Designating City-Wide Collaborative Geofence Sites for Renting and Returning Dock-Less Shared Bikes

Abstract

The dock-less shared bike systems provide a convenient transportation mode for users to find, ride, or return a bike anywhere via GPS-based smartphone apps, with the bike position turmoil arises as side effects. To solve this problem, the geofence technology has been explored and then equipped in the ride-sharing service. However, the inadequate utilization and unreasonable distribution of the geographical resource impact the effectiveness of the geofence sites seriously. In this paper, we propose a collaborative geofence site selection (CGSS), which first pick up the hotspots based on a density-based and collaborationinspired method, and then allocate the geofence sites in the top-ranking hotspots. The CGSS aims to optimize the distribution location and the occupied area for each geofence in the city, so as to maximize the satisfactory degree of customers for both coverage ratio and capacity, with the total supplied geographical area for building geofence sites. The experimental results show that the CGSS method distributes geofence sites with a highly satisfactory degree and utilization rate.

Exploratory Analysis of Real-Time E-Scooter Trip Data in Washington, D.C.

“…It is likely that e-scooter share will enter a “semi-dockless” phase, where high-demand areas in the city will have dedicated e-scooter share parking spaces on the curbside. Geo-fencing, an idea to designate parking areas for dockless vehicles, has been the subject of a preliminary study ( 35 ). In February 2020, DDOT started to install off-sidewalk parking corrals across all its eight wards to regulate e-scooter parking behavior in the District ( 36 ).…”

Electric scooter safety: An integrative review of evidence from transport and medical research domains

“…One possible solution to address the issue of the dockless sharing system could be the allocation of more precise virtual areas (e.g. geofence) for parking in different transport facilities (Cheng, Guo, Chen, & Qin, 2019). These efforts could be considered a type of semi-dockless system that could help plan safe infrastructure for e-scooters and other road users (Zou, Younes, Erdogan, & Wu, 2020).…”

Optimization Model and Algorithm for Dockless Bike-Sharing Systems Considering Unusable Bikes in China

“…Thus, this study only focuses on the maintenance network within a specific region, such as a city center area. With the assistance of IoT and GPS technologies, the bike-sharing system collects real-time information of bikes widely distributed within a specific region [16]. The collected information specifies the statues of a bike, i.e., locked and being used, the locations of locked bike and whether a locked bike being unusable.…”

“…The new challenge in such a system is to determine geographical spots where workers collect and replenish shared bikes. Cheng et al [16] introduce a density-based and collaboration-inspired method to detect the rebalancing spots in a region. However, their method uses the current locations of the available shared bikes but not the locations (i.e., hotspots) where users will intensively rent and return bikes in the coming period soon.…”