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 into account whether the setting of the pick-up point is compatible with the actual traffic environment, resulting in some problems. We have invented a method to select the recommended pick-up point by integrating various traffic influencing factors, so as to ensure that the setting of the pick-up point is compatible with the actual traffic situation, which consists of three steps. Firstly, we studied the rider’s maximum tolerable waiting time and defined an attractive walking range for riders based on the huge amount of data. In the second step, we analyzed spatial distribution characteristics of the taxi demand hotspot and determined candidate pick-up locations. Lastly, the fuzzy analytic hierarchy method was used to select the recommended pick-up point that is most conducive to traffic management from multiple candidate points. A case study was conducted to validate the proposed approach and experimental evidence showed that recommended results based on the approach are in line with the actual situation of the road, and conducive to road traffic management. This recommendation method is based on real ridesourcing orders data.
Highlights
Along with the proliferation of smartphones and the rapid development of wireless communication technologies, ridesourcing apps have emerged in recent years to global popularity
Multi-criteria decision making (MCDM) is concerned with structuring and solving decision and planning problems involving multiple criteria. It can be implemented by various techniques such as weighted sum method (WSM), weighted product method (WPM), analytical hierarchy process (AHP), preference ranking organization method for enrichment evaluation (PROMETEE), elimination and choice expressing reality (ELECTRE), technique for order preference by similarity to ideal solutions (TOPSIS), compromise programming (CP), and muti-attribute utility theory (MAUT) [2]
When using a ridesourcing service, a common problem is that drivers and riders cannot meet quickly
Summary
Along with the proliferation of smartphones and the rapid development of wireless communication technologies, ridesourcing apps have emerged in recent years to global popularity. Multi-criteria decision making (MCDM) is concerned with structuring and solving decision and planning problems involving multiple criteria It can be implemented by various techniques such as weighted sum method (WSM), weighted product method (WPM), analytical hierarchy process (AHP), preference ranking organization method for enrichment evaluation (PROMETEE), elimination and choice expressing reality (ELECTRE), technique for order preference by similarity to ideal solutions (TOPSIS), compromise programming (CP), and muti-attribute utility theory (MAUT) [2]. To cover the shortages of existing research, this paper proposes a novel approach to selecting recommended pick-up points The setting of this virtual online taxi station will facilitate the meeting between rider and driver. 3. To apply the F-AHP method to comprehensively consider various types of traffic conditions to select the recommended pick-up point that best matches the actual traffic environment.
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