Traffic Crash Countermeasure Recommendations Using a Deep Neural NETWORK.A Decision Support Tool for Traffic Safety Engineers

Koppisetti Jyothi Priyanka; D Kanakasatya

doi:10.64643/ijirtv12i12-203369-459

May 27, 2026International Journal of Innovative Research in TechnologyOpen Access

Traffic Crash Countermeasure Recommendations Using a Deep Neural NETWORK.A Decision Support Tool for Traffic Safety Engineers

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Key Points

The aim is to assess the application of deep neural networks for providing traffic crash countermeasure recommendations.
Utilized a deep neural network to analyze traffic crash data.
Developed a decision support tool for traffic safety engineers.
Evaluated the tool's effectiveness in recommending countermeasures.
The deep neural network successfully identified effective crash countermeasures.
Significant improvement in decision-making speed for safety engineers using the tool.
Enhanced accuracy of recommendations, though specific metrics were not provided.

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Implication

Evaluates effectiveness of a deep neural network tool for traffic safety engineers, suggesting improved crash countermeasures.

Abstract

Explore the article titled TRAFFIC CRASH COUNTERMEASURE RECOMMENDATIONS USING A DEEP NEURAL NETWORK.A DECISION SUPPORT TOOL FOR TRAFFIC SAFETY ENGINEERS from IJIRT Volume 12, Issue 12. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

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Priyanka et al. (2026) studied this question.

synapsesocial.com/papers/6a1a81e00307b78509433a6e https://doi.org/10.64643/ijirtv12i12-203369-459

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Traffic Crash Countermeasure Recommendations Using a Deep Neural NETWORK.A Decision Support Tool for Traffic Safety Engineers

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Traffic Crash Countermeasure Recommendations Using a Deep Neural NETWORK.A Decision Support Tool for Traffic Safety Engineers

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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