# V2X-Based Highly Reliable Warning System for Emergency Vehicles
## 2 Literature Survey
Any malfunction of one or more subsystems of RRP may lead to accidents; this is the major disadvantage of this method. In [17], the integer linear program (ILP) gives information about the EV's movement through a transportation link. After collecting the vehicle's speed and location, ILP finds an intra-link path, and vehicles in that path will receive the emergency response vehicle's (ERV) maneuvering instructions and a request to stop at its place. However, this system only works for a single ERV, which is a major disadvantage, as it fails to deal with multiple ERVs. In [29], V2V safety applications are based on forward error correction (FEC) codes such as raptor Q. Their mobility model is used to update the position, speed and acceleration every 100 ms. They evaluated full-duplex operation for cellular V2V for safety broadcast. The system evaluated the comprehensive performance of V2V safety broadcast using cellular and IEEE 802.11p technologies. In [30], to alert other vehicles about the EV'sapproach, exchanging of safety-related broadcast messages between vehicles occurred using V2V communication. These messages are sent periodically to announce each vehicle's current state to other neighboring vehicles, and its performance is increased by a relaying system called relay-assisted enhanced V2V (RA-eV2V). As it is a 360\({}^{\circ}\) communication, we cannot say it is an alert coming only from the vehicle behind it. It is a major drawback of this paper. An optimal transmission reliability enhancement mechanism (OTREM) was proposed in [31] for enhancing the emergency warning system through a cooperative driving strategy. OTREM improves the propagation of the warning messages and modifies the solution for the problems in the warning message transmission. In [32], adaptively changing the sequence of traffic signals based on the traffic density is obtained by using image processing on several road patterns. The server will collect these data and the control traffic lights. Contrast-limited adaptive histogram equalization (CLAHE) is used to reduce the noise in the image. Bilateral filtering is used to smooth the process by maintaining the structure of the image. A binary threshold converts the image into binary. The major disadvantage is that this system will not work at night or in bad weather conditions, and for calculating traffic density, it needs high-definition cameras. In [9], decentralized environmental notification messages (DENM) help vehicles to notify an accident or other hazards on the road. Cellular vehicle-to-everything (C-V2X), characterizes the DENM latency and reliability performances. The conducted study does not work better in bad weather conditions, such as rain or storms, leading to a drawback. In [10], the congestion control protocol tests and validates any V2V-equipped vehicle with the J2945/1 standard. This system works even under heavy traffic congestion with 600 ms of inter-transmit time (ITT) so that a vehicle can be tracked accurately. As it is a 360\({}^{\circ}\) communication, we cannot say it is an alert only from the vehicle behind it. It is a major drawback of this paper. In [33], VANET is used to carry sensing data using DSRC. Multi-hop transmissions for gathering data to RSU in VANET have low data rates and long end-to-end delays. This problem is overcome by using a traffic-differentiated clustering routing (TDCR) mechanism in a software-defined network (SDN)-enabled hybrid vehicular network. Overall, most of the existing solutions consider only the location of the vehicles or the distance of the vehicles in that location. Thus, considering the limited number of factor delays the EV in reaching the destination makes room for this research. Hence, in our proposed J2H approach, we considered additional factors such as the number of lanes, emergency level, types of roads, traffic density, number of EVs approaching, and time of arrival of the vehicles in real time for finding the best way for the EV to travel and reach the destination on-time.