2017/10/31 by Dániel Kondor, Hongmou Zhang, Rémi Tachet des Combes +3 · 77 citations
Computer Science · Engineering · Social Sciences · #Business #Car ownership #Computer science #Computer security #Engineering #Parking guidance and information #Public transport #Sharing economy #Smart Parking Systems Research #Traffic congestion #Traffic flow (computer networking) #Transport engineering #Transportation and Mobility Innovations #Urban Transport and Accessibility #Vehicle miles of travel #Work (physics) #cs.CY #cs.SI
paper · pdf · doi:10.1109/tits.2018.2869085
published in IEEE Transactions on Intelligent Transportation Systems 20(8), 2903-2912 (Institute of Electrical and Electronics Engineers) · IEEE Transactions on Intelligent Transportation Systems, 2018
openalex created_date 2017/11/10 · openalex publication_date 2018/10/19 · arxiv created 2018/10/21 · arxiv updated 2018/10/23 · openalex updated_date 2026/08/05
The increasing availability and adoption of shared vehicles as an alternative to personally owned cars presents ample opportunities for achieving more efficient transportation in cities. With private cars spending on the average over 95% of the time parked, one of the possible benefits of shared mobility is the reduced need for parking space. While widely discussed, a systematic quantification of these benefits as a function of mobility demand and sharing models is still mostly lacking in the literature. As a first step in this direction, this paper focuses on a type of private mobility which, although specific, is a major contributor to traffic congestion and parking needs, namely, home-work commuting. We develop a data-driven methodology for estimating commuter parking needs in different shared mobility models, including a model where self-driving vehicles are used to partially compensate flow imbalance typical of commuting, and further reduce parking infrastructure at the expense of the increased traveled kilometers. We consider the city of Singapore as a case study and produce very encouraging results showing that the gradual transition to shared mobility models will bring tangible reductions in parking infrastructure. In the future-looking, self-driving vehicle scenario, our analysis suggests that up to 50% reduction in parking needs can be achieved at the expense of the increasing total traveled kilometers of less than 2%.