Simulation of Advanced Driver System for a Merging Situation in Highway with MATLAB/Simulink

In recent years, the capacity of highways has become a crucial factor in the creation of traffic jams. Due to the increase in traffic on the roads and the impossibility of increasing the capacity of the road, a difficult situation has been created that leads to an increase in traffic jams with significant economic losses. An easy way to increase the capacity of these roads is to decrease the distance between the cars while maintaining the same speed. This approach immediately raises the problem of safety and collisions between high-speed cars. For these reasons, it is very important to use ACC (adaptive cruise control). The ACC automatically adapts the distance and speed to the vehicle in front and can be used to reduce the impact of deficiencies in the reliability of the driver, for example, stability control, longitudinal control, sudden emergency brake, etc. There is a possibility that in one situation, one or more lanes will be blocked on the highway. In this case, an approach is needed to merge the traffic flow with the remaining lanes. This maneuver is performed by human drivers every day, but in automated driving systems, it remains a challenge [15]. The purpose of this project is the implementation of a decentralized merging algorithm for a two-to-one lane reduction on highways. The system could reduce traffic congestion, particularly by reducing the distance between vehicles. According to [20], “Grouping vehicles into platoons is a method of increasing the capacity of roads. An automated highway system is a proposed technology for doing this. Platoons decrease the distances between cars or trucks using electronic, and possibly mechanical, coupling. This capability would allow many cars or trucks to accelerate or brake simultaneously”. Building and managing a platoon requires multiple technologies and poses problems in the topology of the network and communications [10] and [11] .To ensure the coordination of the vehicles, the following are essential: i) a control algorithm that regulates the relative distance with respect to the vehicle ahead and coordinates all the vehicles to stabilize the platoon, some examples of control design can be seen in [12], and ii) a communication network to exchange information among other platoons, some examples are can see in [13] These technologies also offer new opportunities for cooperative driving vehicles The control aim is the collision-free merging of two platoon of vehicles. The control algorithm can use data received from multiple vehicles in the platoon. In this work is assumed that each vehicle knows its own position and the position of the vehicle ahead. The vehicles are equipped with communication modules, which facilitate completely new strategies for the coordination of the vehicles.Outgoin