# Smart Roads for Autonomous Accident Detection and Warnings
## 2 Related Works
### Cooperative Approaches
All calculations are based on parameters such as accessibility, traffic rules, passenger preferences (for comfort), safety, and energy consumption. The fuzzy rules are based on data learning in real time and on traffic rules. The impact of sensors and their relative relevance to criteria and categories, ways to relax if it is safer, and driver preferences are considered for a more flexible decision. This method is scalable and not restricted to the circumstances presented. Using a collision avoidance algorithm (CAA) and a collision avoidance strategy, the authors suggested an enhanced collision avoidance (eCA) technique [23]. The eCA technique is responsible for identifying vehicles' trajectories in order to avoid crashes. The next vehicles' trajectories are anticipated in particular by projecting the positions of previous vehicles on curved or straight segments through status indicated by blinking lights. The CAS, on the other hand, regulates the speed of the vehicle in order to avoid accidents. A simulation was run on SUMO and NS-3, demonstrating the effectiveness of the strategy by avoiding nearly every collision under all of the tested circumstances. [PERSON] et al. proposed an object-tracking-based algorithm approach to detect accidents (termed Mask-RCNN) [24]. The chance of an accident is computed using the speed and trajectory of the vehicle. On CCTV surveillance footage, it has a high detection rate and a low false alarm rate. The model was tested in a variety of situations (including rain, storms, and low light), and proved effective. They also noted a low false alarm rate of 0.53%. An accident management system was proposed in [25] that makes use of cellular technology in public transportation. This method enables communication across various components, including those in ambulances, RSUs, and servers. Furthermore, in this system, an optimal route-planning algorithm (ORPA) is proposed to optimize aggregate spatial utilization of road networks while lowering the travel cost to operate a vehicle. The ORPA was evaluated through simulations, and findings were compared with other current algorithms. In congested areas, the proposed method can also be used to offer fast routes for ambulances. All vehicles, including ambulances, are required to have a route indicator installed, as well as the ability to use remote correspondence. The ORPA outperformed in terms of average speed and travel duration, according to the evaluation data. The proposed system only works for predicted patterns and can fail due to unpredicted behavior of traffic. With the advancement of 5G technology, V2X, which emphasizes safe driving and traffic management for slightly advanced cars, is rapidly progressing. To ensure the sum rate and compliance with reliability constraints, a unicast communication paradigm [26] was suggested. In a highway scenario, the authors chose signal power and buffer size as the key restrictions for V2X communication. The focus of the study was device-to-device (D2D) resource distribution. Their proposed resource allocation algorithm was applied to resource sharing between user equipment and cellular user equipment. When compared to other existing methods, simulation results revealed that the proposed algorithm had very promising performance. Another study compared DSRC and LTE in infrastructure mode (LTE-I) and LTE-D2D in terms of average end-to-end delay and packet delivery ratio (PDR) under various communication conditions [27], which were achieved by varying the communication perimeter, message generation frequency, and road traffic intensity. In the context of V2V, [PERSON] et al. [28] measured the signal-to-interference-plus-noise ratio and reference signal received power in two scenarios to benchmark ITS-G5 and LTE-V2X (mode 3), in terms of the end-to-end latency and radio frequency conditions. The study looked at the influence of substantial data traffic on an ITS alert service, and the influence of handover on ITS safety services in the context of V2V.