2CAP: A Novel Curve Crash Avoidance Protocol to Handle Curve Crashes in Vehicular Ad-Hoc Network

2CAP: A Novel Curve Crash Avoidance Protocol to Handle Curve Crashes in Vehicular Ad-Hoc Network

Curves are the leading cause of road departure crashes that turn into deaths and severe injuries. Most crashes occur on curved roads because they have different geometrical circumstances from straight roads. A sharp turn on the road creates more difficulty for the driver than a normal curve road. To...

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Bibliographic Details
Published in:IEEE access Vol. 12; pp. 60601 - 60619
Main Authors: Bashir, Raja Rizwan, Saeed, Yousaf, Ali, Abid, Algarni, Abeer D., Muthanna, Ammar, Hijjawi, Mohammad, Alsboui, Tariq
Format: Journal Article
Language:English
Published: Piscataway IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accidents
Algorithms
Avoidance
Crashes
Curve Crash Avoidance
Data collection
Datasets
Information systems
Intelligent sensors
Machine learning
Mobile ad hoc networks
MSE
OBU
Protocol (computers)
Regression analysis
Regression models
Roads
Roads & highways
RSU
Safety
Sensors
Traffic control
VANET
Vehicle safety
Vehicles
Vehicular ad hoc networks
WHO
Wireless sensor networks
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Summary:Curves are the leading cause of road departure crashes that turn into deaths and severe injuries. Most crashes occur on curved roads because they have different geometrical circumstances from straight roads. A sharp turn on the road creates more difficulty for the driver than a normal curve road. To Avoid crashes on the curved road, there is a prerequisite to identify the curved road for drivers that this turn is problematic. Responding intelligently to save precious human life and the country's gross domestic product is necessary. Our paper proposed a Curve Crash Avoidance Protocol (2CAP) in Vehicular Ad-hoc Network (VANET). The Intelligent Curve Crash Avoidance Algorithm is proposed to avoid disastrous vehicle crashes. The sensing Node Operation algorithm works for multiple sensors embedded in the Onboard Unit to gather information on vehicles and road environments. On the other side, road-side unit requests for this collected data via a secure communication channel for processing. A Linear Regression machine learning technique implements the intelligent Unit Operations algorithm. The Intelligent Unit decides to notify the onboard Unit based on gathered data and trained dataset. We implement the scheme using the Linear Regression Machine Learning Model. Multiple sensors, Global Positioning Systems, and Global Information systems use the dataset methodology to classify and predict results. The proposed model is expected to be effective for proper coordination with wireless sensor network equipment.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3349474