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CN-115171366-B - Apparatus and method for predicting traffic information

CN115171366BCN 115171366 BCN115171366 BCN 115171366BCN-115171366-B

Abstract

An apparatus and method for predicting traffic information are provided to improve traffic information prediction accuracy. The apparatus includes a memory storing a plurality of probe data generation models based on characteristics of a road, and a communication device receiving probe data from a probe vehicle traveling on a target road. The controller detects a probe data generation model corresponding to a characteristic of the target road among the plurality of probe data generation models, generates a preset amount of probe data based on the detected probe data generation model, and predicts traffic information of the target road based on the generated probe data and the received probe data.

Inventors

  • JIN NANHE

Assignees

  • 现代自动车株式会社
  • 起亚株式会社

Dates

Publication Date
20260512
Application Date
20210831
Priority Date
20210405

Claims (10)

  1. 1. An apparatus for predicting traffic information, comprising: a memory configured to store a plurality of probe data generation models based on characteristics of a road; a communication device configured to receive probe data from a probe vehicle traveling on a target road, and A controller configured to: Detecting a detection data generation model corresponding to the characteristic of the target road in the plurality of detection data generation models; generating a preset number of detection data based on the detected detection data generation model, and Predicting traffic information of the target link based on the generated probe data and the received probe data, Wherein the probe data is road traffic time, Wherein the controller is configured to generate a preset number of road traffic times based on the detected probe data generation model, and calculate a target road traffic time based on the generated road traffic time and the road traffic time received from the probe vehicle, and Wherein the controller is configured to identify an entry time point of the target road or a reference link of the target road of the probe vehicle, and calculate a time required to pass through the target road or a time required to pass through a reference link of the target road as the traffic information based on the entry time point and the calculated target road traffic time.
  2. 2. The apparatus of claim 1, wherein the controller is configured to calculate an average of the generated road traffic time and the received road traffic time as the target road traffic time.
  3. 3. The apparatus of claim 1, wherein the characteristic of the roadway comprises at least one of a number of the probe vehicles, a type of the roadway, a number of routes, a length of the roadway, and a shape of the roadway.
  4. 4. The apparatus of claim 3, wherein the controller is configured to: calculating a similarity to each characteristic of the road based on the characteristics of the target road, and A detection data generation model corresponding to a characteristic of the road having the highest similarity is detected as a detection data generation model of the target road.
  5. 5. The apparatus according to claim 4, wherein the controller is configured to detect, as the detection data generation model of the target road, a detection data generation model having, as the characteristic of the road, a number of detection vehicles having a smallest difference from the number of detection vehicles of the target road when the detection data generation model of the target road is not detected based on the calculated similarity.
  6. 6. A method for predicting traffic information, comprising the steps of: storing, by a memory, a plurality of probe data generation models based on characteristics of a road; Receiving, by the communication device, probe data of a probe vehicle traveling on a target road; Detecting, by a controller, a probe data generation model corresponding to a characteristic of the target road among the plurality of probe data generation models, and Generating, by the controller, a preset number of probe data based on the detected probe data generation model, and predicting traffic information of the target link based on the generated probe data and the received probe data, Wherein the probe data is road traffic time, Wherein predicting the traffic information of the target road includes generating a preset amount of road traffic time based on the detected probe data generation model, and calculating a target road traffic time based on the generated road traffic time and the road traffic time received from the probe vehicle, and Wherein predicting the traffic information of the target road further includes the steps of identifying an entry time point of the target road of the probe vehicle or a reference section of the target road, and calculating a time required to pass through the target road or a time required to pass through a reference section of the target road based on the entry time point and the calculated target road traffic time as the traffic information.
  7. 7. The method of claim 6, wherein calculating the transit time of the target link comprises: An average of the generated road traffic time and the received road traffic time is calculated as the traffic time of the target road.
  8. 8. The method of claim 6, wherein the characteristic of the roadway includes at least one of a number of the probe vehicles, a type of the roadway, a number of routes, a length of the roadway, and a shape of the roadway.
  9. 9. The method of claim 8, wherein detecting the probe data generation model corresponding to the characteristic of the target link comprises: calculating a similarity to each characteristic of the road based on the characteristics of the target road, and A detection data generation model corresponding to a characteristic of the road having the highest similarity is detected as a detection data generation model of the target road.
  10. 10. The method of claim 9, wherein detecting the probe data generation model corresponding to the characteristic of the target link further comprises: when the detection data generation model of the target road is not detected based on the calculated similarity, the detection data generation model of the target road having the number of detection vehicles having the smallest difference from the number of detection vehicles of the target road is detected as the detection data generation model of the characteristic of the road.

Description

Apparatus and method for predicting traffic information Cross Reference to Related Applications The present application claims priority from korean patent application No. 10-2021-0044210, filed on 5 th 4 th 2021, to the korean intellectual property office, the entire contents of which are incorporated herein by reference. Technical Field The present disclosure relates to techniques for predicting traffic information about a link based on a learning model that generates probe data. Background Generally, a navigation system provides real-time traffic information of a specific area or an optimal route to a destination to a user using real-time traffic information in response to a request of the user. In this regard, the real-time traffic information refers to traffic information at a point of time when a traffic information request of a user is generated. Since such traffic information varies with time, when a user travels along an optimal route using real-time traffic information and reaches a specific point, the real-time traffic information at the specific point is different from the real-time traffic information at the point of time when the traffic information request is generated. Therefore, the traffic information initially provided to the user is less effective. To prevent this, a method of predicting traffic information at a specific point of a time point at which a user desires to reach the specific point using past traffic information and real-time traffic information has been proposed. In this regard, real-time traffic information (e.g., ETA: expected arrival time) is predicted based on probe data (e.g., GPS data) received from probe vehicles traveling on a road. In this regard, in order to predict accurate traffic information (e.g., time taken to pass through a road), the number of probe vehicles passing through the road (or a reference section of the road) during a reference time (e.g., 5 minutes) must exceed a reference value (e.g., 30), but the number of probe vehicles is limited. Finally, conventional traffic information prediction techniques use less than a reference number (e.g., 30) of probe data to predict traffic information of a road, and thus accuracy is significantly reduced. The matters described in the background section are intended to enhance understanding of the background section of the present invention, which may include matters other than those of ordinary skill in the art to which the present technology pertains. Disclosure of Invention The present disclosure has been made to solve the above-mentioned problems occurring in the prior art while maintaining the advantages achieved by the prior art unchanged. An aspect of the present disclosure provides an apparatus and method for predicting traffic information, which have a plurality of probe data generation models that have completed learning for each characteristic of a road, detect a probe data generation model corresponding to a characteristic of a target road among the plurality of probe data generation models, generate predetermined probe data based on the detected probe data generation model, and predict traffic information of the target road based on the generated predetermined probe data and probe data received from a probe vehicle traveling on the target road, thereby improving traffic information prediction accuracy. The technical problems to be solved by the inventive concept are not limited to the above-described problems, and any other technical problems not mentioned herein will be clearly understood by those skilled in the art to which the present disclosure pertains from the following description. According to one aspect of the present disclosure, an apparatus for predicting traffic information may include a memory storing a plurality of probe data generation models based on characteristics of a road, a communication apparatus configured to receive probe data from a probe vehicle traveling on a target road, and a controller configured to detect probe data generation models corresponding to characteristics of the target road among the plurality of probe data generation models, generate a preset number of probe data based on the detected probe data generation models, and predict traffic information of the target road based on the generated probe data and the received probe data. In one implementation, the probe data may be a road transit time (road TRANSIT TIME). The controller may be configured to generate a preset number of road traffic times based on the detected probe data generation model, and calculate a traffic time of the target road based on the generated road traffic times and the road traffic times received from the probe vehicle. In addition, the controller may be configured to calculate an average of the generated road traffic time and the received road traffic time as the traffic time of the target road. The characteristics of the road may include at least one of a number of probe vehicles, a type of