Considering the significant advancements in autonomous vehicle technology, research in this field is of interest to researchers. To automatic parking, controlling steer angle, gas hatch, and brakes need to be learned. Due to the increase in the number of cars and road traffic, car parking space has decreased. Its main reason is information error. Because the driver does not receive the necessary information or receives it too late, he cannot take appropriate action against it. This paper uses two phases: the first phase, for goal coordination, was used genetic algorithms and the Cuckoo search algorithm was used to increase driver information from the surroundings. Using the Cuckoo search algorithm and considering the limitations, it increases the driver’s level of information from the environment. Also, by exchanging information through the application, it enables the information to reach the driver much more quickly and the driver reacts appropriately at the right time. The suggested protocol is called the multi-objective decision-based solution (MODM)-based solution. Here, the technique is assessed through extensive simulations performed in the NS-3 environment. Based on the simulation outcomes, it is indicated that the parking system performance metrics are enhanced based on the detection rate, false-negative rate, and false-positive rate. پرونده مقاله

In recent years, formal methods have been used as an important tool for performance evaluation and verification of a wide range of systems. In the view points of engineers and practitioners, however, there are still some major difficulties in using formal methods. In this paper, we introduce a new formal modeling language to fill the gaps between object-oriented programming languages (OOPLs) used by engineers and the formalisms used for evaluation and verification purposes. We propose the syntax and semantics of a new object-oriented modeling language for discrete-event systems called RayLang. We have designed the syntax of RayLang similar to OOPLs. In RayLang models, objects that are instantiated from classes, run concurrently and can communicate with each other by requesting services. Every object in RayLang models has some internal state variables and some service handlers for executing the requests of other objects. We have shown that Markovian RayLang models can be transformed into continuous-time Markov chains (CTMCs) and then can be solved by existing solution techniques. For modeling, discrete-event simulation and analytic solution of RayLang models, we have implemented these models in the PDETool framework. پرونده مقاله