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Analysis and Prediction of Spatiotemporal Impact of Traffic Incidents for Better Mobility and Safety in Transportation Systems, Research Project
| 题名： | Analysis and Prediction of Spatiotemporal Impact of Traffic Incidents for Better Mobility and Safety in Transportation Systems, Research Project |
| 作者： | Shahabi, C.; Demiryurek, U. |
| 关键词： | Spatiotemporal impact##Traffic accidents##Transportation safety##Transportation network##Mobility applications##dynamic topolgy##Real-time forecasting##Traffic analysis## |
| 摘要： | The goal of this research is to develop a machine learning framework to predict the spatiotemporal impact of traffic accidents on the upstream traffic and surrounding region. We propose a Latent Space Model for Road Networks (LSM-RN), which enables more accurate and scalable traffic prediction by utilizing both topology similarity and temporal correlations. Our framework further enables real-time traffic prediction by 1) exploiting real-time sensor readings to adjust/update the latent spaces, and 2) training as data arrives and predicting on-the-fly. |
| 总页数： | 2 |
| 报告类型： | 科技报告 |
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