VEHICLE DATA ANALYSIS METHOD AND VEHICLE DATA ANALYSIS SYSTEM

• US 20140365029A1
• Filed: 05/15/2012
• Published: 12/11/2014
• Est. Priority Date: 05/16/2011
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation), University of Tokyo
• Original Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation), University of Tokyo
• Inventors: Sugimoto, Hironobu, Takeuchi, Shojiro, Yoshioka, Satomi, Suda, Yoshihiro, Sato, Yoichi, Yamaguchi, Daisuke, Hirasawa, Takayuki, Li, Shuguang
• Granted Patent: US 9,053,593 B2
• Time in Patent Office: Days
• US Class Current: 701/1
• CPC Class Codes: B60W 2050/046 involving external transmission of data to or from the vehicle, e.g. via telemetry, satellite, Global Positioning System [GPS]
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 50/045 Monitoring control system parameters
• CPC Class Codes: G07C 5/02 Registering or indicating driving, working, idle, or waiting time only apparatus forming part of taximeters G07B13/00
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]

Abstract

The invention provides a vehicle data analysis method that enables quantitative analysis of characteristics of vehicle data indicating transition in a driver'"'"'s driving operation, and a vehicle data analysis system using this analysis method. A plurality of vehicle data are collected based a plurality of types of driving operations. Based on an evaluation criterion as an index for evaluating levels of the driving operations, the collected vehicle data are grouped into at least two groups. Characteristic values of the vehicle data differing between these groups are extracted.

Claims

1. A vehicle data analysis method for analyzing vehicle data reflecting a driver'"'"'s driving operation, comprising:

collecting a plurality of pieces of vehicle data based on a plurality of types of driving operations;

grouping these collected pieces of the vehicle data into at least two groups based on an evaluation criterion that is an index for evaluating a level of the driving operation; and

extracting characteristic values of vehicle data differing between the groups.

2. The vehicle data analysis method according to claim 1, further comprising:

obtaining a degree of influence exerted by the extracted characteristic value of vehicle data on the vehicle data evaluated based on the evaluation criterion.

3. The vehicle data analysis method according to claim 1, wherein

the vehicle data includes information indicating at least one of a traffic element, a travel section, and a travel area where the traffic element and travel sections are connected in series, and

the grouping of the vehicle data and the extraction of the characteristic values of the vehicle data are performed by treating the traffic element or the travel section or the travel area as a unit.

4. The vehicle data analysis method according to claim 1, wherein the vehicle data includes information indicating a travel point, and the vehicle data analysis method further comprises:

obtaining a correspondence relationship between the extracted characteristic values of the vehicle data and the travel point, and a correspondence relationship between the extracted characteristic values of the vehicle data and an evaluation result of the vehicle data based on the evaluation criterion.

5. The vehicle data analysis method according to claim 1, further comprising:

normalizing time-series data as the vehicle data based on a travel position.

6. The vehicle data analysis method according to claim 1, wherein

the characteristic values indicate characteristics of one or more driving elements representing a driver'"'"'s driving operation mode, and

the analysis method further comprises obtaining a degree of influence exerted by the driving element on the evaluation criterion for each of the driving elements.

7. The vehicle data analysis method according to claim 1, further comprising:

generating a plurality of candidate data as original data for indicating the characteristic values of the vehicle data by way of frequency resolution of the vehicle data.

8. The vehicle data analysis method according to claim 1, further comprising:

revealing the characteristic values by applying a window function to the vehicle data prior to the extraction of the characteristic values of vehicle data.

9. The vehicle data analysis method according to claim 1, wherein the evaluation criterion is a criterion for grouping that is performed for at least one of evaluation items consisting of fuel efficiency defined by travel distance of a vehicle per unit fuel amount, travel time, vehicle behavior, and lateral jerk of a vehicle.

10. The vehicle data analysis method according to claim 1, wherein

the grouping comprises categorizing the plurality of types of vehicle data into a vehicle data group of “

high”

driving performance level and a vehicle data group of “

low”

driving performance level by way of the grouping based on the evaluation criterion,

the extraction of the vehicle data comprises performing weighting on characteristic values of vehicle data differing in the driving performance level based on a total value of differences of characteristic values which are common between the data group of “

high”

driving performance level and the vehicle data group of “

low”

driving performance level, which are grouped based on the evaluation criterion, and

the difference of the common characteristic values is a difference between the characteristic value of the data categorized by the group of “

high”

driving performance level and the characteristic value of the data categorized by the group of “

low”

driving performance level.

11. A vehicle data analysis system for analyzing vehicle data reflecting a driver'"'"'s driving operation, comprising:

a storage device for storing vehicle data based on a plurality of types of driving operations;

a vehicle data classification unit for grouping the vehicle data stored in the storage device into at least two groups based on an evaluation criterion that is an index for evaluating a level of driving operation; and

a vehicle data analysis unit for extracting characteristic values of vehicle data differing between the groups grouped by the vehicle data classification unit.

12. The vehicle data analysis system according to claim 11, wherein the vehicle data analysis unit further comprises an influence calculation unit for obtaining a degree of influence exerted by the extracted characteristic value on the vehicle data evaluated based on the evaluation criterion.

13. The vehicle data analysis system according to claim 11, wherein

the vehicle data includes information indicating a traffic element, a travel section, and a travel area where the traffic element and travel section are connected in series,

the vehicle data classification unit and the vehicle data analysis unit perform grouping of the vehicle data and extraction of the characteristic values of the vehicle data by treating the traffic element or the travel section or the travel area as a unit.

14. The vehicle data analysis system according to claim 11, wherein

the vehicle data includes information indicating a travel point;

and

the vehicle data analysis unit further obtains a correspondence relationship between the extracted characteristic values of the vehicle data and the travel point, and a correspondence relationship between the extracted characteristic values of the vehicle data and an evaluation result of the vehicle data based on the evaluation criterion.

15. The vehicle data analysis system according to claim 11, wherein the vehicle data analysis unit further comprises a normalization operation unit for normalizing time-series data as the vehicle data based on a travel position.

16. The vehicle data analysis system according to claim 11, wherein

the characteristic values are characteristics of one or more driving elements indicating a driver'"'"'s driving operation mode, and

the vehicle data analysis unit determines a degree of influence exerted by the driving element on the evaluation criterion for each of the driving elements.