CN117037485A - Intelligent expressway active traffic flow control method and system - Google Patents
Intelligent expressway active traffic flow control method and system Download PDFInfo
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Abstract
The invention discloses an intelligent expressway active traffic flow control method and system, which relate to the technical field of intelligent expressway active control and comprise a data layer, a platform layer and an application layer.
Description
Technical Field
The invention relates to the technical field of active control of intelligent expressways, in particular to an intelligent expressway active traffic flow control method and system.
Background
Along with the continuous acceleration of urban and motorized processes in China, the traffic volume of roads is rapidly increased, large-scale expressways (including expressways and urban expressways) are built in various areas and cities in China, the total mileage of the expressways in China is the first place in the world at present, but the traffic management is still very deficient, and especially the intelligent traffic control technology which has been applied for years abroad and has fully proved effects is very little applied to the expressways in China, and the active intervention on the traffic jam and safety of the expressways is seriously insufficient. At present, the China traffic industry is facing transformation and upgrading from traditional capacity construction to efficiency improvement. The construction of large-scale urban road traffic infrastructures has gradually slowed down and tends to be saturated, and refined traffic management and accurate traffic regulation are the directions of future traffic technology development.
The essence of road traffic control is to guide and control the driving behavior of the running vehicle, and to change the input/output and running state of traffic flow by reasonable control method through traffic flow state analysis and prediction, so as to change the traffic flow state to the expected state as much as possible. Through proper road traffic control, the operation capacity of the bottleneck area can be kept near the maximum traffic capacity during congestion, so that the traffic flow stability is ensured, the maximization of the performance of the existing traffic infrastructure is realized, the traffic efficiency is improved, the traffic safety is ensured, and the pollutant emission is reduced. Related studies indicate that: by adopting an advanced traffic control technology, the development of an intelligent traffic system (Intelligent Transportation System, ITS) is beneficial to relieving traffic jam, reducing extra fuel consumption and pollution emission and improving road traffic capacity and traffic flow efficiency.
The traffic department issues notification of traffic department office on accelerating the promotion of new generation national traffic control network and intelligent highway test points, opens new generation national control network and intelligent highway demonstration engineering, mainly surrounds infrastructure digitalization, road and transportation integrated vehicle-road cooperation, and develops test point application based on big data road network comprehensive management, internet plus road network comprehensive service and the like. At present, two major pain points mainly faced by expressway travel in China are safety and congestion, and the main reasons are low data acquisition precision, incomplete data value mining, lack of real-time state risk assessment, insufficient multi-platform coordination control and single management control means, and the adoption of an active expressway traffic flow control system can fully utilize expressway traffic flow information to perform real-time traffic state prediction and risk assessment, so that intelligent high-speed is created, and smooth and safe traffic running is ensured from the global angle of cooperation and scheduling. The active traffic flow control system mainly comprises the functions of variable speed limit control, lane dynamic management, ramp flow control and the like. Active traffic flow control systems have been used in the united kingdom, the united states, the netherlands, australia, etc. countries and regions, and decades of engineering experience has shown that active traffic flow control systems can effectively alleviate congestion and improve traffic safety.
Disclosure of Invention
The invention aims to provide an intelligent expressway active traffic flow control method and system, which are used for solving the problems of low data acquisition precision, incomplete data value mining, lack of real-time state risk assessment, insufficient multi-platform coordination control and single management control means of the expressway in China at present.
In order to achieve the above purpose, the present invention provides the following technical solutions:
an intelligent expressway active traffic flow control system comprises a data layer, a platform layer and an application layer, wherein the data layer comprises a data processing and sensing device, the platform layer comprises a basic algorithm and platform capability, the application layer comprises information release, application scenes and key technologies, the data processing comprises data cleaning, data safety, data storage, data inspection, data searching and data fusion, the sensing device comprises a millimeter wave radar, a weather station, a visibility meter, a road surface state detector, a video camera and an event detector, the millimeter wave radar is a radar working in a millimeter wave band and is usually arranged in a road or at the side of the road, statistics of traffic flow data such as flow, speed, occupancy and the like on each lane are realized through tracking vehicles on the road, the period of the traffic flow data collected by the millimeter wave radar is usually 30 seconds, the weather observation station can detect rainfall, wind power, air temperature and the like of a region where the weather observation station is arranged through various weather sensors, the visibility meter can detect the visibility of a road in real time, the abnormal region of the visibility of the road can be rapidly found, the distribution of the visibility meter on the expressway is more dense for detecting bad weather such as fog of the expressway, the distribution of the weather observation station on the expressway can be sparse because most regions of the expressway generally have similar weather conditions, the basic algorithm comprises Bayesian condition logic, deep learning, machine learning, model prediction control and deep reinforcement learning, the platform capability comprises API service, distributed data service bus, distributed cache, parallel calculation and micro service, the information release comprises release information and control facilities, the application scene comprises a normalized traffic flow operation scene, a road frequent and planned event scene and a road emergency scene, and the key technology comprises a single-point ramp control technology, multi-strategy cooperative control, real-time traffic state prediction, main line variable speed limit control, main line cooperative control of a ramp and full line space-time cooperative control.
As a further scheme of the invention: the release information comprises road traffic risks, traffic information prompts, traffic situations and lane dividing speed limits.
As still further aspects of the invention: the control facility comprises a cantilever screen, a bar screen, a block screen and an RSU (road side unit), wherein the block screen consists of information boards corresponding to each traffic lane and emergency traffic lane, the upper part of each traffic lane consists of a single display screen, the single display area is not less than 1.2m (height) ×1.2m (width), the block screen can display two parts of contents and is divided into a left part and a right part, the left side can display information such as speed, traffic prohibition, lane change and the like according to a control strategy, and the right side can display information such as congestion, accidents, slow vehicles and the like;
the bar screen is positioned above the lanes and consists of a whole display screen, and can be used for displaying road prompt information or independent speed limit information of each lane;
RSU (vehicle-road cooperation road side Unit) is applied to a vehicle-road cooperation scene, is usually installed On a road side, communicates with an On Board Unit (OBU) through a C-V2X technology, and can realize fine variable speed limit management by issuing speed guide information to the OBU.
As still further aspects of the invention: the normalized traffic flow operation scene comprises a scene of overlarge upstream and downstream speed difference, overlarge truck duty ratio, overlarge lane dividing speed difference, special vehicle running and large traffic flow.
As still further aspects of the invention: the frequent and planned event scene of the road comprises road maintenance construction, holiday abnormal congestion, unidirectional or bidirectional traffic interruption, key road congestion and connecting line congestion scenes.
As still further aspects of the invention: the road emergency scene comprises bad weather, pedestrian and animal crossing, road sprinklers, obstacles and traffic accidents.
An intelligent highway active traffic flow control method, the method is as follows;
s1, data acquisition, wherein the data acquisition comprises two parts, one part is traffic flow data, namely traffic flow speed, traffic flow and traffic density of each lane of each control unit of the whole line, and comprises display contents on an information board of each control unit at present; the other part is different types of traffic events contained in the traffic event set, and each event has different reporting time, event level, longitudinal influence range (occupied control unit) and transverse influence range (occupied lane number);
s2, a first-level organization scheme is used for determining a traffic organization scheme under a specific event scene according to the event type of the active control system on the basis of data acquisition content, wherein the traffic organization scheme comprises an event policy influence range, a lowest speed limit value, a lane management condition and corresponding newly issued content as limiting conditions;
S3, a secondary control scheme is adopted, and comprehensive calculation is carried out on all events in an event set according to limiting conditions such as the event priority, the lowest speed limit value of each event, the event grade and the like, so that comprehensive control schemes such as the speed limit value of a control unit, ramp flow control rate, traffic information release content and the like after multi-event fusion are obtained;
and S4, implementing a three-level cooperation scheme, namely implementing a cooperation method of time and space cooperation, including space-time cooperation of a speed limit value, space cooperation of lane limitation, information release priority cooperation and the like on the high-speed full line on the basis of a comprehensive control scheme.
As still further aspects of the invention: the time and space coordination of the speed limit value in the S4 comprises upstream and downstream speed limit smoothness, front and rear period speed limit smoothness and speed difference smoothness between adjacent lanes, the space coordination of the lane limit comprises emergency lane setting space coordination, truck forbidden space coordination and lane closing space coordination, and the information release content mainly comprises daily maintenance operation and maintenance information, disaster and climate event scene information, traffic accident or illegal road occupation information, truck special road opening and closing information, emergency lane opening and closing information, traffic accident risk early warning information and traffic jam prompt information.
Compared with the prior art, the invention has the beneficial effects that:
the system comprises a data layer, a platform layer and an application layer, wherein the data layer fuses and processes multi-metadata through road state sensing equipment, weather stations, visibility meters and the like, the platform layer combines a basic algorithm and a service platform to provide data, and the application layer generates an active traffic flow control scheme according to a real-time traffic flow state through a variable speed limit control technology, a single-point ramp control technology, a real-time traffic state prediction technology, a ramp cooperative control technology, a ramp main line cooperative control technology and a multi-strategy and full-line space-time cooperative control technology, and then issues control information based on control facilities.
Drawings
FIG. 1 is a diagram of a system architecture of the present invention.
FIG. 2 is a hierarchical architecture diagram of the implementation of the control strategy of the present invention.
FIG. 3 is a schematic diagram of a three-stage linkage control zone according to the present invention.
FIG. 4 is a flow chart of the lane closing prompt of the present invention.
FIG. 5 is a message flow distribution diagram in bad weather according to the present invention.
Fig. 6 is a flow chart of information release after a traffic accident.
FIG. 7 is a layout of the road projectile information flow according to the present invention.
Fig. 8 is a flowchart of the road construction information distribution according to the present invention.
Fig. 9 is a flowchart of the traffic congestion information distribution according to the present invention.
Fig. 10 is a schematic diagram of a multi-objective variable speed limit control of the present invention.
Fig. 11 is a flow chart of the multi-objective variable speed limit control of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, in an embodiment of the present invention, an intelligent highway active traffic control system includes a data layer, a platform layer and an application layer, the data layer includes data processing and sensing devices, the platform layer includes a basic algorithm and platform capability, the application layer includes information publishing, application scenarios and key technologies, the data processing includes data cleaning, data security, data storage, data inspection, data searching and data fusion, the sensing devices include millimeter wave radar, weather stations, visibility meters, road surface state detectors, video cameras and event detectors, the millimeter wave radar is a radar operating in millimeter wave band, and is usually installed in a road or at a road side, statistics of traffic flow data such as flow, speed, occupancy and the like on each lane is achieved through tracking vehicles on the road, the period of traffic flow data collected by the millimeter wave radar is usually 30 seconds, the weather observation station can detect rainfall, wind power, air temperature and the like of a region where the weather observation station is arranged through various weather sensors, the visibility meter can detect the visibility of a road in real time, the abnormal region of the visibility of the road can be found rapidly, the distribution of the visibility meter on the expressway is dense for detecting severe weather such as the fog of the expressway, and as most regions of the expressway generally have similar weather conditions, the distribution of the weather observation station on the expressway can be sparse, basic algorithms comprise Bayesian conditions logic, deep learning, machine learning, model prediction control and deep reinforcement learning, and platform capabilities comprise API services, distributed data service buses, distributed caches, parallel computing and micro services;
The information release comprises release information and control facilities, the release information comprises road traffic risks, traffic information prompts, traffic situations and lane division speed limit, the control facilities comprise cantilever screens, bar screens, block screens and RSUs (vehicle road cooperation road side units), the block screens consist of information boards corresponding to each traffic lane and emergency lanes, each lane is composed of a single display screen, the single display area is not lower than 1.2m (height) X1.2 m (width), the block screens can display two parts of contents and are divided into left and right parts, according to a control strategy, the left side can display speed, traffic is forbidden, lane change and other information, the right side can display congestion, accidents, slow vehicles and other information, the bar screens are positioned above the lanes, the bar screens consist of a whole display screen and can be used for displaying road prompt information, or each independent speed limit information, the RSUs (vehicle road cooperation road side units) are applied to a vehicle road cooperation scene and are usually arranged On the road sides, communication is carried out between the vehicle units (OBU, on Board t) through C-V2X technology, and Union Board t can realize accurate speed management by guiding Union the information;
the application scene comprises a normalized traffic flow operation scene, a road frequent and planned event scene and a road emergency scene, wherein the normalized traffic flow operation scene comprises an upstream and downstream speed difference excessively high, a truck duty ratio excessively high, a lane dividing speed difference excessively high, special vehicle running and large traffic flow scene, the road frequent and planned event scene comprises a road maintenance construction, a holiday abnormal congestion, one-way or two-way traffic interruption, a key road section congestion and a connecting line congestion scene, and the road emergency scene comprises bad weather, pedestrian and animal crossing, road casting objects, barriers and traffic accidents;
The key technology comprises a single-point ramp control technology, multi-strategy cooperative control, real-time traffic state prediction, main line variable speed limit control, ramp main line cooperative control and full line space-time cooperative control;
1. variable speed limit control technique
The variable speed limit control technology (Variable Speed Limits) is characterized in that the variable speed limit control technology is used for actively intervening the operation of the expressway traffic flow by changing the speed limit value, so that the purposes of improving the operation of the traffic flow, reducing the speed dispersion, relieving the traffic jam, improving the driving safety and the like are realized.
2. Single-point ramp control technology
The single-point ramp control technology is characterized in that the current traffic state of a main road of an expressway is used as a control condition, the actual flow rate at an entrance ramp is determined by using the technologies such as an optimization technology, an automatic control theory, fuzzy control and neural network control, and the control of the ramp traffic flow rate is realized by means of ramp speed limit or ramp signal lamps.
3. Real-time traffic state prediction technology
The traffic state prediction is a basic component of an intelligent traffic system, and is a typical regression problem of a traffic network time sequence by establishing a prediction method and a model from the traffic state change with randomness and uncertainty according to traffic data obtained by various detection devices and combining historical traffic data and other influencing factors, finding out rules in the traffic state change and predicting future traffic states. The key point is how to select and design a more proper model algorithm aiming at the randomness and uncertainty of the characteristic data and combining with the space-time correlation so as to achieve the purpose of high precision and small error of the predicted result.
4. Ramp cooperative control technology
The ramp cooperative control technology aims at controlling the flow at the bottleneck on the basis of local optimized control of the ramp, and realizes small-range multi-turn internal cooperative control in a static coordination area by combining historical traffic demands and traffic congestion influence ranges. The ramp coordination control mainly aims at optimizing the overall performance of the system, takes the maximum total turn-in flow of the system or the minimum total travel time or the minimum total delay of the system vehicle as performance indexes, takes the adjustment rate of each entrance ramp as a control variable, and takes the traffic capacity as a constraint condition to carry out optimization control.
5. Cooperative control technology for ramp main line
The technology for cooperative control of the main line of the ramp is linkage closed-loop feedback control which simultaneously considers the variable speed limit control of the main line and the ramp control in the bottleneck section, and the variable speed limit control and the ramp control are commonly used control methods for relieving the congestion of the confluence region. The variable speed limiting control is to reduce the vehicle flow which is converged into the converging zone by limiting the upstream running speed of the converging bottleneck zone; the ramp control is to control the number of vehicles which are converged on the entrance ramp and enter the main line by adopting a ramp adjustment rate, and the two methods are to avoid or relieve the congestion of the converging region by reducing the number of vehicles which are converged on the main line converging bottleneck region in unit time, but the entrance ramp vehicles are converged on the main line under the variable speed limit control and are not limited, the speed limit value is solved according to the traffic state of the converging region, and the right of passage of the ramp vehicles is ensured to a certain extent by sacrificing the right of passage of the main line vehicles; the ramp control is opposite to ensure the right of way of the main line vehicle by sacrificing the right of way of the ramp vehicle. The method of coordinated control of the two can effectively avoid the problem of the deviation of the right of way and prevent vehicles on the main line or the ramp from queuing and tracing.
6. Multi-strategy and full-line space-time cooperative control technology
In practical application of the lane-based active control system, a corresponding control strategy is often required to be generated according to events of multiple types and multiple scenes. However, at the same time, only a unique strategy can be displayed on the variable information board under the condition that different event strategies exist simultaneously. And the influence ranges of different events are different, and the unified strategy of the whole line needs to be dynamically adjusted according to the space-time range of each event. In order to meet the above requirements, a multi-strategy and full-line space-time cooperative control technology is proposed. In the multi-strategy cooperative control technology, the strategy display content on each variable information board is optimized according to the constraint conditions of event priority, event speed limit and the like in a multi-event scene, and the full-line space-time cooperative control technology is to dynamically optimize the display content of the full-line strategy by setting the constraint conditions of dynamic speed limit adjustment threshold, adjacent road section speed limit difference threshold, adjacent lane speed limit difference threshold and the like in two dimensions of time and space for the full-line variable information board.
Referring to fig. 2, a method for intelligent highway active traffic control is as follows;
s1, data acquisition, wherein the data acquisition comprises two parts, one part is traffic flow data, namely traffic flow speed, traffic flow and traffic density of each lane of each control unit of the whole line, and comprises display contents on an information board of each control unit at present; the other part is different types of traffic events contained in the traffic event set, and each event has different reporting time, event level, longitudinal influence range (occupied control unit) and transverse influence range (occupied lane number);
S2, a primary organization scheme is used as a basis of data acquisition content, a traffic organization scheme under a specific event scene is determined according to the event type of an active control system, the traffic organization scheme comprises an event strategy influence range, a lowest speed limit value, a lane management condition and corresponding newly issued content, and the traffic organization scheme is used as a limiting condition, specifically, lane closing measures are adopted for two lanes on the outermost side of a four-lane expressway as shown in FIG. 3 due to accidents, and the traffic organization scheme generated by the accidents needs to simultaneously close an upper ramp connected with a main line and issue prompt information for changing lanes to the inner side in advance at the upstream. To ensure continuity of opening and closing of the lanes, the outermost lanes downstream of the accident position need to be closed at the same time;
s3, a secondary control scheme is adopted, and according to limiting conditions such as event priority, the lowest speed limit value of each event, event level and the like, comprehensive calculation is carried out on all events in an event set to obtain comprehensive control schemes such as a control unit speed limit value, ramp flow control rate, traffic information release content and the like after multi-event fusion, specifically, in a control area shown in FIG. 3, a final speed limit value passing through an accident area is required to be determined according to a front accident level, and gradual speed limit control is set in an upstream area of the final speed limit value, so that a vehicle is firstly decelerated to an early warning speed limit in the control area, and a sudden deceleration phenomenon is avoided in the upstream of the accident area;
S4, three-level cooperation schemes are used for implementing time and space cooperation on a high-speed full line on the basis of a comprehensive control scheme, wherein the time and space cooperation comprises time-space cooperation of a speed limit value, space cooperation of a lane limit, information release priority cooperation and the like, the time and space cooperation of the speed limit value comprises upstream and downstream speed limit smoothness, front and rear periodic speed limit smoothness and speed difference smoothness between adjacent lanes, the space cooperation of the lane limit comprises emergency lane setting space cooperation, truck forbidden space cooperation and lane closing space cooperation, the information release content mainly comprises daily maintenance operation and maintenance information, disaster climate event scene information, traffic accident or illegal occupation information, truck special lane opening and closing information, emergency lane opening and closing information, traffic accident risk early warning information and traffic jam prompt information, and particularly in a cooperative area shown in FIG. 3, the speed limit value in the cooperative area needs to be subjected to smooth processing according to the speed limit of a control area, and the traffic volume of an upstream ramp and an outermost lane entering the cooperative area of the speed limit control area is set so as to adapt to the speed limit of a downstream control area.
The implementation of dynamic traffic control relies on the cooperation of road hardware and system software. Road hardware can be divided into road state awareness devices and traffic control devices. The system software can be divided into a big data platform and an active control system according to specific functions.
1. System software and hardware
The road hardware equipment is introduced as follows:
(1) Road state sensing device
The road state sensing equipment is a hardware base for acquiring traffic flow states (such as lane flow, average vehicle speed, lane occupancy and the like) and weather conditions (such as air temperature, rainfall, visibility and the like) on a road, is an important data source for realizing active traffic control, and mainly comprises hardware including a millimeter wave radar, a weather observation station and a visibility meter.
(2) Traffic control apparatus
Traffic control devices are the hardware basis for implementing control of vehicles on roads. The system mainly comprises a cantilever type display screen (hereinafter called cantilever screen for short), a portal type lane dividing display screen (hereinafter called lane dividing screen for short), a portal type bar type display screen (hereinafter called bar screen for short) and a Road Side Unit (RSU) for vehicle-Road cooperation.
The system software is introduced as follows:
(1) Data platform
The big data platform is responsible for carrying out distributed storage, quality inspection, data cleaning and data safety management on mass data generated by sensing equipment in the expressway, and meanwhile, the analysis, fusion and mining of traffic data can be realized by providing a basic big data algorithm.
(2) Control software
The control software adopts a front-back end separation structure and a micro-service architecture, takes a distributed data service bus and a distributed cache as a support, adopts a parallel computing mode, provides various API services, enables the front end to acquire real-time traffic flow, occupancy rate and other information of each road section through man-machine interaction, combines background algorithms such as situation assessment and risk prediction and the like to display future traffic states and road risks of each road section in real time, enables a camera icon to be clicked for a region needing to be focused to acquire a corresponding position road video picture, and enables the rear end to take various key algorithms as a core and to take parallel computing as a support, so as to construct a control strategy module of various events.
The active control system is based on road traffic situation, traffic risk and traffic event data, matches the road traffic event scene, aims at safety and high efficiency, applies theoretical methods such as machine learning, deep reinforcement learning, model predictive control and the like of the front edge, and automatically forms a lane refined control strategy by combining traffic flow basic theory and orienting to the traffic event scene based on relevant national and local standards.
2. Control conditions
The active control system performs active traffic flow control on the highway when the following conditions occur.
(1) Abnormal traffic flow
Based on the traffic flow statistical data of the lane level, the traffic situation is evaluated, and the real-time traffic flow state of the whole line section is analyzed. When a certain area has traffic flow disorder, overlarge traffic flow, overlarge average speed difference among lanes or overlarge average speed difference of upstream and downstream roads, dynamic traffic control is carried out, and the detection core of abnormal traffic flow is in road traffic running state identification research.
The real-time traffic flow state characteristic data acquired by the limited traffic state detectors distributed on the expressway are used for estimating the traffic flow state characteristics of the road section which are not covered by the detectors by applying the traffic flow mechanical model, and meanwhile, the real-time state characteristics of the traffic flow in the road network are accurately acquired by estimating the traffic flow state characteristics in the whole road network through a small amount of state monitoring in the road network based on the dynamic characteristics of the traffic flow system.
(2) Environmental anomalies
When weather conditions such as rain, snow, fog and ice are abnormal, infrastructure health conditions such as road damage and structural damage are abnormal, or traffic facilities such as guardrail damage are abnormal, dynamic traffic control is performed according to the abnormal degree of the road running environment.
Poor weather conditions, such as low visibility, slippery road surfaces, may result in slow and unstable traffic. The system needs to determine the speed limit value matched with the meteorological conditions according to the meteorological data acquired in real time and in combination with the national relevant standards, and the speed limit value is released to road users through the information real-time release technology. The specific meteorological conditions mainly comprise fog, wind, snow, road icing, icing early warning, heavy rainfall and the like. Detection of road structure damage and the like depends on structural sensors arranged in a road, and the road structure affecting driving safety is monitored in an important mode by combining with a full life cycle management system of road equipment.
(3) Traffic event occurrence
And detecting events such as traffic accidents, abnormal parking and the like of the whole line by using traffic radars, event detectors and the like, acquiring detailed information of sudden traffic events in real time, and timely responding by a lane active control system. And grasping planning events such as road maintenance construction and the like, and responding the dynamic traffic control system at regular time based on the occurrence time and place of the events. Event-oriented control is characterized in that traffic events are automatically detected.
Automatic detection of traffic events is of great significance in greatly reducing delays, congestion and accidents caused by the events and improving traffic safety and road service level. A series of detection algorithms such as a statistical method, a traffic flow model-based algorithm, a discriminant analysis algorithm, a data mining-based method and the like are adopted, and the actual observation data and the model prediction result are compared to judge and detect traffic events.
(4) Increased security risk
Based on dynamic traffic flow data, traffic flow abnormality, environment abnormality and traffic event, the dynamic judgment of the real-time road traffic risk level of the whole road section and the prediction of future risk values are realized based on traffic safety risk prediction. And (3) carrying out dynamic traffic control on the areas with the current excessive risk and the possible safety risk in the future, and improving the safety operation level of the expressway.
The risk prediction mainly comprises three indexes: all adjacent lane speed difference risks, all adjacent road segment speed difference risks and road segment real-time risks. 1) All adjacent lane speed difference risks. For each road section, the nearest set of upstream and downstream radar data is taken, and the average speed of each lane 5-10 minutes before the current time in the traffic flow data is extracted as algorithm input. And calculating the speed difference of the adjacent lanes according to the average speed of each lane. And classifying risks according to the preset adjacent lane speed difference threshold values, converting the speed difference into risk indexes of 5 grades, and outputting all adjacent lane speed difference risk grades. 2) And (5) risk of speed difference of all adjacent road sections. And aiming at each road section and the adjacent upstream road section, the latest set of upstream and downstream radar data is taken, and the upstream and downstream average speed 5-10 minutes before the current time in the traffic flow data is extracted as algorithm input. And calculating the speed difference of the adjacent road sections according to the average speed of the adjacent road sections, classifying the risk according to the preset speed difference of the adjacent road sections, converting the speed difference into risk indexes of 5 classes, and outputting the risk of the speed difference of all the adjacent road sections. 3) Real-time risk of road segments. For each road section, a group of nearest upstream and downstream radar data is taken, the upstream average speed, the downstream average speed, the upstream average flow, the downstream average flow, the upstream average occupancy, the downstream average occupancy, the upstream speed standard deviation, the downstream speed standard deviation, the upstream flow standard deviation, the downstream flow standard deviation, the upstream occupancy standard deviation, the downstream occupancy standard deviation, the upstream speed difference, the adjacent lane speed difference and other traffic flow basic data 5-10 minutes before the current time in the traffic flow data are extracted and used as algorithm input, and the traffic flow data are substituted into an accident risk model to calculate the accident probability of each road section. And converting the accident probability into risk indexes of 5 grades according to the road section risk grades set in advance, and outputting the real-time risk of the road section.
3. Three-stage linkage control
In the implementation process of the control strategy, the control strategy generated after the triggering of a single traffic event is fused into the full-line control strategy according to the hierarchical architecture of multi-strategy cooperative coupling control of primary organization, secondary control and tertiary cooperation, so that the full line is uniformly and smoothly controlled.
4. Control technique
(1) Variable speed limit control
1) Variable speed limit control system composition
The variable speed limit control system provides real-time traffic flow characteristic parameters such as vehicle speed, headway, traffic composition and the like through automatic detection devices such as traffic flow detectors, weather sensors, road surface condition sensors and the like, visibility, rainfall, snowfall, road ice thickness, wind speed, wind direction and the like, and on the basis of the information, an optimal speed limit value is determined through a speed limit value optimization model by a computer and is released to a road information board through an information real-time release technology. It provides a more reliable speed limit to the driver, which can improve the driver's compliance with the speed limit.
The highway variable speed limit control system is a system for collecting external information in real time and issuing the information in real time, and consists of four subsystems of environment sensing, event discrimination, control strategy generation and information issuing, wherein the environment sensing system is divided into two systems of traffic flow detection and weather detection, the traffic flow detection subsystem consists of a plurality of traffic flow detection devices, the traffic flow detection devices comprise millimeter wave radars, video cameras, video event detectors and the like, the traffic flow detectors arranged at different positions according to the actual conditions of roads report traffic flow data in a period to a central server according to a preset reporting period, the weather detection subsystem consists of a plurality of weather detection devices such as weather stations, visibility meters, road surface sensors and the like, the weather detection subsystem reports weather, visibility, road conditions and other data in the period to the central server at regular time, and the event discrimination system applies various traffic event scene discrimination algorithms according to traffic flow states, weather environment data and traffic event detection data to generate corresponding traffic events and event classes. The control strategy generation system is based on traffic events and event grades generated by the event discrimination system, combines real-time road traffic states, generates prompt information and target speed limit values which are required to be displayed by the road information board by using a three-level cooperative control algorithm according to the pile number position, the type and other basic information of the road information board, the information release system consists of the information boards of the type which are required to be displayed on the road, and the information release system is combined with the information currently displayed by the road information board according to the target speed limit value of each piece of information, and sends the speed limit values of the information boards to the road information board at fixed time intervals by a smooth gradual change method so as to finally reach the target speed limit value.
2) Variable speed limit control system structure
The variable speed limiting system can be divided into an information acquisition layer, a data transmission layer, a variable speed limiting control layer and an information distribution layer according to the specific functions of each module, the weather detection subsystem and the traffic flow detection subsystem form the information acquisition layer of the variable speed limiting system, the information acquisition layer is the basis of all other subsystems, the information acquisition layer is required to be accurate and reliable, the road basic condition can be sensitively reflected in real time, the data transmission layer receives the data of the information acquisition layer and distributes the speed limiting value to the information distribution layer, a bridge for data transmission is provided, the data acquisition layer can adopt an optical cable or wireless communication mode, the variable speed limiting control layer is the core of the whole variable speed limiting control technology, and the variable speed limiting control layer can be divided into two layers: traffic event discrimination and control strategy generation, wherein the traffic event discrimination generates corresponding traffic event and event grade, the control strategy generation module generates corresponding road prompt information and road speed limit value based on the data, the information distribution layer is a terminal of the whole system, the final speed limit value is distributed on the road, and the distribution of the speed limit information is matched with corresponding law enforcement means and is suitable for different speed limit control targets.
(1) Information acquisition layer: the information acquisition layer has the advantages that the technology can reflect real-time traffic running environment and running condition and perform dynamic speed limiting adjustment, so that the information acquisition layer is a foundation for implementing variable speed limiting control, and the expressway which has implemented variable speed limiting control at present mostly adopts millimeter wave radar and video detectors for acquiring traffic flow parameters; the weather monitoring station and the visibility detector are used for monitoring real-time weather conditions of road sections, traffic flow parameters to be detected comprise speed, flow, density, occupancy, headway and the like, environmental weather data comprise rainfall, wind speed, wind direction, visibility, road surface icing conditions and the like, and the key of the information acquisition layer is the accuracy of the detected traffic flow parameters and weather data and whether the information acquisition layer is sensitive to the changes of traffic flow and weather.
(2) Data transmission layer: the function of the data transmission layer is to carry out data arrangement on information acquired by each hardware facility of the information acquisition layer, and transmit the data to a computer database through the transmission hardware facilities, thereby providing an information interaction way between the road side information acquisition facilities and a control center, playing a role of a communication bridge, currently, the data transmission layer is used for carrying out data information communication by using an optical cable of a highway loop carrier system, and the data transmission layer is required to provide an interface compatible with hardware according to specific requirements or carry out corresponding conversion on the acquired data before transmission so as to reduce the transmission information quantity.
(3) Variable speed limit control layer: the function of the variable speed limit control layer is to analyze real-time traffic flow parameters and weather data according to a control mechanism, and a regulation and control mode of a variable speed limit value is formulated, so that the variable speed limit control layer is a core of the whole variable speed limit control technology, and the layer can be divided into two layers: traffic event discrimination and control strategy generation, wherein the traffic event discrimination generates corresponding traffic events and event levels according to perceived road traffic data and weather data, and the control strategy generation module generates corresponding road prompt information and road speed limit values based on the traffic event data.
(4) Information distribution layer: the function of the information distribution layer is to distribute control commands formulated by the variable speed limit control layer to a driver through the variable speed limit plate, the information distribution layer is a terminal of the whole variable speed limit control system, the variable speed limit control commands of the control center are transmitted to the local control cabinet through the expressway optical cable system, and prompt information and speed limit values are distributed through a bar screen or a block screen on the portal frame.
(2) Dynamic lane management and control technology
The method mainly comprises a lane closing prompt algorithm, wherein the method comprises the following steps: the first step: obtaining event information (such as whether an accident occurs or not and whether a construction section and a construction section length exist at the accident place or not), and the second step: it is determined whether the lane needs to be closed. And a third step of: if the lane needs to be closed, displaying a variable information board above the lane needing to be closed at the place of occurrence of the event or 1km upstream of the construction section: the lane is closed and the lane is changed in advance. If it is not necessary to close the lane, a variable information panel upstream of the lane displays: all lanes are accessible, and the flow chart is shown in fig. 4.
(3) Intersection bottleneck section control technology
Aiming at the problem of frequent congestion of the ramp, an Alinea control method is adopted to carry out single-point control of the ramp. The method has good algorithm stability, is easy to operate, and can effectively keep the stability and high efficiency of traffic flow. The control method is shown as the formula:
wherein r is k And r k-1 The control rate of the ramp in the k-th period and the ramp in the k-1 th period are respectively; k (k) r For adjusting the rate parameter, vehicle/h;the occupancy critical value is corresponding to the traffic volume of the downstream of the main line when the traffic volume reaches the traffic capacity; o (O) k-1 Is the real-time occupancy downstream of the kth-1 cycle.
But the conventional Alinea algorithm does not consider the effect of ramp queue length overflows on the associated intersections. To solve this problem, scholars in previous studies introduced classical queuing constraints to limit r k Is defined in the following range:
max[d k-1 -(l max -l k )/T,R min ]≤r k ≤min(R max ,d k-1 +l k /T)
wherein d k-1 The arrival rate of the vehicles at the ramp of the k-1 period is the vehicle/h; l (L) max Is the maximum length of queuing allowed; l (L) k Queuing length for the kth period; t is the signal period length; r is R max And R is min The upper limit and the lower limit of the ramp flow of the bicycle are respectively adopted.
However, the Alinea method that introduces queuing constraints still has the following problems:
(1) The requirement for an insertable gap when a ramp vehicle enters the main line is ignored, and the requirement is obviously not in line with reality;
(2) When the queuing length is too large, the ramp control rate is adjusted to the maximum value, and the great influence of the ramp control rate on the main line traffic is ignored although the ramp queuing can be effectively dissipated.
Therefore, this section proposes an improved alineate entrance ramp control method, which solves the above-mentioned problems while retaining many advantages of the conventional alineate method.
Firstly, classifying the queuing length of the ramp, defaulting to 0-0.6 l max In the three-stage case, 0.6l max ～0.9l max In the second order, greater than 0.9l max Is the first order case.
For the three-level situation, the critical occupancy of Alinea is calibrated by considering the insertable gap of the ramp traffic flow converging into the main line, so as to ensure the real effectiveness of ramp control:
wherein r is k,max The maximum control rate of the kth period is the vehicle/h; q k,gap Maximum control traffic volume for the kth cycle main line, vehicle/h; o (O) k,gap For the kth period q k,gap The corresponding main line controls the occupancy threshold.
For the second-level situation, the ramp queuing length is gradually increased, and in order to avoid great influence on the main line traffic caused by greatly increasing the ramp control rate, a queuing control model with gradually increased control rate is proposed:
wherein,is a queuing length critical value; k (k) q The adjustment rate is controlled for queuing. / >
On the basis, comprehensively considering the influence of the pluggable gaps, an Alinea model considering queuing is proposed:
max[d k-1 -(l max -l k )/T,R min ]≤r k ≤min(R max ,d k-1 +l k /T)
wherein alpha is a weight coefficient; r is R max And R is min The empirical values were 900 and 180.
By adjusting the alpha value, the aim of gradually increasing the control rate and stably and moderately evacuating ramp queuing can be fulfilled.
For the first order case, r is taken k R is k,max To rapidly dissipate ramp queuing.
(4) Real-time information release technology
Information prompt in bad weather: the bad weather is a main cause of traffic accidents, road congestion and road damage of the expressway, so that weather information is timely and accurately collected, traffic control instructions are scientifically and correctly analyzed, judged, quickly and effectively issued, the bad weather is a necessary measure for reducing accidents, ensuring smoothness, protecting road yield and improving road operation efficiency, when the bad weather occurs, the influence on traffic is large in a general affected range, the local or whole road network is involved, and traffic flow in the local or whole road network in the affected range is required to be shunted or induced, so that the traffic in the road network is more orderly and safe. The information distribution flow chart is shown in fig. 5.
Information prompt after accident occurrence: the traffic accident information is typical dynamic traffic information, the release strategy can adopt an instantaneous state release strategy and a prediction state release strategy, the instantaneous state release strategy can be monitored in real time through a traffic monitoring system, and the information is timely released by utilizing simple criteria or visual image information of traffic parameter values; predictive traffic state distribution strategies often estimate the time of impact of an incident and the duration of traffic congestion through several predictive models to determine whether this information is to be distributed. The information distribution flow chart is shown in fig. 6.
Information prompt of road parabolic: the situation that the sprinkle is unpredictable, especially the goods are scattered, the driver knows that the traffic accident can be caused, but the traffic accident can not be actively selected to give an alarm generally, but the traffic accident can be processed by the driver, in addition, the condition that the sprinkle is difficult to find through monitoring video inspection, especially under special conditions such as night, rainy days and the like is limited due to the limitation of the current monitoring technical conditions, the conventional mode of manual inspection is relied on, the found quantity is limited, and the efficiency is not high. After the sprinkling event occurs, a safety early warning is needed to be made in the first time, the driver behind is prompted to avoid, and an information release flow chart is shown in fig. 7.
Information prompt of road construction: the traffic safety of the construction area is to ensure the normal traffic of the expressway during construction and the personal safety of constructors, and ensure that the constructors and drivers are in a safety protection state, so that traffic diversion, such as road network diversion, road diversion, traffic behavior control, such as warning sign, speed limit sign and the like, can be adopted to ensure the normal traffic of the expressway during construction and the personal safety of the constructors during the normal traffic of the expressway, in addition, special safety protection measures are also set according to the construction operation type to reduce the risk of traffic accidents, and an information release flow chart is shown in fig. 8.
Information prompt of road congestion: traffic congestion can be classified into frequent traffic congestion and sporadic traffic congestion. Common traffic congestion refers to a phenomenon of traffic congestion occurring when traffic demand is greater than the traffic capacity at a fixed bottleneck on a road, and is generally used to describe traffic congestion that repeatedly occurs at certain specific locations and at certain specific times; the sporadic traffic congestion refers to a traffic congestion phenomenon generated when traffic demand is greater than traffic capacity at a temporary bottleneck on a road, and is used for describing traffic congestion caused by the fact that the actual traffic capacity of the road is reduced due to sudden traffic events such as accidents, special weather and the like, so that traffic congestion information needs to be pushed through an information board to prompt a driver to drive carefully. The flow chart is shown in fig. 9.
(5) Traffic flow control policy optimization technique based on infrastructure features
The converging area formed at the junction of the entrance ramp and the main line is the most common traffic bottleneck type on the expressway, and the bottleneck section of the entrance ramp has serious traffic delay and higher accident risk, so that a variable speed limit control strategy for simultaneously improving the traffic safety and the traffic efficiency of the expressway is proposed, a control system schematic diagram is shown in fig. 10, a first variable speed limit mark positioned at the upstream of the bottleneck position is defined as a key mark, as shown in fig. 10 (a), and the function of the control system is to regulate the flow entering the bottleneck position, thereby eliminating the bottleneck traffic jam and avoiding the reduction of the traffic capacity of the bottleneck traffic flow, as shown in fig. 10 (b); the other speed limit markers located in the bottleneck upstream road section are defined as slave variable speed limit markers which function to smooth traffic flow speed fluctuation in the bottleneck upstream road section, and avoid the risk of rear-end collision accidents caused by sudden deceleration of the vehicle during congestion propagation, as shown in fig. 10 (c).
The multi-objective variable speed limit control flow proposed in this section is shown in fig. 11, step 1 firstly obtains real-time traffic flow parameters on a highway traffic flow detector, judges the bottleneck traffic capacity drop amplitude and the key occupancy value according to offline data, then firstly determines the speed limit value of the key variable speed limit sign position, and when the time reaches the variable speed limit control period, calculates the key variable speed limit value by adopting a proportional-integral controller:
VSL C (k)＝VSL C (k-1)+(K P +K I )e o (k)-K P e o (k-1)
VSL in C (k) Is the key variable speed limit value at the moment K P And K I In order to control the parameters of the device, control error for bottleneck position occupancy +.>For the key occupancy, o (k) is the bottleneck position actual measurement occupancy at time k.
And 2, calculating the speed limit value of each subordinate variable speed limit sign position, and when the time reaches the variable speed limit control period, calculating the traffic accident risk in each road section according to the real-time traffic flow data by adopting a real-time rear-end collision accident risk prediction model. When the accident risk value in a certain road section is larger than a set threshold value, starting variable speed limit control of the road section:
V SL (x i ,k+1)＝V SL (default)-ΔV SL (x i ,k),if R i (k)>R TH #
V SL (x i ,k+1)＝min{V SL (default),V SL (x i ,k)+ΔV SL (x i ,k)},else#
v in SL (x i K) is x i Speed limit value, V, of position-variable speed limit sign at time k SL (default) is the default speed limit of road section, deltaV SL (x i K) limit the amplitude of the change in the velocity value, R i (k) For the accident risk in the road section i at the moment k, R TH An accident risk threshold for variable speed limit is activated.
After starting variable speed limit in road section, gradually adjusting the speed limit value to target speed limit value according to the change step length, wherein DeltaV is the change amplitude of the speed limit value, T VSL (x i K+1) is a target speed limit value:
ΔV SL (x i ,k)＝-ΔV,ifT VSL (x i ,k+1)<V SL (x i ,k)-ΔV#
ΔV SL (x i ,k)＝ΔV,ifT VSL (x i ,j+1)>V SL (x i ,k)+ΔV#
ΔV SL (x i ,k)＝0,ifV SL (x i ,k)-ΔV<T VSL (x i ,k+1)<V SL (x i ,k)+ΔV#
then, checking the speed limit value of the adjacent road section, and adjusting the speed limit value when the speed limit value difference of the adjacent road section is larger than the maximum allowable value delta V', thereby avoiding large-scale speed fluctuation in the space range:
ΔV SL (x i ,k)＝-ΔV',ifT VSL (x i ,k+1)>T VSL (x i-1 ,k+1)+ΔV'#
after the speed limit value of each speed limit sign position is determined, checking the speed limit value, if the speed limit value exceeds the allowable range [ VSL ] min ,VSL max ]And when the control method is used, adopting the maximum value or the minimum value in the range for the next control period, rounding the calculated speed limit value to be an integer multiple of 5mph, and issuing on the corresponding variable speed limit sign.
Although the present invention has been described with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements and changes may be made without departing from the spirit and principles of the present invention.
Claims (8)
1. An intelligent highway active traffic flow control system comprises a data layer, a platform layer and an application layer, and is characterized in that: the data layer comprises data processing and sensing equipment, the platform layer comprises basic algorithm and platform capability, the application layer comprises information release, application scenes and key technologies, the data processing comprises data cleaning, data safety, data storage, data inspection, data searching and data fusion, the sensing equipment comprises millimeter wave radar, a weather station, a visibility meter, a road surface state detector, a video camera and an event detector, the basic algorithm comprises Bayesian condition logic, deep learning, machine learning, model prediction control and deep reinforcement learning, the platform capability comprises API service, distributed data service bus, distributed cache, parallel computing and micro service, the information release comprises release information and control facilities, the application scenes comprise normalized traffic flow operation scenes, road frequent and planned event scenes and road emergency scenes, and the key technologies comprise single-point ramp control technology, multi-strategy cooperative control, real-time traffic state prediction, main line variable speed limit control, main line cooperative control and full line space-time cooperative control.
2. The intelligent highway active traffic flow control system according to claim 1, wherein: the release information comprises road traffic risks, traffic information prompts, traffic situations and lane dividing speed limits.
3. The intelligent highway active traffic flow control system according to claim 1, wherein: the control facilities comprise a cantilever screen, a bar screen, a block screen and an RSU (vehicle road cooperation road side unit).
4. The intelligent highway active traffic flow control system according to claim 1, wherein: the normalized traffic flow operation scene comprises a scene of overlarge upstream and downstream speed difference, overlarge truck duty ratio, overlarge lane dividing speed difference, special vehicle running and large traffic flow.
5. The intelligent highway active traffic flow control system according to claim 1, wherein: the frequent and planned event scene of the road comprises road maintenance construction, holiday abnormal congestion, unidirectional or bidirectional traffic interruption, key road congestion and connecting line congestion scenes.
6. The intelligent highway active traffic flow control system according to claim 1, wherein: the road emergency scene comprises bad weather, pedestrian and animal crossing, road sprinklers, obstacles and traffic accidents.
7. An intelligent expressway active traffic flow control method is characterized in that: the method is as follows;
s1, data acquisition, wherein the data acquisition comprises two parts, one part is traffic flow data, namely traffic flow speed, traffic flow and traffic density of each lane of each control unit of the whole line, and comprises display contents on an information board of each control unit at present; the other part is different types of traffic events contained in the traffic event set, and each event has different reporting time, event level, longitudinal influence range (occupied control unit) and transverse influence range (occupied lane number);
s2, a first-level organization scheme is used for determining a traffic organization scheme under a specific event scene according to the event type of the active control system on the basis of data acquisition content, wherein the traffic organization scheme comprises an event policy influence range, a lowest speed limit value, a lane management condition and corresponding newly issued content as limiting conditions;
s3, a secondary control scheme is adopted, and comprehensive calculation is carried out on all events in an event set according to limiting conditions such as the event priority, the lowest speed limit value of each event, the event grade and the like, so that comprehensive control schemes such as the speed limit value of a control unit, ramp flow control rate, traffic information release content and the like after multi-event fusion are obtained;
And S4, implementing a three-level cooperation scheme, namely implementing a cooperation method of time and space cooperation, including space-time cooperation of a speed limit value, space cooperation of lane limitation, information release priority cooperation and the like on the high-speed full line on the basis of a comprehensive control scheme.
8. The intelligent highway active traffic control method according to claim 7, wherein: the time and space coordination of the speed limit value in the S4 comprises upstream and downstream speed limit smoothness, front and rear period speed limit smoothness and speed difference smoothness between adjacent lanes, the space coordination of the lane limit comprises emergency lane setting space coordination, truck forbidden space coordination and lane closing space coordination, and the information release content mainly comprises daily maintenance operation and maintenance information, disaster and climate event scene information, traffic accident or illegal road occupation information, truck special road opening and closing information, emergency lane opening and closing information, traffic accident risk early warning information and traffic jam prompt information.
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