Measurement is not enough for global road safety: implementation is key

Hyder, Adnan A.

doi:10.1016/s2468-2667(18)30262-7

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…The lack of representative motorcycle helmet use data is a serious global concern for governments and road safety actors. Automated helmet use detection for motorcycle riders is a promising approach to efficiently collect large, [34], it is a prerequisite for targeted enforcement and education campaigns, which can lower the rate of injuries and fatalities [35].…”

Section: Discussionmentioning

confidence: 99%

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Detecting motorcycle helmet use with deep learning

Siebert

2020

Accident Analysis & Prevention

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The continuous motorization of traffic has led to a sustained increase in the global number of road related fatalities and injuries. To counter this, governments are focusing on enforcing safe and law-abiding behavior in traffic. However, especially in developing countries where the motorcycle is the main form of transportation, there is a lack of comprehensive data on the safety-critical behavioral metric of motorcycle helmet use. This lack of data prohibits targeted in existing roadside traffic surveillance infrastructure and can facilitate targeted data-driven injury prevention campaigns with real-time speed. Implications of the proposed method, as well as measures that can further improve detection accuracy are discussed.

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Section: Discussionmentioning

confidence: 99%

“…the Yangon II observation site. While the sole collection of data does not increase road safety by itself [34], it is a prerequisite for targeted enforcement and education campaigns, which can lower the rate of injuries and fatalities [35].…”

Section: Discussionmentioning

confidence: 99%

Detecting motorcycle helmet use with deep learning

Siebert

2020

Accident Analysis & Prevention

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“…The current research on IoV-based traffic safety is examined in this section Table 2. According to Hyder et al [33], governments must assume responsibility for maintaining road safety and providing funding for efficient interventions to reduce accidents. Road traffic injuries and fatalities are a major global public health concern.…”

Section: Table 1: Synopsis Of the Reviewed Literature On Driving And ...mentioning

confidence: 99%

A Comprehensive Review of the Literature on Machine Learning-Based Road Safety Prediction Techniques for Internet of Vehicles (IoV)-Enabled Vehicles

Munish Kumar Tiwari

2023

tjjpt

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The goal of this comprehensive assessment of the literature is to ascertain the state-of-the-art in machine learning (ML)-based vehicle safety measure prediction, obstruction estimate, and road traffic analysis the vehicle-related internet (IoV). In particular, we concentrate on confirming the necessity and extent of federated studying in this area. A decentralized machine learning method called federated learning enables numerous edge devices to train a shared model together while storing the data locally. We looked through numerous scholarly databases and a few chosen peer-reviewed papers on the subject. The paper outlines the benefits and future prospects of federated learning in road traffic analysis and vehicle safety while highlighting the current drawbacks and restrictions of the conventional centralized ML systems. In addition, we examined the state of the art studies in federated learning for road traffic analysis at the time and noted any knowledge gaps as well as potential future study areas. The results of this paper show the extent to which federated learning is required in the subject of road traffic analysis and vehicle safety, as well as how it can be used to get around some of the drawbacks of centralized machine learning techniques.

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“…Road traffic injuries and fatalities are a significant public health concern worldwide, and governments need to take responsibility for ensuring road safety and providing resources for effective interventions to mitigate accidents, according to Hyder et al [33]. Zong, Fang, et al [34] developed a severity causation network that uses information entropy and Bayesian networks to forecast severity indexes, aiding managers in scrutinising the severity of traffic accidents to enhance safety measures and minimise casualties and property damages.…”

Section: ) Machine Learning Based Collision Scope Predictionmentioning

confidence: 99%

Machine Learning-Based Road Safety Prediction Strategies for Internet of Vehicles (IoV) Enabled Vehicles: A Systematic Literature Review

Reddy,

Muralidhar

2023

IEEE Access

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This systematic literature review aims to investigate the current state-of-the-art in machine learning (ML) based road traffic analysis, hindrance estimation, and predicting vehicle safety measures for the Internet of Vehicles (IoV). Specifically, we focus on the verification of the scope and need of federated learning in this field. Federated learning is a decentralized ML technique that allows multiple edge devices to collaboratively train a shared model while keeping the data locally. We searched various academic databases and selected peer-reviewed publications related to the topic. The review highlights the existing challenges and limitations of the traditional centralized ML approaches and presents the advantages and potential benefits of federated learning in road traffic analysis and vehicle safety. Furthermore, we analyzed the current state-of-the-art research in federated learning for road traffic analysis and identified the research gaps and future research directions. The findings of this review demonstrate the scope and need of federated learning in the field of road traffic analysis and vehicle safety, as well as the potential of federated learning to overcome the limitations of the centralized ML approaches.INDEX TERMS Internet of Vehicles, driving behavior analysis, machine learning, collision prediction, traffic accidents, deep learning, and risk assessment.

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Measurement is not enough for global road safety: implementation is key

Cited by 10 publications

References 6 publications

Detecting motorcycle helmet use with deep learning

Detecting motorcycle helmet use with deep learning

A Comprehensive Review of the Literature on Machine Learning-Based Road Safety Prediction Techniques for Internet of Vehicles (IoV)-Enabled Vehicles

Machine Learning-Based Road Safety Prediction Strategies for Internet of Vehicles (IoV) Enabled Vehicles: A Systematic Literature Review

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