# A Systematic Literature Review of Autonomous and Connected Vehicles in Traffic Management
## 3 Research Analysis
### Traffic Management Methodologies Consisiting of Primary Goals
#### 3.2.2 Safety  
One of AIM's main objectives is to increase a specific intersection's safety. By concentrating on several subgoals, such as preventing collisions and resolving potential conflicts, several strategies have been put forth to accomplish this aim. Model Predictive Control is a strategy presented by [25] to ensure the intersection's traffic flow is free of collisions. For comparison, examples of simulations were created in the VISSIM and CarSim simulation platforms. Similarly, ref. [58] developed a cooperative driving technique for navigating intersections to reduce crashes and accidents. They suggested a decentralized method that enables moving vehicles to navigate intersections safely by successively resolving local optimization issues. Similarly, ref. [92] proposed a rule-based way to establish optimal vehicle order and safe braking while considering real-time collision detection. The speed control approach serves as the method's foundation to prevent crashes, clarify the order of the vehicles, and let them pass through the uncontrolled junction. To reduce AV conflicts at an unsignalized junction, a cooperative approach was suggested in [25]; when a conflict was found, the proposed technique used the cost function to determine the best course of action for the vehicle. A centralized model predictive control (MPC) was also recommended by [93] to regulate the AVs crossing the junction and avoid crashes. They expressed the issue as a convex quadratic program in spatial coordinates to produce the best possible trajectories. They also considered penalized time gaps to boost safety in the event of sensor faults. Along the same line, to keep track of the control inputs and enhance vehicle safety [92], a mixed-integer quadratic programming (MIQP)-based real-time intersection supervisor was created to improve vehicle safety. The junction supervisor may override the vehicle control instructions to ensure safe operation. To address the coordination issue at intersections, ref. [60] proposed utilizing a dispersed and parallelizable technique called the augmented Lagrangian-based alternating direction inexact Newton (ALADIN) approach. Deep learning algorithms are also helpful for improving safety at intersections aside from that. One paper [93] suggested a safety framework based on the common Time to Collision (TTC) metric in this context. The framework primarily examines the possibility of lateral overlap and the time difference between the target vehicle and its surrounding vehicles. Later, an automated technique for developing trajectory data is constructed with image processing to generate the trajectory data from the study sections. With the growth of technology, it is now possible to produce trajectory data in real-time and put the safety framework in place. The essential areas of the road network may be identified using the research approach to receive better care and increase safety in such areas. In non-signalized junction scenarios, ref. [60] suggested a design strategy for the coordination of velocity profiles of autonomous vehicles. The synchronization is driven by the need to minimize energy loss caused by vehicle collisions and stop-and-go junction procedures. Another study [94] focused on connected autonomous vehicles working at smart crossings using a suitable navigation technique. This effort aims to develop a cooperative navigation system that will enable cooperative collision avoidance to improve the intersection's capacity and safety. This research's effectiveness is verified in a MATLAB/Simulink environment. Doing this prevents the car from hitting any other vehicles at the junction. As shown in Table 3, the techniques to enhance safety could be categorized as rule-based (for instance, [57; 94]), optimizing (e.g., [43; 61]), hybrid (e.g., [25]), and machine learning (e.g., [43]) techniques to create conflict-free intersection management approaches. Highly suggested base cases and strategies were examined in a simulated setting.