In this paper, we study the deployment potential of automated minibuses (AmBs) on the first-mile part of public transport (PT) trips or short (sub)urban commutes by comparing “regular” (fixed route and fixed schedule) and “flexible” (door-to-door and on-demand) service types. For reaching that goal, we run a stated choice experiment in the Netherlands. The participants have assessed the referred two AmB alternatives compared to their current travel mode (car, PT, or active modes (AM) – bicycle and walking) used as the main mode for unimodal travellers or as access travel mode to transit lines for multimodal travellers. The results of a joint mixed logit model estimation based on data obtained from Dutch travellers show that there are similarities and differences in the preferences for the AmBs service type within and between the segments of travellers (car, PT, and AM) and that these are mostly in instrumental variables (cost and time) and attitudes. Current PT users prefer the flexible service to regular service based on their perception of in-vehicle travel time and waiting time, while current users of car and AM do not show a difference in preference between the two services concerning these variables. Moreover, their perception of in-vehicle travel time and waiting time is not significantly different from PT users’ perception of those variables in the regular service. This may mean that for non-PT users (car and AM), AmB’s flexibility of door-to-door transport is not seen as offering a significant advantage over what they think about public transport. When looking at the preferences of potential users explained by underlying psychological factors, we conclude that a positive attitude towards riding in AmBs is a significant factor in all three segments of travellers. Trust, usefulness, and enjoyment in using AmBs are important prerequisites for car and PT users to choose either service type. The experience with technology positively influences the preferences of current PT users for both AmB services.

The continuing urbanization and corresponding increase in transport demand are putting pressure on the accessibility, safety, sustainability, livability, and efficiency of urbanized regions. Public transport is regarded as a sustainable mode of transport for these regions and therefore transport policies aim to increase its attractiveness. However, public transport is facing last-mile connectivity problems. The application of Autonomous Mobility on-Demand (AMoD) as a feeder service for public transport hubs can potentially improve the first and last-mile trip leg which increases the attractivity of public transport. However, will such a system be financially viable when applied in an urban area? and what kind of operation will lead to the highest system performance? In this research, this question is addressed by proposing a method that connects macro transport modeling and agent-based modeling (ABM). An existing gravity-based travel demand estimation model built in a macro simulation tool is used to predict passenger demand across all the OD pairs of a city. For those OD pairs that can use the AMoD as first /last mile this is modeled using an agent-based rationale to be able to simulate the behavior of passengers and vehicles within that specific area of the city. The simulation model is applied to the case study area of the south of Rotterdam, in The Netherlands, where metro Station Zuidplein and the rail Station Lombardijen function as two AMoD hubs. Using the case study, the impact of relocation, ridesharing, and charging strategy is assessed in regards to financial viability. Among other insights, results show that the AMoD service leads to a profit on a typical business day for the operating companies despite the high-quality level of the service (very low average waiting time for a vehicle). If this particular system would not consist of automated vehicles and one would have to pay a salary to drivers, it would not be possible to make a profit on a typical business day. Moreover, results show that activating dynamic ridesharing and using wireless fast chargers at the stations results in the most financially viable operation. Activating automatic relocations results in the most costly operation.

This paper gives an overview of the projects and pilots with automated vehicles as public transport in the Netherlands as well as the remaining research questions and preliminary results of passenger related studies regarding expected ridership.

De ontwikkeling van zelfrijdende voertuigen neemt wereldwijd een hoge
vlucht. Hoe zal die automatiseringsslag ons openbaar vervoer beïnvloeden?
TU Delft en Goudappel Coffeng inventariseerden de visie en mening van de
verschillende ov-autoriteiten in Nederland.

Automatische voertuigen staan volop in de belangstelling en de techniek ontwikkelt zich snel. De mogelijkheden lijken rooskleurig; het verminderen van het aantal ongevallen, het bieden van vervoer voor iedereen en het verminderen van de uitstoot. In het beginstadium leek de focus met name te liggen op het ontwikkelen van automatische privé voertuigen, maar inmiddels staat ook automatisch OV volop in de belangstelling.
In Nederland zijn allerlei pilots ontwikkeld met automatische voertuigen/shuttles. Om een beeld te krijgen van de actuele ontwikkelingen, de plannen en de resterende onderzoeksvragen, is onderzoek uitgevoerd op basis van gesprekken met de OV-autoriteiten van Nederland. Tijdens deze gesprekken is gesproken over de kansen en bedreigingen van het Nederlandse OV en hoe zij denken dat automatische voertuigen daar op in kunnen spelen. Tevens is gesproken over de haalbaarheid, visies, risico’s en zijn kennishiaten achterhaald. Ten slotte zijn ook alle (potentiële) pilot locaties in kaart gebracht.

De OV-autoriteiten zijn het overwegend met elkaar eens dat het huidige openbaar vervoer op de hoofdassen zal blijven bestaan, met alleen voor rail automatische voertuigen. Buiten de hoofdassen verwachten de OV-autoriteiten wel mogelijkheden voor automatisch vervoer op de weg. Wanneer gesproken wordt over de voornaamste uitdagingen voor het huidige OV-systeem wordt veelal gesproken over het toegankelijk houden van het OV, het omgaan met de bevolkingskrimp en vergrijzing en het rendabel houden van het OV.
Op veel plaatsen in Nederland wordt of is al geëxperimenteerd met automatische voertuigen. Deze pilots, experimenten of demonstraties zijn veelal technisch ingestoken. Echter, de uitdagingen met betrekking tot het inzetten van een automatisch voertuig reiken verder dan alleen het technisch vlak. De geïnterviewde partijen geven aan dat het belangrijk is om de focus van de aanstaande pilots meer op de reiziger te richten en op het eindplaatje. Hierbij is het belangrijk om na te denken over de lange termijn implementatie.
De hedendaagse concessies zoals we die kennen zullen gaan veranderen door de komst van automatische voertuigen. Concessies worden flexibeler en er ontstaat ruimte om te experimenteren met nieuwe concepten zoals automatische voertuigen. Gedurende een concessie kan er steeds vaker naast de vastgestelde dienstuitvoering geëxperimenteerd worden en kan een transitie pad uitgestippeld worden. De OV-autoriteiten zijn helder over de toekomst: automatische voertuigen in het OV komen niet met een ‘big bang’ maar zullen geleidelijk hun intrede vinden.

The last mile in a public transport trip is known to bring a large disutility for passengers, because the conventional transport modes for this stage of the trip can, in many cases, be rather slow, inflexible and not provide a seamless experience to passengers. Fully automated vehicles (AVs), that is, those which do not need a driver, could act as a first mile/last mile connection to mass public transport modes. In this paper, we study a system that we call Automated Last-Mile Transport (ALMT), which consists of a fleet of small, fully automated, electric vehicles to improve the last mile performance of a trip done in a train. An agent-based simulation model was proposed for the ALMT whereby a dispatching algorithm distributes travel requests amongst the available vehicles using a FIFO sequence and selects a vehicle based on a set of specified control conditions (e.g. travel time to reach a requesting passenger). The model was applied to the case-study of the connection between the train station Delft Zuid and the Technological Innovation Campus (Delft, The Netherlands) in order to test the methodology and understand the performance of the system in function of several operational parameters and demand scenarios. The most important conclusion from the baseline scenario was that the ALMT system was only able to compete with the walking mode and that additional measures were needed to increase the performance of the ALMT system in order to be competitive with cycling. Relocating empty vehicles or allowing pre-booking of vehicles led to a significant reduction in average waiting time, whilst allowing passengers to drive at a higher speed led to a large reduction in average travel time, whilst simultaneously reducing system capacity as energy use is increased.