CN113918869A - Method for calculating traffic capacity of right-turn vehicle in advance for non-forced priority mixed transportation travel - Google Patents
Method for calculating traffic capacity of right-turn vehicle in advance for non-forced priority mixed transportation travel Download PDFInfo
- Publication number
- CN113918869A CN113918869A CN202111026497.0A CN202111026497A CN113918869A CN 113918869 A CN113918869 A CN 113918869A CN 202111026497 A CN202111026497 A CN 202111026497A CN 113918869 A CN113918869 A CN 113918869A
- Authority
- CN
- China
- Prior art keywords
- advance
- traffic
- calculating
- bicycle
- motor vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000008447 perception Effects 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000012821 model calculation Methods 0.000 abstract description 4
- 230000007812 deficiency Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 4
- 230000008520 organization Effects 0.000 description 3
- 238000005457 optimization Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000003780 insertion Methods 0.000 description 1
- 230000037431 insertion Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Evolutionary Computation (AREA)
- Analytical Chemistry (AREA)
- Computer Hardware Design (AREA)
- Operations Research (AREA)
- Chemical & Material Sciences (AREA)
- Algebra (AREA)
- Geometry (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a method for calculating the traffic capacity of a right-turn vehicle in advance for non-forced priority mixed transportation travel, and relates to the technical field of traffic. The invention comprises the following steps: establishing a relational expression of the bicycle flow and the speed of the motor vehicle turning right in advance, and step 2: according to the existing model, solving the coefficient of the relational expression of the bicycle flow and the motor vehicle speed which turns right in advance, and 3: and calculating the number of vehicles which pass through the conflict area by the vehicles turning right in advance in the unsaturated traffic state. The invention fully describes the characteristic that vehicles turning right in advance pass through the bicycle flow without forcing priority based on the microcosmic driving force model of the right-turning vehicle with safe driving force and efficient driving force, can reflect the actual traffic running state better, effectively improves the model precision, fully considers the influence of heterogeneous bicycle traffic flow on the vehicles turning right in advance, makes up the deficiency of the previous method on the consideration of heterogeneous bicycle traffic parameters, and has stronger reliability of the model calculation result.
Description
Technical Field
The invention relates to the technical field of traffic, in particular to a method for calculating the traffic capacity of a vehicle turning right in advance for non-forced priority mixed traffic travel.
Background
The phenomenon of mixed traffic trip of motor vehicles and bicycles is an important traffic trip characteristic in China, the analysis of the mixed traffic trip characteristic is an important basis of a refined and scientific traffic organization optimization scheme, the conflict between right-turning motor vehicles and passing self-propelled vehicles at an urban road intersection is an important reason causing urban traffic jam and safety challenge, the separation of the right-turning vehicles by means of a right-turning diversion island in advance becomes a traffic organization means generally adopted at the intersection, and the key of the right-turning vehicle traffic organization by means of the means is to calculate the traffic capacity of the right-turning motor vehicles in advance;
the existing method for calculating the traffic capacity of the advanced right-turn vehicle generally assumes that bicycles enjoy priority traffic right and cannot describe the influence of the parallel running of the bicycles on the right-turn vehicle, and is oriented to the method for calculating the traffic capacity of the advanced right-turn vehicle for non-mandatory priority mixed traffic travel;
in order to meet the challenge and increase engineering operability, a hybrid bicycle traffic wave calculation method based on space perception is disclosed in patent document with application publication number CN109243174A, and the method is based on a space perception hybrid traffic flow model, analyzes space ratios in different hybrid bicycle traffic states and determines the density and flow rate of the hybrid bicycles;
on the basis of the method, the non-mandatory prior traffic behavior of the motor vehicles turning right in advance under the traffic environment of the hybrid bicycles is fully considered, a right-turn traffic capacity calculation model with higher precision is established, theoretical support is provided for traffic canalization design and signal timing parameter optimization of intersections, and the limitation that the conventional right-turn traffic capacity calculation model is insufficient in consideration of the non-mandatory prior traffic characteristics and the flow of the hybrid bicycles is overcome.
Disclosure of Invention
The invention aims to provide a method for calculating the traffic capacity of a vehicle turning right in advance for non-forced priority mixed transportation travel, which aims to solve the existing problems that: the non-forced prior traffic behavior of the motor vehicle turning right in advance in the traffic environment of the hybrid bicycle cannot be fully considered, and the construction of the right-turning traffic capacity calculation model is not precise enough.
In order to achieve the purpose, the invention provides the following technical scheme: a method for calculating the traffic capacity of a vehicle turning right in advance for non-forced priority mixed transportation travel comprises the following specific steps:
step 1: establishing a relational expression of the bicycle flow and the speed of the motor vehicle turning right in advance;
v is the running speed of the motor vehicle turning right in advance, t is the running time of the motor vehicle turning right in advance, dV/dt is the derivative of the speed V of the motor vehicle turning right in advance to the running time t, q is the bicycle flow, andfor average speed of the bicycle, Ce、ke、Cs、Cp、ksIs a constant to be solved in the relational expression;
step 2: solving the coefficient of the expression of the relationship between the bicycle flow and the speed of the motor vehicle turning right in advance according to the existing model
And step 3: calculating the number of vehicles which pass through a conflict area by the motor vehicles turning right in advance in the unsaturated traffic state;
Q=3600/ts=3600V/(lc+lb)
said t issFor the purpose of advancing the right-turn of the motor vehicle in the unsaturated traffic state to pass through the conflictHeadway of a zone, saidcTo advance the length of the right turn collision zone, the lbThe length of the right-turn vehicle is advanced;
and 4, step 4: calculating the traffic capacity of the motor vehicle turning right in advance:
said QmWhen the bicycle flow is 0, the maximum value of the number of vehicles passing through the conflict area by the motor vehicle turning right in advance in the unsaturated traffic state is C0To advance the saturation flow rate of the right turn vehicle.
The step 1 comprises four steps:
the first step is as follows: the existing method obtains the perceived density k of the hybrid bicycle based on spatial perception:
the perception density k can be calculated by a hybrid bicycle traffic wave calculation method based on space perception, which is published by the application number CN 109243174A;
secondly, obtaining a parameter C by fitting the relation of 1/V and kp;
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is based on the microcosmic driving force model of the right-turning vehicle with safe driving force and efficient driving force, fully describes the characteristic of non-forced preferential passing of the right-turning motor vehicle when passing through the bicycle flow in advance, can better reflect the actual traffic running state and effectively improves the model precision;
2. the method fully considers the influence of heterogeneous bicycle traffic flow on the motor vehicles turning right in advance, overcomes the defect of the conventional method for considering heterogeneous bicycle traffic parameters, and has stronger reliability of model calculation results.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic view of data acquisition points of a test area;
FIG. 3 is a schematic diagram showing comparison between different model calculation values and observation results for point A;
FIG. 4 is a schematic diagram showing comparison between different model calculation values and observation results for point B;
FIG. 5 is a schematic diagram of the bicycle of the present invention for advancing a right turn vehicle to traverse a bicycle collision zone.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The first embodiment is as follows:
as shown in fig. 1-4:
a method for calculating the traffic capacity of a vehicle turning right in advance for non-forced priority mixed transportation travel comprises the following specific steps:
step 1: establishing a relational expression of the bicycle flow and the speed of the motor vehicle turning right in advance;
said V being of a motor vehicle turning right in advanceThe running speed, t is the running time of the vehicle turning right ahead, dV/dt is the derivative of the speed V of the vehicle turning right ahead to the running time t, q is the bicycle flow, andfor average speed of the bicycle, Ce、ke、Cs、Cp、ksIs a constant to be solved in the relational expression;
step 2: solving the coefficient of the expression of the relationship between the bicycle flow and the speed of the motor vehicle turning right in advance according to the existing model
And step 3: calculating the number of vehicles which pass through a conflict area by the motor vehicles turning right in advance in the unsaturated traffic state;
Q=3600/ts=3600V/(lc+lb)
said t issThe time headway that the right-turning motor vehicle passes through the conflict area in advance under the unsaturated traffic state is represented by lcTo advance the length of the right turn collision zone, the lbThe length of the right-turn vehicle is advanced;
and 4, step 4: calculating the traffic capacity of the motor vehicle turning right in advance:
said QmWhen the bicycle flow is 0, the maximum value of the number of vehicles passing through the conflict area by the motor vehicle turning right in advance in the unsaturated traffic state is C0To advance the saturation flow rate of the right turn vehicle.
The step 1 is realized by the following four steps:
the first step is as follows: the existing method obtains the perception density k of the hybrid bicycle based on space perception;
the perception density k can be calculated by a hybrid bicycle traffic wave calculation method based on space perception, which is published by the application number CN 109243174A;
secondly, obtaining a parameter C by fitting the relation of 1/V and kp;
Example two:
in the embodiment, the field investigation data of intersections between the north road of the city of the round city of Kunming, Yunnan province and the Beijing road are further selected to verify the prediction method.
Obtaining a data acquisition point location schematic of the test area according to FIG. 2;
the results of the verification are shown in table 1 by calculating the mean percent of traffic flow (MAPE) data analysis results, applied to the MAPE calculation formula as follows:
model precision comparison of different advance right-turn motor vehicle traffic capacity
The result shows that compared with the VISSIM simulation model, the HCM2010 model and the gap insertion model, the MAPE of the calculated value and the actual value of the traffic capacity of the right-turn car in advance is minimum, the accuracy is highest, the advantages are obvious in the traffic state (the flow of the bicycle is more than 1900bic/h/m) with large flow, and the superiority of the method is fully verified.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (5)
1. The method for calculating the traffic capacity of the vehicle turning right in advance for the non-forced priority mixed transportation travel comprises the following steps: the method comprises the following specific steps:
step 1: establishing a relational expression of the bicycle flow and the speed of the motor vehicle turning right in advance;
step 2: according to the existing model, solving the coefficient of the relational expression of the bicycle flow and the motor vehicle speed which turns right in advance;
and step 3: calculating the number of vehicles which pass through a conflict area by the motor vehicles turning right in advance in the unsaturated traffic state;
and 4, step 4: and calculating the traffic capacity of the motor vehicle turning right in advance.
2. The method for calculating the traffic capacity of the advanced right-turn vehicle for the non-forced priority mixed transportation according to claim 1, wherein the method comprises the following steps: the expression in the step 1 is as follows:
v is the running speed of the motor vehicle turning right in advance, t is the running time of the motor vehicle turning right in advance, dV/dt is the derivative of the speed V of the motor vehicle turning right in advance to the running time t, q is the bicycle flow, andfor average speed of the bicycle, Ce、ke、Cs、Cp、ksIs a constant to be solved in the relational expression.
3. The method for calculating the traffic capacity of the advanced right-turn vehicle facing the non-forced priority mixed transportation according to claim 2, wherein the method comprises the following steps: the step 1 comprises the following steps:
the first step is that: calculating the perception density k of the hybrid bicycle based on space perception;
secondly, the following steps: obtaining the parameter C by fitting the relation of 1/V and kp;
4. The method for calculating the traffic capacity of the advanced right-turn vehicle for the non-forced priority mixed transportation according to claim 1, wherein the method comprises the following steps: the calculation formula of the step 3 is as follows:
Q=3600/ts=3600V/(lc+lb)
said t issThe time headway that the right-turning motor vehicle passes through the conflict area in advance under the unsaturated traffic state is represented by lcTo advance the length of the right turn collision zone, the lbTo advance the length of the right-hand vehicle.
5. The method for calculating the traffic capacity of the advanced right-turn vehicle facing the non-forced priority mixed transportation according to claim 3, wherein the method comprises the following steps: the calculation formula of the step four is as follows:
said QmWhen the bicycle flow is 0, the maximum value of the number of vehicles passing through the conflict area by the motor vehicle turning right in advance in the unsaturated traffic state is C0To advance the saturation flow rate of the right turn vehicle.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111026497.0A CN113918869B (en) | 2021-09-02 | 2021-09-02 | Advanced right-turn vehicle traffic capacity calculation method for non-forced priority mixed traffic travel |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202111026497.0A CN113918869B (en) | 2021-09-02 | 2021-09-02 | Advanced right-turn vehicle traffic capacity calculation method for non-forced priority mixed traffic travel |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113918869A true CN113918869A (en) | 2022-01-11 |
CN113918869B CN113918869B (en) | 2024-04-02 |
Family
ID=79233793
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202111026497.0A Active CN113918869B (en) | 2021-09-02 | 2021-09-02 | Advanced right-turn vehicle traffic capacity calculation method for non-forced priority mixed traffic travel |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113918869B (en) |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101246514A (en) * | 2008-03-20 | 2008-08-20 | 天津市市政工程设计研究院 | City fast road intercommunicated overpass simulation design system and method for establishing design model |
CN105374216A (en) * | 2014-08-06 | 2016-03-02 | 王大海 | Signal control method, system and equipment for making vehicles almost not stop in waiting zone |
CN106548633A (en) * | 2016-10-20 | 2017-03-29 | 中国科学院深圳先进技术研究院 | A kind of variable guided vehicle road control method of road network tide flow stream |
CN108492562A (en) * | 2018-04-12 | 2018-09-04 | 连云港杰瑞电子有限公司 | Intersection vehicles trajectory reconstruction method based on fixed point detection with the alert data fusion of electricity |
CN109559504A (en) * | 2018-09-02 | 2019-04-02 | 吉林大学 | Signalized intersections electric bicycle opens the determination method of bright time in advance |
CN112185101A (en) * | 2019-07-01 | 2021-01-05 | 王大海 | Optimal control system simplification and numerical simulation capable of passing through waiting area without stopping |
CN113327436A (en) * | 2021-01-18 | 2021-08-31 | 兆边(上海)科技有限公司 | Main line coordination control optimization method based on track data |
-
2021
- 2021-09-02 CN CN202111026497.0A patent/CN113918869B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101246514A (en) * | 2008-03-20 | 2008-08-20 | 天津市市政工程设计研究院 | City fast road intercommunicated overpass simulation design system and method for establishing design model |
CN105374216A (en) * | 2014-08-06 | 2016-03-02 | 王大海 | Signal control method, system and equipment for making vehicles almost not stop in waiting zone |
CN106548633A (en) * | 2016-10-20 | 2017-03-29 | 中国科学院深圳先进技术研究院 | A kind of variable guided vehicle road control method of road network tide flow stream |
WO2018072240A1 (en) * | 2016-10-20 | 2018-04-26 | 中国科学院深圳先进技术研究院 | Direction-variable lane control method for tidal traffic flow on road network |
CN108492562A (en) * | 2018-04-12 | 2018-09-04 | 连云港杰瑞电子有限公司 | Intersection vehicles trajectory reconstruction method based on fixed point detection with the alert data fusion of electricity |
CN109559504A (en) * | 2018-09-02 | 2019-04-02 | 吉林大学 | Signalized intersections electric bicycle opens the determination method of bright time in advance |
CN112185101A (en) * | 2019-07-01 | 2021-01-05 | 王大海 | Optimal control system simplification and numerical simulation capable of passing through waiting area without stopping |
CN113327436A (en) * | 2021-01-18 | 2021-08-31 | 兆边(上海)科技有限公司 | Main line coordination control optimization method based on track data |
Non-Patent Citations (3)
Title |
---|
LI BING等: "capacity estimation of advance right-turn motor vehicles considering nonstrict priority crossing behaviors under mixed-traffic conditions", JOURNAL OF TRANSPORTATION ENGINEERING, 9 December 2021 (2021-12-09), pages 1 - 10 * |
曲昭伟;罗瑞琪;陈永恒;曹宁博;邓晓磊;汪昆维;: "信号交叉口右转机动车轨迹特性", 浙江大学学报(工学版), vol. 52, no. 02, 15 February 2018 (2018-02-15), pages 341 - 351 * |
梁丽娟: "路侧公交专用车道下借道右转出口交织长度研究", 中国优秀硕士学位论文全文数据库工程科技II辑, no. 6, 15 June 2020 (2020-06-15), pages 034 - 829 * |
Also Published As
Publication number | Publication date |
---|---|
CN113918869B (en) | 2024-04-02 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113781806B (en) | Mixed traffic flow passing method used in intelligent network connection environment | |
Zhao et al. | Cellular automata model for traffic flow at intersections in internet of vehicles | |
CN103208191B (en) | The optimization method of signal coordinated control under a kind of urban road intersection supersaturated condition | |
Toledo et al. | Modeling traffic through a sequence of traffic lights | |
Li et al. | Traffic energy and emission reductions at signalized intersections: a study of the benefits of advanced driver information | |
CN107016858B (en) | Pre-signal control method for intersection multi-flow direction waiting area and dislocation type stop line | |
CN102433811A (en) | Method for determining minimum distance of road intersections in harbor district | |
CN109523808B (en) | Channelized optimization method for left-turn displacement intersection | |
CN106781435A (en) | A kind of Fei Xinkong intersections platooning passing method based on radio communication | |
CN110472271A (en) | A kind of non-motorized lane Mixed contact construction method of microscopic traffic simulation | |
CN102359043A (en) | Method for determining passageway distance of port road on the basis of two-dimensional cellular automaton model | |
CN109131349B (en) | Method for inhibiting road traffic ghost from being blocked | |
CN110021192A (en) | Deviation alarm method, intelligent alarm device and vehicle | |
CN113918869A (en) | Method for calculating traffic capacity of right-turn vehicle in advance for non-forced priority mixed transportation travel | |
CN110217274A (en) | A kind of determination method and device in vehicle coasting section | |
Ma et al. | An extended car-following model accounting for average optimal velocity difference and backward-looking effect based on the Internet of Vehicles environment | |
CN105109487B (en) | A kind of vehicle efficient operation speed optimization method | |
Liu et al. | A refined and dynamic cellular automaton model for pedestrian–vehicle mixed traffic flow | |
CN112373482B (en) | Driving habit modeling method based on driving simulator | |
CN105185129A (en) | Road signal lamp arrangement | |
Ou et al. | Modeling electric bicycle’s abnormal behavior at a signalized intersection | |
CN114239272A (en) | Hybrid bicycle flow microscopic modeling method and device based on retrograde behavior | |
CN108053660A (en) | A kind of control method of reduction vehicle exhaust CO2 emission towards traffic flow | |
CN115223347A (en) | Early warning for red light running of vehicle and vehicle speed control method | |
CN109559000A (en) | A kind of vehicle platoon travel control method and management platform |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |