2019
DOI: 10.3390/su11041097
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A Pick-Up Points Recommendation System for Ridesourcing Service

Abstract: In the ridesourcing industry, drivers are often unable to quickly and accurately locate the waiting position of riders, but patrol or wait on the road, which will seriously affect the management of the road traffic order. It may be a good idea to provide an online virtual site for the taxi to facilitate convergence of the rider and driver. The concept of recommended pick-up point is presented in this paper. At present, ridesourcing service platforms on the market have similar functions, but they do not take in… Show more

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Cited by 11 publications
(7 citation statements)
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“…Previous studies on taxi demand prediction are generally based on historical taxi trajectory data. Previous studies have shown the feasibility of obtaining predictions from historical taxi trajectory data [1,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Methods of traffic demand prediction can be classified into three types: linear system theory (such as the autoregressive moving average model [24], Kalman filtering model, and time series model), nonlinear system theory (such as the neural network model, gray prediction model, and random forest model (RFM)), and combination forecasting model (CFM).…”
Section: Introductionmentioning
confidence: 99%
“…Previous studies on taxi demand prediction are generally based on historical taxi trajectory data. Previous studies have shown the feasibility of obtaining predictions from historical taxi trajectory data [1,[5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Methods of traffic demand prediction can be classified into three types: linear system theory (such as the autoregressive moving average model [24], Kalman filtering model, and time series model), nonlinear system theory (such as the neural network model, gray prediction model, and random forest model (RFM)), and combination forecasting model (CFM).…”
Section: Introductionmentioning
confidence: 99%
“…There are three reasons why some TNC drivers opt to circulate rather than parking immediately after a ride: (1) TNC drivers often cannot quickly and accurately locate the waiting positions of riders. Therefore, cruising on the road helps them to find a new request in a shorter time [117]; (2) Drivers mainly search for riders based on their self-interest and experiences and, therefore, those uncoordinated searching strategies lead to longer idle driving [77]; and (3) In downtown, there are a restricted number of places for drivers to park. Therefore, vacant taxis can only cruise on roads while awaiting their next ride [24].…”
Section: Negative Environmental Impactsmentioning
confidence: 99%
“…In such an industry environment, positioning technology not only meets basic positioning and navigation requirements but also brings huge changes to more scenarios. According to the application of positioning technology, the projects under construction and completed projects of the domestic integrated pipeline gallery can be divided into passive personnel positioning based on online patrol [1], personnel positioning based on WiFi [2], personnel positioning based on UWB (ultrawide band) technology [3], personnel positioning based on RFID (radio frequency identification) technology [4], and personnel positioning based on Bluetooth technology [5]. Among them, WiFi-based fingerprint positioning has been the most widely used due to its low cost, multiuser accessibility, wide coverage, high transmission rate, and strong anti-interference ability.…”
Section: Introductionmentioning
confidence: 99%