The complex demand pattern of ride-sourcing remains to be a challenge to transportation modeling practitioners due to the infancy and the inherently dynamic nature of the ride-sourcing system. Spatial effects exploration and analysis protocols can provide informative insights on the underlying structure of demand and trip characteristics. Those protocols can be thought of as an opportunistic strategy to alleviate the complexity and help specifying the appropriate econometric models for the system. Spatial effects exploration is comparable to point pattern analysis, in which, signals from spatial entities, like census tracts, can be analyzed statistically to reveal whether a specific phenomenon respective signal distribution is a completely random process or if it follows some regular pattern. The results of such analysis help to explore the investigated phenomenon and conceptualize its causal forces. In this paper, we apply spatial pattern analysis edge methods integrated into a visual analytics framework to: (1) test the null hypothesis of system demand complete randomness; (2) further analyze and explain this demand in terms of the origin-destination (OD) flow and trips characteristics, i.e., length and duration; and (3) develop a pattern profile of the demand and trip characteristics to provide potential directions to modeling and predictive analytics approaches. This framework helps explain the ride-sourcing system demand and trip characteristics in space and time to fill the gap in integrating the system in multimodal transportation frameworks. We use the ride-sourcing trip dataset released from the City of Chicago, USA, for the year 2019 to showcase the proposed methods and their novelty in capturing such effects as well as explaining the underlying complexities in a streamlined workflow. The ride-sourcing demand hotspots were explored and identified in the city’s central business district. A novel method to capture and analyze the origin-destination flowlines was developed and implemented. Finally, a complementary trip characteristics pattern analysis was conducted to fully comprehend the system and validate the findings from the system demand points and OD-flowlines.
Praca została poświęcona tematyce transportu miejskiego i jego uzupełnieniu usługami oferowanymi przez systemy działające w myśl koncepcji gospodarki współdzielenia (ang. sharing economy). Autorzy skupili się na przedstawieniu idei sharing economy. Zaprezentowali obszary związane z tą koncepcją oraz typy usług, jakie stwarza ona w przypadku miejskich systemów transportowych. Ponadto odnieśli się także do często skomplikowanej dla użytkowników anglojęzycznej nomenklatury, określającej konkretne usługi systemowe. Omówione zostały pojęcia takie, jak car-sharing, bike-sharing, skuter-sharing, peer-to-peer car-sharing, ride-sourcing, ride-sharing czy car-pooling. Celem pracy było przybliżenie koncepcji sharing economy w nawiązaniu do miejskich systemów transportowych.
EN
The work was dedicated to urban transport systems and its complementation by the sharing economy idea. Authors presented the sharing economy concept, its areas and types of services connected with urban transport systems. In addition, they also referred to the often complicated for users, characteristic for transportation part of sharig economy nomenclature. Issues such as car-sharing, bikesharing, scooter-sharing, peer-to-peer car-sharing, ride-sourcing, ride-sharing or car-pooling have been discussed. The aim of the work was to present the concept of sharing economy in relation to urban transport systems.
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