Mobility as a Service (MaaS) is a recent innovative transport concept, anticipated to induce significant changes in the current transport practices. However, there is ambiguity surrounding the concept; it is uncertain what are the core characteristics of MaaS and in which way they can be addressed. Further, there is a lack of an assessment framework to classify their unique characteristics in a systematic manner, even though several MaaS schemes have been implemented around the world. In this study, we define this set of attributes through a literature review, which is then used to describe selected MaaS schemes and existing applications. We also examine the potential implications of the identified core characteristics of the service on the following three areas of transport practices: travel demand modelling, a supply-side analysis, and designing business model. Finally, we propose the necessary enhancements needed to deliver such an innovative service like MaaS, by establishing the state of art in those fields.@en

De impliciete belofte van Mobility as a Service is dat we hiermee vanzelf het autobezit zullen terugdringen. Maar is dat wel zo? Onderzoekers van de TU Delft deden onderzoek naar de mogelijkheden van een typische en voor de stad ideale MaaS-component: vraaggestuurd openbaar vervoer. Zal deze nieuwe modaliteit op korte termijn tot de gewenste modal shifts leiden?@en

The emergence of on-demand transport services is set to change the mobility landscape in urban areas. This study investigates the potential scalability of an on-demand mobility system to substitute motorised trips performed by private cars and public transport in Amsterdam, The Netherlands. We adopt an agent-based simulation framework and investigate scenarios where either private and pooled on-demand services replace private car trips, public transport trips, or both private car and public transport trips. Service performance in terms of level of service offered and operational efficiency are analysed. Results indicate that pooled on-demand services fare better than private on-demand in terms of veh-km travelled and the empty drive ratio. Private on-demand services generate 43%, 38%, and 44% more veh-km than pooled on-demand services when on-demand services replace car trips, public transport trips, or car and public transport trips, respectively. However, private on-demand services offer shorter total travel times than pooled on-demand for all scenarios.@en

The recent technological innovations in various ICT platforms have given rise to innovative mobility solutions. Such systems could potentially address some of the inherent shortcomings of a line/schedule based public transport system. Previous studies either assumed that flexible on-demand services are used as an exclusive door-to-door service or offered as a feeder connection to high-capacity public transport services. However, users may combine line/schedule based public transport systems (Fixed PT) and on-demand services (Flexible PT) so that their travel impedance is minimized. To this end, we propose a multimodal route choice and assignment model that allows users combining Fixed and Flexible PT or use them as individual modes while demand for these services is endogenously determined. The model takes into account the dynamic demand–supply interaction using an iterative learning framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to a network centered around the city of Amsterdam, The Netherlands. Scenarios where Fixed PT and Flexible PT are offered as mutually exclusive modes or can be combined into a single journey, are analysed. Results indicate that Flexible PT is predominantly used for covering <30% of the trip length, indicating that it is mainly used as an access or egress mode to Fixed PT. This results with an overall increase in the share of public transport trips. Also, the average waiting time of Flexible PT users when used in combination with Fixed PT are lower than the scenario where each of them is used as an exclusive mode.@en

The recent emergence of innovative mobility solutions is changing the mobility landscape in urban areas. However, it remains unknown how the combined operation of private and pooled on-demand services affect service performance and the required dimensioning of the fleet size for such services. This study develops a model to determine the fleet size of an on-demand system offering private service and pooled service, where the demand for these services is an outcome of modal choices. We investigate the fleet size required when taking either the perspective of Transit Planning Authority (Agency) or Service Provider (Operator). The model is implemented for the network of Amsterdam North. Results show that the objectives of Agency and Operator yield different total fleet sizes with the Agency requiring a larger fleet than the Operator and that the optimal scenario for the Agency would be the one where only private on-demand service is offered.@en

The emergence of innovative mobility solutions that offer flexible transport services, is changing the way urban public transport systems will be designed. Such mobility solutions offer on demand transport services and hence can solve the problems inherent with traditional line based and schedule based public transport systems. It is essential to understand the dynamics of this new demand-supply market with co-existing and competing fixed and flexible public transport. However, the performance of the system comprising of users and transit services and the factors influencing them, have received limited attention in literature. In this paper a model is developed to analyse the system performance when the modes of fixed public transport and flexible public transport operate in competition. The model is implemented in the multi-agent simulation framework MATSim with dynamic assignment in which the users optimise their travel plan through iterative learning from the service experienced and altering their travel plan. The scenarios in which the flexible public transport offer private and shared services are considered. The system performance is analysed for varying fleet size of flexible public transport and ratio of cost of flexible to fixed public transport. @en

The recent technological innovations have given rise to innovative mobility solutions. Public transport systems combining such services need novel models for the design of services. We develop a multimodal route choice and assignment model for combined use of line/schedule based public transport systems (fixed public transport) and demand responsive services (flexible public transport). The model takes into account the dynamic demand-supply interaction using an iterative learning model framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to the test network of Sioux Falls. Results, in terms of modal split, fleet utilization, and passenger waiting times are analysed for scenarios in which fixed and flexible public transport are offered as competing modes as well as potential complementing modes.@en

The emergence of innovative mobility services, is changing the way people travel in urban areas. Such systems offer on-demand service (door-To-door or stop-To-stop, individual or shared) to passengers. In addition to providing flexible services to passengers, past studies suggested that such services could effectively absorb the demand for private cars thereby reducing network congestion and demand for parking. This study investigates the potential of a ride-sourcing service to absorb the demand for public transport and private cars for the city of Amsterdam. Results indicate that a ride-sourcing vehicle could potentially serve the demand currently served by nine privately owned vehicles and that a fleet size equivalent to 1.3% and 2.6% of the total public transport trips, are required to provide doorto-door and stop-To-stop times comparable to those yielded by the current public transport system. Results from the modal shift indicate that most PT trips are substituted by active modes and most car trips are substituted by ride-sourcing service.@en

Binnen het concept van Mobility-as-a-Service nemen de ‘vervoersdiensten op aanvraag’, vervoer wanneer en hoe we het willen, een belangrijke plek in. Wat is het potentieel van deze diensten? En als ze eenmaal geïmplementeerd zijn, wat betekent dat dan voor de prestatie van het vervoerssysteem als geheel? PhD’er Jishnu Naraya van TU Delft deed hier onderzoek naar – en toonde en passant aan hoe nuttig agent-based modellen zijn.@en

The past decade has seen vast advancements in various ICT (Information Communication, and Technology) platforms. These advancements have enabled the rise of innovative mobility solutions e.g. on-demand transport services. Such solutions offer flexible transport services to users in which users can receive tailor-made mobility solutions. Increasing evidence from the literature points at the potentially disruptive effects of such innovative mobility solutions on urban mobility. The effects range from traditional modes such as privately owned cars and public transport losing their market share to on-demand services, to the subsequent need for public transport systems to evolve to stay relevant. Modelling tools for the design and assessment of such on-demand transport services therefore needs to account for its implications for urban mobility by considering its interaction with other travel modes. Existing studies that have looked into the design and analysis of on-demand services largely overlooked the impact of these services on other travel modes and vice-versa. The existing literature hence considered the design and analysis of on-demand systems without investigating this effect of on-demand services on other travel modes and their overall impact on urban mobility. This study attempts to fill this research gap by developing an approach to the design and analysis of on-demand services in an urban mobility context. Two types of on-demand services are considered in this thesis, namely private and pooled. Both private and pooled on-demand services are characterised by a fleet of vehicles controlled by a central dispatching unit. They provide door-to-door service to passengers’ travel requests in real time. While the private on-demand service provides taxi-like service to passengers, pooled on-demand service allows multiple passengers to share the service. @en