Can we realize seamless traffic safety at smart intersections by predicting and preventing impending crashes?

IF 5.7 1区 工程技术 Q1 ERGONOMICS
B M Tazbiul Hassan Anik, Mohamed Abdel-Aty, Zubayer Islam
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引用次数: 0

Abstract

Intersections are frequently identified as crash hotspots for roadways in major cities, leading to significant human casualties. We propose crash likelihood prediction as an effective strategy to proactively prevent intersection crashes. So far, no reliable models have been developed for intersections that effectively account for the variation in crash types and the cyclical nature of Signal Phasing and Timing (SPaT) and traffic flow. Moreover, the limited research available has primarily relied on sampling techniques to address data imbalance, without exploring alternative solutions. We develop an anomaly detection framework by integrating Generative Adversarial Networks (GANs) and Transformers to predict the likelihood of cycle-level crashes at intersections. The model is built using high-resolution event data extracted from Automated Traffic Signal Performance Measures (ATSPM), including SPaT and traffic flow insights from 11 intersections in Seminole County, Florida. Our framework demonstrates a sensitivity of 76% in predicting crash events using highly imbalanced crash data along with real-world SPaT and traffic data, highlighting its potential for deployment at smart intersections. Overall, the results provide a roadmap for city-wide implementation at smart intersections, with the potential for multiple real-time solutions for impending crashes. These include adjustments in signal timing, driver warnings using various means, and more efficient emergency response, all with major implications for creating more livable and safe cities.

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来源期刊
CiteScore
11.90
自引率
16.90%
发文量
264
审稿时长
48 days
期刊介绍: Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.
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