Smart space logistic service for real-time ridesharing

The paper describes a logistic service-based approach to real-time ridesharing based on smartspace concept. Smart-M3 information platform is used as smart space infrastructure for presented approach. The service is based on Smart-M3 RDF ontology which is formed by ontology slices of participants' mobile devices. The paper presents an algorithm for finding appropriate fellow- travelers for drivers as well as definition of acceptable pick-up and drop-off points for them

Commuter segmentation and openness to sharing services : a Swiss case study

The transportation sector is experiencing increasing pressure from emerging megatrends. Digitalisation, individualisation and the aging of society are leading to increasing traffic, mobility demand and capacity shortages. At the same time, new mobility concepts and offers are under development. In this highly dynamic environment, decision-makers and transport planners are under pressure to react. As society requests new and more comfortable mobility services, car-as well as ridesharing are seen as a part of the solution. Tailor-made mobility services have the potential to meet customer needs and increase the acceptance and use of public transport. In order to better understand the needs, we propose a classification of the commuter society into easily distinguishable groups based on an extensive commuter survey conducted in the city of Basel, Switzerland. This classification should enable more precisely targeted policy measures that save costs and increase adoption of sustainable ways of commuting. Key parameters influencing users’ openness towards car- and ridesharing are derived through an ordinal logistic regression analysis. Together with the classification based on a cluster analysis, they serve as starting points for a sustainable transformation of the commuter environment. The paper further places the findings in context by discussing how recent trends in mobility could support acceptance of new mobility concepts. Successfully transforming today’s commuting realm requires a coordinated effort from both policy-makers and society itself, integrating new and innovative mobility solutions in a public–private form of cooperation

Modeling Individual Activity and Mobility Behavior and Assessing Ridesharing Impacts Using Emerging Data Sources

Predicting individual mobility behavior is one of the major steps of transportation planning models. Accurate prediction of individual mobility behavior will be beneficial for transportation planning. Although previous studies have used different data sources to model individual mobility behaviors, they have several limitations such as the lack of complete mobility sequences and travel mode information, limiting our ability to accurately predict individual movements. In recent years, the emergence of GPS-based floating car data (FCD) and on-demand ride-hailing service platforms can provide innovative data sources to understand and model individual mobility behavior. Compared to the previously used data sources such as mobile phone and social media data, mobility data extracted of the new data sources contain more specific, detailed, and longitudinal information of individual travel mode and coordinates of the visited locations. This dissertation explores the potential of using GPS-based FCD and on-demand ride-hailing service data with different modeling techniques towards understanding and predicting individual mobility and activity behaviors and assessing the ridesharing impacts through three studies

Quantifying the benefits of vehicle pooling with shareability networks

Taxi services are a vital part of urban transportation, and a considerable contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort quantifiable in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad-hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that with increasing but still relatively low passenger discomfort, cumulative trip length can be cut by 40% or more. This benefit comes with reductions in service cost, emissions, and with split fares, hinting towards a wide passenger acceptance of such a shared service. Simulation of a realistic online system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets or when willingness to share is low.Comment: Main text: 6 pages, 3 figures, SI: 24 page

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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How does the ride-hailing systems demand affect individual transport regulation?

This paper analyses, on the light of the Brazilian legislation, the individual transport legal issues derived by the entrance of the ride-hailing companies into the market. The legal problem of ridesourcing services revolves around determining its nature as public or private. Regarding this, changes in the current legislation have being proposed to characterize the service as illegal or legal and to force the delimitations of its operation before the transport network of each municipality. In addition, this paper analyses socio demographic and travel characteristics of the Brazilian ridesourcing demand. Based on this demand point of view, a logistic regression model was generated to predict the probability of riderspliting system use. The results show that the majority of ridesourcing trips is replacing taxi and public transport trips. According to the logistic regression model, safety is the main reason that influences the decision of sharing trips via ridespliting. The other relevant factors are directly or indirectly related to service cost. The use of larger vehicles for sharing trips can become a competitive mode for public transport and generate a greater clash between public transport and ridesourcing companies than the one between the taxi industry and technology companies.Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

Intelligent tourist guiding service based on Smart-M3 platform

The paper proposes an intelligent tourist guiding service based on the Smart-M3 information platform and context management technology. It suggests attractions that are better to attend based on the tourist preferences and current situation in the region. The Smart-M3 platform implements a concept of the smart space providing the information sharing infrastructure in the intelligent tourist guiding service. The smart space is a decentralized infrastructure that allows different devices to share required information between them. The main benefit of the presented approach is to assist tourists in the region using their personal mobile devices. Such mobile devices need only Internet connection and capability to show appropriate information to tourists

Context-based access control for ridesharing service

The paper describes a context-based access control model for a ridesharing service. Ridesharing is a shared use of a car by the driver and one or more passengers for a joint trip. The service is based on the smart space concept. For this purpose the Smart-M3 platform is used. Currently the Smart-M3 platform doesn't have an appropriate access control mechanism meeting the following requirements: supporting a flexible, descriptive and well-defined policy language and taking into consideration the context information. Therefore, the usage of the context-based access control model has been proposed. This model is built as a combination of the role-based and attribute-based access control models. It uses roles, which are assigned dynamically based on the user's context, and meets the requirements to the access control in the smart space. An analysis of information transfer through the ridesharing service modules is used for defining the user's context. The model has been implemented within an access control broker, which controls the access to the smart space resources

Web mapping service for mobile tourist guide

Development of context-aware systems depends on the context definition and the context components. The entity location was always one of the main context components. For using location, a map service that provides possibilities of working with geographical information and showing results on the map is needed. The paper describes an implementation of a web mapping service for a mobile tourist guide, which is a context-aware service developed for supporting travelers before, during and after the trip. The mapping service provides possibilities of map showing, routing, geocoding, and has minimal license restrictions. The paper provides an analysis of existing web mapping systems such as Google, Microsoft, Yandex and describes implementation of free web mapping service for the mobile tourist guide based on OpenStreetMap, Leaflet, PostGIS, pgRouting, and Nominatim projects