# Smart Roads for Autonomous Accident Detection and Warnings
## 2 Related Works
### Hybrid Approaches
In a vehicle, two types of sensors are installed: one is a bio-medical sensor that helps monitor the heart rate of the driver, and the other is a vehicular sensor to collect information about acceleration, temperature, tire pressure, etc. The microcontroller obtains inputs from these sensors and manipulates them to find any abnormalities. If abnormal values are found, it obtains the current location through a GPS module. After obtaining location information, it sends the information to nearby RSUs, which forward it to a central server to guide the ambulance to the target location. The drawback of this technique is that if the cellular signals are not present or weak, the required communication may fail, and the delay may be life-threatening. [PERSON] et al. [39] used GSM, a GPS, and an accelerometer-based system for detecting accidents. It provides alerts by sending an SMS to an emergency number when any accident is detected. The Arduino microcontroller is used for processing. The GPS and the accelerometer are attached to input pins, and GSM is used for the I/O port. The processor is responsible for all calculations performed locally, and then an alert is sent to an emergency number using the GSM cellular network. However, the proposed solution has no ability to inform other vehicles about the incident. [PERSON] et al. [40] developed a system to detect accidents using GPS information. In this technique, the receiver extracts the complete GPRMC sentence by demodulating RF signals from GPS satellites. The sentence holds all necessary information about the speed, time, and location of the vehicle. The last two values for each attribute are stored in memory and manipulated by the local processor for detection of any abnormalities. If the processor finds an accident, it raises a HIGH flag that results in autonomous initialization of emergency procedures. Before sending the message, the processor waits for manual cancellation by the driver if no help is required. After five seconds, an SMS alert is generated by the processor with the destination of the emergency. [PERSON] et al. [41] proposed a smartphone-based accident detection and notification system. The internal sensors of a smartphone are used to detect accidents, and the camera is used for recording images and video. If an accident happens, the video and/or images are sent to an emergency number. One major drawback of this approach is that every smartphone is prone to false positives. [PERSON] et al. [42] built an application for Android phones with an algorithm for autonomous detection of accidents. Mobile phones are connected to a single-board computer (SBC) through a USB serial cable. The accident detection algorithm takes values from the internal sensors of smartphones and vehicles. Whenever an accident occurs, the application detects it and broadcasts a message to all nearby vehicles. The nearby vehicles are informed by the color on the phone screen: green means the road is clear, and red means there is an accident nearby. Every smartphone, however, is prone to false positives. [PERSON] et al. proposed and developed a system that utilizes GSM, a GPS, the IoT, and GPRS technology with different vehicular sensors and microcontrollers [43]. An Arduino microcontroller receives input from vehicular sensors and sends a message via GSM modules using cellular technology if it obtains an abnormal value. Information about an incident's location is taken from the GPS. The proposed system is expensive due to the multiple technologies and sensors. [PERSON] et al. [44] investigates a possible approach toward 5G VAN. The vehicular networks can lease available spectrum from existing cellular networks through base stations (BS) or access points using dynamic spectrum access (AP). They compared LTE performance from current legacy solutions to projected 5G trends. [PERSON] et al. [45] investigated an evolution of V2X communication based on 802.11 bd and 5G NR, and explain that multi-access edge computing (MEC) can bring cloud closer to vehicular nodes.