WO2012024957A1 - Procédé pour la fusion de données de courant de circulation en temps réel et dispositif pour celui-ci - Google Patents

Procédé pour la fusion de données de courant de circulation en temps réel et dispositif pour celui-ci Download PDF

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Publication number
WO2012024957A1
WO2012024957A1 PCT/CN2011/075408 CN2011075408W WO2012024957A1 WO 2012024957 A1 WO2012024957 A1 WO 2012024957A1 CN 2011075408 W CN2011075408 W CN 2011075408W WO 2012024957 A1 WO2012024957 A1 WO 2012024957A1
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WO
WIPO (PCT)
Prior art keywords
road
state
real
trust
traffic flow
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.)
Ceased
Application number
PCT/CN2011/075408
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English (en)
Chinese (zh)
Inventor
夏伟
魏俊华
胡健
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Beijing Cennavi Technologies Co Ltd
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Beijing Cennavi Technologies Co Ltd
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Application filed by Beijing Cennavi Technologies Co Ltd filed Critical Beijing Cennavi Technologies Co Ltd
Publication of WO2012024957A1 publication Critical patent/WO2012024957A1/fr
Anticipated expiration legal-status Critical
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Classifications

    • 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
    • G08G1/02—Detecting movement of traffic to be counted or controlled using treadles built into the road
    • 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
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control

Definitions

  • FIG. 2 is a schematic diagram of an operation speed and a road condition state of acquiring a road by using a coil according to Embodiment 1 of the present invention
  • the embodiment shown in FIG. 1 provides a real-time traffic flow data fusion method, which specifically includes the following steps: 1 01. Calculate, according to each real-time traffic flow data of the at least two real-time traffic flow data, a road state S and a running speed V corresponding to the road under each of the real-time traffic flow data.
  • the method for calculating the corresponding road state S and the running speed V of the road under each of the real-time traffic flow data is different, and the following describes how to calculate the road in the FCD, traffic, respectively.
  • Corresponding road state S and running speed V under flow induction coil data and event information data is different, and the following describes how to calculate the road in the FCD, traffic, respectively.
  • Step 3 Through map matching, the path is estimated to get the path corresponding to all GPS points of each vehicle. Specifically, it can be realized by the following methods: Selecting the possible matching roads based on the latitude and longitude coordinates of the GPS points, generally there are multiple, filtering the roads that are too large with the angle of the road through the direction of the GPS points, and the time passing through the GPS points The order and the road connection are determined to match the road.
  • the vehicle detector can obtain the time T1 passing through the first coil and the time T2 passing through the second coil, respectively, assuming the two adjacent coils.
  • the actual distance is D
  • the road state S is obtained based on the operating speed.
  • Event information data is usually collected by hand, and can be divided into internal collections and field collections.
  • the internal collection mainly collects traffic information from FM stations or collects data through video observations.
  • the field collection mainly depends on the collection. Personnel manually visualize the specific road traffic flow conditions. Both of these methods can directly obtain a more accurate road state S, but the running speed V is generally based on the road condition.
  • the state of the road condition mentioned in the embodiment of the present invention includes: smooth, slow, or congested.
  • the road state S is specifically: when the running speed V is less than 20 km/h, determining that the road state S is congested; when the running speed V is greater than or equal to 20 km/h and less than 40 km/h, determining that the road state S is slow; When the running speed V is greater than or equal to 40 km/h, it is determined that the road condition state S is unblocked.
  • this step can be implemented by the following sub-steps (not shown):
  • 102B Determine a trust degree corresponding to each real-time traffic flow data according to a conversion formula and a state accuracy rate of each of the real-time traffic flow data within a preset time range.
  • step 102 determines that the trustworthiness of each of the four real-time traffic flow data is as shown in Table 2:
  • the trust degree of the road in the road condition state in this step is: the sum of trust degrees corresponding to all real-time traffic flow data used when calculating the road state. The following describes in detail how to calculate the trust of the road under various road conditions.
  • the road state S having the highest trust degree is used as the current road condition of the road. a state, and calculating a current running speed of the road according to the running speed V corresponding to the road in the road state S with the highest degree of trust.
  • the current running speed V of the road G is calculated by the following process: ⁇ using the weighted average value of the road running speed V corresponding to the road state with the highest trust state as the current state of the road The running speed, wherein the weight value is a trust degree corresponding to the real-time traffic flow data used when calculating the running speed V.
  • the corresponding running speeds of the road G in the slow state are 21 km/h, 29 km/h and 27 km/h, respectively, and the calculation results are "21 km/h”.
  • the real-time traffic flow data is "FCD2", and the real-time traffic flow data used when calculating "29 km/h” is “coil”, and the real-time traffic flow data used when "27 km/h” is calculated is " Event "; according to Table 2, the "FCD2" corresponds to a degree of trust of 5, the "coil” corresponds to a degree of trust of 10, and the “event” corresponds to a degree of trust of 9.
  • the difference between the trust degree of the highest trust state of the road state and the trust state of the road state state with the second highest trust state is less than a preset threshold, according to the running speed of the road under each of the real-time AC data. Recalculating the current running speed of the road and determining the current road state of the road according to the current running speed.
  • FCD 1 represents the floating car data obtained from company 1
  • FCD2 represents the floating car data obtained from company 2
  • coil represents traffic flow induction coil data
  • event represents event information data.
  • the state of the road with the highest degree of trust is unblocked, and the corresponding trust degree is 1 5; the state of the road with the second highest degree of trust is slow, and the corresponding trust degree is also 15 .
  • the difference is less than the preset threshold of 7.5, and the difference may be less than the preset threshold of 7.5.
  • a corresponding running speed V under real-time AC data is recalculated to obtain a current running speed of the road, and a current road condition state of the road is determined according to the current running speed.
  • a weighted average of the running speed V of the road under each of the real-time AC data may be used as the current running speed of the road, where the weight value is In order to calculate the trust degree corresponding to the real-time traffic flow data used when the running speed V is obtained.
  • the current running speed of the road raft is calculated by taking the application scenario 2 as an example.
  • the running speed V of the road w under the four kinds of real-time AC data is: 45 km. /h, 30 km/h, 21 km/h, 50 km/h.
  • the embodiment of the present invention obtains different trust degrees according to the state accuracy of different real-time traffic flow data, and obtains the current degree of trust by analyzing the trust distribution of the road in each road state and the weighted average of the trust. Running speed and traffic status.
  • the road condition information obtained by one of the traffic flow data is used as the current road condition information of the road, and the embodiment of the present invention can effectively utilize the accuracy of various real-time traffic flow data, thereby improving the road condition information of the road. accuracy.
  • the foregoing method may further include the following step 106: 106. Verify, by using the event information data, the current road state and the current running speed of the calculated road.
  • Re-verification using event information data is mainly to verify the restricted class information. For example, when a restricted traffic event occurs on a road, the road should not have traffic flow information. For example, when an unexpected event that causes congestion is present, the threshold value of the running speed corresponding to the road state can be lowered by referring to the speed value on the road, so that the state tends to be congested.
  • an embodiment of the present invention provides a real-time traffic flow data fusion apparatus, including: a first processing unit 11, a second processing unit 12, a determining unit 13, a state fusion unit 14, and a speed fusion unit 15.
  • the first processing unit 11 is configured to sequentially calculate, according to each real-time traffic flow data of the at least two real-time traffic flow data, a road state S and a corresponding road condition corresponding to each real-time traffic flow data.
  • Speed V is configured to sequentially calculate, according to each real-time traffic flow data of the at least two real-time traffic flow data, a road state S and a corresponding road condition corresponding to each real-time traffic flow data.
  • the second processing unit 12 is configured to sequentially determine the reliability corresponding to each of the real-time traffic flow data
  • the determining unit 13 is configured to determine the trust degree of the road in each road condition state; the state fusion unit 14 is configured to: when the trust degree of the road state with the highest trust degree and the trust state of the road state state with the second highest trust degree are not smaller than Presetting a threshold value, using the road state S having the highest degree of trust as the current road state of the road, and according to the road, the trust degree is the most
  • the running speed V corresponding to the high road condition S calculates the current running speed of the road;
  • the speed fusing unit 15 is used for the trust degree of the road state with the highest trust degree and the trust state of the road state with the second highest trust degree.
  • the difference is less than the preset threshold, and the current running speed of the road is recalculated according to the corresponding running speed V of the road under each of the real-time AC data, and the road is determined according to the current running speed. Current traffic status.
  • the second processing unit may perform function subdivision (not shown), and specifically includes: a calculation module and a conversion module.
  • the calculation module is configured to sequentially calculate a state accuracy rate of each of the real-time traffic flow data within a preset time range; and the conversion module is configured to sequentially perform the data according to the conversion formula and each of the real-time traffic flow data.
  • the state fusion unit specifically uses the value obtained by weighting and averaging the corresponding running speed V of the road in the road state with the highest trust degree as the current running speed of the road.
  • the weight value is a trust degree corresponding to the real-time traffic flow data used when calculating the running speed V.
  • the speed fusing unit specifically uses the weighted average of the running speed V of the road under each of the real-time AC data as the current running speed of the road, wherein the weight value is calculated and calculated.
  • the letter corresponding to the real-time traffic flow data used when the running speed V is used Ten degrees.
  • the above apparatus may further include: an inspection unit 16.
  • the checking unit 16 is configured to verify the current road state and the current running speed of the calculated road using the event information data.
  • the real-time traffic flow data fusion device provided by the embodiment of the present invention combines at least two real-time traffic flow data to calculate the current road state and the running speed of the road, and the at least two traffic flow data respectively correspond to different trust degrees.
  • the road condition information obtained by selecting one of the traffic flow data is used as the current road condition information of the road, and the embodiment of the present invention can effectively utilize the accuracy of various real-time traffic flow data, thereby improving the road condition information of the road. The accuracy.
  • the embodiments of the present invention are mainly applied to the process of integrating real-time traffic flow data, and can improve the accuracy of the road condition information of the road.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Traffic Control Systems (AREA)

Abstract

L'invention porte sur un procédé de fusion de données de courant de circulation en temps réel et sur un dispositif pour celui-ci. Le procédé met en œuvre : la détermination du niveau de confiance de la route dans différents états de condition de route ; lorsque la différence entre le niveau de confiance de l'état de condition de route avec le niveau de confiance le plus élevé et le niveau de confiance de l'état de condition de route avec le niveau de confiance élevé secondaire n'est pas inférieure à un seuil prédéterminé, l'adoption d'un état de condition de route S avec le niveau de confiance le plus élevé comme état de condition de route actuel de la route, et la détermination de la vitesse de circulation actuelle de la route en fonction d'une vitesse de circulation correspondante V de la route sous l'état de condition de route S avec le niveau de confiance le plus élevé ; et, sinon, le recalcul de la vitesse de circulation actuelle de la route en fonction de la vitesse de circulation correspondante V de la route sous chaque type de données de courant de circulation en temps réel, et la détermination de l'état de condition de route actuel de la route en fonction de la vitesse de la circulation actuelle.
PCT/CN2011/075408 2010-08-23 2011-06-07 Procédé pour la fusion de données de courant de circulation en temps réel et dispositif pour celui-ci Ceased WO2012024957A1 (fr)

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CN2010102606037A CN101937616B (zh) 2010-08-23 2010-08-23 实时交通流数据融合方法及装置
CN201010260603.7 2010-08-23

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Publication number Priority date Publication date Assignee Title
CN101937616B (zh) * 2010-08-23 2012-06-27 北京世纪高通科技有限公司 实时交通流数据融合方法及装置
CN102063793B (zh) * 2011-01-12 2012-10-31 上海炬宏信息技术有限公司 检测路况信息的方法和系统
CN102568208B (zh) * 2012-02-07 2014-01-01 福建工程学院 基于浮动车技术的路段限速信息识别方法
CN102737502A (zh) * 2012-06-13 2012-10-17 天津大学 基于gps数据的道路交通流预测方法
CN102930735A (zh) * 2012-10-25 2013-02-13 安徽科力信息产业有限责任公司 一种基于交通视频的城市实时交通路况信息发布方法
CN105070058B (zh) * 2015-08-11 2017-09-22 甘肃万维信息技术有限责任公司 一种基于实时路况视频的精准路况分析方法及系统
CN107798864A (zh) * 2016-09-06 2018-03-13 高德信息技术有限公司 一种道路通行速度的计算方法和装置
CN108346303B (zh) * 2018-04-09 2021-06-11 天津中兴智联科技有限公司 一种公交车识别和定位的实现方法及实现系统
CN112419712B (zh) * 2020-11-04 2021-12-10 同盾控股有限公司 道路断面车速检测方法及系统

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