| Paper Abstract and Keywords |
| Presentation |
2025-02-18 13:50
Developing an Intersection Risk Estimation Using Semantic Segmentation
Kazuto Nakagawa, Kazuma Nishimura, Jin Kadotani, Osamu Sugiyama, Masahiro Tada (Kindai Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In 2023, 57.3% of traffic accidents in Japan occurred at intersections. Although high-accident-frequency intersections are prioritized for countermeasures, accidents at the ten most hazardous intersections represented only 0.08% of all intersection-related accidents, indicating that risk persists across a broad range of intersections. Recently, the Naturalistic Driving Study （NDS）, which collects everyday driving data using dashcams, has gained attention as a way to measure real-world traffic conditions. Because NDS datasets are typically large, past studies have extracted intersection-related data using road network data regarding intersections as high-risk locations. However, intersection risk is not uniform and is often elevated where the driver’s field of view is restricted by obstacles. Road network data generally lack information about such obstacles which lead to visibility constraints. To address this gap, this study proposes a machine learning model that estimates intersection risk by combining single-image features with segmentation features. Evaluation results show that including segmentation features increased the F1 score to 97%, compared with 92% for a model using image features alone. These findings suggest that the proposed method effectively estimates intersection risk. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Sight Distance / Naturalistic Driving Study / Semantic Segmentation / Machine Learning / / / / |
| Reference Info. |
ITE Tech. Rep., vol. 49, no. 4, ME2025-11, pp. 57-61, Feb. 2025. |
| Paper # |
ME2025-11 |
| Date of Issue |
2025-02-11 (MMS, ME, AIT, SIP) |
| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
|
| Conference Information |
| Committee |
ME AIT MMS IEICE-IE IEICE-ITS SIP |
| Conference Date |
2025-02-18 - 2025-02-19 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Hokkaido Univ. |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Image Processing, etc. |
| Paper Information |
| Registration To |
ME |
| Conference Code |
2025-02-ME-AIT-MMS-IE-ITS-SIP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Developing an Intersection Risk Estimation Using Semantic Segmentation |
| Sub Title (in English) |
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| Keyword(1) |
Sight Distance |
| Keyword(2) |
Naturalistic Driving Study |
| Keyword(3) |
Semantic Segmentation |
| Keyword(4) |
Machine Learning |
| Keyword(5) |
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| Keyword(6) |
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| 1st Author's Name |
Kazuto Nakagawa |
| 1st Author's Affiliation |
Kindai University (Kindai Univ.) |
| 2nd Author's Name |
Kazuma Nishimura |
| 2nd Author's Affiliation |
Kindai University (Kindai Univ.) |
| 3rd Author's Name |
Jin Kadotani |
| 3rd Author's Affiliation |
Kindai University (Kindai Univ.) |
| 4th Author's Name |
Osamu Sugiyama |
| 4th Author's Affiliation |
Kindai University (Kindai Univ.) |
| 5th Author's Name |
Masahiro Tada |
| 5th Author's Affiliation |
Kindai University (Kindai Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2025-02-18 13:50:00 |
| Presentation Time |
15 minutes |
| Registration for |
ME |
| Paper # |
MMS2025-11, ME2025-11, AIT2025-11, SIP2025-11 |
| Volume (vol) |
vol.49 |
| Number (no) |
no.4 |
| Page |
pp.57-61 |
| #Pages |
5 |
| Date of Issue |
2025-02-11 (MMS, ME, AIT, SIP) |