| Presentation | 2020-12-11 Prediction of Train Delays at Stations Using Convolutional Neural Networks with Actual Operation Data Tsukasa Takahashi, Takumi Fukuda, Sei Takahashi, Hideo Nakamura, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Trains in the metropolitan area have high congestion rates during rush hours. Congestion causes delays, and there is a lot of research and countermeasures to mitigate the delays. In order to evaluate the effect of the countermeasure against delay, we need to evaluate the delays before and after the countermeasures. When the evaluation is done by simulation, it is necessary to predict the delays according to the driving conditions. We defined a series to facilitate the extraction of features from the actual operation data, and used a convolutional neural network to learn the features, and obtained the highest prediction accuracy of 67.1% for Station I. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Delay resolution / Delay improvement / Train delay / Operation management / Machine learning / Convolutional neural network |
| Paper # | DC2020-63 |
| Date of Issue | 2020-12-04 (DC) |
| Conference Information | |
| Committee | DC |
|---|---|
| Conference Date | 2020/12/11(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hiroshi Takahashi(Ehime Univ.) |
| Vice Chair | Tatsuhiro Tsuchiya(Osaka Univ.) |
| Secretary | Tatsuhiro Tsuchiya(Nihon Univ.) |
| Assistant | |
| Paper Information | |
| Registration To | Technical Committee on Dependable Computing |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prediction of Train Delays at Stations Using Convolutional Neural Networks with Actual Operation Data |
| Sub Title (in English) | |
| Keyword(1) | Delay resolution |
| Keyword(2) | Delay improvement |
| Keyword(3) | Train delay |
| Keyword(4) | Operation management |
| Keyword(5) | Machine learning |
| Keyword(6) | Convolutional neural network |
| 1st Author's Name | Tsukasa Takahashi |
| 1st Author's Affiliation | Nihon University(Nihon Univ.) |
| 2nd Author's Name | Takumi Fukuda |
| 2nd Author's Affiliation | Nihon University(Nihon Univ.) |
| 3rd Author's Name | Sei Takahashi |
| 3rd Author's Affiliation | Nihon University(Nihon Univ.) |
| 4th Author's Name | Hideo Nakamura |
| 4th Author's Affiliation | The University of Tokyo(The Univ. of Tokyo) |
| Date | 2020-12-11 |
| Paper # | DC2020-63 |
| Volume (vol) | vol.120 |
| Number (no) | DC-288 |
| Page | pp.pp.23-26(DC), |
| #Pages | 4 |
| Date of Issue | 2020-12-04 (DC) |