# Smart Roads for Autonomous Accident Detection and Warnings
## 3 Proposed Accident Alert Light and Sound System  
In BWC, MVCs can happen where a number of approaching vehicles can lead to another accident. In this case, damage and the number of injured people, and/or fatalities might increase. The common cause for this type of accident is poor visibility whereby drivers cannot see the accident until they come upon it (approximately 10 to 15 m away). At that distance, braking will not stop the vehicles in time and, as a result, they become part of the accident. In modern vehicles, some preventive and protective systems are installed for the safety of the driver and passengers. However, in Third World countries, for example, more than 80% of vehicles have no factory-installed protective systems [53]. Until now, no system can handle such situations for all vehicles in an old or late model. Based on the literature review, almost all the work carried out so far is either used for modern vehicles or to make older vehicles into Evs. Evs have some system installed in either a mobile phone application or a microcontroller-based system. All vehicles that have any type of preventive measure and alert system are considered equipped vehicles. Evs act as a source generating accident alert messages. However, if a vehicle is damaged badly or burned in an accident, the system may fail, and no information may be sent to an EOC. In a mobile-phone-based system, the mobile phone may be damaged in an accident. It is not easy to convert all old vehicles into Evs due to financial costs. Another limitation is the need for timely calibration of the sensors in smartphone-based and vehicle-based systems, which is difficult to do. Mobile phones are often prone to false positives, and GSM signals may drop in some areas. If a GPS is used to find locations, major drawbacks are inaccurate and depend on satellite signals. It is difficult to use pre-saved locations while vehicles are moving. It is also notable that no research work has been carried out for accident detection by nEVs. There is a need for a system that works from outside the vehicle for detection of an accident and generating alerts for approaching vehicles in order to avoid MVCs. A new concept of making smart roads is introduced here. SRs have different types of sensors and actuators installed for autonomous detection of accidents. SRs have nodes (a completely independent system) that are nearly 50 m apart. Because these nodes are fixed on the roadside, it is possible to use their pre-saved locations. A node that detects an accident sends its pre-saved location to an EOC for the quickest rescue operation, saving lives and reducing damage. The main part of the SR is an alert system, called an AALS, which makes drivers of approaching vehicles aware of an accident. The AALS is a system designed for nEVs and EVs to avoid MVCs. Most of the previous researchers have tried to build a system in which vehicles are able to sense and communicate with each other through devices. In short, they try to make all vehicles equipped. However, equipping all vehicles with the same type of prevention and communication mechanism is difficult to achieve. Modern vehicles may have a factory-built protection system installed. In the system proposed here, a golden yellow blinking light is used with a siren to alert vehicles to an accident. According to one study of different colored lights, red and golden yellow light are visible from a long distance and in bad weather [54]. Red lights are already used for traffic signals; thus, using golden yellow light is a good option. Another parallel way of alerting drivers is with a loud siren, so drivers can hear it and take precautionary measures to avoid being involved in an MVC, especially in BWC. These alerts are generated through an auto mechanism. The proposed system will be installed on both sides of the road. A complete system based on applied studies was built with hardware (including microcontroller boards), different sensing units, and with alert functions.