Barriers and risks of Mobility-as-a-Service (MaaS) adoption in cities: A systematic review of the literature

Highly populated cities depend highly on intelligent transportation systems (ITSs) for reliable and efficient resource utilization and traffic management. Current transportation systems struggle to meet different stakeholder expectations while trying their best to optimize resources in providing various transport services. This paper proposes a Microservice-Oriented Big Data Architecture (MOBDA) incorporating data processing techniques, such as predictive modelling for achieving smart transportation and analytics microservices required towards smart cities of the future. We postulate key transportation metrics applied on various sources of transportation data to serve this objective. A novel hybrid architecture is proposed to combine stream processing and batch processing of big data for a smart computation of microservice-oriented transportation metrics that can serve the different needs of stakeholders. Development of such an architecture for smart transportation and analytics will improve the predictability of transport supply for transport providers and transport authority as well as enhance consumer satisfaction during peak periods.

MOBDA: Microservice-Oriented Big Data Architecture for Smart City Transport Systems

A comprehensive review on IoT-based infrastructure for smart grid applications

The continuing growth of urbanisation poses a real threat to the operation of transportation services in large metropolitan areas around the world. As a response, several initiatives that promote public transport and active travelling have emerged in the last few years. Mobility as a Service (MaaS) is one such initiative with the main goal being the provision of a holistic urban mobility solution through a single interface, the MaaS operator. The successful implementation of MaaS requires the support of a technology platform for travellers to fully benefit from the offered transport services. A central component of such a platform is a journey planner with the ability to provide trip options that efficiently integrate the different modes included in a MaaS scheme. This paper presents a heuristic that implements a scenario-based journey planner for users of MaaS. The proposed heuristic provides routes composed of different modes including private cars, public transport, bike-sharing, car-sharing and ride-hailing. The methodological approach for the generation of journeys is explained and its implementation using a microservices architecture is presented. The implemented system was trialled in two European cities and the analysis of user satisfaction results reveal good overall performance.

Heuristic-Based Journey Planner for Mobility as a Service (MaaS)

Recently, the commercial potentials and practical values of Mobility as a Service (MaaS) have been witnessed for sustainable development of smart cities in the field of intelligent transportation. Driven by the Internet of Vehicles (IoV), vehicles gradually become mobile living spaces to satisfy diverse demands of occupants, where the media functionalities, scenario scopes, and user engagements can be all expended dramatically. In the era of 5G/B5G, the intelligent connected vehicles are considered as super media because of the improved In-Vehicle Infotainment (IVI). In this paper, relying on the advanced communication and intelligent techniques, we investigate the IoV-based vehicle-mounted media scenarios and construct IVI solutions for the MaaS. Firstly, we propose the characteristics of vehicle-mounted media scenarios and present the IVI evolution from the aspects of hearing, vision and multi-sensory media services. Secondly, we point out the main features and limitations of IoV-based IVI in 3G/4G. Finally, exploring the potential of super media, both the linkage display and IVI collaborative modes in vehicle-centric media scenarios are introduced as IVI solutions for the MaaS in 5G-V2X and beyond, which intend to further improve the audio-visual experiences of occupants and observers in urban environments.

Internet of Vehicle Empowered Mobile Media Scenarios: In-Vehicle Infotainment Solutions for the Mobility as a Service (MaaS)

Mobility as a Service (MaaS) is a concept that aligns with both current and future mobility demands of users, namely intermodal, personalized, on-demand and seamless. Although the number of shared mobility, electric mobility and multimodal passenger transport users is rapidly growing, until now, the list of MaaS and electric Mobility as Service (eMaaS) providers is quite short. This could partly be explained by the lack of a common architecture that facilitates the complex integration of all actors involved in the (e)MaaS ecosystem. The goal of this publication is to give an overview of the state of the art regarding (e)MaaS’ ecosystems and architectures. Moreover, it aims to support the further development of eMaaS by proposing a definition and a novel system architecture for eMaaS. Firstly, the state of the art of the MaaS ecosystem is reviewed. Secondly, the eMaaS ecosystem that builds upon our definition of eMaaS is described and the MaaS system- and technical- architectures found in literature are reviewed. Finally, an eMaaS architecture that focuses on the integration of MaaS and electric mobility systems is presented. With the definition, ecosystem and system architecture presented in this work, the aim is to support the further development of the eMaaS concept.

https://www.mdpi.com/2032-6653/11/1/7/pdf

State of the Art of Mobility as a Service (MaaS) Ecosystems and Architectures: An Overview of, and a Definition, Ecosystem and System Architecture for Electric Mobility as a Service (eMaaS)

Mobility as a Service (MaaS) is a concept that aligns with both current and future mobility demands of users, namely intermodal, personalized, on-demand and seamless. Although the number of shared mobility, electric mobility and multimodal passenger transport users is rapidly growing, until now, the list of MaaS and electric Mobility as Service (eMaaS) providers is quite short. This could partly be explained by the lack of a common architecture that facilitates the complex integration of all actors involved in the (e)MaaS ecosystem. In this paper we first review the state of the art of (e)MaaS ecosystems and architectures. Secondly, we propose an eMaaS ecosystem and an innovative eMaaS architecture that focuses on the integration of MaaS and electric mobility systems. With this work, we aim to support the further development of eMaaS.

Gadi Lenz

Papers

State of the Art of Mobility as a Service (MaaS) Ecosystems and Architectures: An Overview of, and a Definition, Ecosystem and System Architecture for Electric Mobility as a Service (eMaaS)

State of the art of electric Mobility as a Service (eMaaS): an overview of ecosystems and system architectures