# Smart Roads for Autonomous Accident Detection and Warnings
## 2 Related Works
### Hybrid Approaches  
[PERSON] et al. [30] created a method for vehicular communications using ZigBee wireless technology in order to prevent accidents. A GPS modem is utilized in this system to determine an accident's exact location. Blynk applications on smartphones are used to save data to the cloud. When a car's distance from a neighboring vehicle is lower than a certain threshold, the vehicle uses ZigBee to send messages to the adjacent vehicle, alerting the driver to take suitable action. A collision avoidance system was developed [31] based on ZigBee where GPS technology is used to find a vehicle's current location. In this system, the brakes of the vehicle are controlled using the automatic braking system (ABS) in the recent vehicles. The proposed model is used in Aws with a protective system already installed. The research they carried out was limited to line-of-sight visualization by a camera and IR sensors. Many researchers and practitioners have adopted cameras, radar, and LiDAR in vehicles with a GPS for safe or autonomous driving. For the study in [32], the localization problem was solved by using radar data (pulse-based short-range radar) of the route in relation to a fresh traversal. The approach requires only the latest traversal history for the route, rather than storing and processing large amounts of data. The proposed approach was tested and validated to localize a truck on a road by using a five-minute dataset. Results after the experiments showed root mean square (RMS) errors of 7.3 cm laterally and 37.7 cm longitudinally, with the worst case being 27.8 cm and 115.1 cm, respectively [33]. Another problem with this approach is unexpected objects in dynamic surroundings. In recent years, optical camera communication (OCC) [34] has been employed for communication between vehicles and RSUs. For a variety of activities, including traffic sign recognition and determining the distance between two vehicles, OCC employs a light-emitting diode (LED), an image sensor, and infrared (IR) rays. In a vehicle ad hoc network (VANET), the highest data rate reached to date with OCC is 55 Mbps. That paper included a survey of the literature on OCC, receiver and transmitter topologies, as well as some open research problems. [PERSON] [35] investigated a highway accident detection system using CCTV and a Calogero-Moser system (an integrable system used at a crossroads). The effort attempted to overcome the difficulty in object recognition in shade and nighttime environments. In order to develop an accurate detection system, the flow of a vehicle trace was discovered to be similar to a Wigner distribution in terms of level spacing. Later on, [PERSON] developed an advanced road traffic analytics processing system [36] that can process and analyze all the data in near real time. The suggested framework was evaluated usingdata collected from 41 CCTV cameras along the Icheon-to-Gangneung highway in Korea. The prediction method was implemented in a neighborhood between CCTV cameras. [PERSON] et al. [37] suggested an approach in which LiDAR and a camera are utilized to detect and prevent a vehicle from entering a restricted space. The beacons were normal orange traffic cones with a vertical luminous pole. They reduced false-positive LiDAR detection by projecting beacons in camera footage using DL, and by validating the detection using neural-network-learned projection from the camera into the LiDAR space. The utility of the suggested approach was proved via data acquired at MississippiPipi State University's Center for CAVS. [PERSON] et al. [38] proposed a system for accident management using cellular-technology-based VANETs. This technique ensures real-time communication between various vehicles, including crashed vehicles and ambulances, and roadside communicating units that send all updates to a server. An algorithm is used for optimal routing of an ambulance to its target, i.e., the location of the injury.