an alternative mode. These findings can have significant impact on urban transport policy design when applied to a city-specific transport system and a population with a higher degree of economic and social inequality