MultiModal Route Planning in Mobility as a Service

IEEE Access

In the last decades, the cities' capacity for generating digital information has grown exponentially. In this context, the successful implementation of smart cities' concept depends on the current possibility of handling the significant volumes of sensed data. This is particularly notorious in the case of urban mobility. Researchers in the field of urban planning have shown a great interest in urban mobility problems, proposing different route recommendation services towards making it easier and safer to move around the city. This paper addresses the development of an urban data platform and how to obtain and integrate information from sensors and other data sources to provide aggregated and intelligent views of raw data to support urban mobility. With the aim of evaluating the efficiency of the developed platform, we present an intelligent urban mobility solution, where the context-awareness, user preferences, and environmental factors play a significant role in the process of route planning. Finally, our work provides an experiment to assess different long-range wireless communication technologies to enable its implementation within an urban environment. INDEX TERMS Smart city platform, Internet of Things, urban mobility, multimodal transportation, smart mobility. ANAS AL-RAHAMNEH received the M.Sc. degree in software development with The International School for Postgraduate Studies, University of Granada, Granada, Spain, in 2013. He is currently pursuing the Ph.D. degree in communications technology, bioengineering, and renewable energies with the School of Electrical, Electronic and Communication Engineering,

The project i-Tour delivers a personal travel assistant, developed for smartphones, capable of routing users through a multimodal transport network. Additionally public transportation companies can interact with their customers through the access to ICT platforms. On top of multimodal routing features we have developed a system to deliver a full Web 2.0 communication tools that allows transportation providers and their partners to promote incentive schemes through the offer of ancillary services, when people are on the move and according to their location, in order to better serve them (providing a services that is useful to a given person, within a given place, at a given time) and to reduce CO 2 emissions. An incentives scheme would be also based on rewarding mechanisms and/or mileage-like campaigns, directly provided through the use of the such system as check-in check-out procedures for all the users. The solution developed is a cross-technology platform (available for both fixed and mobile devices), which works as a gateway for all the information related to public transportation. This information can be updated also by the end-users that work as prosumers. The actors of the system are: public transportation companies, public administrations, private partners that can offer services on the move, publishers, end-users. In this way all the stakeholders are interested to contribute and keep alive the community of users in order to get qualified leads. i-Tour becomes a communication system that can potentially serve million of users at the same time, and it is based over the most up-to-date internet technologies, such as web services and cloud computing networks.

arXiv (Cornell University), 2021

Over the last few years, MaaS has been extensively studied and evolved into offering a multitude of mobility services that continuously increase, from alternative car or bike sharing modes to autonomous vehicles, that aspire to become a part of this novel ecosystem. MaaS provides end-users with multimodal, integrated and digital mobility solutions, including a multitude of different choices able to cover users' specific needs in a personalized manner. This practically leads to a range of novel MaaS products, that may have complex structures and the challenge of matching them to user preferences and needs, so that suitable products can be provided to end-users. Moreover, in the everyday use of MaaS, travelers require support to identify routes to reach their destination that adhere to their personal preferences and are aligned to the MaaS product they have purchased. This paper tackles these two user-centric challenges by exploiting state-of-the-art techniques from the field of Personalization and Recommendation systems and integrating them in MaaS platforms and route planning applications.

Transportation Research Part A-policy and Practice, 2020

2007 IEEE Intelligent Transportation Systems Conference, 2007

Travellers require information on individual transport systems when planning a journey. Many transportrich urban environments contain numerous underlying transport infrastructures, offering a traveller various ways to complete the journey. This paper presents the Smart Traveller Information Service, a system designed to offer travellers an easy to use and efficient means of planning journeys in an otherwise complex multi-modal transport environment. The Smart Traveller Information Service bridges the coordination gap between the available transport systems (both public and private), and hides the complexity of the travel planning process from the user. This allows travellers to construct detailed journey plans without concerning themselves with the often heterogeneous and disjoint nature of the available transport facilities.

Transportation Research Part A: Policy and Practice, 2019

Mobility as a Service (MaaS) is often cited as providing an alternative solution to car ownership and car dominated lifestyles. However, MaaS as it currently exists appears to cater mainly for a specific segment of society-those who live close enough to walk to good quality public transport for daily journeys and close enough to access car share/car rental for other trips which public transport cannot serve. By default, this is limited to large, dense urban areas. This paper considers the evolution of intermodal journey planning that incorporates carpooling with public transport in the transition towards MaaS for suburban areas. It introduces a new journey planning App (known as RideMyRoute) that allows users to discover and make connected journeys involving carpooling and public transport, presenting key aspects of its design, development and testing. Results from a trial of the RideMyRoute App in four European test sites (Canton Ticino, Brussels, Zagreb and Ljubljana) revealed that the App was able to suggest trip planning solutions which included carpool options for one in five journey planning solutions and that the majority (85%) of these were solutions that involved connection from carpool to public transport. This is a significant advance on what is currently available through existing carpool provider systems or journey planning apps/services and could potentially increase the attractiveness of MaaS options in suburban markets. However, quality of data feeding the App from external sources remained an issue, as it is with all MaaS systems, and recommendations for future practice are presented. In conclusion, the new intermodal trip planning algorithm and data structure supporting it provide a fundamental stepping stone towards incorporating carpool services within MaaS-type offerings in the future.

Sustainability

Transportation and mobility in smart cities are undergoing a grave transformation as new ways of mobility are introduced to facilitate seamless traveling, addressing travelers’ needs in a personalized manner. A novel concept that has been recently introduced is Mobility-as-a-Service (MaaS), where mobility services are bundled in MaaS Plans and offered to end-users through a single digital platform. The present paper introduces a recommender system for MaaS Plans selection that supports travelers to select bundles of mobility services that fit their everyday transportation needs. The recommender filters out unsuitable plans and then ranks the remaining ones on the basis of their similarity to the users’ characteristics, habits and preferences. The recommendation approach is based on Constraint Satisfaction Problem (CSP) formalisms combined with cosine similarity techniques. The proposed method was evaluated in experimental settings and was further embedded in real-life pilot MaaS app...

Proceedings of the 15th International Conference on Web Information Systems and Technologies, 2019

In this paper, we present SmartMobility, an application for multimobility information services in a smart city, exploiting an ecosystem of IoT devices. Such application, designed for a real case study, is extremely heterogeneous in terms of IoT devices and implements a wide range of services for citizens. The application aims at contributing to reducing traffic generated by private vehicles in the city besides helping drivers going towards high traffic areas by presenting real-time mobility data from different sources. The experiments carried out in this study have evaluated some behaviors of the application in front of different configurations, allowing understanding how the experience varies under a wide number of devices and services, particularly in terms of mobility alternatives offered to the final user. The research findings showed that the bus transportation service is the most common one, while carsharing and bikesharing are not widespread and must be improved.

Mobile Networks and Applications, 2017

Mobility is a crucial sector for the livability of urban spaces, both in terms of accessibility for people with disabilities, and in terms of enjoyability by people with different interests. The deep transformation mobility is undergoing, heading towards commoditization of the full spectrum of transportation services, can lead to efficient solutions based on the same principle for all these needs. This paper shows how the approach based on the flexible orchestration of microservices allows to build applications that are, at the same time, more easily suited to the specific needs of different user categories, and more seamlessly integrated in the Mobility as a Service approach to smart mobility.

2003

Enabling mobility in urban and populous areas needs innovative tools and novel techniques for individual traffic planning. We present a prototype of a traffic information system enabling personalized route planning plus advanced services like traffic jam alerting. The best routes are efficiently computed using the SR-Combine algorithm, subject to various user preferences and current traffic situation gathered dynamically from several Internet sources. We implemented a J2EE application server which smoothly adapts to distributed online processing, once high bandwidth networks like UTMS are available.