EP2447924A1 - Système d'établissement de la situation de trafic sur une voie de circulation - Google Patents

Système d'établissement de la situation de trafic sur une voie de circulation Download PDF

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Publication number
EP2447924A1
EP2447924A1 EP11186461A EP11186461A EP2447924A1 EP 2447924 A1 EP2447924 A1 EP 2447924A1 EP 11186461 A EP11186461 A EP 11186461A EP 11186461 A EP11186461 A EP 11186461A EP 2447924 A1 EP2447924 A1 EP 2447924A1
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EP
European Patent Office
Prior art keywords
traffic
section
vehicle
road
measuring cross
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
EP11186461A
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German (de)
English (en)
Other versions
EP2447924B1 (fr
Inventor
Peter Aicher
Jürgen Mück
Thomas Sachse
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Siemens Mobility GmbH
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Siemens AG
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Publication of EP2447924A1 publication Critical patent/EP2447924A1/fr
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Publication of EP2447924B1 publication Critical patent/EP2447924B1/fr
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count

Definitions

  • the invention relates to a system for determining the traffic situation on a road section according to the preamble of claim 1.
  • the traffic situation On roads, for example on sections of a motorway, the traffic situation should be described as accurately as possible. This concerns both the current traffic situation and the tendency of a changing traffic situation in order to be able to recognize incidents as early as possible.
  • the vehicle traffic on the road has to be detected. This is done by trackside arranged traffic detectors, the local - ie at the point at which they are arranged - capture the traffic situation.
  • trackside arranged traffic detectors the local - ie at the point at which they are arranged - capture the traffic situation.
  • Data transmission means transmit the locally detected traffic data from the traffic detectors to an evaluation device.
  • the traffic volume and from the detected speeds an average speed for a measuring cross section is obtained.
  • a differential analysis of the traffic loads at the start of the line and at the end of the line can be used to conclude that a potential incident has occurred.
  • the invention is therefore based on the object to provide a system of the type mentioned, which allows an improved determination of the traffic situation on a road.
  • the traffic detectors are also designed to detect, from a vehicle passing through the respective measuring cross-section, a distinguishing characteristic that can be uniquely assigned to this vehicle and a passage time, and to transmit them to the evaluation device by means of the data transmission means.
  • the evaluation device can be arranged locally on one of the two measuring cross-sections or in a route station, a sub-center or a traffic control center.
  • the evaluation device comprises analysis means which are designed to compare detection characteristics detected at the first and second measurement cross-sections and to calculate an average travel time and / or an average travel speed for the road route from the passage times of matching recognition features.
  • a vehicle identification feature which can also be detected anonymously - that is, with no possibility of inferring the driver or the holder of the vehicle - an individual vehicle that has entered the road section through the first measuring cross section can be recognized when it exits through the second measuring cross section .
  • the travel time of this vehicle can be calculated.
  • an average travel time for the road route can be calculated.
  • the mean travel time is then known route length and a mean cruising speed of the vehicles available, which can be compared for improved determination of the traffic situation with the local average speeds at the beginning and end of the road.
  • the traffic detectors are adapted to record a series of digital video images of the respective measuring cross section and to capture by image evaluation means a passage of a vehicle, a passage time of the vehicle passage, a speed of the passing vehicle and a vehicle registration number of the passing vehicle as traffic data.
  • image evaluation algorithms known per se, in addition to the detection of a vehicle passage and its time, the speed of the vehicle and identification features, such as the official license plate number indicated on the license plate, can also be detected via optical pattern recognition, the color or the dimensions of a vehicle.
  • the traffic detectors may be implemented as a combination of known, possibly already installed detectors for detecting local traffic data and from video cameras with automatic number plate recognition. However, it is sufficient to arrange only one video detector at each of the measuring cross sections, which then acquires all the traffic data mentioned via the image evaluation means, which is advantageous in the case of new installations or the replacement of defective traffic detectors.
  • the image evaluation means of the traffic detectors are further adapted to from the recorded series of digital video images of the respective measuring cross section a lane used by the passing vehicle and / or a Vehicle class of the passing vehicle to capture as traffic data.
  • these detect a plurality of lanes of a lane and, with appropriate image analysis, can provide traffic data for a more detailed analysis of the traffic situation, taking into account the individual lanes.
  • An improved analysis of the traffic situation is also possible by recording the vehicle class, ie two-wheelers, passenger cars, trucks, buses, etc., which can also be easily determined by digital image analysis from the recorded video images.
  • the vehicle class can also be used as part of the recognition feature of a vehicle in order to obtain greater security in the central comparison of the recognition features.
  • the analysis means are designed to calculate a speed profile for the road section from average speeds at the measuring cross sections and the average cruising speed.
  • a linear velocity profile extending over the road, which has as boundary values the locally measured mean velocities at the measuring cross sections.
  • the boundary values are still assumed, but the speed profile may change if the mean cruising speed does not correspond to the mean of the boundary values. If the mean cruising speed is greater or less than the mean value of the boundary values, the actual speed profile is a curve with a convex or concave section.
  • the analysis means of the system according to the invention are designed to conclude from a concave velocity profile to an incident on the road.
  • a concave velocity profile assumes that the mean cruising speed is less than the mean of the boundary values, and may even be less than both boundary values.
  • the boundary values are the same so far, it was previously assumed that the cruising speed is constant across the road, and at a correspondingly high speed value, it was concluded that the traffic flow was trouble-free.
  • the mean cruising speed is less than the margins, it can be concluded that the actual vehicle speed inside the road has to be well below the mean cruising speed. If these conditions are very pronounced, it can be concluded on a road accident.
  • the analysis means are designed to calculate traffic densities and therefrom levels of traffic quality from traffic intensities and average speeds at the measurement cross sections.
  • the traffic density indicates the number of vehicles per kilometer of track length and results from the quotient of traffic volume and average speed for a measuring point. With medium speed, it forms the basis for determining the traffic quality according to six quality levels, as described in Manual for the Design of Road Traffic Facilities "(HBS 2001 ), the Research Association for Road and Transportation eV, Cologne, are published.
  • traffic density and average speed form the basis for determining the traffic situation according to four traffic levels, as published in "Leaflet for the equipment of traffic computer centers and sub-centers" (MARZ 99), the Federal Highway Research Institute, Bergisch Gladbach.
  • Vk diff for the section related accident detection, which also depends on the traffic densities and the mean speeds at the ends of the lines.
  • the analysis means are designed to calculate an individual travel time for the road route from the passage times of matching identification features and to determine from the standard deviation of the individual travel times indications of the traffic situation on the road. For example, a large spread of individual travel times can be an indication of unbound traffic on the road.
  • the analysis means are designed to calculate the traffic intensity on a ramp located between the measurement cross sections for lateral entry into the road or for exit therefrom by the recognition features of vehicles passing the first measurement cross section with the recognition features of be matched to the second measuring cross-section passing vehicles.
  • the ramp traffic intensities are of particular interest for traffic planning and traffic-dependent traffic control.
  • the traffic intensity on an entrance ramp results from the vehicles that leave the road section through the second measuring cross-section, but are not retracted there by the first measuring cross-section.
  • the traffic intensity on an exit ramp results from the vehicles which have entered the road section through the first measuring cross section, but do not extend through the second measuring cross section.
  • the information about the strength of the traffic streams interlinking or dividing at a ramp further improves the determination of the traffic situation on such a road section.
  • an inventive system for determining the traffic situation on a road S for example, a section of a highway with a right lane S1 and a left lane S2, as roadside infrastructure at least a first traffic detector 10 and downstream of a second traffic detector 20.
  • the first traffic detector 10 is arranged on a first measuring cross-section 1 of the road section S in order to detect vehicles F entering the road S when they pass the first measuring cross-section 1.
  • the second traffic detector 20 is arranged on a second measuring cross section 2 of the road S to detect vehicles F exiting the road S when passing through the second measuring cross section 2.
  • the measuring sections 1 and 2 limit the road S with a length d of several kilometers.
  • the traffic detectors 10 and 20 are designed as video detectors which record a series of digital video images of the first or second measuring cross section 1 or 2 and forward them to digital image evaluation means connected to image evaluation means 11 and 21, respectively.
  • the image evaluation means 11 and 21 have not shown computer and memory means which are set up to execute image evaluation algorithms.
  • the evaluation of a series of images belonging to a vehicle F passing through a measuring cross-section 1 or 2 delivers the passage time t, the speed v, an identification feature z, the vehicle class k and the used lane Sn, n stands for 1 or 2 as a local traffic data set , of the passing vehicle F.
  • the detected traffic data are analyzed in an evaluation device 30, which may be located locally at one of the two measuring sections 1 or 2 or in a route station, a sub-center, a motorway control center or other traffic control center, to determine the traffic situation on the road section S.
  • the evaluation device 30 is in communication communication with the traffic detectors 10 and 20, for example for wireless data transmission according to the general packet-oriented radio service, in short GPRS.
  • the data transmission means 40 required for this purpose are known per se and are not shown in detail.
  • Local traffic intensities and average speeds are calculated from the detection of the number of vehicles F passing through a measuring cross-section 1 or 2 in a measuring interval and their velocities v. From this, local traffic densities are calculated as the quotient of traffic intensity and average speed.
  • the previously collected with known traffic detectors local traffic data for the determination of the traffic situation are provided. Qualified statements about the traffic quality (level of service) and the traffic situation according to the traffic levels "free traffic”, “dense traffic”, “slow-moving traffic” and "traffic jam” can already be made from these traffic variables.
  • a distance analysis of the traffic loads at the beginning and at the end of the road S for example on the Störkennster Vk diff , feasible. Through them, if in a time interval significantly more vehicles F drive into the road S than move out of it, be closed to a fault.
  • the traffic detectors 10 and 20 are designed to record further traffic data, which contribute to a more accurate determination of the traffic situation.
  • the traffic detectors 10 and 20 identify features z of the respective measuring cross section 1 and 2, respectively Vehicles F detects what allows recognition of a vehicle F detected on the first measuring cross section 1 at the second measuring cross section 2.
  • Identification feature z that uniquely identifies a vehicle F can be the official motor vehicle license plate, which can be read out of the video images via optical pattern recognition algorithms.
  • the color or the dimensions of a vehicle F can serve as alternative or additional recognition features z.
  • the passage time t and the speed v of the passing vehicle F are detected as a local traffic data set and transmitted to analysis means 31 of the evaluation device 30, these traffic data sets can be checked centrally for matching recognition features z.
  • the difference of the passage times t from data records with matching recognition features z then gives the individual travel time of the traffic data sets associated vehicle F for the road S. From the known route length d then follows directly the individual cruising speed of the vehicle. If the average of individual travel times and travel speeds originating from a measurement interval is formed, one obtains an average travel time and a mean cruising speed v 12 for the road route S. From the scattering or standard deviation of the individual travel times, further conclusions can be drawn regarding the traffic situation on the road S to be pulled. Thus, a strong spread of travel times is an indication of an unbound traffic on the road S is.
  • the average cruising speed v 12 is used to obtain a more accurate velocity profile v (s).
  • the diagram shows the course of the velocity v (s) as a function of the distance s along the road-distance S.
  • the speed v (0) and v (d) is the mean velocities v 1 and v 2 .
  • v 1 is slightly larger as v 2 , indicating a slowdown in traffic towards the exit.
  • a linear progression has been assumed hitherto, which is represented by the solid line.
  • the traffic situation analyzes can be further refined by taking into account the vehicle class k and / or the lane Sn used in the traffic data collected. All statements can then be made specifically for the different vehicle classes or groups of vehicle classes or separately for each of a multi-lane road segment S.
  • a ramp R for lateral entry into the road S, as in FIG. 1 represented, or for the exit therefrom, the traffic volume on the ramp R can be calculated with the system according to the invention in an advantageous manner.
  • the identification features z of the first measuring cross section 1 passing vehicles F with the recognition features z of the second measuring cross section 2 passing vehicles F are to be compared.
  • the traffic volume on the entry ramp R shown results from the vehicles F, which leave the road- ⁇ stretch S through the second measuring cross-section 2, but not retracted by the first measuring section 1. Accordingly, the traffic intensity results on an exit ramp from the vehicles F, which are retracted into the road section through the first measuring cross section 1, but do not extend through the second measuring cross section 2.
  • the traffic situation determined according to the invention and its tendency to change are included in the traffic-dependent control of, for example, variable traffic signs, which impose speed restrictions - possibly lane-related - or can also output information texts about a prevailing dangerous situation in order to influence drivers of vehicles F on or upstream of the road stretch S.
  • the system according to the invention also contributes considerably to traffic safety.
  • the traffic situation is more accurate with only one type of traffic detector and thus can be determined inexpensively.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Traffic Control Systems (AREA)
EP11186461.7A 2010-10-29 2011-10-25 Système d'établissement de la situation de trafic sur une voie de circulation Not-in-force EP2447924B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102010049763 2010-10-29
DE102010062025A DE102010062025A1 (de) 2010-10-29 2010-11-26 System zur Ermittlung der Verkehrssituation auf einer Straßenstrecke

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EP2447924A1 true EP2447924A1 (fr) 2012-05-02
EP2447924B1 EP2447924B1 (fr) 2018-03-28

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103280109A (zh) * 2013-06-08 2013-09-04 北京云星宇交通工程有限公司 旅行时间的获取方法及装置、预测系统
EP2874132A3 (fr) * 2013-09-27 2015-12-09 Thales Holdings UK Plc Appareil et procédé de gestion de trafic
CN109035772A (zh) * 2018-08-08 2018-12-18 上海工程技术大学 基于收费数据的高速公路交通运行态势识别方法和装置
CN113935158A (zh) * 2021-09-27 2022-01-14 北方工业大学 一种针对高速公路事故多发点的交通检测器优化布设方法

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103021181B (zh) * 2012-12-30 2014-10-08 西安费斯达自动化工程有限公司 基于宏观离散交通流模型的交通拥堵监控预报方法
EP2887332B1 (fr) 2013-12-23 2016-09-07 Siemens Aktiengesellschaft Procédé et système de détermination d'une situation de trafic sur une voie de circulation
CN107909813A (zh) * 2017-10-09 2018-04-13 宁波工程学院 一种道路车辆车速及车间时距检测系统及方法

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EP0978811A2 (fr) * 1998-08-07 2000-02-09 Siemens Aktiengesellschaft Procédé et appareil de saisie de durée de trajets de véhicules
WO2001069569A2 (fr) * 2000-03-15 2001-09-20 Raytheon Company Systeme automatique predictif de detection d'accident utilisant une identification automatique de vehicules
WO2009030892A2 (fr) * 2007-09-05 2009-03-12 Trw Limited Surveillance de la circulation
WO2010097325A1 (fr) * 2009-02-27 2010-09-02 Siemens Aktiengesellschaft Procédé et système de détection d'incidents sur un tronçon de route

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103280109A (zh) * 2013-06-08 2013-09-04 北京云星宇交通工程有限公司 旅行时间的获取方法及装置、预测系统
EP2874132A3 (fr) * 2013-09-27 2015-12-09 Thales Holdings UK Plc Appareil et procédé de gestion de trafic
CN109035772A (zh) * 2018-08-08 2018-12-18 上海工程技术大学 基于收费数据的高速公路交通运行态势识别方法和装置
CN113935158A (zh) * 2021-09-27 2022-01-14 北方工业大学 一种针对高速公路事故多发点的交通检测器优化布设方法
CN113935158B (zh) * 2021-09-27 2024-04-09 北方工业大学 一种针对高速公路事故多发点的交通检测器优化布设方法

Also Published As

Publication number Publication date
EP2447924B1 (fr) 2018-03-28
DE102010062025A1 (de) 2012-05-03

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