An Incident Detection Model Using Random Forest Classifier

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
O. ElSahly, A. Abdelfatah
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引用次数: 0

Abstract

Traffic incidents have adverse effects on traffic operations, safety, and the economy. Efficient Automatic Incident Detection (AID) systems are crucial for timely and accurate incident detection. This paper develops a realistic AID model using the Random Forest (RF), which is a machine learning technique. The model is trained and tested on simulated data from VISSIM traffic simulation software. The model considers the variations in four critical factors: congestion levels, incident severity, incident location, and detector distance. Comparative evaluation with existing AID models, in the literature, demonstrates the superiority of the developed model, exhibiting higher Detection Rate (DR), lower Mean Time to Detect (MTTD), and lower False Alarm Rate (FAR). During training, the RF model achieved a DR of 96.97%, MTTD of 1.05 min, and FAR of 0.62%. During testing, it achieved a DR of 100%, MTTD of 1.17 min, and FAR of 0.862%. Findings indicate that detecting minor incidents during low traffic volumes is challenging. FAR decreases with the increase in Demand to Capacity ratio (D/C), while MTTD increases with D/C. Higher incident severity leads to lower MTTD values, while greater distance between an incident and upstream detector has the opposite effect. The FAR is inversely proportional to the incident’s location from the upstream detector, while being directly proportional to the distance between detectors. Larger detector spacings result in longer detection times.
一种基于随机森林分类器的事件检测模型
交通事故对交通运营、安全和经济产生不利影响。高效的自动事件检测(AID)系统对于及时准确的事件检测至关重要。本文利用随机森林(RF)这一机器学习技术开发了一个现实的AID模型。该模型在VISSIM交通仿真软件的仿真数据上进行了训练和测试。该模型考虑了四个关键因素的变化:拥堵程度、事故严重程度、事故地点和探测器距离。与文献中现有AID模型的比较评估证明了所开发模型的优越性,表现出更高的检测率(DR)、更低的平均检测时间(MTTD)和更低的误报率(FAR)。在训练过程中,RF模型实现了96.97%的DR、1.05分钟的MTTD和0.62%的FAR。在测试过程中,它实现了100%的DR、1.17分钟的MTOD和0.862%的FAR。FAR随需求容量比(D/C)的增加而降低,MTTD随D/C的增加而增加。更高的事件严重性会导致更低的MTTD值,而事件和上游探测器之间的距离越大则会产生相反的效果。FAR与上游探测器的入射位置成反比,而与探测器之间的距离成正比。探测器间距越大,探测时间越长。
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来源期刊
Smart Cities
Smart Cities Multiple-
CiteScore
11.20
自引率
6.20%
发文量
0
审稿时长
11 weeks
期刊介绍: Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.
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