CN106991817B - Method for determining traffic capacity of road sections of multi-level road network - Google Patents

Method for determining traffic capacity of road sections of multi-level road network Download PDF

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CN106991817B
CN106991817B CN201710368945.2A CN201710368945A CN106991817B CN 106991817 B CN106991817 B CN 106991817B CN 201710368945 A CN201710368945 A CN 201710368945A CN 106991817 B CN106991817 B CN 106991817B
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road
vehicle
traffic
density
capacity
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CN106991817A (en
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韩直
岳海亮
余晓南
朱湧
陈晓利
付立家
杨桪
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China Merchants Chongqing Communications Research and Design Institute Co Ltd
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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
    • G08G1/0125—Traffic data processing

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Abstract

The invention provides a multi-stage circuitThe method for determining the traffic capacity of the network section comprises the following steps: s1, acquiring a road distribution condition in a road network, comprising the following steps: dividing a road network into m road sections, expressing a road section set by X, dividing a jth road section xj into n slope sections, expressing a slope section set by Y, expressing a slope length set by Z, S2, respectively calculating the road section capacity Qj when the jth road section achieves the maximum efficacy, S3, calculating the capacity Q of the whole road network according to the road section capacity Qj:
Figure DDA0001302194120000011
by the method and the device, the traffic capacity of the multi-level road network can be accurately calculated, an accurate result can be obtained, and the application range can be enlarged.

Description

Method for determining traffic capacity of road sections of multi-level road network
Technical Field
The invention relates to a traffic analysis method, in particular to a method for determining traffic capacity of road sections of a multi-level road network.
Background
In the traffic field, traffic capacity of a road network is one of key elements for analyzing road network balance and traffic coordination, in the prior art, a method for determining the traffic capacity of the road network comprises a space-time consumption method, a linear programming method, a cut-set method, a traffic distribution simulation method, a supply analysis method, a narrow-sense road network capacity analysis method and the like, but the conventional method is generally based on a theoretical model, has small limitation and application range, and the final analysis result is inaccurate.
Therefore, in order to solve the above technical problems, it is necessary to provide a new method.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method for determining traffic capacity of a road segment of a multi-level road network, which can accurately calculate the traffic capacity of the multi-level road network and obtain an accurate result, and can improve a use range.
The invention provides a method for determining the traffic capacity of a road section of a multi-level road network, which comprises the following steps:
s1, acquiring a road distribution condition in a road network, comprising the following steps:
dividing a road network into m road segments, and representing a road segment set by X, wherein X is (X1, X2, …, xj, … xm), and j is 1,2, …, m, and the road network is divided according to different design speeds;
dividing the j-th road segment xj into n slope segments, wherein Y represents a slope segment set, and Z represents a slope length set, wherein Y is (Y1, Y2, …, yk, … yn), Z is (Z1, Z2, …, zk, … zn), and k is 1,2, …, n;
s2, respectively calculating the road section capacity Qj when each j road section achieves the maximum efficacy, wherein:
Figure BDA0001302194100000021
wherein the content of the first and second substances,
Figure BDA0001302194100000022
representing the optimal vehicle density of each k-th slope section when the road is at the maximum efficacy;
s3, calculating the capacity Q of the whole road network according to the road section capacity Qj:
Figure BDA0001302194100000023
further, in step S2, the optimum vehicle density is determined by the following method
S21, establishing a first traffic efficiency model:
Figure BDA0001302194100000025
k is derived for both sides of the equation of the first traffic performance model:
Figure BDA0001302194100000026
when in use
Figure BDA0001302194100000027
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure BDA0001302194100000028
where kj is the blocking density, v fα and β are the weights of the traffic density and the interval average speed in the traffic flow respectively, which are the free flow speed;
s22, establishing a second traffic efficiency model:
and respectively deriving k from two ends of the equation of the second traffic efficiency model:
Figure BDA00013021941000000210
when in use
Figure BDA00013021941000000211
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure BDA0001302194100000031
where kj is the blocking density, v fFor free flow velocity, k mDensity at maximum flow;
s23, forming a value range according to the density values k obtained by the first traffic efficiency model and the second traffic efficiency model, namely
Figure BDA0001302194100000032
Taking values within the value range, namely:
Figure BDA0001302194100000033
further, the blocking density kj is determined by:
s210, road parameters including the friction coefficient phi of the jth road section are obtained jAverage vehicle length
Figure BDA0001302194100000034
The speed of the tracking vehicle is V2, the speed of the leading vehicle is V1, the minimum distance between the front end and the tail end of the leading vehicle when the tracking vehicle stops, and the gradient Sj of the j section;
s211, establishing a minimum vehicle tail space model of the tracking vehicle and the front vehicle under the condition that the tracking vehicle does not collide with the front vehicle, and calculating the minimum vehicle tail space d of the tracking vehicle and the front vehicle according to road parameters, wherein:
Figure BDA0001302194100000035
wherein tr is the response time of the tracking vehicle;
s213, calculating the blocking density kj according to the following formula:
Figure BDA0001302194100000036
further, in step S210, the average vehicle length is acquired by the following method
Figure BDA0001302194100000037
Acquiring the vehicle type c of the j section and the length l of the q type vehicle qAnd the proportion p of the qth vehicle to the total traffic volume of the jth road section qAnd calculating the average vehicle length according to the following formula
Figure BDA0001302194100000041
Figure BDA0001302194100000042
The invention has the beneficial effects that: according to the invention, the attributes of the road network and the attributes of the vehicles are fully considered in the analysis process of the traffic capacity of the multilevel road network, so that the accuracy of the final calculation result of the traffic capacity can be effectively ensured, and the road network is subjected to corresponding segmentation processing in the analysis process, so that the adaptability of the method is effectively improved, the limitations of the existing method are effectively removed, and accurate data support can be provided for traffic management.
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The invention is further described below with reference to the following figures and examples:
FIG. 1 is a flow chart of the present invention.
Detailed Description
Fig. 1 is a flowchart of the present invention, and as shown in the figure, the method for determining traffic capacity of a multi-level road network section provided by the present invention includes the following steps:
s1, acquiring a road distribution condition in a road network, comprising the following steps:
dividing a road network into m road segments, and representing a road segment set by X, wherein X is (X1, X2, …, xj, … xm), and j is 1,2, …, m, and the road network is divided according to different design speeds;
dividing the j-th road segment xj into n slope segments, wherein Y represents a slope segment set, and Z represents a slope length set, wherein Y is (Y1, Y2, …, yk, … yn), Z is (Z1, Z2, …, zk, … zn), and k is 1,2, …, n;
s2, respectively calculating the road section capacity Qj when each j road section achieves the maximum efficacy, wherein:
Figure BDA0001302194100000043
wherein the content of the first and second substances,
Figure BDA0001302194100000044
representing the optimal vehicle density of each k-th slope section when the road is at the maximum efficacy;
s3, calculating the capacity Q of the whole road network according to the road section capacity Qj:
Figure BDA0001302194100000051
by the invention, the analysis process of the traffic capacity of the multi-level road networkThe method fully considers the self attributes (namely the grade, the gradient and the friction coefficient of the road) of the road network and the attributes of the vehicles, analyzes from the practical angle of the road network, thereby effectively ensuring the accuracy of the final calculation result of the traffic capacity, and performs corresponding segmentation processing on the road network in the analysis process, thereby effectively improving the adaptability of the method, being particularly suitable for the complicated traffic capacity analysis of the road network, effectively removing the limitation of the existing method, and providing accurate data support for traffic management.
In the present embodiment, in step S2, the optimum vehicle density is determined by the following method
Figure BDA0001302194100000052
S21, establishing a first traffic efficiency model:
k is derived for both sides of the equation of the first traffic performance model:
Figure BDA0001302194100000054
when in use
Figure BDA0001302194100000055
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure BDA0001302194100000056
where kj is the blocking density, v fα and β are the weights of the traffic density and the interval average speed in the traffic flow respectively, which are the free flow speed;
s22, establishing a second traffic efficiency model:
Figure BDA0001302194100000057
and respectively deriving k from two ends of the equation of the second traffic efficiency model:
Figure BDA0001302194100000058
when in use
Figure BDA0001302194100000059
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure BDA0001302194100000061
where kj is the blocking density, v fFor free-flow speed, i.e. design speed, k, under different road grade conditions mDensity at maximum flow;
s23, forming a value range according to the density values k obtained by the first traffic efficiency model and the second traffic efficiency model, namely
Figure BDA0001302194100000062
Taking values within the value range, namely:
Figure BDA0001302194100000063
wherein the optimal density value of the ith road section is
Figure BDA0001302194100000064
α and β are the weight occupied by the traffic density k and the interval average vehicle speed v in the traffic flow, if the weight of the average vehicle speed is large, the weight of the traffic density is reduced, and if the weight of the average vehicle speed is small, the weight of the traffic density is increased.
In this embodiment, the blocking density kj is determined by the following method:
s210, road parameters including the friction coefficient phi of the jth road section are obtained jAverage vehicle length
Figure BDA0001302194100000065
The speed of the tracking vehicle is V2, the speed of the leading vehicle is V1, the minimum distance between the front end and the tail end of the leading vehicle when the tracking vehicle stops, and the gradient Sj of the j section;
s211, establishing a minimum vehicle tail space model of the tracking vehicle and the front vehicle under the condition that the tracking vehicle does not collide with the front vehicle, and calculating the minimum vehicle tail space d of the tracking vehicle and the front vehicle according to road parameters, wherein:
Figure BDA0001302194100000066
wherein tr is the response time of the tracking vehicle;
s213, calculating the blocking density kj according to the following formula:
Figure BDA0001302194100000071
by the method, the traffic jam density can be accurately determined, and the accuracy of the result is facilitated.
In the present embodiment, in step S210, the average vehicle length is obtained by the following method
Figure BDA0001302194100000072
Acquiring the vehicle type c of the j section and the length l of the q type vehicle qAnd the proportion p of the qth vehicle to the total traffic volume of the jth road section qAnd calculating the average vehicle length according to the following formula
Figure BDA0001302194100000073
By the method, the average vehicle length can be calculated quickly and accurately, and guarantee is provided for subsequent calculation.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.

Claims (3)

1. A method for determining the traffic capacity of road sections of a multi-level road network is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring a road distribution condition in a road network, comprising the following steps:
dividing a road network into m road segments, and representing a road segment set by X, wherein X is (X1, X2, …, xj, … xm), and j is 1,2, …, m, and the road network is divided according to different design speeds;
dividing the j-th road segment xj into n slope segments, wherein Y represents a slope segment set, and Z represents a slope length set, wherein Y is (Y1, Y2, …, yk, … yn), Z is (Z1, Z2, …, zk, … zn), and k is 1,2, …, n;
s2, respectively calculating the road section capacity Q when the jth road section achieves the maximum efficacy jWherein:
Figure FDA0002112742280000011
wherein the content of the first and second substances, represents the optimal vehicle density for the kth slope segment when the road is at maximum efficacy;
determining an optimal vehicle density by
Figure FDA0002112742280000013
S21, establishing a first traffic efficiency model:
k is derived for both sides of the equation of the first traffic performance model:
Figure FDA0002112742280000015
when in use
Figure FDA0002112742280000016
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure FDA0002112742280000017
wherein k is jTo block density, v fα and β are the weights of the traffic density and the interval average speed in the traffic flow respectively, which are the free flow speed;
s22, establishing a second traffic efficiency model:
Figure FDA0002112742280000018
and respectively deriving k from two ends of the equation of the second traffic efficiency model:
Figure FDA0002112742280000021
when in use
Figure FDA0002112742280000022
The traffic efficiency of the road is the maximum, and at the moment, the following results can be obtained:
Figure FDA0002112742280000023
wherein k is jTo block density, v fFor free flow velocity, k mDensity at maximum flow;
s23, forming a value range according to the density values k obtained by the first traffic efficiency model and the second traffic efficiency model, namely Taking values within the value range, namely:
Figure FDA0002112742280000026
s3, according to the road section capacity Q jCalculating the capacity Q of the whole road network:
Figure FDA0002112742280000027
2. the method for determining the traffic capacity of a road segment of a multi-level road network according to claim 1, wherein: the blocking density k is determined by j：
S210, road parameters including the friction coefficient phi of the jth road section are obtained jAverage vehicle length
Figure FDA0002112742280000028
Tracking vehicle speed v 2Speed v of the leading vehicle 1The minimum distance between the head and the tail of the front vehicle when the tracking vehicle stops and the gradient Sj of the jth road section;
s211, establishing a minimum vehicle tail space model of the tracking vehicle and the front vehicle under the condition that the tracking vehicle does not collide with the front vehicle, and calculating the minimum vehicle tail space d of the tracking vehicle and the front vehicle according to road parameters, wherein:
Figure FDA0002112742280000029
wherein, t rTo track vehicle response times;
s212, calculating the blocking density k according to the following formula j：
Figure FDA0002112742280000031
3. The method of determining traffic capacity of road segments of multi-level road network according to claim 2, characterized in that: in step S210, the average vehicle length is acquired by the following method
Figure FDA0002112742280000032
Acquiring the vehicle type c of the j section and the length l of the q type vehicle qAnd the proportion p of the qth vehicle to the total traffic volume of the jth road section qAnd calculating the average vehicle length according to the following formula
Figure FDA0002112742280000033
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