FPGA Implementation of an Intelligent Traffic Light Controller (I-TLC) in Verilog
The objective of this paper is to design and implement an intelligent Traffic Light Controller system for a four way road intersection. The design is carried out using Verilog, and the hardware is implemented on a FPGA. The chosen intersection involves a 'main road' (heavy traffic flow) and a 'side road' (less traffic flow), which is equipped with sensors to detect the presence of traffic or pedestrians. The functionality of the system has undergone thorough verification through simulations conducted in the Xilinx ISE Design Studio software environment. Furthermore, it has been physically deployed on a Xilinx Spartan-3E FPGA board xc3s500e-4-fg320. A traffic light controller can be realized through the use of a microcontroller, Application-Specific Integrated Circuits (ASICs), or Field-Programmable Gate Arrays (FPGAs). FPGAs however offer significant advantages in terms of re-programmability, speed, and parallel processing capabilities, making them ideally suited for implementing complex, adaptive logic required by smart traffic management systems; thus, making this model of TLC extremely adaptive and cost efficient at the same time as compared to other existing models with reduced hardware usage and delay constraints.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Explainability of Intelligent Transportation Systems using Knowledge Compilation: a Traffic Light Controller Case
Usage of automated controllers which make decisions on an environment are widespread and are often based on black-box models. We use Knowledge Compilation theory to bring explainability to the controller's decision given…
Intelligent Traffic Light via Policy-based Deep Reinforcement Learning
Intelligent traffic lights in smart cities can optimally reduce traffic congestion. In this study, we employ reinforcement learning to train the control agent of a traffic light on a simulator of urban mobility. As a dif…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)Proposal of a Takagi-Sugeno Fuzzy-PI Controller Hardware
This work proposes dedicated hardware for an intelligent control system on Field Programmable Gate Array (FPGA). The intelligent system is represented as Takagi-Sugeno Fuzzy-PI controller. The implementation uses a fully…
Design Of Fuzzy Logic Traffic Controller For Isolated Intersections With Emergency Vehicle Priority System Using MATLAB Simulation
Traffic is the chief puzzle problem which every country faces because of the enhancement in number of vehicles throughout the world, especially in large urban towns. Hence the need arises for simulating and optimizing tr…
Hardware Neural Control of CartPole and F1TENTH Race Car
Nonlinear model predictive control (NMPC) has proven to be an effective control method, but it is expensive to compute. This work demonstrates the use of hardware FPGA neural network controllers trained to imitate NMPC w…
Model Predictive Control