Abstract
Most individuals involved in traffic accidents receive assistance from drivers, passengers, or other people. However, when a traffic accident occurs in a sparsely populated area or the driver is the only person in the vehicle and the crash results in loss of consciousness, no one will be available to send a distress message to the proper authorities within the golden window for medical treatment. Considering these issues, a method for detecting high-speed head-on and single-vehicle collisions, analyzing the situation, and raising an alarm is needed. To address such issues, this paper proposes a deep learning-based Internet of Vehicles (IoV) system called DeepCrash, which includes an in-vehicle infotainment (IVI) telematics platform with a vehicle self-collision detection sensor and a front camera, a cloud-based deep learning server, and a cloud-based management platform. When a head-on or single-vehicle collision is detected, accident detection information is uploaded to the cloud-based database server for self-collision vehicle accident recognition, and a related emergency notification is provided. The experimental results show that the accuracy of traffic collision detection can reach 96% and that the average response time for emergency-related announcements is approximately 7 s.
Highlights
In recent years, traffic accidents have become increasingly common
THE PROPOSED DEEPCRASH IOV SYSTEM To increase the survival rate of accident victims involved in high-speed head-on and single-vehicle vehicle collisions, this paper proposes a deep learning-based intelligent Internet of Vehicles (IoV) system that can immediately sense whether a high-speed head-on or single-vehicle collision has occurred
The proposed DeepCrash system consists of an in-vehicle infotainment (IVI) telematics platform with vehicle collision detection sensors, a cloud-based deep learning server, and a cloud-based management platform
Summary
Traffic accidents have become increasingly common. In 2015, the global status report on road safety from the World Health Organization (WHO) [1] noted that approximately 1.25 million people die each year from traffic accidents worldwide. When a traffic accident occurs in the suburbs or the driver is the only person in the vehicle and the crash results in loss of consciousness, no one is available to notify the proper authorities within the ‘‘golden window period’’ for medical treatment, and this delay reduces the survival rate. Considering these issues, an infrastructure is needed for collision detection, analysis, and notification is needed. An IoV system for high-speed head-on and single-vehicle accident detection, analysis, and emergency notification is composed of sensors, actuators, heterogeneous networks, rescue service centers, and a cloud-based management platform.
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