CN114862011A - Road section time-interval traffic demand estimation method considering congestion state - Google Patents
Road section time-interval traffic demand estimation method considering congestion state Download PDFInfo
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Abstract
The invention provides a road section time-interval traffic demand estimation method considering a congestion state, aiming at the characteristic that real road section traffic demands can reach a detection section after being delayed when a road is in the congestion state, section detection data and floating car data are combined, the corresponding relation between each traffic demand analysis time interval boundary moment and each traffic flow detection time interval boundary moment is determined, the traffic flow detection time interval corresponding to each analysis time interval is determined, and the road section time-interval traffic demand estimation method considering the congestion state is established, so that the accuracy of traffic demand calculation of each time interval is improved.
Description
Technical Field
The invention belongs to the technical field of traffic demand estimation methods, and particularly relates to a road section time-interval traffic demand estimation method considering a congestion state.
Background
The traffic demand of the road section is basic data of the work of each stage of road traffic planning, design, control and management. For the built road, the cross-section traffic flow can be detected by devices such as an induction coil, a radar and a video gate. In the past, the detected section traffic flow in each time period is generally equal to the section traffic demand in each time period. However, when the road is in a crowded state, a part of real section traffic demands reach the detection section after a delay due to the road congestion, the traffic demands obtained by the section traffic flow detection in the period are smaller than the real traffic demands, and the traffic demands obtained by the traffic flow detection in the period later are larger than the real traffic demands.
Aiming at the estimation error caused by directly using the detected section traffic flow as the section traffic demand under the crowded state of the road, no specific coping method is seen, and no invention patent of the method is searched.
The document retrieval of the prior art finds that the road section traffic demand estimation method mainly comprises the following steps:
1. traffic demand forecasting based on land use. In the traffic planning stage, the traffic demand is predicted mainly by investigating and analyzing the existing traffic system and the land utilization condition, so that the traffic demand of the road section can be obtained. The traffic demand prediction method comprises four stages of traffic generation, traffic distribution, mode division and traffic distribution. Representative works include urban traffic planning, Chicago Area transfer Study.
2. And estimating the traffic demand based on the road section traffic flow detection. For the constructed road, the actual traffic flow of the section of the road can be detected through equipment such as an induction coil, a radar, a video bayonet and the like, and the detected traffic flow of the section of each time interval is equal to the traffic demand of the section of each time interval. Representative works include traffic investigations and analyses.
3. On the basis of the method 2, the detection error of detection equipment is further considered, the section traffic flow is corrected, and running parameters such as road traffic capacity, travel time, queuing length and the like are analyzed on the basis. Representative works include research on methods for estimating traffic demands of road segments under congestion conditions, research on estimating traffic demands of urban road intersections based on dynamic data, analysis and application of traffic demands of urban expressway based on data driving, and the like.
4. Traffic demand estimation based on mobile data such as cell phone signaling. Based on mobile data such as mobile phone signaling, information including road speed, traffic flow, crowding degree and the like is obtained according to trip information of a traveler. Representative results include a method and a system for acquiring traffic condition information based on mobile phone signaling data (patent No. ZL201810474891.2) and a model for acquiring intersection traffic flow and flow direction information by using mobile phone signaling and checkpoint data (patent application No. CN 201910757345.4).
The method 1 aims at the traffic demand prediction in the planning stage, and does not relate to the actual time-interval traffic demand estimation aiming at the current situation.
The method 2 is a traditional method for estimating the traffic demand of the section of the road, however, obvious errors exist in the road in a crowded state, and the actually detected traffic flow of the section in a certain period of time is smaller than the real traffic demand of the section.
The method 3 is to correct the error of the detection equipment on the basis of the method 2, and has no improvement effect on the calculation error of the traffic demand of the road section in the crowded state in the method 2.
Method 4 is to use mobile data, which is different from the data source used in method 2, but the processing method of detecting the section traffic flow of each time interval to be equal to the section traffic demand of each time interval is not changed, so that the calculation error of the road section traffic demand under the crowded state similar to method 2 also exists.
However, when the traffic demand of the section in each time interval is calculated by using detection data, a corresponding processing method is not provided aiming at the characteristic that the real traffic demand reaches the detection section after being delayed due to road congestion in a congestion state. This results in errors in the calculation of the traffic demand, and traffic flow detection data in a congested period will be smaller than the actual traffic demand, and traffic flow detection data in a later period will be larger than the actual traffic demand. Therefore, the prior art lacks an estimation method for the traffic demand of the road section in the crowded state in time intervals.
Disclosure of Invention
The invention aims to solve the problems and provides a road section time-sharing traffic demand estimation method considering the congestion state. The method aims at the characteristic that real traffic demands can reach a detection section in a delayed manner due to road congestion in a congestion state, section detection data and floating car data are combined, and the traffic demands are calculated by determining traffic flow detection time periods corresponding to analysis time periods.
The technical scheme of the invention is as follows:
referring to fig. 1, a method for estimating a traffic demand of a road section in time intervals considering a congestion state calculates the traffic demand of each time interval by sequentially performing the following 7 steps.
Step 1: the analysis period is divided. Determining a total analysis time [ t ] for a target road section b ,t e ]And it is divided into I periods, denoted as T 1 ,T 2 ,...,T i ,...,T I . Two successive analysis periods T i And T i+1 Is defined as t i(i+1) 。
Step 2: an analysis range is set. The analysis section is denoted by X c Section, setting L meters at the upstream of the analysis section as analysis boundary and recording as X l Cross section, then analysis range is X l To X c Section, wherein the distance L should be greater than the queue length at the analysis section.
And step 3: the freestream vehicle speed is determined. Fitting a traffic flow-density curve by using section detection historical data so as to calculate the speed v of the free flow of the road f (ii) a The form of the curve of the traffic flow-density can adopt a triangle, and three basic parameters needing fittingIncluding road traffic capacity q 0 Optimum density k 0 And plug density k j (ii) a Then the free stream vehicle speed v f Can be calculated from the formula (1).
And 4, step 4: calculating the speed of each floating vehicle reaching the road section X according to the free flow c The time of day. At analysis time [ t b ,t e ]Will pass through the cross section X c And X l All the floating cars are numbered according to the time sequence and are marked as the floating cars 1,2, a. For any floating car n, the passing section X thereof can be obtained l At time t ln And through section X c At time t cn (ii) a So that it can be calculated by equation (2) to reach section X at the free stream vehicle speed c Time of day of
And 5: determining the closest before and after each dividing moment
Demarcation time t for any two analysis periods i(i+1) Searching in the order of the vehicle number n from small to large
Find the two moments before and after the closest moment
And
that is to say that the temperature of the molten steel,
and
satisfies the formula (3).
Step 6: determining traffic demand points t i(i+1) And analyzing the traffic flow corresponding to the boundary time to detect the boundary time. Determined by step 5
And
a vehicle k can be obtained i(i+1) And (k +1) i(i+1) Through section X c Time of day of
And
i.e. the traffic demand analysis demarcation time t i(i+1) Corresponding traffic flow detection boundary time t ci(i+1) Should be in
Within a time period; further suppose that
The traffic state does not change in the short time period, and the traffic demand analysis demarcation moment t can be determined according to the formula (4) i(i+1) Corresponding traffic flow detection boundary time t ci(i+1) 。
And 7: output eachAnd analyzing the traffic demand of the time period. For an arbitrary analysis period T i Traffic demand D i Is [ t ] c(i-1)i ,t ci(i+1) ]Section X in time period c Detected traffic flow
Wherein t is when i ═ 1 c(i-1)i ＝t b When i is 1, t ci(i+1) ＝t e I.e. Q i Can be determined by equation (5).
The key point of accurately estimating the traffic demand of the road section in the crowded state is to determine the corresponding relation between the dividing time of each traffic demand analysis time interval and the dividing time of the traffic flow detection time interval. The prior art has the defect that the two are equal in sign. In the calculation process, the condition that the actual traffic demand reaches the detection section after delay in the crowded state is fully considered, and a corresponding relation model of the actual traffic demand and the detection section is established based on a traffic flow theory, so that the accuracy of the traffic demand calculation in each period is improved.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention provides a road section time-interval traffic demand estimation method considering a congestion state, which is applicable to time-interval traffic demand estimation under the congestion and non-congestion states of a road.
2. The method provided by the invention considers the characteristic that the actual traffic demand reaches the detection section after delay in a crowded state, and establishes the corresponding relation between the time interval boundary time of each traffic demand analysis period and the time interval boundary time of traffic flow detection.
Drawings
FIG. 1 is a schematic diagram of the main timing parameters of the present invention;
fig. 2 is a schematic view of road geometry in embodiment 1 of the present invention.
Detailed Description
A traffic demand estimation method of a road section considering a congestion state according to the present invention will be described in more detail with reference to the schematic drawings, in which preferred embodiments of the present invention are shown, it being understood that those skilled in the art can modify the present invention described herein while still achieving the advantageous effects of the present invention, and therefore, the following description should be construed as being widely known to those skilled in the art and not as limiting the present invention.
The invention will be further described with reference to the embodiment shown in fig. 2.
Example 1:
the road geometry in embodiment 1 of the present invention is shown in fig. 2, where the section from X-0 m to X-1040 m is three lanes, the section from X-1040 m to X-1100 m is gradually transited to two lanes, and the target section for traffic demand estimation is located at X c Position 940 m. The traffic flow X is 0m on the incoming road segment, the flow is as shown in table 1, 10% of the vehicles in the incoming traffic flow are floating cars, and the vehicle with the vehicle number of 1 is set as a floating car. A cross section traffic flow detector is arranged at X c At 940m, the position information of the floating vehicle at each moment can be acquired. The traffic flow simulation in example 1 was performed by the Vissim simulation software, and the free flow speed was set to 60 km/h. It is now necessary to estimate the traffic demand every 600s target section within 400s to 5200 s.
| Time period(s) | Input traffic flow (veh/h) |
| 0-400 | 2000 |
| 400-1000 | 2000 |
| 1000-1600 | 4500 |
| 1600-2200 | 2000 |
| 2200-2800 | 4500 |
| 2800-3400 | 2000 |
| 3400-4000 | 4500 |
| 4000-4600 | 2000 |
| 4600-5200 | 2000 |
TABLE 1
The method of the invention is adopted to the road X c The cross section traffic demand is estimated, and the specific process is briefly described as follows:
step 1: the analysis period is divided. Estimating demand according to traffic demand of target section in time intervals, and dividing analysis time intervals into [400,1000 ]]、[1000,1600]、[1600,2200]、[2200,2800]、[2800,3400]、[3400,4000]、[4000,4600]And [4600,5200]Eight time intervals, the dividing time of two continuous analysis time intervals being t 12 ＝1000s、t 23 ＝1600s、t 34 ＝2200s、t 45 ＝2800s、t 56 ＝3400s、t 67 4000s and t 78 ＝4600s。
Step 2: an analysis range is set. Setting the analysis range as the target section and the upstream 800m range thereof, namely, the analysis range is X l 140m to X c ＝940m。
Step (ii) of3: the freestream vehicle speed is determined. The free flow speed is set to be v according to Vissim simulation f ＝60km/h。
And 4, step 4: calculating the speed of each floating vehicle reaching the target road section X according to the free flow speed c The time of day. According to the formula (2), calculating the section X of the target road where all floating vehicles reach c The calculation results are shown in table 2.
TABLE 2
And 5: determining the closest before and after each dividing moment
According to the formula (3), the closest demarcation time t is obtained i(i+1) Two moments before and after
And
and its corresponding floating car number k i(i+1) And (k +1) i(i+1) The calculation results are shown in table 3.
TABLE 3
Step 6: and determining the traffic flow detection boundary time corresponding to each traffic demand analysis boundary time. By floating car number k i(i+1) And (k +1) i(i+1 ) The passing section X can be inquired c Time of day of
And
and according to the formula (4), the traffic demand analysis score can be determinedTime of demarcation t i(i+1) Corresponding traffic flow detection boundary time t ci(i+1) The calculation results are shown in table 4.
TABLE 4
And 7: and outputting the traffic demand of each analysis period. And (5) obtaining the traffic demand of each analysis time period according to the formula (5) and the data of the section traffic detector. The calculation results, the conventional method results (traffic flow of the detector in each time period), the traffic demand truth values and the error analysis of the invention are shown in table 5. Therefore, the estimation errors of the method for the traffic demand in each time period are less than 5%, and the average error of the whole analysis time period is 1.1%. Compared with the traditional method, the accuracy is obviously improved, the maximum improvement percentage reaches 27.3%, and the average improvement of the whole analysis period is 11.2%.
TABLE 5
The above description is only a preferred embodiment of the present invention, and does not limit the present invention in any way. It will be understood by those skilled in the art that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. A road section time-interval traffic demand estimation method considering a congestion state is characterized by comprising the following steps:
s1: determining total analysis time aiming at a target road section, and dividing the total analysis time into a plurality of time periods;
s2: setting an analysis section and an analysis boundary, and setting the analysis boundary to the analysis section as an analysis range;
s3: fitting a traffic flow-density curve by using the section detection historical data, and further calculating the free flow speed of the road;
s4: calculating the time when each floating vehicle reaches the road section according to the free flow speed;
s5: for the dividing time of any two analysis time intervals, finding the front time and the rear time which are closest to the dividing time;
s6: determining traffic flow detection demarcation time corresponding to each traffic demand analysis demarcation time;
s7: and outputting the traffic demand of each analysis period.
2. The method according to claim 1, wherein in step S1, a total analysis time [ t ] is set b ,t e ](ii) a Total analysis time [ t ] b ,t e ]Divided into I periods, denoted T 1 ,T 2 ,...,T i ,...,T I Wherein two analysis periods T are continued i And T i+1 Is defined as t i(i+1) 。
3. The method for estimating a traffic demand according to claim 2, wherein the analysis section is set to X in S2 c Section, setting L meters at the upstream of the analysis section as analysis boundary and recording as X l Cross section, then the analysis range is X l To X c And (4) cutting the section.
4. The method according to claim 3, wherein in step S3, the speed of the free stream of the road is v f The traffic flow-density curve adopts a triangle, and three basic parameters needing fitting comprise road traffic capacity q 0 Optimum density k 0 And plug density k j The free-flow vehicle speed is calculated by the following equation:
5. the method for estimating a traffic demand according to claim 4, wherein the step S4 is specifically as follows: at analysis time [ t b ,t e ]Will pass through the cross section X c And X l All the floating cars are numbered according to the time sequence and are marked as the floating cars 1,2, a. Acquiring the passing section X of any floating car n l At time t ln And through section X c At time t cn (ii) a Thereby calculating the arrival section X of the random floating car under the speed of n free flows through a calculation formula c Time of day of
The calculation formula is expressed as:
6. the method for estimating a traffic demand according to claim 5, wherein the step S5 is specifically as follows: the dividing time of any two analysis time intervals is t i(i+1) For the dividing time t of any two analysis periods i(i+1) Searching in the order of the vehicle number n from small to large
Find the closest t i(i+1) The two moments before and after the moment are respectively
And
the above-mentioned
And
and said t i(i+1) The following formula is satisfied:
7. the method for estimating a traffic demand according to claim 6, wherein the step S6 is specifically as follows: a vehicle k can be obtained i(i+1) And (k +1) i(i+1) Through section X c Time of day of
And
i.e. the traffic demand analysis demarcation time t i(i+1) Corresponding traffic flow detection boundary time t i(i+1) Should be in
Within a time period; further suppose that
The traffic state does not change in the time period, and the traffic demand analysis demarcation time t i(i+1) Corresponding traffic flow detection boundary time t ci(i+1) Determined by the following equation:
8. the method for estimating a traffic demand according to claim 7, wherein the step S7 is specifically as follows: for an arbitrary analysis period T i Traffic demand D i Is [ t ] c(i-1)i ,t ci(i+1) ]Section X in time period c Detected traffic flow
Wherein t is when i ═ 1 c(i-1)i ＝t b When i is equal to 1, t ci(i+1) ＝t e I.e. Q i Determined by the following equation:
9. the method for estimating traffic demand according to claim 3, wherein in said S2, the distance L is greater than the queue length at the analysis section.
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