Identifying the rail operating features associated to intermodal freight rail operation delays

in Transportation Research. Part C, Emerging Technologies (2023), 147

Exploring the potential of Google Popular Times for transit demand estimation

Scientific Conference (2023)

MaaS modelling: a review of factors, customers’ profiles, choices and business models

Scientific Conference (2022, November)

Mobility-as-a-Service (MaaS) is regarded as one of the emerging solutions to offer integrated, seamless, and flexible multi-modal mobility services as an alternative to privately owned mobility resources ... [more ▼]

Mobility-as-a-Service (MaaS) is regarded as one of the emerging solutions to offer integrated, seamless, and flexible multi-modal mobility services as an alternative to privately owned mobility resources. MaaS gathers collective services such as public transport, shared solutions and other types of new mobility (e.g., on-demand ride services) and ancillary services (e.g., discounted parking) in bundles, accessed via monthly subscriptions. The key distinction between this system and traditional multi-modal systems managed by independent service providers is that payment for services is done through a single digital platform. MaaS is expected to change the way users will choose their modes of transport to reach their daily activities, and how service providers will generate profits, cooperate, and compete. From a wider perspective, MaaS is expected to favour a decline in car ownership and foster sustainable mobility, especially if the services increase the efficiency and utilisation of mass transit. To that aim, it is critical to obtain a thorough grasp of feasible and sustainable business models that suit the diverse needs of customers as well as the diverse and often competing objectives of service providers. In contrast, traditional transportation planning models typically assess solutions in a limited period of time (i.e., the peak hour) and use different simplifying assumptions (e.g., single trip-based choices, no interaction between service providers). This paper aims to provide a general modelling framework relating all main actors in the MaaS ecosystem and identify and discuss all factors that are considered relevant to define customers’ profiles and business models based on a comprehensive review of the literature. Gaps and challenges from the current studies are highlighted and future research directions are recommended. [less ▲]

Comparing MaaS Business Plans Using an Agent Based Modelling Approach

Scientific Conference (2022, June 02)

The Mobility-as-a-service is based on customized bundles in which different mobility services are gathered under one subscription-based digital platform. Currently, in the literature MaaS packages have ... [more ▼]

The Mobility-as-a-service is based on customized bundles in which different mobility services are gathered under one subscription-based digital platform. Currently, in the literature MaaS packages have been customized and hypothesized through surveys and pilot projects, underlining the lack of a model able to capture and compare MaaS business plans when different bundles are provided. This study aims to simulate different MaaS plans in the users’ mode choice set using an agent-based model and to study the MaaS potential demand heterogeneity. Results show that MaaS users who experience long daily travel times are indifferent to the type of package provided, while time-limited package members substitute the car by travelling longer distances using public transport and free-floating car-sharing services. In contrast, the trip-discounted bundle members are less willing to substitute the car and they use public transport within a long trip chain, reducing their trip time [less ▲]

Evaluating Mobility Service Providers’ Strategies in an Activity-Based Supernetwork

Scientific Conference (2022, June)

A Mathematical Problem with Equilibrium Constraints (MPEC) is formulated to capture the relationships between multiple Mobility Service Providers (MSPs) and the users of a multimodal transport network ... [more ▼]

A Mathematical Problem with Equilibrium Constraints (MPEC) is formulated to capture the relationships between multiple Mobility Service Providers (MSPs) and the users of a multimodal transport network. The network supply structure is represented as a supernetwork where users’ daily activity chains are represented sequentially and their modal choices to reach different destinations are based on the mobility services active in each connection. At the upper level, a profit maximization formulation is introduced to describe MSPs’ behaviour. At the lower level, groups of users choose the routes with the lowest cost, according to Wardrop’s first equilibrium principle. Due to non-separable interactions between supernetwork links, the equilibrium conditions defining users travel behaviour are written as Variational Inequality (VI). Finally, a numerical example is presented in order to show the characteristics of the model when car-sharing, bus and private car are available in the network. [less ▲]

IS PERIMETER CONTROL AN EMERGING STRUCTURE IN NETWORK-WIDE URBAN TRAFFIC MANAGEMENT?

Scientific Conference (2022, January)

Analysis of MaaS membership attributes: An agent-based approach

in Transportation Research Procedia (2022)

Systematic Analysis and Modelling of Profit Maximization on Carsharing

in Journal of Advanced Transportation (2022)

Principles for setting single or multiline bus holding control based on network characteristics

Scientific Conference (2022)

Estimating Public Transport Demand Information Using Crowdsourced Data

Scientific Conference (2022)