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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework

February 1, 2023

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Authors

Zhengyang Zhou

University of Science and Technology of China


Yang Wang

University of Science and Technology of China


Xike Xie

University of Science and Technology of China


Lianliang Chen

University of Science and Technology of China


Hengchang Liu

University of Electronic Science and Technology of China


DOI:

10.1609/aaai.v34i01.5480


Abstract:

Real-time traffic accident forecasting is increasingly important for public safety and urban management (e.g., real-time safe route planning and emergency response deployment). Previous works on accident forecasting are often performed on hour levels, utilizing existed neural networks with static region-wise correlations taken into account. However, it is still challenging when the granularity of forecasting step improves as the highly dynamic nature of road network and inherent rareness of accident records in one training sample, which leads to biased results and zero-inflated issue. In this work, we propose a novel framework RiskOracle, to improve the prediction granularity to minute levels. Specifically, we first transform the zero-risk values in labels to fit the training network. Then, we propose the Differential Time-varying Graph neural network (DTGN) to capture the immediate changes of traffic status and dynamic inter-subregion correlations. Furthermore, we adopt multi-task and region selection schemes to highlight citywide most-likely accident subregions, bridging the gap between biased risk values and sporadic accident distribution. Extensive experiments on two real-world datasets demonstrate the effectiveness and scalability of our RiskOracle framework.

Topics: AAAI

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HOW TO CITE:

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework Proceedings of the AAAI Conference on Artificial Intelligence (2020) 1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework AAAI 2020, 1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu (2020). RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework. Proceedings of the AAAI Conference on Artificial Intelligence, 1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. 2020. RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework. "Proceedings of the AAAI Conference on Artificial Intelligence". 1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. (2020) "RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework", Proceedings of the AAAI Conference on Artificial Intelligence, p.1258-1265

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu, "RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework", AAAI, p.1258-1265, 2020.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. "RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. "RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 1258-1265.

Zhengyang Zhou||Yang Wang||Xike Xie||Lianliang Chen||Hengchang Liu. RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework. AAAI[Internet]. 2020[cited 2023]; 1258-1265.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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