Capacity expansion management and control method for predictable easily-congested road section

Abstract

The invention discloses a capacity expansion management and control method for predictable easily-congested road sections, and relates to the technical field of traffic management and control, historical data of each ETC portal in a near period of time on an expressway are collected, and historical traffic operation states of each road section in the monitoring range of each ETC portal are calculated; according to the historical traffic operation state of each road section, easily-congested road sections are screened, easily-congested routes are formed, and the daily average traffic volume of the easily-congested routes is calculated; and formulating a capacity expansion control strategy according to the daily average traffic volume of the easily-congested route. The method is used for solving the problems of large traffic flow and low traffic efficiency of predictable easily-congested road sections, capacity expansion can be carried out in a way of adding lanes and the like for regular and long-term easily-congested road sections so as to improve the traffic capacity, the method is a mesoscopic periodic strategy, conventional microcosmic management and control are improved to mesoscopic management and control, and the traffic efficiency is improved. Optimized configuration and efficient utilization of traffic resources can be realized, and the operation efficiency and the service level of the whole traffic system can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic control, and in particular to a method for controlling the expansion of a road section that is predictably prone to congestion. Background Art

[0002] At present, the video surveillance coverage rate of expressways is 100%, with full-time monitoring, full-time detection, and full-area coverage; LED screens are installed in service areas, toll stations, bridges, super-large bridges, medium-span and above tunnels, tunnel groups, interchanges, ramps, diversion areas, etc. The installation of ETC gantries not only realizes automatic toll collection without stopping, but also provides support for accurate perception of traffic on expressways. From coverage rate, layout density to equipment types, the field sensing equipment of expressways can meet the requirements of intelligent and refined control of expressways.

[0003] The congested sections of expressways have a certain predictability. Predictable congested sections refer to regular sections with stable spatiotemporal characteristics of congestion that will not change within a certain period of time. For example, the scope and duration of high-saturation traffic congestion sections on statutory holidays are regular, but dynamic traffic organization is difficult because the duration is long and the traffic volume is too concentrated to be diverted in a short period of time. Therefore, through the analysis of historical data, the spatiotemporal characteristics of congestion are extracted, and relatively static expansion control is adopted to improve road capacity and alleviate traffic congestion; bottleneck sections are also congested sections, such as tunnels and long bridges, and the spatiotemporal characteristics of congestion are also stable. For this kind of congestion characteristics in a certain period (when the traffic flow characteristics of the road network have not changed significantly), it can be mined through big data, and combined with road network structure, collection equipment, ETC gantry data, induction equipment, traffic safety facilities, Internet information release, etc., to carry out control, realize the intelligent expansion of roads, and improve road traffic efficiency.

[0004] At present, there are many equipment installed in the electromechanical system of highways, such as: ETC gantry (OBU receiver, video surveillance, induction screen), smart toll station (unmanned toll card, self-service payment machine), video cloud (one every 2km), radar, traffic modulation system, smart service area (mainly video), severe weather monitoring, etc. The basic equipment investment is large, but once it is a holiday, the highway is seriously congested and the public travel comfort is extremely poor. The reason is that after the equipment is invested, its real value has not been brought into play. Summary of the invention

[0005] In order to overcome the defects in the above-mentioned prior art, the present invention provides a capacity expansion control method for road sections that are foreseeably prone to congestion, which is used to solve the problems of large traffic flow and low traffic efficiency in road sections that are foreseeably prone to congestion.

[0006] To achieve the above object, the present invention adopts the following technical solutions, including: A method for controlling and expanding the capacity of a road section that is prone to foreseeable congestion, characterized in that it comprises the following steps: S1, collects historical data of each ETC gantries on the expressway in the recent period; S2, based on historical data, calculates the historical traffic operation status of each road section under the monitoring range of each ETC gantry; S3, based on the historical traffic operation status of each road section, select the road sections prone to congestion, form the routes prone to congestion, and calculate the daily average traffic volume of the routes prone to congestion; S4, formulate capacity expansion and control strategies based on the daily average traffic volume of routes prone to congestion.

[0007] Preferably, the road sections prone to congestion are divided into road sections prone to congestion on weekdays, weekends, and holidays; adjacent road sections prone to congestion on weekdays are connected to form routes prone to congestion on weekdays; adjacent road sections prone to congestion on weekends are connected to form routes prone to congestion on weekends; adjacent road sections prone to congestion on holidays are connected to form routes prone to congestion on holidays; the daily average traffic volume of routes prone to congestion on weekdays, routes prone to congestion on weekends, and routes prone to congestion on holidays are calculated respectively, and capacity expansion control is carried out on weekdays, weekends, and holidays.

[0008] Preferably, the proportion of each road section that experiences severe congestion on weekdays, weekends, and holidays is calculated based on the historical traffic operation status of each road section; if the proportion of a road section that experiences severe congestion on weekdays, weekends, or holidays exceeds a set threshold, then the road section corresponds to a section that is prone to congestion on weekdays, weekends, or holidays; otherwise, the road section is a section that is not prone to congestion.

[0009] Preferably, the daily average traffic volume of the congested route is calculated as follows: Qmax=max[n(j),...,n(j+z)]×max[Qds(j),...,Qds(j+z)]; The starting section of the congested route is numbered j, and the ending section is numbered j+z, where z≥0; n(j) represents the number of lanes in the jth section; Qds(j)=max[Qds a (j)|a∈A], Qds(j) is the maximum daily cross-sectional traffic volume of a single lane on the jth road section; Qds a (j) is the daily cross-sectional traffic volume of a single lane on the j-th road section on the a-th day, and A is the corresponding set of days.

[0010] Preferably, the expansion control strategy is as follows: If the average daily traffic volume Qmax of the congested route < C, no expansion control is carried out; if C ≤ Qmax < C + Co, the emergency lane is opened; if Qmax ≥ C + Co, while the emergency lane is opened, the oncoming lane is also temporarily opened, and the oncoming lane is closed when the maximum daily cross-sectional traffic volume Qmax’ of the previous day of the congested route < C + Co; Among them, C is the maximum traffic capacity of the congested route, and Co is the traffic capacity of the corresponding emergency lane of the congested route.

[0011] Preferably, the calculation method of the maximum daily cross-sectional traffic volume of the previous day of the congested route is as follows: Qmax’ = max[n(j),..., n(j + z)] × max[Qds’(j),..., Qds’(j + z)]; Among them, the starting section number of the congested route is j, the ending section number is j + z, z ≥ 0; n(j) represents the number of lanes of the j-th section; Qds’(j) is the daily cross-sectional traffic volume of a single lane of the previous day of the j-th section.

[0012] Preferably, collect the historical data of each ETC gantry on the highway in a recent period; remove the day before the holiday and the day after the holiday from all working days to form a set of working-day days; form a set of weekend days with all weekends; form a set of holiday days with all holidays plus the day before the holiday and the day after the holiday.

[0013] Preferably, the specific process of step S2 is as follows: S21, collect the daily cross-sectional traffic volume of a single lane of each section in a recent period as sample data, and construct a total sample set X; X = {Qds m (i)|i = 1, 2, 3,...; m = 1, 2, 3,..., M}, where Qds m (i) is the daily cross-sectional traffic volume of a single lane of the i-th section on the m-th day, and M is the total number of days in a recent period; S22, divide the total number of days in a recent period into working days, weekends, and holidays to form a set of working-day days A1, a set of weekend days A2, and a set of holiday days A3; Divide the total sample set X into three sample sets, which are: Working-day sample set x1 = {Qds a1 (i)|i = 1, 2, 3,...,a1 ∈ A1}, where Qds a1 (i) is the daily cross-sectional traffic volume of a single lane of the i-th section on the a1-th day; Weekend sample set x2 = {Qds a2 (i)|i = 1, 2, 3,...,a2 ∈ A2}, where Qdsa2 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a2; Holiday sample set x3={Qds a3 (i)|i=1,2,3,...,a3∈A3}, where Qds a3 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a3; S23, dividing the congestion level into w levels according to the severity of the congestion, and setting the corresponding cluster category to w; S24, using a clustering algorithm, clustering the three sample sets respectively, dividing each sample set into w categories and obtaining w cluster centers; S25, determine the congestion level of each road section every day in the recent period: calculate Qds m (i) The Euclidean distance with each cluster center of the corresponding sample set. The category corresponding to the cluster center with the smallest Euclidean distance is selected as the congestion level of the i-th road section on the m-th day.

[0014] Preferably, the daily cross-sectional traffic volume of a single lane of a road section is calculated as follows: Calculate the hourly cross-sectional traffic volume of a road section: ; Among them, Q h is the hourly section traffic volume of the road section, in units of pcu / h. The hourly section traffic volume refers to the number of vehicles passing through the section within 1 hour, which is converted into standard vehicles for counting; k v is the conversion coefficient of the vth model, Q h,v is the hourly cross-sectional traffic volume of the vth vehicle type; h represents hour; Calculate the daily cross-sectional traffic volume of a road section: ; Among them, Qd is the daily cross-sectional traffic volume of the road section; Calculate the daily cross-sectional traffic volume of a single lane of a road section: Qds=Qd / n; Among them, Qds is the daily cross-sectional traffic volume of a single lane of the road section, and n is the number of lanes of the road section.

[0015] Preferably, the method further includes step S5, iterating according to the above steps S1-S4 to update the capacity expansion control strategy.

[0016] The advantages of the present invention are: (1) The present invention solves the problem of large traffic flow and low traffic efficiency on sections of roads that are prone to foreseeable congestion. It can reduce accident hazards to a certain extent, save travel costs, increase the traffic capacity of sections of roads prone to congestion, and improve the satisfaction of travelers.

[0017] (2) The present invention aims at road sections prone to regular and long-term congestion, and can expand the capacity by adding lanes and other means to improve the traffic capacity. Road sections prone to congestion are often traffic bottlenecks. Through management and control measures, the traffic pressure at these bottlenecks can be effectively alleviated, the operating efficiency of the entire transportation network can be improved, and the waiting time and delays of vehicles on these sections can be reduced.

[0018] (3) The present invention is a meso-cyclical strategy that moves from conventional micro-control to meso-control, which helps to achieve optimal allocation and efficient utilization of transportation resources and improve the operating efficiency and service level of the entire transportation system.

[0019] (4) The present invention proposes a relatively static control strategy within a certain period of time. It is highly targeted, especially for regularly congested sections, such as sections congested during holidays. It is a strategy that lasts for a long time and covers a wide range. The control strategy runs through the entire process from before the holiday congestion begins to the end of the congestion. Unlike short-term or emergency traffic management measures, this strategy intervenes before the holiday congestion begins and lasts until the congestion ends, ensuring that the control measures can play a role throughout the entire congestion cycle. It has risen from conventional micro-control to meso-control, which helps to achieve the optimal allocation and efficient utilization of traffic resources and improve the operating efficiency and service level of the entire transportation system.

[0020] (5) The present invention conducts in-depth mining of data such as traffic flow, speed, and accident records of highways under the same historical period and conditions to identify sections prone to congestion. At the same time, combined with relatively real-time daily traffic volume data, the present invention continuously monitors road conditions and adopts a control strategy that combines static and dynamic control. For sections with regular and long-term congestion, such as sections with high saturation traffic during holidays, physical expansion can be carried out by adding lanes, etc. to improve road capacity, guide vehicles to be reasonably diverted, and avoid worsening congestion.

[0021] (6) The capacity expansion control of predictable congested sections of the present invention is a meso-periodic strategy between static control and dynamic control. When the road network does not change, the traffic flow characteristics remain unchanged. In this case, congestion is a completely predictable law; when the traffic flow changes, the characteristics of the congestion will also change. Therefore, when the traffic flow characteristics of the road network change significantly, the program can be re-run to generate a capacity expansion control strategy that adapts to the traffic flow. The strategy is evaluated and adjusted regularly to ensure that it always matches the current traffic flow characteristics, thereby achieving road capacity expansion and improved traffic capacity. For congested sections under conditions of super-saturated traffic, starting from the management demand side, a complete set of active capacity expansion control technologies are used. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1The present invention is a flow chart of a method for controlling the expansion of a road section that is prone to predictable congestion. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] like Figure 1 As shown, a method for capacity expansion control of a predictably congested road section includes the following steps: S1, acquisition of basic data: collect historical data of each ETC gantry on the highway in the recent period (specifically one year) and remove abnormal data. ETC gantry data includes: ETC gantry number, ETC gantry name, direction, longitude, latitude, pile number, type, vehicle passing data, and vehicle model. The section under the monitoring range of the i-th ETC gantry is recorded as the i-th section, i=1,2,3,...

[0025] The specific process of step S1 is as follows: S11, calculate the hourly section traffic volume of each road section: ; Among them, Q h (i) is the hourly cross-sectional traffic volume of the ith road section, in pcu / h. The hourly cross-sectional traffic volume refers to the number of vehicles passing through the road section within 1 hour, which is converted into standard vehicles for counting; k v is the conversion coefficient of the vth model, Q h,v (i) is the hourly cross-sectional traffic volume of the vth vehicle type on the ith road section; h represents the hour. The following table 1 is a table of vehicle type conversion coefficients.

[0026] Table 1 Vehicle type conversion coefficient correspondence table

[0027] S12, calculate the daily cross-sectional traffic volume of each road section: ; Among them, Qd(i) is the daily cross-sectional traffic volume of the i-th road section. The daily cross-sectional traffic volume of a road section refers to the number of vehicles passing through the road section in one day.

[0028] S13, calculate the daily cross-sectional traffic volume of a single lane of each road section: Qds(i)=Qd(i) / n(i); Among them, Qds(i) is the daily cross-sectional traffic volume of a single lane on the i-th road section. The daily cross-sectional traffic volume of a single lane on a road section refers to the number of vehicles passing through the single lane section on the road section within one day, and n(i) is the number of lanes on the i-th road section.

[0029] Since the cross-sectional traffic volume of a highway includes the cross-sectional traffic volume of all lanes, but different sections of a highway may have different numbers of lanes, in order to keep the calculation in the same dimension, the daily cross-sectional traffic volume Qds(i) of a single lane of each section is used as the basic data.

[0030] S2, calculate the historical traffic operation status of each road section: on the premise that the road network structure of the expressway has not changed, that is, the expressway has not undergone changes such as reconstruction, expansion, and new construction, collect the single-lane daily cross-sectional traffic volume of each section of the expressway within one year as sample data; use the K-means clustering algorithm to classify it into several congestion levels, and obtain the cluster center corresponding to each category; subsequently, by calculating the Euclidean distance between the single-lane daily cross-sectional traffic volume of each section and the cluster center of each category, determine the historical traffic operation status of each section, that is, the congestion level.

[0031] K-means clustering algorithm is an existing clustering analysis algorithm, which can be obtained by directly calling the k-means cluster function in conventional analysis software.

[0032] The specific process of step S2 is as follows: S21, collect the daily cross-sectional traffic volume of a single lane of each section of the expressway within one year as sample data, and construct the total sample set X; X = {Qds m (i)|i=1,2,3,...;m=1,2,3,...,M}, where Qds m (i) is the daily cross-sectional traffic volume of a single lane on the i-th road section on the m-th day, where M is the total number of days in a year.

[0033] S22, divide the total number of days in a year into working days, weekends, and holidays, remove the day before and the day after the holiday from all working days to form a working day set A1; all weekends form a weekend day set A2; all holidays plus the day before and the day after the holiday to form a holiday day set A3.

[0034] The total sample set X is divided into three sample sets, namely: Weekday sample set x1={Qds a1 (i)|i=1,2,3,...,a1∈A1}, where Qds a1 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a1; Weekend sample set x2={Qdsa2 (i)|i=1,2,3,...,a2∈A2}, where Qds a2 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a2; Holiday sample set x3={Qds a3 (i)|i=1,2,3,...,a3∈A3}, where Qds a3 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a3; the holiday sample set x3 also includes sample data from the day before and the day after the holiday.

[0035] S23, classify the congestion level into 5 levels according to the congestion level, namely free flow, smooth flow, slow flow, congestion, and severe congestion, and set the classification category of the K-means clustering algorithm to 5.

[0036] S24, calling the k-means cluster function to run the K-means clustering algorithm, classifying the three sample sets respectively, dividing each sample set into five categories and obtaining five cluster centers: V1={α1, α2, α3, α4, α5}; V2={β1, β2, β3, β4, β5}; V3={γ1, γ2, γ3, γ4, γ5}; Among them, V1 is the cluster center set of the weekday sample set x1; α1, α2, α3, α4, and α5 are arranged in order from small to large, corresponding to the cluster centers of the five categories of free flow, smooth flow, slow flow, congestion, and severe congestion on weekdays; V2 is the cluster center set of the weekend sample set x3; β1, β2, β3, β4, and β5 are arranged in order from small to large, corresponding to the cluster centers of the five categories of free flow, smooth flow, slow flow, congestion, and severe congestion on weekends; V3 is the cluster center set of the holiday sample set x3; γ1, γ2, γ3, γ4, and γ5 are arranged in order from small to large, corresponding to the cluster centers of the five categories of free flow, smooth flow, slow flow, congestion, and severe congestion on holidays.

[0037] S25, determine the congestion level of each road section every day within a year: calculate Qds m (i) The Euclidean distance from each cluster center of the corresponding sample set, and the category corresponding to the cluster center with the smallest Euclidean distance is selected as the congestion level of the i-th road section on the m-th day; If m∈A1, then calculate Qds respectively m(i) The Euclidean distance from the five cluster centers of the weekday sample set x1, namely α1, α2, α3, α4, and α5, and the category corresponding to the cluster center with the smallest Euclidean distance is selected as the congestion level of the i-th road section on the m-th day; If m∈A2, then calculate Qds respectively m (i) The Euclidean distance from the five cluster centers of the weekend sample set x2, namely β1, β2, β3, β4, and β5, and the category corresponding to the cluster center with the smallest Euclidean distance is selected as the congestion level of the i-th road section on the m-th day; If m∈A3, then calculate Qds respectively m (i) The Euclidean distance from the five cluster centers of the holiday sample set x3, namely γ1, γ2, γ3, γ4, and γ5, is used to select the category corresponding to the cluster center with the smallest Euclidean distance as the congestion level of the i-th road section on the m-th day.

[0038] S3, screening of road sections prone to congestion: based on the traffic operation status of each road section, screen the road sections prone to congestion, form routes prone to congestion, and calculate the daily average traffic volume of the routes prone to congestion.

[0039] The specific process of step S3 is as follows: S31, based on the historical traffic operation status of the ith road section, calculate the proportion of severe congestion on the ith road section on weekdays, weekends, and holidays: R1i=N1i / NA1; R2i=N2i / NA2; R3i=N3i / N32; Among them: R1i is the proportion of severe congestion on the i-th road section on weekdays, that is, the severe congestion rate; N1i is the number of days in a year when the i-th road section suffers from severe congestion on weekdays; NA1 is the total number of weekdays in a year, that is, the size of the weekday day set A1; R2i is the proportion of severe congestion on the i-th road section on weekends; N2i is the number of days in a year when the i-th road section suffers from severe congestion on weekends; NA2 is the total number of weekends in a year, that is, the size of the weekend day set A2; R3i is the proportion of severe congestion on holidays on the i-th road section; N3i is the number of days in a year when the i-th road section suffers from severe congestion on holidays; NA3 is the total number of holidays in a year, that is, the size of the holiday day set A3.

[0040] S32: judging whether the i-th road section is a road section prone to congestion according to the severe congestion rate of the i-th road section on weekdays, weekends, and holidays: If R1i ≥ 50%, or R2i ≥ 50%, or R3i ≥ 50%, the road section under the i-th ETC gantry is a congested section; if R1i<50%, and R2i<50%, and R3i<50%, the road section under the i-th ETC gantry is not a congested section.

[0041] Among them, if R1i ≥ 50%, the i-th road section is a section prone to congestion on weekdays; if R2i ≥ 50%, the i-th road section is a section prone to congestion on weekends; if R3i ≥ 50%, the i-th road section is a section prone to congestion on holidays.

[0042] S33, conduct congestion characteristic analysis on road sections prone to congestion: through data visualization technology, road sections prone to congestion are displayed on the map, and the distribution of road sections prone to congestion is intuitively analyzed.

[0043] Road segmentation is an important part of highway management, and it is usually based on changes in traffic flow. When traffic flow changes at a certain location (such as an increase or decrease in the number of lanes, entrances and exits, intersections, etc.), the location is regarded as a node of a road segment, thus forming different road segments. ETC gantries are important equipment for monitoring traffic flow on highways, and are usually installed at places where traffic flow changes, such as the starting point, end point of a road segment, or a key point in the middle of a highway. Since ETC gantries can collect traffic data in real time, such as traffic volume and speed, they play a vital role in highway management. Since ETC gantries are set up at each place where traffic flow changes, there is a one-to-one correspondence between road segmentation and ETC gantry settings. This correspondence makes it possible to analyze and evaluate the traffic conditions of a road segment through the data collected by the ETC gantries.

[0044] The selected sections prone to congestion may be scattered points distributed in the highway network, but they may also be connected into a linear pattern in the highway network; adjacent weekday sections prone to congestion are connected to form weekday routes prone to congestion; adjacent weekend sections prone to congestion are connected to form weekend routes prone to congestion; adjacent holiday sections prone to congestion are connected to form holiday routes prone to congestion; if a section prone to congestion has no adjacent sections prone to congestion, then the section prone to congestion constitutes a route prone to congestion alone.

[0045] S34, calculating the daily average traffic volume of the congested route, where: The average daily traffic volume Q1max on the congested routes on weekdays is: Q1max=max[n(j1),...,n(j1+z1)]×max[Qds1(j1),...,Qds1(j1+z1)]; Among them, the starting section of the route prone to congestion on weekdays is numbered as j1, and the ending section is numbered as j1+z1, z1≥0; n(j1) represents the number of lanes in the j1th section; Qds1(j1)=max[Qds a1 (j1)|a1∈A1], Qds1(j1) is the maximum daily cross-sectional traffic volume of a single lane on the j1th road section on a working day; Qds a1 (j1) is the daily cross-sectional traffic volume of a single lane on the j1-th road section on the a1-th day, and A1 is the set of working days.

[0046] The average daily traffic volume Q2max on weekend congested routes is: Q2max=max[n(j2),...,n(j2+z2)]×max[Qds2(j2),...,Qds2(j2+z2)]; The starting section of the weekend congested route is numbered j2, and the ending section is numbered j2+z2, where z2≥0; n(j2) represents the number of lanes in the j2th section; Qds2(j2)=max[Qds a2 (j2)|a2∈A2], Qds2(j2) is the maximum daily traffic volume of a single lane on the j2-th road section on weekends; Qds a2 (j2) is the daily cross-sectional traffic volume of a single lane on the j2-th road section on the a2-th day, and A2 is the set of weekend days.

[0047] The average daily traffic volume Q3max of routes prone to congestion during holidays is: Q3max=max[n(j3),...,n(j3+z3)]×max[Qds3(j3),...,Qds3(j3+z3)]; Among them, the starting section of the route prone to congestion on holidays is numbered j3, and the ending section is numbered j3+z3, z3≥0; n(j3) represents the number of lanes in the j3th section; Qds3(j3)=max[Qds a3 (j3)|a3∈A3], Qds3(j3) is the maximum daily traffic volume of a single lane on the j3rd road section during holidays; Qds a3 (j3) is the daily cross-sectional traffic volume of a single lane on the j3-th road section on the a3-th day, and A3 is the set of holiday days.

[0048] S4, formulate capacity expansion control strategy: formulate capacity expansion control strategy based on the daily average traffic volume of congested routes.

[0049] If the daily average traffic volume Q1max of the congestion-prone route on weekdays < C, then no expansion control is carried out on the congestion-prone route on weekdays; if the daily average traffic volume of the congestion-prone route on weekdays satisfies C ≤ Q1max < C + Co, where C is the maximum traffic capacity of the congestion-prone route on this weekday and Co is the traffic capacity of the emergency lane corresponding to the congestion-prone route on this weekday, then the first expansion control strategy is adopted for the congestion-prone route on weekdays; if the daily average traffic volume Q1max of the congestion-prone route on weekdays ≥ C + Co, then the second expansion control strategy is adopted for the congestion-prone route on weekdays.

[0050] If the daily average traffic volume Q2max of the congestion-prone route on weekends < C, then no expansion control is carried out on the congestion-prone route on weekends; if the daily average traffic volume of the congestion-prone route on weekends satisfies C ≤ Q2max < C + Co, then the first expansion control strategy is adopted for the congestion-prone route on weekends; if the daily average traffic volume Q2max of the congestion-prone route on weekends ≥ C + Co, then the second expansion control strategy is adopted for the congestion-prone route on weekends.

[0051] If the daily average traffic volume Q3max of the congestion-prone route on holidays < C, then no expansion control is carried out on the congestion-prone route on holidays; if the daily average traffic volume of the congestion-prone route on holidays satisfies C ≤ Q3max < C + Co, then the first expansion control strategy is adopted for the congestion-prone route on holidays; if the daily average traffic volume Q3max of the congestion-prone route on holidays ≥ C + Co, then the second expansion control strategy is adopted for the congestion-prone route on holidays.

[0052] The first expansion control strategy specifically includes the following measures: 1) Opening of the emergency lane: The merging node upstream of the congestion-prone route is the starting point for opening the emergency lane, which is usually the first key node where congestion begins to form; The exit node downstream of the congestion-prone route is the end point for opening the emergency lane, ensuring that after exiting the congestion area, vehicles can safely and orderly exit the emergency lane.

[0053] 2) Adding safety facilities and using temporary traffic signs and guide signs: 明显的指示牌 should be set up on the upstream section where the emergency lane is opened to remind drivers that the emergency lane will be opened ahead and guide them to use the emergency lane correctly; The ETC gantry induction screen upstream should release the prompt information of "the emergency lane of the upcoming section can be driven" in advance to ensure that drivers can make preparations in advance; In the end transition area where the emergency lane is open, a guidance screen is set up to issue a reminder that "the emergency lane on the road ahead cannot be occupied" to ensure that the driver can exit the emergency lane safely and orderly.

[0054] 3) Start capturing illegal parking and lane change on solid lines: In sections where emergency lanes are open, illegal parking and lane change capture will be activated to ensure that drivers comply with traffic regulations and do not stop or change lanes at will.

[0055] By issuing reminder messages such as “No illegal parking, lane changing, and illegal photography” on the guidance screen, drivers’ awareness of complying with traffic rules is enhanced.

[0056] 4) Set up signal control at the ramp entrance in front of the toll station square: According to the capacity of the main line section and the real-time traffic flow, the speed at which vehicles enter the toll station is dynamically adjusted to optimize traffic flow distribution, ensure that there is no excessive congestion in front of the toll station, and ensure that traffic on the main line can pass smoothly.

[0057] 5) Synchronize information to Internet map navigation: Traffic information such as the opening of emergency lanes, guidance screens, and checkpoint photography can be synchronized to the Internet map navigation system to provide drivers with accurate navigation services.

[0058] 6) Provide a toll-free policy to guide vehicles to exit the expressway from the nearest toll station to ease congestion: In the road network topology, the location of toll stations is related to road sections. Relevant geographic elements are retrieved based on the explicit topological relationships established in the database (mainly the adjacency and association relationships between road network structural elements). Through topological retrieval, the nearest toll station that can be driven out can be found.

[0059] The second expansion control strategy is as follows: If the traffic flow in the opposite lane is smooth, the service level is high, and the movable guardrail of the central dividing strip within the congested route is available, that is, the conditions for borrowing the opposite lane are met, then the opposite lane can be dynamically borrowed while the emergency lane is open. When the maximum daily cross-sectional traffic volume of the congested route on the previous day is less than C+Co, that is, when the traffic status is restored, the opposite lane will be closed. If the conditions for borrowing the opposite lane are not met, the first expansion control strategy will still be adopted.

[0060] The maximum daily cross-sectional traffic volume of the congested route on the previous day is calculated as follows: Q1max'=max[n(j1),...,n(j1+z1)]×max[Qds'(j1),...,Qds'(j1+z1)]; Q2max'=max[n(j2),...,n(j2+z2)]×max[Qds'(j2),...,Qds'(j2+z2)]; Q3max'=max[n(j3),...,n(j3+z3)]×max[Qds'(j3),...,Qds'(j3+z3)]; Among them, Qds'(j1) is the daily cross-sectional traffic volume of a single lane on the j1th section of the previous day; Qds'(j2) is the daily cross-sectional traffic volume of a single lane on the j2th section of the previous day; Qds'(j3) is the daily cross-sectional traffic volume of a single lane on the j3th section of the previous day.

[0061] S5: Iterate according to the above steps S1-S4 to update the capacity expansion control strategy.

[0062] The capacity expansion control of predictable congested sections is a meso-periodic strategy between static control and dynamic control. When the road network does not change, the traffic flow characteristics remain unchanged. In this case, congestion is a completely predictable law; when the traffic flow changes, the characteristics of congestion will also change. Therefore, when the traffic flow characteristics of the road network change significantly, the program can be re-run to generate a capacity expansion control strategy that adapts to the traffic flow. The strategy is evaluated and adjusted regularly to ensure that it always matches the current traffic flow characteristics, thereby achieving road capacity expansion and improved traffic capacity. For sections prone to congestion under conditions of supersaturated traffic, starting from the management demand side, a complete set of active capacity expansion control technologies are used.

[0063] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for capacity expansion control of predictable congested road sections, characterized in that: The following steps are involved: S1, collects historical data of each ETC gantries on the expressway in the recent period; S2, based on historical data, calculates the historical traffic operation status of each road section under the monitoring range of each ETC gantry; S3, based on the historical traffic operation status of each road section, select the road sections prone to congestion, form the routes prone to congestion, and calculate the daily average traffic volume of the routes prone to congestion; S4, formulate capacity expansion and control strategies based on the daily average traffic volume of routes prone to congestion.

2. A method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: The congested sections are divided into congested sections on weekdays, weekends, and holidays; adjacent congested sections on weekdays are connected to form a congested route on weekdays; adjacent congested sections on weekends are connected to form a congested route on weekends; adjacent congested sections on holidays are connected to form a congested route on holidays; Calculate the daily average traffic volume for routes prone to congestion on weekdays, weekends, and holidays, and conduct capacity expansion control on weekdays, weekends, and holidays.

3. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: Based on the historical traffic operation status of each road section, the proportion of each road section that experiences severe congestion on weekdays, weekends, and holidays is calculated; if the proportion of a road section that experiences severe congestion on weekdays, weekends, or holidays exceeds the set threshold, then the road section corresponds to a section that is prone to congestion on weekdays, weekends, or holidays; otherwise, the road section is a section that is not prone to congestion.

4. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: The daily average traffic volume of congested routes is calculated as follows: Qmax=max[n(j),...,n(j+z)]×max[Qds(j),...,Qds(j+z)]; The starting section of the congested route is numbered j, and the ending section is numbered j+z, where z≥0; n(j) represents the number of lanes in the jth section; Qds(j)=max[Qds a (j)|a∈A], Qds(j) is the maximum daily cross-sectional traffic volume of a single lane on the jth road section; Qds a (j) is the daily cross-sectional traffic volume of a single lane on the j-th road section on the a-th day, and A is the corresponding set of days.

5. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: The specific expansion control strategy is as follows: If the daily average traffic volume Qmax < C of the congested route, no capacity expansion control will be carried out; if C≤ Qmax < C+Co, the emergency lane will be opened; if Qmax ≥ C+Co, while opening the emergency lane, the opposite lane will also be temporarily opened, and the opposite lane will be closed when the maximum daily cross-sectional traffic volume Qmax' < C+Co of the previous day on the congested route; Among them, C is the maximum capacity of the route prone to congestion, and Co is the capacity of the emergency lane corresponding to the route prone to congestion.

6. A method for controlling the expansion of a predictably congested road section according to claim 5, characterized in that: The maximum daily cross-sectional traffic volume of the congested route on the previous day is calculated as follows: Qmax'=max[n(j),...,n(j+z)]×max[Qds'(j),...,Qds'(j+z)]; The starting section of the congested route is numbered j, and the ending section is numbered j+z, where z≥0; n(j) represents the number of lanes in the j-th section; and Qds'(j) represents the daily cross-sectional traffic volume of a single lane in the j-th section on the previous day.

7. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: Collect historical data of each ETC gantries on the highway in the recent period; remove the day before and the day after the holiday from all working days to form a working day set; all weekends form a weekend day set; all holidays plus the day before and the day after the holiday to form a holiday day set.

8. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: The specific process of step S2 is as follows: S21, collect the daily cross-sectional traffic volume of a single lane of each road section in a recent period as sample data, and construct a total sample set X; X = {Qds m (i)|i=1,2,3,...;m=1,2,3,...,M}, where Qds m (i) is the daily cross-sectional traffic volume of a single lane on the i-th road section on the m-th day, where M is the total number of days in the recent period; S22, dividing the total number of days in a recent period into working days, weekends, and holidays to form a working day set A1, a weekend day set A2, and a holiday day set A3; The total sample set X is divided into three sample sets, namely: Weekday sample set x1={Qds a1 (i)|i=1,2,3,...,a1∈A1}, where Qds a1 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a1; Weekend sample set x2={Qds a2 (i)|i=1,2,3,...,a2∈A2}, where Qds a2 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a2; Holiday sample set x3={Qds a3 (i)|i=1,2,3,...,a3∈A3}, where Qds a3 (i) is the daily cross-sectional traffic volume of a single lane on the ith road section on day a3; S23, dividing the congestion level into w levels according to the severity of the congestion, and setting the corresponding cluster category to w; S24, using a clustering algorithm, clustering the three sample sets respectively, dividing each sample set into w categories and obtaining w cluster centers; S25, determine the congestion level of each road section every day in the recent period: calculate Qds m (i) The Euclidean distance with each cluster center of the corresponding sample set. The category corresponding to the cluster center with the smallest Euclidean distance is selected as the congestion level of the i-th road section on the m-th day.

9. A method for controlling the expansion of a predictably congested road section according to claim 4 or 6, characterized in that: The calculation method of daily cross-sectional traffic volume of a single lane of a road section is: Calculate the hourly cross-sectional traffic volume of a road section: ； Among them, Q h is the hourly section traffic volume of the road section, in units of pcu / h. The hourly section traffic volume refers to the number of vehicles passing through the section within 1 hour, which is converted into standard vehicles for counting; k v is the conversion coefficient of the vth model, Q h,v is the hourly cross-sectional traffic volume of the vth vehicle type; h represents hour; Calculate the daily cross-sectional traffic volume of a road section: ； Among them, Qd is the daily cross-sectional traffic volume of the road section; Calculate the daily cross-sectional traffic volume of a single lane of a road section: Qds=Qd / n; Among them, Qds is the daily cross-sectional traffic volume of a single lane of the road section, and n is the number of lanes of the road section.

10. The method for controlling the expansion of a predictably congested road section according to claim 1, characterized in that: The method further includes step S5, iterating according to the above steps S1-S4 to update the capacity expansion control strategy.

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