Designing demand responsive transport services in small-sized cities using an agent-based model

This paper presents an agent-based model (ABM) to simulate and compare two different operation strategies of a public transport service in small-sized cities, namely a fixed-route transit (FRT) and a demand-responsive transport (DRT) service, under varying demand rates and supply configurations. The ABM builds upon a previous work by the...

Repositioning in shared mobility systems: Combining model predictive control and approximate dynamic programming

The global market for personal mobility has transformed over the last decade. Traditional taxi services have to compete with the emergence of ride-hailing services such as Uber and Lyft. Rapid developments in available algorithms and real-time inter-connectivity of travellers and vehicles offer mobility-on-demand (MOD) services new possibilities...

Large-scale online ridesharing: the effect of assignment optimality on system performance

Mobility-on-demand (MoD) systems consist of a fleet of shared vehicles that can be hailed for one-way point-to-point trips. The total distance driven by the vehicles and the fleet size can be reduced by employing ridesharing, i.e., by assigning multiple passengers to one vehicle. However, finding the optimal passenger-vehicle assignment in an...

A business class for autonomous mobility-on-demand: Modeling service quality contracts in dynamic ridesharing systems

With the popularization of transportation network companies (TNCs) (e.g., Uber, Lyft) and the rise of autonomous vehicles (AVs), even major car manufacturers are increasingly considering themselves as autonomous mobility-on-demand (AMoD) providers rather than individual vehicle sellers. However, matching the convenience of owning a vehicle...

Potential of on-demand services for urban travel

On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing they may actually increase total vehicle miles travelled, worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the...

Machine and deep learning models for vehicle routing problems: a literature review

Vehicle routing problems (VRPs), a generalization of the traveling salesman problem, are extensively studied combinatorial optimization problems for their practical application. Many solution methods, e.g., exact and heuristic algorithms, have been proposed in the last few decades but require relatively much computation time due to the NP-hard...

Dynamic Fleet Management for Autonomous Vehicles: Learning- and optimization-based strategies

Autonomous vehicles (AVs) have been heralded as the key to unlock a shared mobility future where transportation is more efficient, convenient, and cheaper. However, the AV utopia can only come to fruition if the majority of users trust that autonomous mobility-on-demand (AMoD) systems are on a par with owning a vehicle in terms of service...

Shared Mobility-on-Demand Systems: Flattening the Service Level Distribution

In recent years, Shared Mobility-on-Demand systems have emerged as a great method for door-to-door transportation. Studies have shown that it is possible to route vehicles and assign requests to vehicles efficiently in large-scale systems. These studies commonly report one-dimensional performance metrics such as average vehicle occupancy,...

Opportunities for integration between Mobility as a Service (MaaS) and freight transport: A conceptual model

This paper explores the potential integration of freight transport into a Mobility as a Service (MaaS) environment. MaaS is a user-oriented service concept providing door-to-door mobility solutions for people. It integrates services of multiple providers, enabling searching, booking, and payment through a single digital platform. Although...

Exact matching of attractive shared rides (ExMAS) for system-wide strategic evaluations

The premise of ride-sharing is that service providers can offer a discount, so that travellers are compensated for prolonged travel times and induced discomfort, while still increasing their revenues. While recently proposed real-time solutions support online operations, algorithms to perform strategic system-wide evaluations are crucially...

If you are late, everyone is late: late passenger arrival and ride-pooling systems' performance

Sharing rides in on-demand systems allow passengers to reduce their fares and service providers to increase revenue, though at the cost of adding uncertainty to the system. Notably, the uncertainty of ride-pooling systems stems not only from travel times but also from unique features of sharing, such as the dependency on other passengers'...

Route Optimisation For Mobility-On-Demand Systems With Ride-Sharing

Privately owned cars are an unsustainable mode of transportation, especially in cities. New Mobility on Demand (MoD) services should offer a convenient and sustainable alternative to privately owned cars. Notable in this field is the recent uprise of ride-sharing services such as offered by companies like Uber and Grab. Such services, especially...