CN109086915B - GIS-based network appointment order receiving and path planning method - Google Patents

GIS-based network appointment order receiving and path planning method Download PDF

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CN109086915B
CN109086915B CN201810768279.6A CN201810768279A CN109086915B CN 109086915 B CN109086915 B CN 109086915B CN 201810768279 A CN201810768279 A CN 201810768279A CN 109086915 B CN109086915 B CN 109086915B
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何通能
杨力乙
陈德富
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Zhejiang University of Technology ZJUT
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Abstract

A GIS-based network appointment order receiving and path planning method comprises the following steps: a1, obtaining passenger order receiving request information; a2, classifying the passengers needing to receive orders according to destinations; a3, calculating the average starting distance, the travel cost and the urgency of each group of travels; a4, carrying out normalization processing on each group of passenger trips according to the starting point distance, the trip cost and the urgency; a5, carrying out normalization processing on each group of strokes, namely calculating a priority quantization standard according to a weight proportion; a6, reordering according to the priority quantization standard, and giving priority to the former journey over the latter journey; a7, sequentially importing the sequenced journey groups and the corresponding destination position information into ArcMap according to the priority order; a8, creating a Network analysis layer by using VRP in Network analysis Tool in ArcMap. The invention improves the order receiving efficiency and the travel efficiency of the net appointment vehicle.

Description

GIS-based network appointment order receiving and path planning method
Technical Field
The invention relates to the fields of geographic information data processing, traffic road engineering, path planning and computer application, in particular to a GIS-based network appointment order receiving and path planning method.
Background
With the rapid development of Chinese economy and the continuous progress of the technological level, the traditional Chinese traveling mode is also changed continuously. The traditional taxi traveling mode is gradually replaced by a novel traveling mode. The internet technology is updated and the mobile intelligent terminal is developed, so that the online appointment vehicle gradually enters the field of vision of the public. Through advanced mobile phone application software and a positioning platform, vehicles are reserved at a mobile terminal, a nearest vehicle owner can respond at the first time, and the traveling efficiency is greatly improved in such a mode, so that the method is very popular among people.
The travel mode of the net appointment vehicle is more hot, and the main reasons for the rapid development of the new travel mode comprise three points: the first, traditional taxi industry is subject to many negative comments, such as refusal of loading, black cars, abusive passengers, detours, etc. Secondly, with the maturity of 4G networks and the popularization of mobile terminals such as mobile phones, positioning services have become more accurate, which provides technical guarantee for internet and travel. Thirdly, the owner of the vehicle can utilize leisure time to develop the part-time activities, which accords with the characteristics of sharing economy, and the passenger has stronger demand for finding a convenient and fast travel mode in the environment of difficult vehicle taking.
However, under the convenient and fast appearance of the net appointment vehicle, the order receiving reasonability and the travel efficiency of the vehicle owners have great problems. For example: the problem of difficulty in calling the bus, and some passengers with high urgency are arranged at the last pick-up; the vehicle owner often walks around according to the platform system to push the order, and can not find a proper route by turning to half to connect the passengers passing by, thus resulting in low efficiency; due to the randomness of platform pushing and the subjective variability of the order receiving and sending sequence of the car owner, the delay time caused by frequent call invoicing of passengers and unreasonable schedule planning of the complaint car owner is considered, the main reason is considered, the order receiving sequence is unreasonable optimized, the unreasonable schedule planning is made by the car owner according to experience, the time cost is wasted, and the trip experience of the user is reduced.
Therefore, the existing network appointment order receiving and route planning method has the defects and needs to be improved.
Disclosure of Invention
In order to overcome the defects of low order receiving efficiency and low travel efficiency of the conventional network appointment order receiving and travel planning method, the invention provides a GIS-based network appointment order receiving and path planning method for improving the order receiving efficiency and the travel efficiency of the network appointment vehicle, which is based on a GIS network analysis technology and relates to the fields of geographic information data processing, traffic road engineering, path planning, computer application and the like.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a GIS-based network appointment order receiving and path planning method comprises the following steps:
a1, obtaining order receiving information O of a passenger request in a set kilometer range, wherein the order receiving information comprises a starting point, a destination and a price;
a2, classifying passengers needing to receive orders according to destinations, and dividing passenger routes with destinations in a reasonable range into a group, and recording the group as O ═ O1,o2,…,oi,…onIn which o isiThe destinations are the passenger routes of the same place, n represents the number of the destinations, and i is more than or equal to 0 and less than or equal to n;
a3, standardizing according to the three dimensions of the starting distance between the passenger and the vehicle owner, the travel cost and the urgency degree, and processing the divided passenger order as follows: calculating the average starting distance of each group of passenger trips, summing the starting distances of each group of trips, and dividing the sum of the starting distances of each group of trips by the total number of the group of trips to obtain the average starting point distance di(ii) a The total price of the travel charge of each group of passengers is recorded as pi(ii) a According to the special description filled by passengers, judging the emergency situation through a platform context analysis tool, defaulting to be one level, taking the highest emergency degree of each group of passenger trips as the emergency degree of the group of trips, and marking as ei；
A4, normalizing each group of passenger trips according to the starting distance, the trip cost and the emergency degree of the passenger and the vehicle owner, and averaging the starting distance d of each group of tripsiDividing the average starting distance by the sum of the average starting distances of each group to obtain the normalized average starting distance of each group of strokes
Figure BDA0001729587910000021
Dividing the cost price of each group of the trips by the sum of the prices of all the trips to obtain the normalized cost of each group of the trips
Figure BDA0001729587910000022
Dividing each group of travel emergency degree by the sum of all travel emergency degrees to obtain the normalized passenger travel emergency degree of each group
Figure BDA0001729587910000023
Figure BDA0001729587910000024
A5, reordering each group of trips according to the weight proportion by the data after normalization processing, and calculating the priority z of taking orders of each group of trips according to the formula (2)i，
Figure BDA0001729587910000031
Wherein the weight ratio is selected by platform big data analysisdRepresents the average starting point distance
Figure BDA0001729587910000032
Weight of (a), ωpIndicating trip cost
Figure BDA0001729587910000033
Weight of (a), ωeWeight, ω, representing degree of urgency of journeyd+ωp+ωe1, and 0 ≤ ωd≤1,0≤ωp≤1，0≤ωe≤1；
A6, z to be finally calculatediSorting in a big to small manner, ziThe larger the trip, the higher the trip priority;
a7, sequentially importing the sorted travel groups and the corresponding destination position information into ArcMap according to the priority order, and displaying the travel groups and the corresponding destination position information in Map more intuitively;
a8, analyzing the travel path; the method comprises the steps of importing road data information around a vehicle owner into an ArcMap, creating a Network analysis layer by utilizing VRP in Network analysis Tool in the ArcMap, sequentially using travel groups as stop points in the layer according to a priority order, using the road information as a path, and finally analyzing to obtain an optimal pick-up travel path by using the least time spent on the path and the highest cost performance as a judgment standard.
Further, in the step A8, the VRP creates a network analysis layer, in which a solution corresponding to the requirement is generated by setting network analysis classes, such as sites, paths, stops, site accesses and point barriers.
Still further, the generated solution is a basic optimal method of network analysis in ArcMap, or a corresponding optimal method generated by adding custom scripts.
The invention has the following beneficial effects: the network appointment vehicle order receiving and path planning method is a sorting method, is a sorting method for determining the priority to the travel sequence according to the distance between the passenger and the vehicle owner starting point, the travel cost and the urgency degree, is combined with a GIS, analyzes a travel route based on actual road information, and improves the order receiving efficiency and the travel efficiency of the network appointment vehicle.
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Fig. 1 is a flow chart of a method for network appointment order taking and path planning based on a GIS.
Fig. 2 is a diagram of the sorted travel positions shown in ArcMap.
Fig. 3 is an optimal pick-up route graph generated after network analysis processing.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 to 3, a method for network appointment order taking and path planning based on a GIS includes the following steps:
a1, obtaining passenger order receiving information O in a set kilometer range (such as five kilometers), wherein the order receiving information comprises a starting point, a destination and a price, and also can comprise thank you fee, special instructions and the like, and a specific initialization range can be manually set by a vehicle owner;
a2, classifying passengers needing to receive orders according to destinations, and dividing passenger routes with destinations in a reasonable range into a group, and recording the group as O ═ O1,o2,…,oi,…onIn which o isiThe destinations are the passenger routes of the same place, n represents the number of the destinations, and i is more than or equal to 0 and less than or equal to n; note that the judgment of the same destination needs to be combined with the elevation data of the GIS urban road distribution map;
a3, standardizing according to the three dimensions of the starting distance between the passenger and the vehicle owner, the travel cost and the urgency degree, and processing the divided passenger order as follows: calculating the average starting distance of each group of passenger trips, summing the starting distances of each group of trips, and dividing the sum of the starting distances of each group of trips by the total number of the group of trips to obtain the average starting point distance di(ii) a The total price of each group of passenger travel fees (including the travel base price and the thank you fee) is recorded as pi(ii) a According to the special description filled by passengers, judging the emergency situation through a platform context analysis tool, defaulting to be one level, taking the highest emergency degree of each group of passenger trips as the emergency degree of the group of trips, and marking as ei；
A4, normalizing each group of passenger trips according to the starting distance, the trip cost and the emergency degree of the passenger and the vehicle owner, and averaging the starting distance d of each group of tripsiDividing the average starting distance by the sum of the average starting distances of each group to obtain the normalized average starting distance of each group of strokes
Figure BDA0001729587910000041
Dividing the cost price of each group of the trips by the sum of the prices of all the trips to obtain the normalized cost of each group of the trips
Figure BDA0001729587910000042
Dividing each group of travel emergency degree by the sum of all travel emergency degrees to obtain the normalized passenger travel emergency degree of each group
Figure BDA0001729587910000043
Figure BDA0001729587910000044
A5, reordering each group of trips according to the weight proportion by the data after normalization processing, and calculating the priority z of taking orders of each group of trips according to the formula (2)i，
Figure BDA0001729587910000051
Wherein ω isdRepresents the average starting point distance
Figure BDA0001729587910000052
Weight of (a), ωpIndicating trip cost
Figure BDA0001729587910000053
Weight of (a), ωeWeight, ω, representing degree of urgency of journeyd+ωp+ωe1, and 0 ≤ ωd≤1,0≤ωp≤1,0≤ωe≤1；
The weight proportion can be related to a mode selected by a vehicle owner; the vehicle owner can select the order taking and route planning styles according to the current actual situation, wherein the styles comprise highest price priority, shortest time priority, least kilometer number priority, highest cost performance priority and the like. In different modes, the weight proportion of the starting distance, the travel cost and the emergency degree of each group of travel is different. Generally, in the highest price mode, the weight ratio of the travel cost is often greater than the weight ratio of the other two. The platform can dynamically adjust the weight proportion of each parameter in real time according to big data analysis;
a6, z to be finally calculatediSorting in a big to small manner, ziThe larger the trip, the higher the trip priority;
a7, sequentially importing the sorted travel groups and the corresponding destination position information into ArcMap according to the priority order, and displaying the travel groups and the corresponding destination position information in Map more intuitively; importing terrain conditions, traffic density factors, human factors, weather factors and the like acquired from a third party into ArcGIS Pro, and realizing and generating final road real-time data information through Spatial analysis Tools;
a8, analyzing the travel path; the method comprises the steps of importing road real-time data information around a vehicle owner into an ArcMap, creating a Network analysis layer by utilizing VRP in Network analysis Tool in the ArcMap, sequentially using travel groups as stop points in the layer according to a priority order, using the road information as a path, and finally analyzing according to judgment standards corresponding to a bill receiving and path specification style selected by the vehicle owner to obtain an optimal bill receiving travel path.
Further, in the step A8, the VRP creates a network analysis layer, in which a solution corresponding to the requirement is generated by setting network analysis classes, such as sites, paths, stops, site accesses and point barriers.
Still further, the generated solution is a basic optimal method of network analysis in ArcMap, or a corresponding optimal method generated by adding custom scripts. With reference to fig. 2 and 3, taking a vehicle owner order taking of a certain network car appointment as an example, a network car appointment order taking and path planning method based on a GIS includes the following steps:
a1, obtaining passenger request order information in a five-kilometer range [ { starting point: "Zhejiang industrial university of Zhejiang province 288 on Zhenchun city, Zhenzhou city, Town city, Hangzhou city, destination: "Wuchangdao 1 Xixi impression city in Hangzhou city", journey price: "13.00", thank you fee: "5.00", Special Specification: "pick me as soon as possible" }, { starting point: "Zhejiang industrial university of Zhejiang province 288 on Zhenchun city, Zhenzhou city, Town city, Hangzhou city, destination: 'Hangzhou West stream 875 V.V. hardware shop', travel price: "13.50", thank you fee: "0.00", special note: "none" }, { starting point: "Tianmu mountain road 402 number China wetland museum in Hangzhou city", destination: 'Hangzhou city ancient mound road Zhejiang commercial wealth center', travel price: "16.80", thank you fee: "5.00", Special Specification: "urgent, please speed up me" }, { starting point: "Hangzhou hong Kong 21 Baoli international movie city, destination: "Ju Dao No. 100 in West lake region of Hangzhou city", journey price: "30.50", thank you fee: "10.00", special statement: "none" }, { starting point: "Hangzhou city wuchang dao 165 Jing Source International", destination: "Zhejiang science and technology institute of Zhongzhou city, Zhonghou province 318", travel price: "20.00", thank you fee: "5.00", Special Specification: "urgent, please speed up me" }, { starting point: "mountain road and home garden of red bayberry in Hangzhou city", destination: "the travel price of the hangzhou city and the lusheng west roc hotel": "8.00", thank you fee: "0.00", special note: "none" };
a2, classifying passengers needing to receive orders according to destinations, dividing passenger routes with destinations in a reasonable range into a group, and recording the group as O ═ O1,o2,…,oi,…onIn which o isiThe destination is the passenger travel of the same place, n represents the number of the destinations, and n is 6;
a3, standardizing according to the three dimensions of the starting distance between the passenger and the vehicle owner, the travel cost and the urgency degree, and processing the divided passenger order as follows: calculating the average starting distance d for each group of passenger tripsi{3,2,4,5,6,1}, in units of kilometers; total price p of travel charge for each group of passengersi(ii) 18.00,13.50,21.80,40.50,25.00,8.00}, units (yuan); each group of passenger travel urgency ei2,1,3,1, unit (none);
a4, normalizing each group of passenger trips according to the starting distance, the trip cost and the emergency degree, and averaging the starting point distance d of each group of tripsiDividing by the sum of the average starting point distances of each group to obtain
Figure BDA0001729587910000061
Dividing the cost price of each group of the trips by the sum of the prices of all the trips to obtain
Figure BDA0001729587910000062
Dividing the emergency degree of each group of strokes by the sum of the emergency degrees of all strokes to obtain
Figure BDA0001729587910000063
Figure BDA0001729587910000071
A5, assuming that the owner is urgent at the moment, and wants to complete order receiving and travel tasks as soon as possible, the shortest time mode is preferably adopted, and the platform obtains the parameter weight proportion omega according to dynamic big data analysisd＝0.6,ωp＝0.3,ωeAnd (3) reordering each group of strokes according to the weight proportion by using the normalized data, and calculating the order taking priority z of each group of strokes according to the formula (1)i＝{0.1466,0.0979,0.1929,0.2476,0.2652,0.0568}
Figure BDA0001729587910000072
A6, z to be finally calculatediSorting in a big to small manner, ziThe larger the travel priority, the higher the order after the sort is { z }5,z4,z3,z1,z2,z6}；
A7, sequentially importing the sorted travel groups and the corresponding destination position information into ArcMap according to the priority order, and displaying the travel groups and the corresponding destination position information in Map more intuitively, as shown in FIG. 2;
a8, analyzing the travel path; the method comprises the steps of importing road data information around a vehicle owner into an ArcMap, creating a Network analysis layer by utilizing VRP in Network analysis Tool in the ArcMap, sequentially using travel groups as stop points according to priority order in the layer, using the road information as a path, and finally analyzing by taking the least time spent on the path as a judgment standard to obtain an optimal pick-up travel path, as shown in figure 3.
While the foregoing has described the preferred embodiments of the present invention, it will be apparent that the invention is not limited to the embodiments described, but can be practiced with modification without departing from the essential spirit of the invention and without departing from the spirit of the invention.

Claims (3)

1. A GIS-based network appointment order receiving and path planning method is characterized by comprising the following steps:
a1, obtaining order receiving information W of a passenger request in a set kilometer range, wherein the order receiving information comprises a starting point, a destination and a price;
a2, classifying passengers needing to receive orders according to destinations, dividing passenger routes with destinations in a reasonable range into a group, and recording the group as O ═ O1,o2,…,oi,…onIn which o isiThe destinations are the passenger routes of the same place, n represents the number of the destinations, and i is more than or equal to 0 and less than or equal to n;
a3, standardizing according to the three dimensions of the starting distance between the passenger and the vehicle owner, the travel cost and the urgency degree, and processing the divided passenger order as follows: calculating the average starting distance of each group of passenger trips, summing the starting distances of each group of trips, and dividing the sum of the starting distances of each group of trips by the total number of the group of trips to obtain the average starting point distance di(ii) a The total price of the travel charge of each group of passengers is recorded as pi(ii) a According to the special description filled by passengers, judging the emergency situation through a platform context analysis tool, defaulting to be one level, taking the highest emergency degree of each group of passenger trips as the emergency degree of the group of trips, and marking as ei；
A4, normalizing each group of passenger trips according to the distance of the starting point, the trip cost and the emergency degree, and averaging the distance d of the starting point of each group of tripsiDividing the average starting point distance of each group to obtain the normalized average starting point distance of each group of strokes
Figure FDA0003101140230000011
Dividing the cost price of each group of the trips by the sum of the prices of all the trips to obtain the normalized cost of each group of the trips
Figure FDA0003101140230000012
Dividing each group of travel emergency degree by the sum of all travel emergency degrees to obtain the normalized passenger travel emergency degree of each group
Figure FDA0003101140230000013
Figure FDA0003101140230000014
A5, reordering each group of trips according to the weight proportion by the data after normalization processing, and calculating the priority z of taking orders of each group of trips according to the formula (2)i，
Figure FDA0003101140230000015
Wherein the weight ratio is selected by platform big data analysisdRepresents the average starting point distance
Figure FDA0003101140230000016
Weight of (a), ωpIndicating trip cost
Figure FDA0003101140230000017
Weight of (a), ωeWeight, ω, representing degree of urgency of journeyd+ωp+ωe1, and 0 ≤ ωd≤1,0≤ωp≤1,0≤ωe≤1；
A6, z to be finally calculatediSorting in a big to small manner, ziThe larger the trip, the higher the trip priority;
a7, sequentially importing the sorted travel groups and the corresponding destination position information into ArcMap according to the priority order, and displaying the travel groups and the corresponding destination position information in Map more intuitively;
a8, analyzing the travel path; the method comprises the steps of importing road data information around a vehicle owner into an ArcMap, creating a Network analysis layer by utilizing VRP in Network analysis Tool in the ArcMap, sequentially using travel groups as stop points in the layer according to a priority order, using the road information as a path, and finally analyzing to obtain an optimal pick-up travel path by using the least time spent on the path and the highest cost performance as a judgment standard.
2. The method for network appointment order taking and path planning based on GIS as claimed in claim 1, wherein in the step A8, the VRP creates a network analysis layer, in which a solution for the corresponding requirement is generated by setting network analysis classes, wherein the network analysis classes include sites, paths, stop points, site visits and point obstacles.
3. The method for network appointment order taking and path planning based on GIS as claimed in claim 1, wherein the generated solution in step A8 is a basic optimal method for network analysis in ArcMap, and a custom script can be added to generate a corresponding optimal method.
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Application publication date: 20181225

Assignee: Foshan shangxiaoyun Technology Co.,Ltd.

Assignor: JIANG University OF TECHNOLOGY

Contract record no.: X2024980000078

Denomination of invention: A GIS-based method for online ride hailing vehicle ordering and path planning

Granted publication date: 20210803

License type: Common License

Record date: 20240104