Dynamic car sharing and matching method based on time and cost constraints

Abstract

The invention provides a more universal dynamic car sharing and matching method, which solves the problem of real-time matching of a passenger and an optimal driver meeting the conditions under two constraint conditions of car sharing time and car sharing cost of the passenger. The dynamic car sharing and matching method comprises the three steps of step 1, establishing a dynamic car sharing and matching model including time, cost and a skyline relation model; step 2, establishing a dynamic car sharing data structure including Driver Table, Matching Table, Grid index and the like; and step 3, carrying out dynamic car sharing and matching with core conception of guaranteeing high efficiency of matching through reducing or postponing calculation of a shortest path as possible; meanwhile, through setting a skyline constraint of the driver, the calculated amount of matching is further reduced, and in comparison with the other alternative driver, the matched driver is better in the aspect of time or cost.

Description

technical field [0001] The present invention belongs to the intersection field of location based service (LBS, Location Based Service) and geographic information system (Geographic Information System). Based on the dynamic carpooling matching technology based on time and cost constraints, it can provide passengers with candidate drivers who meet their carpooling requirements in real time. Background technique [0002] With the rapid increase in the number of urban vehicles, problems related to road traffic are becoming more and more serious, such as the increase in the demand for parking space, the decrease in air quality caused by the increase in oil consumption, and urban traffic congestion. These problems are recognized worldwide as affecting people's lives. The main reason for the quality. Although the policy has adopted a series of methods to solve the above problems, such as restricting the purchase of vehicles through number lottery, restricting some license plate nu...

AI Technical Summary

Problems solved by technology

[0004] Since the calculation of the shortest path on the road traffic network is involved in the specific matching process, in practice, it is necessary to match a large number of carpooling routes corresponding to drivers and passengers, so large-scale shortest path calculation makes it difficult to realize dynamic carpooling

The matching technologies used in the existing dynamic carpooling systems all have different restrictions on the matching model, which in turn have different defects: (1) only return the k nearest neighbor drivers at the passenger’s starting position, regardless of the driver’s original destination, In this case, the passenger may find a driver who is close to the driver to take the car, but the end point of the driver's route is far away from the passenger's end point, resulting in high carpooling costs; (2) The passenger's route must be a part of the driver's route, Such constraints are not flexible enough in practical applications and may miss some drivers who can provide passengers with reasonable carpooling prices through appropriate detours; (3) Similar to buses, drivers need to designate pick-up and drop-off points in advance, and passengers need to walk to Get on at the corresponding pick-up point and then walk back to the destination from the drop-off point. This carpooling method makes passengers limited to specific pick-up and drop-off points, which is not flexible in practical applications; (4) The starting point and The destination must be within a certain range and cannot deviate too far. However, in practice, some drivers may offer a lower and more reasonable carpooling fee even if the starting point is far from the passenger’s starting point.

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