Traffic prediction in a bike-sharing system

Minimizing Multimodular Functions and Allocating Capacity in Bike-Sharing Systems

“…In this work, we assume that the predicted demand is given, e.g., using the methods of O'Mahony and Shmoys [2015] or Singhvi et al [2015]. Further methods to predict demand have been suggested by Li et al [2015], , and among others. Our results can be combined with any approach that predict demand at each station independently of all others.…”

Spatiotemporal analysis of urban mobility dynamics: a case study of bicycle sharing system

“…If the homogenous users can be grouped into certain clusters, it would be possible to measure cluster predictability level and use their collective trends to make a cluster-based prediction than using non-homogenous of whole users. It is also expected that the same user types have similar responses to external factors such as hour of the day, day of the week, nearby points of interest, station spatial layout, and weather [17]. How users move both spatially and temporally over the BSS, therefore, has been a subject of several previous studies [30,71,72,74].…”

“…The majority of BSS analyses use data from big cities such as London [19,31,46,72,[75][76][77][78][79], Washington DC [12,17,27,47,56,76,[80][81][82][83][84][85], Paris [86][87][88][89][90][91][92][93][94], and New…”

“…York [17,81,89,[95][96][97]. Other studied data sets are from Chicago [73,80,98,99], Lyon [63,65,74,100], Boston [12,76,80,101], Barcelona [11,70,102], Hangzhou [15,16,103], Brisbane [61,83], Minneapolis [76,104], Vienna [105,106], Denver [76,84], Pisa [64,107], Dublin [14,108], Minnesota [84], Seville [102], Montreal [109] Helsinki [110], Vancouver [111], Nanjing [112], and Castellon [113].…”

“…Recently, most BSS research studies have conducted their analysis and prediction at an aggregate level [15][16][17] to observe the global and local trends, for example at city and cluster scale, since almost all BSS public datasets contain information about trips, but these are not linked to individual users. This study uses what we believe is the only public BSS dataset that provides information on (anonymized) individual users.…”