# Smart Roads for Autonomous Accident Detection and Warnings
###### Abstract  
An increasing number of vehicles on the roads increases the risk of accidents. In bad weather (e.g., heavy rainfall, strong winds, storms, and fog), this risk almost doubles due to bad visibility as well as road conditions. If an accident happens, especially in bad weather, it is important to inform approaching vehicles about it. Otherwise, there might be another accident, i.e., a multiple-vehicle collision (MVC). If the Emergency Operations Center (EOC) is not informed in a timely fashion about the incident, fatalities might increase because they do not receive immediate first aid. Detecting humans or animals would undoubtedly provide us with a better answer for reducing human fatalities in traffic accidents. In this research, an accident alert light and sound (AALS) system is proposed for auto accident detection and alerts with all types of vehicles. No changes are required in non-equipped vehicles (nEVs) and EVs because the system is installed on the roadside. The idea behind this research is to make smart roads (SRs) instead of equipping each vehicle with a separate system. Wireless communication is needed only when an accident is detected. This study is based on different sensors that are used to build SRs to detect accidents. Pre-saved locations are used to reduce the time needed to find the accident's location without the help of a global positioning system (GPS). Additionally, the proposed framework for the AALS also reduces the risk of MVCs. vehicle; road; accident; autonomous; smart road 20  
provided in nEVs. A question arises about why we rely on vehicle sensors or smartphone-based systems. The GSM signal is weak in many distant areas, and communication links might be unstable in those areas. On the other hand, a GPS requires 10 to 15 min to fix a location for the first time, which leads to late broadcasts. The main goal of this research is to:  
1. introduce a new framework of smart road based on multiple sensors to save the lives of people injured in an accident, and protect people and vehicles against MVCs;
2. detect Vas autonomously without using vehicular sensors;
3. alert drivers of approaching vehicles about an accident, even without vehicular communications;
4. inform an Emergency Operations Center (EOC) about an accident and its location without needing a GPS. According to one dictionary, the word accident is defined as \"an uncertain event which may lead to injury, loss of life, or property damage\" [2]. An accident is also defined as \"an event in which one or more vehicles hit in such a way that may lead to loss of life or injury or vehicle damage, resulting in a traffic blockage on the road\". The risks for loss of life, injuries, and other damage may increase if an incident is not reported to an EOC in a timely fashion. Lives can be saved by sending timely information about an accident through an automated mechanism. Moreover, quick automobile accident detection and an alert system are required to protect approaching vehicles against an MVC. Several methods have been implemented in advanced vehicles (Avs) for avoiding an accident. An accident threat is detected through sensors installed in vehicles or by using smartphone sensors. Previous researchers have used accelerometers, smoke detectors, infrared (IR) obstacle sensors, proximity sensors, and biosensors to detect an accident. A microcontroller board collects sensor information. A GPS receiver is used for location tracking and monitoring speeds, while GSM, LTE, and 5G technologies send information about an accident. Event information can include the location and time, videos, and images of the event for the EOC. There are two methods to detect accidents autonomously; we can equip all vehicles, or we can develop smart roads that can sense any type of accident and convey messages wirelessly to an EOC. To protect vehicles around the accident area, a new framework is proposed, i.e., an accident alert light and sound (AALS) system.