CN110491143A - A kind of current multi-target optimal design method of traffic - Google Patents

A kind of current multi-target optimal design method of traffic Download PDF

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Publication number
CN110491143A
CN110491143A CN201910787050.1A CN201910787050A CN110491143A CN 110491143 A CN110491143 A CN 110491143A CN 201910787050 A CN201910787050 A CN 201910787050A CN 110491143 A CN110491143 A CN 110491143A
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China
Prior art keywords
intersection
formula
indicates
traffic
indicate
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CN201910787050.1A
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Inventor
曾小清
盖松雪
詹继飞
应沛然
熊启鹏
袁腾飞
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Suzhou Budze Information Technology Co Ltd
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Suzhou Budze Information Technology Co Ltd
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Priority to CN201910787050.1A priority Critical patent/CN110491143A/en
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention discloses a kind of current multi-target optimal design methods of traffic, comprising: step S1, from the effective green time g in intersection each periodeiIt releases signal period C and obtains vehicles average delay time, intersection vehicles stop frequency and intersection capacity in conjunction with the traffic flow data of investigation；Step S2, intersection Model for Multi-Objective Optimization is established using formula (1), in formula (1), parameter D, H, CAP are solved using formula (2), and formula (1) and formula (2) meet formula (3)；Step S3 is constrained by solving to intersection Model for Multi-Objective Optimization, and using formula (4), to adjust the signal time distributing conception of intersection, improves the passage effect of intersection.The present invention carries out clustering by the lane saturation degree to intersection, carries out multiple-objection optimization to intersection and promotes the passage effect and service level of intersection by establishing model algorithm.

Description

A kind of current multi-target optimal design method of traffic
Technical field
The present invention relates to a kind of current multi-target optimal design methods of traffic, the traffic operation pipe applied to intersection Reason field.
Background technique
In recent years, the traffic blocking problem of China's urban road intersection is on the rise.With vehicle ownership not Disconnected to rise, urban road increasingly congestion takes place frequently so as to cause Urban Road Traffic Accidents.Once it gets congestion on road, it will be straight The operational efficiency for reducing road network is connect, is also easy to induce second accident.The configuration of intersection time resource namely integrative design intersection, Research origin is more early, and from First signal lamp in 1868 since Britain occurs, experts and scholars are in terms of integrative design intersection Research is also gradually goed deep into.With going deep into for research, the traffic background that many scholars consider also extends to region from single-point intersection Intersection and traffic network, corresponding Optimized model also become multiple target from single goal, and Consideration is also from initial delay Time, the algorithm of utilization was also each has something to recommend him supplemented with stop frequency, the traffic capacity, carbon emission, fuel consumption etc..But it is existing Technology still lack it is a kind of can the traffic capacity, vehicles average delay time and vehicle parking number to intersection carry out it is more The method of target complex optimum.
Chinese patent literature CN108765989A provides a kind of guided vehicle road letter that intersection straight and turning left is variable This method comprises: formulating the operation rule in lane, and variable arrow signal lamp is arranged in number control method；With Webster public affairs Formula calculates main signal timing；According to the phase difference between pre-signal and main signal, pre-signal timing is determined；Setting pre-signal lamp, Lane change graticule and traffic sign are prompted, realizes that guided vehicle road carries out the cyclical-transformation in straight and turning left lane.This method considers Be guided vehicle road carry out straight and turning left lane cyclical-transformation, realize intersection guided vehicle road signal control, still cannot Carry out multi-target optimal design.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of current multi-target optimal design sides of more superior traffic Method, can to intersection carry out multiple target index under optimal control, by practical intersection carry out traffic data collection and Analysis, specifies the optimization direction of intersection, to establish corresponding signal time distributing conception.
To achieve the goals above, the present invention is realised by adopting the following technical scheme:
A kind of current multi-target optimal design method of traffic, comprising:
Step S1: from the effective green time g in intersection each periodeiSignal period C is released, in conjunction with the traffic flow of investigation Data are measured, obtain vehicles average delay time, intersection vehicles stop frequency and intersection capacity；
Step S2: intersection Model for Multi-Objective Optimization, formula (1) are established using formula (1) are as follows:
Wherein, D indicates the mean delay time of vehicle, s；
D0Indicate the initial delay time at stop of vehicle, s；
H indicates vehicle in intersection parking number；
H0Indicate vehicle in the initial stop frequency in intersection；
CAP indicates the traffic capacity of intersection, pcu/h；
CAP0Indicate the initial traffic capacity of intersection, pcu/h；
α indicates the weighted value of vehicles average delay, [0,1]；
β indicates that vehicle is averaged the weighted value of stop frequency, [0,1]；
γ indicates the weighted value of intersection capacity, [0,1]；
In formula (1), parameter D, H, CAP are solved using formula (2), formula (2) are as follows:
Wherein, i indicates the i-th phase of intersection；
J indicates the i-th phase jth entrance driveway；
qijIndicate the magnitude of traffic flow, pcu/h；
C indicates time signal period, s；
geiIndicate the effective green time of phase i, s；
sijIndicate saturation flow, pcu/h；
X indicates saturation degree, i.e. the ratio between entrance driveway actual traffic amount and the traffic capacity；
Formula (1) and formula (2) meet formula (3), formula (3) are as follows:
Wherein, gemax, geminIndicate the maximin of effective green time, s；
Cmax, CminIndicate the maximin of signal period, s；
Step S3: it is constrained by being solved to intersection Model for Multi-Objective Optimization, and using formula (4), to adjust The signal time distributing conception of whole intersection improves the passage effect of intersection, formula (4) are as follows:
F=Fit (f (gei))+B1·f(p1)+B2·f(p2)+B3·f(p3)+B4·f(p4)
Wherein, B1, B2, B3, B4It indicates penalty, takes 10000,1000000,1000000,100000 respectively；
f(p1), f (p2), f (p3), f (p4) value condition it is as follows:
f(p1)=[max (0,15-min (ge))]2；
f(p2)=[min (0,80-max (ge))]2；
f(p3Max)=[(0,30-C)]2；
f(p4Min)=[(0,180-C)]2。
Compared with prior art, technical solution provided by the invention has the advantage that
1, the present invention carries out clustering by the lane saturation degree to intersection, chooses the traffic capacity, the vehicle of intersection Mean delay time and vehicle parking number to carry out multiple-objection optimization to intersection, by establishing model algorithm, are promoted The passage effect and service level of intersection.
2, the present invention can carry out the optimal control under multiple target index to intersection, by handing over practical intersection Logical data collection and analysis, specify the optimization direction of intersection, to establish corresponding signal time distributing conception.
3, the present invention can enrich existing intersection signal timing scheme, by carrying out multiple target index point to intersection Analysis, can more adapt to the traffic flow environment currently changed.
4, the Matlab program that the present invention is write by itself, while by being improved to genetic algorithm, it can make to count Calculate it is more accurate with it is quick.
5, the present invention constrains algorithm by setting up penalty, avoids subjective factor from influencing, to a certain extent Also operation efficiency is improved.
Detailed description of the invention
Fig. 1 is intersection area schematic of the present invention.
It is as shown in the figure: 1, entrance driveway；2, exit ramp.
Specific embodiment
The present invention is described in detail with reference to the accompanying drawing:
Intersection region shown in referring to Fig.1, the current multi-target optimal design method of traffic of the present invention are logical Cross and clustering carried out to the lane saturation degree of intersection, choose the traffic capacity of intersection, the vehicles average delay time and Vehicle parking number to carry out multiple-objection optimization to intersection, by establishing model algorithm, promoted intersection passage effect and Service level, specifically includes the following steps:
Step S1: from the effective green time g in intersection each periodeiSignal period C is released, in conjunction with the traffic flow of investigation Data are measured, obtain vehicles average delay time, intersection vehicles stop frequency and intersection capacity；
Step S2: intersection Model for Multi-Objective Optimization, formula (1) are established using formula (1) are as follows:
Wherein, D indicates the mean delay time of vehicle, s；
D0Indicate the initial delay time at stop of vehicle, s；
H indicates vehicle in intersection parking number；
H0Indicate vehicle in the initial stop frequency in intersection；
CAP indicates the traffic capacity of intersection, pcu/h；
CAP0Indicate the initial traffic capacity of intersection, pcu/h；
α indicates the weighted value of vehicles average delay, [0,1]；
β indicates that vehicle is averaged the weighted value of stop frequency, [0,1]；
γ indicates the weighted value of intersection capacity, [0,1]；
In formula (1), parameter D, H, CAP are solved using formula (2), formula (2) are as follows:
Wherein, i indicates the i-th phase of intersection；
J indicates the i-th phase jth entrance driveway；
qijIndicate the magnitude of traffic flow, pcu/h；
C indicates time signal period, s；
geiIndicate the effective green time of phase i, s；
sijIndicate saturation flow, pcu/h；
X indicates saturation degree, i.e. the ratio between entrance driveway actual traffic amount and the traffic capacity；
Formula (1) and formula (2) meet formula (3), formula (3) are as follows:
Wherein, gemax, geminIndicate the maximin of effective green time, s；
Cmax, CminIndicate the maximin of signal period, s；
Step S3: it is constrained by being solved to intersection Model for Multi-Objective Optimization, and using formula (4), to adjust The signal time distributing conception of whole intersection improves the passage effect of intersection, formula (4) are as follows:
F=Fit (f (gei))+B1·f(p1)+B2·f(p2)+B3·f(p3)+B4·f(p4)
Wherein, B1, B2, B3, B4It indicates penalty, takes 10000,1000000,1000000,100000 respectively；
f(p1), f (p2), f (p3), f (p4) value condition it is as follows:
f(p1)=[max (0,15-min (ge))]2；
f(p2)=[min (0,80-max (ge))]2；
f(p3Max)=[(0,30-C)]2；
f(p4Min)=[(0,180-C)]2。
Compared with prior art, technical solution provided by the invention can carry out the optimization under multiple target index to intersection Control specifies the optimization direction of intersection, to establish corresponding by carrying out traffic data collection and analysis to practical intersection Signal time distributing conception.The present invention can enrich existing intersection signal timing scheme, by carrying out multiple target to intersection Index analysis can more adapt to the traffic flow environment currently changed.The Matlab program that the present invention is write by itself, simultaneously By being improved to genetic algorithm, can make to calculate it is more accurate with it is quick.The present invention is by setting up penalty to algorithm It is constrained, subjective factor is avoided to influence, also improve operation efficiency to a certain extent.

Claims (1)

1. a kind of current multi-target optimal design method of traffic characterized by comprising
Step S1: from the effective green time g in intersection each periodeiSignal period C is released, in conjunction with the magnitude of traffic flow number of investigation According to obtaining vehicles average delay time, intersection vehicles stop frequency and intersection capacity；
Step S2: intersection Model for Multi-Objective Optimization, formula (1) are established using formula (1) are as follows:
Wherein, D indicates the mean delay time of vehicle, s；
D0Indicate the initial delay time at stop of vehicle, s；
H indicates vehicle in intersection parking number；
H0Indicate vehicle in the initial stop frequency in intersection；
CAP indicates the traffic capacity of intersection, pcu/h；
CAP0Indicate the initial traffic capacity of intersection, pcu/h；
α indicates the weighted value of vehicles average delay, [0,1]；
β indicates that vehicle is averaged the weighted value of stop frequency, [0,1]；
γ indicates the weighted value of intersection capacity, [0,1]；
In formula (1), parameter D, H, CAP are solved using formula (2), formula (2) are as follows:
Wherein, i indicates the i-th phase of intersection；
J indicates the i-th phase jth entrance driveway；
qijIndicate the magnitude of traffic flow, pcu/h；
C indicates time signal period, s；
geiIndicate the effective green time of phase i, s；
sijIndicate saturation flow, pcu/h；
X indicates saturation degree, i.e. the ratio between entrance driveway actual traffic amount and the traffic capacity；
Formula (1) and formula (2) meet formula (3), formula (3) are as follows:
Wherein, gemax, geminIndicate the maximin of effective green time, s；
Cmax, CminIndicate the maximin of signal period, s；
Step S3: being constrained by solving to intersection Model for Multi-Objective Optimization, and using formula (4), is handed over to adjust The signal time distributing conception of prong improves the passage effect of intersection, formula (4) are as follows:
F=Fit (f (gei))+B1·f(p1)+B2·f(p2)+B3·f(p3)+B4·f(p4)
Wherein, B1, B2, B3, B4It indicates penalty, takes 10000,1000000,1000000,100000 respectively；
f(p1), f (p2), f (p3), f (p4) value condition it is as follows:
f(p1)=[max (0,15-min (ge))]2；
f(p2)=[min (0,80-max (ge))]2；
f(p3Max)=[(0,30-C)]2；
f(p4Min)=[(0,180-C)]2。
CN201910787050.1A 2019-08-25 2019-08-25 A kind of current multi-target optimal design method of traffic Pending CN110491143A (en)

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Cited By (1)

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Publication number Priority date Publication date Assignee Title
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CN108470444A (en) * 2018-03-21 2018-08-31 特斯联（北京）科技有限公司 A kind of city area-traffic big data analysis System and method for based on genetic algorithm optimization
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111524345A (en) * 2020-03-27 2020-08-11 武汉理工大学 Induction control method for multi-objective optimization under constraint of real-time queuing length of vehicle
CN111524345B (en) * 2020-03-27 2021-11-02 武汉理工大学 Induction control method for multi-objective optimization under constraint of real-time queuing length of vehicle

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Application publication date: 20191122