Early warning method for online car-hailing order service duration abnormity

Abstract

The invention discloses an online car-hailing order service duration abnormity early warning method, which comprises the following steps: S1, starting, a passenger places an order, and a driver clicks that the passenger gets on the car; s2, judging whether the order service type is an instant vehicle use type or not; s3, if the vehicle is used instantly, recording the predetermined getting-on time t1, the estimated arrival time t2 and the system time t3 of the passenger; s4, if not, the actual boarding time t of the passenger, the estimated arrival time t2 and the system time t3 are recorded; s5, t3gt is judged; t2, if yes, listing the orders into an overtime non-arrival queue; according to the invention, the condition that the online car-hailing order is not settled for a long time is automatically identified and warned, and the condition that the driver does not settle the order intentionally or unintentionally is found before the customer complaints; the order state and the service duration are monitored in real time and at high frequency, possible system faults or other unforeseen circumstances are found in time, and the anti-risk capability of the platform is enhanced.

Description

Technical Field

[0001] The present invention belongs to the technical field of online car-hailing, and specifically relates to an early warning method for abnormal service duration of an online car-hailing order. Background Art

[0002] In online ride-hailing orders, there are often cases where the order status is in service for a long time. There are three main reasons for this type of order.

[0003] (1) Passengers have special needs for the use of the vehicle for a long period of time. For example, if the vehicle is used for more than 24 hours, it is considered a very rare case.

[0004] (2) After the passenger arrives at the drop-off location, the driver deliberately does not click or forgets to swipe to settle the order, leaving the order in the in-service state.

[0005] (3) If the driver reports an abnormal order status or other unexpected events occur, manual intervention is required to quickly investigate.

[0006] When the above situations (2) and (3) occur, most of the time it is because the passengers find that the order has not been settled, which results in a large amount of fees. Only after they complain to the customer service can the customer service be intervened and corrected. This leads to a decrease in customer satisfaction and an increase in the platform's manual processing costs.

[0007] To this end, the present invention designs an early warning method for abnormal service time of online car-hailing orders. Summary of the invention

[0008] The purpose of the present invention is to provide an early warning method for abnormal service duration of online car-hailing orders to solve the problems raised in the above-mentioned background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions: an early warning method for abnormal service time of online car-hailing order, S1: start, the passenger places an order, and the driver clicks that the passenger has boarded the car;

[0010] S2: Determine whether the order service type is instant car use;

[0011] S3: If the car is used immediately, the passenger's scheduled boarding time t1, estimated arrival time t2, and system time t3 are recorded;

[0012] S4: If not, record the passenger's actual boarding time t, estimated arrival time t2, and system time t3;

[0013] S5: Determine if t3>t2. If so, put the order into the timeout queue;

[0014] S6: If not, determine whether the order has been completed. If so, it means that the order is normal and no warning is required. If not, re-execute step S5;

[0015] S7: Check the order status every m minutes; determine whether t3-t2 is less than N;

[0016] S8: If yes, the order is normal;

[0017] S9: If not, the order timeout has not exceeded the threshold, and an early warning pops up to the customer service system;

[0018] S10: Customer service performs early warning verification.

[0019] Preferably, in step S7, the value of the query period m can be set manually.

[0020] Preferably, in step S7, the threshold N can be manually set according to circumstances.

[0021] Preferably, in step S2, it is determined whether the order service type is instant car use, because the standards for long-term services for instant car use and non-instant car use need to be specified differently.

[0022] Preferably, the estimated arrival time t2 and the system time t3 in step S2 are the same as the estimated arrival time t2 and the system time t3 in step S3.

[0023] Compared with the prior art, the beneficial effects of the present invention are: the present invention automatically identifies and warns of situations where online ride-hailing orders have not been settled for a long time, and discovers situations where drivers intentionally or unintentionally fail to settle orders before customers complain; it monitors order status and service time in real time and at high frequency, promptly discovers possible system failures or other unexpected situations, and enhances the platform's ability to resist risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] See also Figure 1 ,The present invention provides a technical solution: an early warning method for abnormal service time of online car-hailing orders,S1: start, the passenger places an order, and the driver clicks that the passenger has boarded;

[0027] S2: Determine whether the order service type is instant car use. Hint 1: The long-term service standards for instant car use and non-instant car use need to be specified separately;

[0028] S3: If the car is used immediately, the passenger's scheduled boarding time t1, estimated arrival time t2, and system time t3 are recorded;

[0029] S4: If not, record the passenger's actual boarding time t, estimated arrival time t2, and system time t3;

[0030] S5: Determine if t3>t2. If so, put the order into the timeout queue;

[0031] S6: If not, determine whether the order has been completed. If so, it means that the order is normal and no warning is required. If not, re-execute step S5;

[0032] S7: Check the order status every m minutes; determine whether t3-t2 is less than N;

[0033] S8: If yes, the order is normal;

[0034] S9: If not, the order timeout has not exceeded the threshold, and an early warning pops up to the customer service system;

[0035] S10: Customer service performs early warning verification.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A warning method for abnormal service time of online car-hailing orders, characterized by: S1: At the beginning, the passenger places an order and the driver clicks that the passenger has boarded the car; S2: Determine whether the order service type is instant car use; S3: If the car is used immediately, the passenger's scheduled boarding time t1, estimated arrival time t2, and system time t3 are recorded; S4: If not, record the passenger's actual boarding time t, estimated arrival time t2, and system time t3; S5: Determine if t3>t2. If so, put the order into the timeout queue; S6: If not, determine whether the order has been completed. If so, it means that the order is normal and no warning is required. If not, re-execute step S5; S7: Query the order status every m minutes; Determine whether t3-t2 is less than N; S8: If yes, the order is normal; S9: If not, the order timeout has not exceeded the threshold, and an early warning pops up to the customer service system; S10: Customer service performs early warning verification.

2. According to claim 1, a warning method for abnormal service duration of online car-hailing order, characterized in that: In step S7, the value of the query period m can be set manually.

3. The method for early warning of abnormal service duration of online car-hailing order according to claim 1, characterized in that: In step S7, the threshold N can be manually set according to the situation.

4. The method for early warning of abnormal service duration of online car-hailing order according to claim 1, characterized in that: In step S2, it is determined whether the order service type is instant car use, because the standards for long-term services for instant car use and non-instant car use need to be specified differently.

5. The method for early warning of abnormal service duration of online car-hailing order according to claim 1, characterized in that: The estimated arrival time t2 and the system time t3 in step S2 are the same as the estimated arrival time t2 and the system time t3 in step S3.

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