Towards automated traffic accident reconstruction using ITS and multi-sensor data fusion

Q1 Engineering

Transportation Engineering Pub Date : 2026-03-01 Epub Date: 2026-02-14 DOI:10.1016/j.treng.2026.100425

Bruno M. Correia, Pieter H.H. Aparício, Rogério M.G. Martins, Anabela M. Bernardino, Eugénia M. Bernardino, Rosa I.A.C. Matias, Paulo M.A. Costa, Rui V.G.B. Monteiro, Sílvio P. Mendes, Paulo J.G. Loureiro

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引用次数: 0

Abstract

Traffic accident reconstruction is essential for understanding collision dynamics and supporting forensic, insurance, and legal investigations. This paper presents a unified software platform that integrates heterogeneous data sources, including Event Data Recorder (EDR) telemetry, Light Detection and Ranging (LiDAR), drone photogrammetry, and Cooperative Intelligent Transport Systems (ITS) data, into a single analytical environment. The proposed solution fuses spatial, temporal, and contextual information to enable consistent, evidence-based 3D reconstruction of crash scenarios. A prototype implementation demonstrates the feasibility of multi-source data harmonization and visualization, supporting reproducible and objective analysis. The architecture, data flow, and functional results are described, highlighting the system’s potential contribution to more transparent and data-driven accident investigation.

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基于ITS和多传感器数据融合的交通事故自动重建研究

交通事故重建对于理解碰撞动力学和支持法医、保险和法律调查至关重要。本文提出了一个统一的软件平台，集成了异构数据源，包括事件数据记录仪（EDR）遥测，光探测和测距（LiDAR），无人机摄影测量和协作智能交通系统（ITS）数据，到一个单一的分析环境。提出的解决方案融合了空间、时间和上下文信息，以实现一致的、基于证据的碰撞场景3D重建。一个原型实现证明了多源数据协调和可视化的可行性，支持可重复和客观的分析。介绍了该系统的架构、数据流和功能结果，强调了该系统对更透明和数据驱动的事故调查的潜在贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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