Safety net car-sharing method and system based on big data mining

A safety net and big data technology, applied in safety net car-hailing methods and systems, can solve the problems that drivers cannot know the densely populated areas of peer competitors, drivers do not have the right to choose independently, and the purpose is not simple, so as to optimize the car-hailing experience, Optimize travel mode and safety, save communication cost effect

Inactive Publication Date: 2019-01-22
赵菁
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The birth of online car-hailing has changed the pattern of the traditional taxi-hailing market. In the existing online car-hailing system, drivers and passengers can only dispatch orders passively and one-way from the background. Drivers evaluate star ratings, but this simple, one-way evaluation method is difficult to feed back customers' real opinions and needs.

Method used

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  • Safety net car-sharing method and system based on big data mining
  • Safety net car-sharing method and system based on big data mining
  • Safety net car-sharing method and system based on big data mining

Examples

Experimental program
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Embodiment 1

[0033] The present invention provides a safe online car-hailing method based on big data mining, wherein, the online car-hailing driver independently chooses to go to the target area according to the analysis results of the passengers or the driver in the target area, and the passenger independently selects the area where the conditions are met when using the car The vehicle makes an appointment for the order. After the passenger reserves the order, the order is sent to the background. The background plans and designs the recommended route for the location of the departure and destination in the passenger order. The background sends the recommended route to the driver together with the order. The driver confirms the order, and the order takes effect after the two parties reach an agreement. The location and other information are confirmed through the contact information given by the two parties in the background. At the same time, the background monitors the order. After the ord...

Embodiment 2

[0043] Such as Figure 12 As shown, the present invention provides a safe online car-hailing method based on big data mining, wherein the online car-hailing driver chooses to go to the target area independently according to the passenger analysis result map or the driver analysis result map in the target area, and the passenger chooses independently when using the car. Qualified vehicles in the area make reservations for the order. After the passenger reserves the order, the order is sent to the background. The background plans the route between the driver and the passenger and designs a recommended route. The background sends the recommended route together with the order to The driver, the driver confirms the order, and the order will take effect after the two parties reach an agreement. The location and other information will be confirmed through the contact information given by the background, and the background will monitor the order.

[0044] Based on the analysis of the ...

Embodiment 3

[0048] In this embodiment, the method used in selecting an order is the same as in Embodiments 1 and 2. The difference is that after the order is generated, neither the driver nor the passenger can know the contact information of the other party in advance. When the driver arrives within 5 kilometers of the passenger, the driver can Obtain the passenger's contact information given by the background, the contact information is an encrypted mobile phone number, and the contact information is valid for five minutes, and it will be re-encrypted and replaced every five minutes. When the passenger cancels the order, the driver cannot contact the passenger. Way.

[0049] This method protects the privacy of both the driver and the passenger, and avoids the situation that the driver harasses the passenger or the passenger repeatedly harass the driver.

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Abstract

The invention provides a safety net car-sharing method and a safety net car-sharing system based on big data mining, a net car sharing driver independently chooses to go to the target area, when passengers choose their own vehicles, the passengers make an appointment for an order, after the passenger has made an appointment, order is sent to background, the recommended route is designed for the position between the driver and the passenger by path planning in the background. The recommended route is sent to the driver together with the order. The driver confirms the order. The order takes effect after the two parties reach an agreement. The position and other information are confirmed by the contact information of both parties given in the background. At the same time, the order is monitored in the background. The invention has the following advantages: the driver and the passenger have the autonomous choice right, the order can be monitored at the same time to ensure the personal safety of both sides, and the behavior of the passenger and the driver can be predicted through the big data mining, so that the passenger and the driver can better match the receiving order.

Description

technical field [0001] The invention relates to the field of online car-hailing, in particular to a safe online car-hailing method and system based on big data mining. Background technique [0002] The birth of online car-hailing has changed the pattern of the traditional taxi-hailing market. In the existing online car-hailing system, drivers and passengers can only dispatch orders passively and one-way from the background. Drivers evaluate star ratings, but this simple, one-way evaluation method is difficult to feed back customers' real opinions and needs. Make a reminder, and at the same time, the driver does not have the right to choose independently, so he is often reported and blackmailed by malicious bad reviewers. At the same time, the driver cannot know the densely populated areas of competitors, and feels confused and helpless about the driving route he is about to go. Rough judgments based on long-term experience. Contents of the invention [0003] In order to ...

Claims

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Application Information

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IPC IPC(8): G06Q10/02G06Q10/06G06Q50/30
CPCG06Q10/02G06Q10/06311G06Q50/30
Inventor 赵菁赵金宝张华禹郭玉丽丁紫钰邓楠尹晓盛
Owner 赵菁
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