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A ground bus two-stage optimization scheduling method driven by mass operation data

A technology of operating data and public transportation, which is applied in the field of public transportation data mining and intelligent public transportation, and can solve problems such as insufficient consideration of dynamic scheduling

Active Publication Date: 2019-06-14
BEIJING UNIV OF TECH
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  • Description
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Problems solved by technology

However, although this system has static and dynamic scheduling, it is only deployed based on one factor, and the dynamic scheduling is not considered enough

Method used

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  • A ground bus two-stage optimization scheduling method driven by mass operation data
  • A ground bus two-stage optimization scheduling method driven by mass operation data
  • A ground bus two-stage optimization scheduling method driven by mass operation data

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0168] Implementation plan area: Beijing Express 107 Road, 650 Road

[0169] Step 1, static scheduling

[0170] Step 1.1, static optimization of bus stops

[0171] After analyzing a large amount of historical data, first counting the number of boardings and landings at each station of each line, it is concluded that Hujialou North Station, Guanghuaqiao North Station, and Dabeiyao North Station that Yuntong Line 107 and Line 650 pass through together are large passenger flow stations. Get the time-varying passenger flow curves of each station, taking Dabeiyao North Station as an example figure 1 shown

[0172] Step 1.2, static optimization of bus lines

[0173] Since the departure timetable involves too many times and stations, only the departure timetables of the above three stations at 6:10-7:40 a.m. are shown. As shown in Table 6, it is the departure schedule of Yuntong 107 Road at these three stations from 6:30 to 7:30 on a certain day in history. The departure frequen...

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Abstract

The invention discloses a ground bus two-stage optimization scheduling method driven by mass operation data, and the method depends on historical operation data, real-time dynamic data and other multi-source bus big data to carry out static and dynamic combined two-stage bus scheduling, and introduces a line group to carry out regional cooperative scheduling. And the system outputs a daily bus time table of a static region through periodical analysis of three layers of historical passenger flow data space-time characteristics of a station, a single line and a bus corridor line group. The regional bus system takes a static scheduling operation table as a basis, and imports bus dynamic operation data in real time, including bus card swiping data and bus GPS data, to perform dynamic operationanalysis of three layers of stations, single lines and bus corridor line groups, and to identify the problem of real-time bus operation and passenger flow supply and demand matching in a region. Higher-quality public transport service meeting travel requirements is provided for urban resident travel, and attraction of a public transport system and public transport service satisfaction are improved.

Description

technical field [0001] The invention relates to a two-stage optimized scheduling method for ground public transportation driven by massive operating data, and belongs to the technical field of intelligent public transportation and the field of public transportation data mining. Background technique [0002] Public transportation has the advantages of large capacity, green and energy-saving. Under the background of rapid urban population growth, increasingly severe traffic congestion, and increasing energy consumption in transportation, public transportation has broad application prospects. However, the current urban ground bus operation has problems such as unstable vehicle intervals, unbalanced passenger flow, and long waiting time for passengers, which has led to a continuous decline in the service level and passenger flow sharing rate of the ground bus. Moreover, the overall operation level of ground public transport in my country is currently low. Most small and medium-s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26G06N3/08
Inventor 翁剑成赵虹剑刘哲刘晟岐祁昊
Owner BEIJING UNIV OF TECH
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