Space-time clustering-based method to optimize shareability in real-time ride-sharing

Real-time ride-sharing has become popular in recent years. However, the underlying optimization problem for this service is highly complex. One of the most critical challenges when solving the problem is solution quality and computation time, especially in large-scale problems where the number of received requests is huge. In this paper, we rely on an exact solving method to ensure the quality of the solution, while using AI-based techniques to limit the number of requests that we feed to the solver. More precisely, we propose a clustering method based on a new shareability function to put the most shareable trips inside separate clusters. Previous studies only consider Spatio-temporal dependencies to do clustering on the mobility service requests, which is not efficient in finding the shareable trips. Here, we define the shareability function to consider all the different sharing states for each pair of trips. Each cluster is then managed with a proposed heuristic framework in order to solve the matching problem inside each cluster. As the method favors sharing, we present the number of sharing constraints to allow the service to choose the number of shared trips. To validate our proposal, we employ the proposed method on the network of Lyon city in France, with half-million requests in the morning peak from 6 to 10 AM. The results demonstrate that the algorithm can provide high-quality solutions in a short time for large-scale problems. The proposed clustering method can also be used for different mobility service problems such as car-sharing, bike-sharing, etc.

Assessing the Potential of “Mobility as a Service” in Passenger Maritime Transport

This article assesses the potential of Mobility as a Service in passenger maritime transport from the supply perspective by collecting and analyzing data provided by interviews to key experts in passenger transport from both industry and academia. “Mobility as a service” in passenger maritime transport (also in this article referred as “Maritime MaaS”) describes the integration of passenger maritime services with land mobility into a single mobility service delivered through a unique platform for planning, booking, ticketing, and payment. The scope of this article is to explore the potential interest of mobility service providers to develop a MaaS that has as a backbone coastal shipping at the Aegean Archipelagos, in Greece. The Maritime MaaS ecosystem with its key actors is identified, while the perceived challenges, opportunities, and benefits envisaged by the adaptation of this innovative concept from urban transport to the maritime sector are recorded. Computer-assisted interviews were performed at a panel of 17 experts representing different types of decision makers. Participants were selected according to their current industry position or their academic profile. A content analysis with the use of NVIVO was conducted, followed by a SWOT (strengths, weaknesses, opportunities, and threats) analysis based on the experts’ input, in order to assess the MaaS business environment. Results indicate that the maritime transport sector is relatively ready to adopt MaaS from a technological readiness perspective, while land transport seems to be in a lower level of technological readiness. PAYG (pay as you go) MaaS business model is preferred than a “MaaS package” model by most stakeholders. Finally, main challenges toward MaaS implementation are the discrepancies in reliability of service among different transport modes and the ferry fleet operational flexibility ceilings that are imposed by legal framework for ferry routings in Greece.

When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration

Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future.

User Behavioral Intentions toward a Scooter-Sharing Service: An Empirical Study

This paper proposes an innovative shared scooter service whereby scooter owners can authorize the rental of their scooters to others through a mobile service platform. It constitutes a public short-distance mobility service for travelers and increases the efficient utilization of each private scooter. The study examines the adoption of scooter-sharing services by travelers and adapts the unified theory of acceptance and use of technology, attitude, and user experience (UX) to investigate the factors that may influence traveler acceptance of scooter-sharing services. The data were collected from Taiwanese travelers who used the shared scooters provided in this study and completed pre- and post-use subjective ratings of the scooter-sharing service (n = 99), analyzed using a hierarchical multiple regression analysis. The results indicate that the model constructs of habit, social influence, and environmental protections may positively affect users’ behavioral intentions toward shared scooters, while performance expectancy and effort expectancy may negatively affect intention to use. Attitudes and UX had no direct effect on intention to use. In light of the findings, recommendations for improving the design of scooter-sharing services, implications for service providers, and a reference basis for the development of future shared micro-mobility services are provided.

Variability in Human Mobility during the Third Wave of COVID-19 in Japan

Understanding factors regarding individual variability in human mobility during the COVID-19 pandemic would help inform future political and medical decisions. Particularly, understanding environmental factors would provide effective evidence for future urban development and the construction of a mobility service. Given the limited related evidence thus far, we investigated inter-individual variability in human mobility regarding life space during COVID-19 in Japan. We conducted an online survey to assess human mobility, demographics, and personality, and city structure surveys for objective environmental factors. Human mobility was assessed using the Life Space Assessment (LSA) questionnaire. Result revealed that the total LSA score was significantly higher in people who were men, middle-aged, working, living with their children, public transportation users, bicycle users, and car drivers, and those having a higher score for extraversion and ego resiliency and a lower score for conscientiousness. People living in the city with high traffic on the roads between plains and mountains had a higher LSA score, and had a lower score where there were many plains with a consistent road density, revealing diverse individual and environmental factors associated with human mobility during the pandemic. Thus, political decisions for urban development should consider these characteristics, the pandemic, and individual convenience.

Open Innovation in the Shared Mobility Market

The market for shared mobility services is growing very quickly. New types of vehicles have been introduced, and the offer of available services and functionalities has expanded, the purpose of which is to improve the quality of service. Despite all the improvements, it is still not possible to speak of achieving full availability of systems that meet the needs of users. This is due to the reluctant involvement of operators of shared mobility systems in joining Mobility as a Service platforms based on the idea of open innovation. The aim of the article is to analyze the factors influencing the limitations in the development of open innovations in the form of Mobility as a Service (MaaS) services. The authors focus on identifying the challenges and concerns faced by shared mobility service providers. The article supports the development of the concept of open innovation in shared mobility services. It also contains practical recommendations for the development of MaaS systems. The results of the developed research can be used by operators of shared mobility services, transport authorities, or IT service providers providing MaaS services to strengthen cooperation and integration using the language of mutual benefit.

Towards Sustainable Liveable City: Management Operations of Shared Autonomous Cargo-Bike Fleets

Finding a sustainable mobility solution for the future is one of the most competitive challenges in the logistics and mobility sector at present. Policymakers, researchers, and companies are working intensively to provide novel options that are environmentally friendly and sustainable. While autonomous car-sharing services have been introduced as a very promising solution, an innovative alternative is arising: the use of self-driving bikes. Shared autonomous cargo-bike fleets are likely to increase the livability and sustainability of the city, as the use of cargo-bikes in an on-demand mobility service can replace the use of cars for short-distance trips and enhance connectivity to public transportation. However, more research is needed to develop this new concept. In this paper, we investigate different rebalancing strategies for an on-demand, shared-use, self-driving cargo-bikes service (OSABS). We simulate a case study of the system in the inner city of Magdeburg using AnyLogic. The simulation model allows us to evaluate the impact of rebalancing on service level, idle mileage, and energy consumption. We conclude that the best proactive rebalancing strategy for our case study is to relocate bikes only between neighboring regions. We also acknowledge the importance of bike relocation to improve service efficiency and reduce fleet size.