WO2016197936A1 - Procédé de prédiction d'état de circulation et de temps de déplacement - Google Patents

Procédé de prédiction d'état de circulation et de temps de déplacement Download PDF

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Publication number
WO2016197936A1
WO2016197936A1 PCT/CN2016/085202 CN2016085202W WO2016197936A1 WO 2016197936 A1 WO2016197936 A1 WO 2016197936A1 CN 2016085202 W CN2016085202 W CN 2016085202W WO 2016197936 A1 WO2016197936 A1 WO 2016197936A1
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WO
WIPO (PCT)
Prior art keywords
traffic
segmented
traffic conditions
time
roads
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PCT/CN2016/085202
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English (en)
Chinese (zh)
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刘光明
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刘光明
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Publication of WO2016197936A1 publication Critical patent/WO2016197936A1/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
    • G08G1/0125—Traffic data processing
    • G08G1/0133—Traffic data processing for classifying traffic situation
    • 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

Definitions

  • the present invention relates to maps and navigation, and more particularly to predicting traffic conditions and travel times.
  • multiple candidate driving routes are provided. For these multiple candidate routes, electronic navigation will estimate the time that may be needed for people to refer to when selecting a route. However, the estimated time for electronic navigation is generally based on current traffic conditions. Since the traffic condition when the route is selected is not equal to the traffic situation when actually traveling to the road section, the estimated time actually differs from the time taken by the route when actually traveling.
  • a method of embodying a predicted traffic condition on a map comprising the steps of: segmenting a road on a map; and obtaining a current intersection of each of the segmented roads Traffic conditions of the current situation and the previous time; based on the current traffic conditions and the traffic conditions of the previous time, calculate the traffic trend of each segmented road; estimate the segments based on the current traffic conditions and traffic trends of each segmented road The traffic conditions of the road in the future; and the traffic conditions of the estimated future time of each segmented road are presented on the map.
  • the traffic condition is a traffic speed
  • the traffic condition change trend of each segment road is calculated by comparing the current traffic speed with the traffic speed of the previous time.
  • the traffic condition is a congestion index
  • the traffic condition change trend of each segment road is calculated by comparing the current congestion index with the congestion index of the previous time.
  • the traffic conditions of the future time of each of the segmented roads are estimated based on events to be occurred on each of the segmented roads in the future.
  • the segmented roads on the map with different traffic conditions are presented in different colors.
  • a method for predicting travel time comprising the steps of: identifying one or more candidate driving routes on a map according to a departure place and a destination; and classifying each candidate driving route a segment; obtaining a current traffic condition of each segmented road of each candidate driving route and a traffic condition of a previous time; calculating each candidate based on the current traffic condition of each segmented road of each candidate driving route and the traffic condition of the previous time Traffic trend of each segmented road of the driving route; estimating the time of each segment reaching each segmented road according to the current traffic situation; estimating each segment based on the current traffic conditions and traffic conditions of each segmented road a traffic condition of the road at the estimated time of arrival; estimating the travel time of each of the segmented roads of each of the candidate driving routes based on the traffic conditions of the respective segmented roads at the estimated time of arrival; and each of each of the candidate driving routes
  • the total travel time is estimated by the travel time of the segmented road.
  • the traffic condition is a traffic speed
  • the traffic condition change trend of each segment road is calculated by comparing the current traffic speed with the traffic speed of the previous time.
  • the traffic condition is a congestion index
  • the traffic condition change trend of each segment road is calculated by comparing the current congestion index with the congestion index of the previous time.
  • the traffic conditions of the future time of each of the segmented roads are estimated based on events to be occurred on each of the segmented roads in the future.
  • the total travel time of each candidate driving route is obtained by adding the travel times of the respective divided roads of each of the candidate driving routes.
  • FIG. 1 is a flow chart of a method of embodying a predicted traffic condition on a map in accordance with an embodiment of the present invention.
  • FIG. 2 is a flow chart of a method of predicting travel time in accordance with an embodiment of the present invention.
  • FIG. 1 is a flow chart 100 of a method of embodying a predicted traffic condition on a map in accordance with an embodiment of the present invention.
  • the road on the map is first segmented.
  • the current electronic maps basically segment the roads on the map to indicate different traffic conditions.
  • the segmentation of the road may be based on distance, for example, every 1 km or every 500 meters, 100 meters, 50 meters, 10 meters, or any other suitable distance as a segment; the segmentation of the road may also be based on the setting of the traffic light, for example, The road between every two (or more) traffic lights is a segment; the segmentation of the road can also be based on the planning of the block, for example, each block, the road between each intersection as a segment.
  • step 103 the current traffic conditions of the respective segmented roads and the traffic conditions of the previous time are obtained.
  • the physical quantity reflecting the traffic condition may be the driving speed or the congestion index.
  • the speed of 40-60 km per hour can be considered as smooth.
  • the speed of 20-40 km per hour can be considered as slow driving.
  • the speed of 20 km or less can be considered as congestion.
  • the speed of 5 km or less can be considered as serious. Congestion, and so on.
  • the congestion index is used as the physical quantity reflecting the traffic situation. For example, a congestion index of 0-10 can be used.
  • the congestion index may be obtained based on the traveling speed of the car passing through the road section within a certain period of time, or may be obtained based on the number of cars connected to each other through the end of the road section within a certain period of time.
  • the current traffic condition such as the traffic speed or congestion index of the road section
  • the current traffic condition can be obtained through public real-time data measured by the local traffic jurisdiction.
  • the traffic condition of the road section at the previous time can be found, for example, the traffic speed or congestion index of the road section at that time.
  • a period of time may refer to 5 minutes, 10 minutes, 15 minutes, or any other suitable period of time.
  • the traffic condition change trend of each segmented road is calculated.
  • the current traffic condition is compared to the traffic condition of the previous time to calculate a trend of traffic conditions for each of the segmented roads.
  • the trend of traffic conditions may be a trend of speed, that is, comparing the current traffic speed with the traffic speed of the previous time.
  • the current transit speed is communicated with the previous time.
  • the difference between the line speeds is compared with the speed of the previous time, and the ratio obtained is the speed change trend index.
  • the current speed of a road section is 40 km/h, and the speed of traffic before 15 minutes is 50 km/h.
  • a congestion index eg, between 0 and 10 the greater the value indicating more congestion
  • the above-mentioned speed change trend index and congestion change trend index are examples of trends in traffic conditions.
  • the traffic conditions of the previous time may be a plurality of traffic conditions of the previous time. Therefore, it is possible to obtain a curve of the trend of traffic conditions by traffic conditions at several time points.
  • users want to predict traffic conditions in the future, such as predicting traffic conditions after 30 minutes. If it is currently 16:00, the user wants to predict traffic conditions after 30 minutes, ie 16:30.
  • the traffic conditions of the future time of each of the segmented roads are estimated based on the current traffic conditions of each of the segmented roads and the trend of the traffic conditions.
  • a traffic situation of 16:30 should be predicted at 16:00, and the traffic condition at 16:00 can be multiplied by (1 + traffic trend (eg traffic trend) * time ratio) This is estimated to have a traffic situation of 16:30.
  • the process can be calculated as follows:
  • step 105 the example adopted in step 105 is adopted, that is, the current traffic condition is a vehicle speed of 30 km/h or a congestion index of 4.0, and the traffic condition change trend within 15 minutes is a speed change trend index + 0.25 and a congestion change trend index -0.20 .
  • the future time should match the time used to calculate the trend of change. For example, to predict traffic conditions after 30 minutes, the trend within 15 minutes can be used instead of the trend within 5 minutes. In particular, for larger time spans, such as half an hour or more, the trend curve (curve fit) should be used to estimate and apply the trend of change.
  • a road section will be traffic controlled (for example, restricted traffic) at 16:30 due to foreign affairs activities.
  • traffic controlled for example, restricted traffic
  • the estimated traffic conditions for the future time of each of the segmented roads are presented on the map.
  • each segmented road on the map estimates its own traffic conditions in the future.
  • These predicted traffic conditions need to be presented on the map.
  • different presentations are made on the map.
  • the segmented roads on the map with different predicted traffic conditions are presented in different colors.
  • the rendering mode can be grayscale, texture, shadow, and flash in addition to color. Shuo can even be a sound prompt, a voice prompt, a pitch change, or a tactile distinction.
  • FIG. 2 is a flow chart 200 of a method of predicting travel time in accordance with an embodiment of the present invention.
  • one or more candidate driving routes are identified on the map based on the departure place and the destination.
  • many electronic maps have the functions of travel planning or driving navigation.
  • the car navigation system also has the functions of travel planning or driving navigation.
  • One or several candidate driving routes are identified on the map according to the destination selected by the user and the current location of the user (departure place) or the departure place specified by the user. For example, three driving routes such as route 1, route 2, and route 3 are identified.
  • each candidate driving route is segmented.
  • the current traffic conditions of the respective segments of each of the candidate driving routes are acquired and the traffic conditions of the previous time.
  • step 103 Regarding the manner of obtaining the current traffic conditions of the respective segments of each of the candidate driving routes and the traffic conditions of the previous time, reference may be made to the specific discussion of step 103 in the flowchart of FIG.
  • a traffic condition change trend of each segment of each candidate driving route is calculated based on the current traffic condition of each segment of each candidate driving route and the traffic condition of the previous time.
  • the traffic condition is a traffic speed
  • a traffic condition change trend of each of the segmented roads is calculated by comparing the current traffic speed with the traffic speed of the previous time.
  • the traffic condition is a congestion index
  • the traffic condition change trend of each segment road is calculated by comparing the current congestion index with a congestion index of a previous time.
  • the future time should match the time used to calculate the trend of change. For example, to predict traffic conditions after 30 minutes, the trend within 15 minutes can be used instead of the trend within 5 minutes. In particular, for larger time spans, such as half an hour or more, the trend curve (curve fit) should be used to estimate and apply the trend of change.
  • the time to reach each of the segmented roads in each route is estimated based on the current traffic conditions.
  • Existing electronic navigation applications have corresponding functions. In fact, it is equivalent to let e-navigation calculate the time required from the starting point to each segmented road according to the current traffic conditions. For example, if there are 10 segmented roads in a candidate route, the required roads from the starting point to the 2nd, 3rd, ..., 10th segment roads are calculated according to the current traffic conditions of each segmented road. time. For example, it takes 10 minutes, 20 minutes, ..., 70 minutes, respectively.
  • the traffic conditions of the respective segmented roads at the estimated time of arrival are estimated.
  • the above example of 10 segmented roads is still used.
  • the current traffic conditions for the 1st, 2nd, 3rd, ... 10th segmented roads have been obtained.
  • the current vehicle speeds are 40, 40, 30, ..., 50 km/h, respectively, or the current congestion indices are 4.0, 4.0, 4.8, ..., 3.0, respectively.
  • the traffic trends of these segmented roads are 0.0, +0.1 (within 5 minutes), +0.2 (within 10 minutes), ..., +0.2 (within 60 minutes) (speed trend) or 0.0, -0.1 ( Within 5 minutes), -0.2 (within 10 minutes), ..., -0.2 (within 60 minutes) (congestion trend). Therefore, the traffic conditions of each segmented road at the estimated time of arrival can be estimated as follows:
  • the first segmented road current - speed 40 km / h, congestion index 4.0;
  • a road section will be traffic controlled (for example, restricted traffic) after half an hour due to foreign affairs activities.
  • traffic controlled for example, restricted traffic
  • the travel time of each of the segmented roads of each of the candidate driving routes is estimated based on the traffic conditions of the respective segmented roads at the estimated time of arrival.
  • the estimated travel time of each segmented road is obtained.
  • the estimated travel time of each segmented road can also be obtained based on the congestion index of the length of each segmented road and the estimated time of arrival estimated in step 213.
  • the above example of 10 segmented roads is still used, and the driving times of the first, second, third, ..., and 10th roads are 10 minutes, 8 minutes, and 9 minutes, respectively. , «,5 minutes.
  • the total travel time is estimated based on the travel time of each of the segmented roads of each of the candidate travel routes.
  • the total travel time for each candidate driving route is N minutes.
  • one or more candidate driving directions are provided.
  • e-navigation estimates the time that may be needed for people to refer to when selecting a route.
  • the estimated time for electronic navigation is generally based on current traffic conditions. By The traffic condition at the time of selecting the route is not equal to the traffic situation when actually traveling to the road section, so the estimated time is actually much different from the time taken by the route when actually traveling.
  • the present invention enables a prediction of future traffic conditions to be provided when people select a driving route to more accurately estimate the travel time spent for reference.

Abstract

La présente invention porte sur un procédé de prédiction d'état de circulation et de temps de déplacement, comprenant les étapes consistant : à segmenter des routes sur une carte (101) ; à acquérir un état de circulation actuel et un état de circulation précédent de chacune des routes segmentées (103) ; sur la base de l'état de circulation actuel et de l'état de circulation précédent, à calculer la tendance de variation d'état de circulation de chacune des routes segmentées (105) ; sur la base de l'état de circulation actuel et de la tendance de variation d'état de circulation de chacune des routes segmentées, à estimer l'état de circulation d'un temps futur de chacune des routes segmentées (107) ; et à présenter l'état de circulation estimé du temps futur de chacune des routes segmentées sur la carte (109). Le procédé peut également être utilisé pour prédire un temps de déplacement, comprenant les étapes consistant : sur la base de l'état de circulation actuel et de la tendance de variation d'état de circulation de chacune des routes segmentées (211), à estimer l'état de circulation de chacune des routes segmentées au niveau d'un temps estimé d'arrivée, de manière à estimer le temps de déplacement sur chacune des routes segmentées de chaque trajectoire de conduite candidate (213) ; et selon le temps de déplacement sur chacune des routes segmentées de chaque trajectoire de conduite candidate, à estimer le temps de conduite total (215).
PCT/CN2016/085202 2015-06-09 2016-06-08 Procédé de prédiction d'état de circulation et de temps de déplacement WO2016197936A1 (fr)

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CN201510312501.8A CN104851298B (zh) 2015-06-09 2015-06-09 预测交通状况和行车时间

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CN104851298B (zh) * 2015-06-09 2017-06-27 刘光明 预测交通状况和行车时间
CN106887137B (zh) * 2015-12-15 2019-12-17 高德信息技术有限公司 拥堵事件提示方法及装置
CN109872664B (zh) * 2019-01-09 2021-04-09 武汉中联智诚科技有限公司 一种智慧导游装置
US11823574B2 (en) 2019-03-28 2023-11-21 Beijing Baidu Netcom Science And Technology Co., Ltd. Method and apparatus for prediction road condition, device and computer storage medium
CN111854777B (zh) * 2019-04-30 2023-04-14 长城汽车股份有限公司 导航路线行驶时间的更新方法、导航方法、系统及车辆
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