WO2019145232A1

WO2019145232A1 - Method for monitoring traffic and traffic monitoring system

Info

Publication number: WO2019145232A1
Application number: PCT/EP2019/051276
Authority: WO
Inventors: Bernhard MINGE; Jochen Dieter; Reinhard KOY-OBERTHÜR
Original assignee: Vitronic Dr.-Ing. Stein Bildverarbeitungssysteme Gmbh
Priority date: 2018-01-24
Filing date: 2019-01-18
Publication date: 2019-08-01
Also published as: EP3518204A1

Abstract

The invention relates to a method for monitoring traffic, wherein the traversal of a monitored region (12) by vehicles (2, 3, 4) is detected by means of a traffic monitoring system (7, 8) which ascertains the traffic density in the monitored region (12). Furthermore, the detected vehicles (2, 3, 4) are classified, and a vehicle model is assigned to each detected vehicle (2, 3, 4) on the basis of the classification, said vehicle model including the expected pollutant emission of the detected vehicle, wherein the pollutant content is ascertained in the ambient air in the monitored region (12).

Description

Traffic monitoring and traffic monitoring system

description

The invention relates to a method for traffic monitoring in which the passage of vehicles in a monitored area is detected by means of a traffic monitoring system, the traffic density in the monitored area is determined, and further the detected vehicles are classified and each detected convincing vehicle based on the classification Vehicle model is assigned, which includes the expected pollutant emissions of the detected vehicle. Furthermore, the invention relates to a traffic monitoring system for carrying out such a method.

Such a method is known from US 2017/091350 A1. US 2017/091350 A1 describes a method for computer-aided modeling of the distribution of pollutant emissions caused by vehicles traveling on a road network. A pollutant emission estimate is made for individual segments of the road network by the assignment of emission profiles for at least a subset of vehicles detected in the segment.

US 2016/0042234 A1 describes a method for vehicle counting and pollutant emission estimation. Vehicles driving on a road are captured and classified. The pollutant emission of the vehicles is subsequently taken from the classification of conversion tables on the Fland.

The object of the present invention is to provide a method for traffic monitoring and a traffic monitoring system in which the air quality can be assessed on the basis of the currently prevailing traffic in order to be able to create a dynamic traffic management. The object is achieved by a method of traffic monitoring, in which the passage of vehicles in a monitored area is detected by means of a traffic monitoring system, the traffic density in the monitored area is determined, and further the detected vehicles are classified and each detected vehicle based on the classification a vehicle model is assigned, which includes the expected pollutant emissions of the detected vehicle, wherein the pollutant content is determined in the ambient air in the monitored area.

The traffic monitoring system is placed on an area to be monitored, for example a road or a road, in order to be able to detect the vehicles traveling on the roadway. The detected vehicles are classified in order to be able to assign a vehicle model to them via the expected pollutant emission. The classification may be that the vehicle type, whether it is a passenger car, a lorry or a motorcycle, is detected and assigned. Further, a classification may be derived based on the identification of the make and model of the vehicle. It is also possible to detect a badge of the vehicle emission class, for example using imaging techniques. To determine the pollutant content in the ambient air can be used on existing data, which are provided by information services. In order to obtain a timely and locally accurate determination of the concentration of pollutants, it can be provided that the pollutant content detected in the ambient air through the traffic monitoring system, that is measured. In addition or as an alternative to detecting the pollutant content, noise emissions can also be determined or measured.

The classification of the detected vehicles can be based on at least one external feature from the group axis number, length, width, height and Idenfikationsabzei- Chen. Based on the number of axles, length, width and height can be closed for example on the vehicle type. Identification badges may be the representation of the make of the vehicle and the model. The model can also be estimated from the longitudinal axes, length, width and height as appropriate. In addition, identification badges can be a badge of the pollution class of the Vehicle, for example, on the windscreen, a dangerous goods sign or the vehicle registration number.

In addition to the expected pollutant emissions of the detected vehicle, the vehicle model may also include the expected noise emission of the detected vehicle. Thus, on the vehicle model on the one hand on the local air quality based on the expected pollutant emissions are concluded, but also on the expected or prevailing noise emissions. In order to determine the traffic density in the monitored area, it is possible to make use of already existing data provided via traffic information services. In order to obtain a timely and accurate information about the traffic density in the monitored area, it can be provided that the traffic density in the monitored area is detected by the traffic monitoring system.

The traffic density can be determined in the monitored area on the basis of at least one of the measured quantities from the group number of detected vehicles in a specific time span, speed of the detected vehicles and distance from each other of the detected vehicles.

For example, it is possible to determine whether a traffic congestion has arisen or is about to emerge or how high the likelihood of a congestion will be. For this purpose, the concentration of at least one pollutant from the group of carbon monoxide, carbon dioxide, nitrogen monoxide, nitrogen dioxide, ozone and fine dust can be detected by means of the traffic monitoring system as pollutant content in the ambient air in the monitored area. To represent the expected pollutant emissions of the detected vehicle can be made of data of the exhaust emissions of the vehicle type, which were determined by the manufacturer or by third institutions. On the other hand, this can serve the pollutant class of the vehicle. In addition, if the speed of the vehicles is recorded, the expected pollutant emission be determined depending on the speed of the detected vehicle or the average speed of traffic.

It can be provided that meteorological data for the monitored area are determined. For this purpose, it is possible to fall back on already available meteorological data from weather information providers. Alternatively or additionally, the traffic monitoring system can also be configured such that the meteorological rule data are detected by the traffic monitoring system. As meteorological data in the monitored area at least one value from the group air temperature, wind speed, wind direction, air pressure, humidity and humidity rainfall can be detected. Thus, the analysis of the me- teorological data can provide information, among other things, on how the pollutant content, for example due to a prevailing wind, will develop in the future. In this case, such a statement can be made both for the monitored area and for adjacent areas. In this case, the pollutant content of the ambient air in the monitored area is calculated on the basis of the vehicle model. In one embodiment of the method, it can be provided that the calculated pollutant content is compared with the determined pollutant content of the ambient air. Thus, for example, a plausibility check can be made. Here, the determined pollutant content may be based on already available data from information providers or on the basis of measurements by the traffic monitoring system.

In one refinement of the method, the determined data or the data acquired by the traffic monitoring system can be sent to a central station or to user terminals (eg mobile telephones). The central station can serve to generate a current position of the monitored area.

The method can also be used to predict the traffic situation, ie the traffic density in the monitored area, based on the determined data and the data collected by the traffic monitoring system, wherein preferably the predicted traffic situation is used for traffic control. Thus, among other things, congestion situations can be predicted and avoided by suitable measures for traffic control or traffic management. In the case of several traffic monitoring systems, an overall situation of a larger area can also be analyzed and, if necessary, controlled.

The invention is further achieved by a traffic monitoring system for carrying out the method as described above, the traffic monitoring system comprising sensors for detecting and classifying vehicles, sensors for detecting the pollutant content of the environment, and a processing unit for assigning a vehicle model to the vehicles detected vehicles has.

The sensors of the traffic monitoring system can be installed laterally from a roadway or on a bridge or a gantry above the roadway. The traffic monitoring system can be provided as a stationary unit or designed to be mobile, so that it can be used at various areas to be monitored. Alternatively, the sensors can also be arranged in a device for monitoring red light. In addition, it is also conceivable that the traffic monitoring system is part of a vehicle. The sensors can include 3D scanners (Lidar), radars and cameras.

The method described above and the traffic monitoring system described above make it possible to create an intelligent infrastructure for dynamic traffic management in order to manage traffic flows with the distribution of information about the current traffic situation and environmental impact, possibly also with the aid of controllable traffic guidance devices. To steer so that over moderate traffic and environmental pollution in certain places are reduced. The advantage of the present invention is that the data can be made available at short notice and relate to specific monitored areas. Furthermore, the environmental impact can be predicted for the near future due to the vehicle model and the expected pollutant emissions. Furthermore, existing data can be used in order to be able to make the prognosis for a longer period of time in the future. Preferred embodiments of the invention are explained in more detail below with reference to the fi gures. Show here

1 is a plan view of a first embodiment of a traffic monitoring system on a lane with two lanes,

Figure 2 is a plan view of a second embodiment of a traffic monitoring system on a lane with two lanes, and

Figure 3 shows schematic data sets with determined data and from a traffic monitoring system according to Figure 1 detected data.

Figure 1 shows a plan view of a lane 1 with a first vehicle 2, a second vehicle 3 and a third vehicle 4, the track in a direction F in each case in one of two lanes, a right lane 5 and a left lane 6 move.

A traffic monitoring system with a traffic measuring station 7 and a world measuring station 8, are placed on the lane 1. The traffic measuring station 7 with sensors for detecting and classifying vehicles detects vehicles 2, 3, 4 passing through the traffic measuring station 7 and detects, for example, their speed and lane affiliation. The traffic measuring station 7 may be a sta tionäre column or box-shaped device on the side of the lane 1 with a sensor in the form of a laser scanner or lidar system (light detection and ranging system), radar system and / or cameras. Alternatively, the Verkehrsmesssta tion 7 may be a mobile device or vehicle trailer.

The traffic measuring station 7 detects, for example, the height, width and length of the vehicle and the number of axles in order to classify the detected vehicles 2, 3, 4 on the basis of this data. After the vehicle type is recognized by the classification, an assignment of a mathematical vehicle model with the pollutant class or the expected pollutant emissions of the detected vehicle can take place. The detected measured values of the traffic measuring station 7 are for each vehicle in FIG

3 shown in the upper boxes. Here the results in the left box show that the vehicle 2 was assigned the following vehicle model: Vehicle 2 is a car, drives 45 km / h, is on the left lane 6, has the emission class Euro 5 and comes from the district of Darmstadt and transported no dangerous goods. A vehicle model assignment has also been made for the vehicle 3 (car) and vehicle

4 (truck) performed with the values shown in Figure 3. By this classification, an estimate of the pollutant concentration in the ambient air in the monitored area 12 shown in Figure 1 can now be vorgenom men.

Furthermore, in the embodiment shown, meteorological data (for example, precipitation amounts, wind strength, wind direction and air temperature) and air quality data (for example pollutant concentrations of sulfur dioxide, carbon monoxide and particulate matter) are recorded with the environmental measuring station 8, for which the environmental measuring station 8 is provided, inter alia, with sensors designed to detect the pollutant content in the ambient air. The ambient air quality data obtained in this way can be compared with the estimated data and checked for plausibility.

The recorded measured values (environmental measurement data) of the environmental measuring station 8 are shown in FIG. 3 in the lower boxes. The left box shows the meteorological data. On the lane 1, a temperature of 15 ° C was measured, 0% Nie impact detected and a wind with a wind force of 2 Beaufort from south-east cher direction determined.

The air quality data shown in the right box also refer to local measurements in this example. Here, sulfur dioxide (SO2 = 2.0 pg / m ³ ), carbon monoxide (CO = 0.3 mg / m ³ ) and particulate matter (PMio = 16.6 pg / m ³ ) were measured, with the daily mean value of particulate matter at maximum 50 pg / m ³ may lie. For carbon monoxide the daily limit value is 10 mg / m ³ and for sulfur dioxide the maximum limit is 20 pg / m ^{3 of} the annual mean value. All measured and estimated data were collected in the central station 10 and are compared in a data processing unit 11 and tested and / or further processed.

All evaluated data can be sent to a user, for example to a navigation device or to a traffic control center. This purpose is served by a central station which optionally processes the data and distributes it to users (not shown here).

FIG. 2 likewise shows a first vehicle 2, a second vehicle 3 and a third vehicle 4, which move in the direction of travel F on a two-lane roadway 1. The difference from the embodiment according to FIG. 1 is that the traffic measuring station 7 is located above the roadway 1 on a bridge 9 or a gantry. Alternatively, the traffic measuring station 7 can be fastened to a mast be.

LIST OF REFERENCE NUMBERS

1 lane

2 first vehicle

3 second vehicle

4 third vehicle

5 right lane

6 left lane

7 traffic measurement station

8 environmental measuring station

9 bridge

10 central station

1 1 data processing unit

12 monitored area

F direction of travel

Claims

Procedure for traffic monitoring and traffic monitoring system claims

1. Traffic monitoring method in the

the passage of vehicles (2, 3, 4) in a monitored area (12) by means of a traffic monitoring system (7, 8) is detected,

the traffic density in the monitored area (12) is determined, and further the detected vehicles (2, 3, 4) are classified and assigned to each detected vehicle (2, 3, 4) on the basis of the classification a vehicle model is assigned, which expected pollutant emissions of the detected vehicle includes, characterized in that the pollutant content in the ambient air in the monitored area (12) is determined.

2. The method according to claim 1, characterized in that the classification of the detected vehicles (2, 3, 4) based on at least one external feature from the group number of axes, length, width, fleas and identification badge takes place.

3. The method according to any one of claims 1 or 2, characterized in that the vehicle model includes the expected noise emissions of the detected vehicle.

4. The method according to any one of claims 1 to 3, characterized in that the traffic density and / or the pollutant content of the ambient air in the monitored area (12) by means of the traffic monitoring system (7) is detected.

5. The method according to any one of claims 1 to 4, characterized in that the traffic density in the monitored area (12) by means of traffic monitoring system (7) based on at least one of the measured variables from the group number of detected vehicles (2, 3, 4) in a certain time span, speed of the detected vehicles (2, 3, 4) and distance of consecutive detected vehicles (2, 3, 4) is detected.

6. The method according to any one of claims 1 to 5, characterized in that as the pollutant content of the ambient air in the monitored area (12) the concentration of at least one pollutant from the group Kohlenstoffmo noxide, carbon dioxide, nitrogen monoxide, nitrogen dioxide, ozone and fine dust by means of the traffic monitoring system ( 8) is detected.

7. The method according to any one of claims 1 to 6, characterized in that noise emissions are determined in the monitored area.

8. The method according to any one of claims 1 to 7, characterized in that meteorological data for the monitored area (12) are determined.

9. The method according to claim 8, characterized in that as meteorological data in the monitored area (12) at least one value from the group air temperature, wind speed, wind direction, air pressure, humidity and precipitation amount by means of Verkehrsüberwachungsan position (8) is detected.

10. The method according to any one of claims 1 to 9, characterized in that based on the vehicle model, the pollutant content of the ambient air in the monitored area (12) is calculated.

1 1. A method according to claim 10, characterized in that the calculated pollutant content is compared with the determined pollutant content of the ambient air.

12. The method according to any one of claims 1 to 11, characterized in that the future pollutant content in the ambient air in the monitored Be rich (12) and / or in adjacent areas based on the vehicle models of the detected vehicles (2, 3, 4) and on basis the data on the traffic density and / or the determined pollutant content in the ambient air is predicted.

13. The method according to any one of claims 1 to 12, characterized in that the determined data and the traffic monitoring system (7, 8) detected data are sent to a central station (10) or to user terminals.

14. The method according to any one of claims 1 to 13, characterized in that on the basis of the determined data and of the traffic monitoring system (7, 8) detected data, the traffic situation is predicted, with preference, the predicted traffic situation is used for traffic control.

15. Traffic monitoring system for carrying out the method according to one of claims 1 to 14, wherein the traffic monitoring system has the following:

Sensors (7) for detecting and classifying vehicles,

Sensors (8) for detecting the pollutant content of the ambient air, and a data processing unit for assigning a vehicle model to the detected vehicles (2, 3, 4).