Melih Akay 🦾

        • Active learning
        • Adjoint Matrix
        • Adjugate Matrix
        • Analysis of Variances
        • Best Linear Unbiased Estimator
        • Bicycle Model
        • Block matrix
        • Cofactor Matrix
        • Complex Conjugate
        • Complex Numbers
        • Conjugate Matrix
        • Crame'r-Rao lower bound
        • Curriculum learning
        • Definite matrix
        • Degenerate random variable
        • Descriptive Statistics
        • Determinant
        • Diagonal Matrix
        • Differential Equations
        • Direction fields
        • Distance
        • Distribution parameters
        • Dummy encoding
        • Echelon form
        • Efficiency of an estimator
        • Eigendecomposition
        • Eigenvalues
        • Eigenvectors
        • Encoding categorical variables
        • Estimation
        • Estimator
        • Euclidean Distance
        • Evaluating estimators
        • Exact equations
        • Existence-uniqueness theorem for differential equations
        • Expected Value
        • Exponential growth or decay
        • Fisher information
        • Gamma distribution
        • Gaussian elimination
        • Generalized inverse
        • Generative models
        • Homogeneous equations
        • Hungarian Algorithm
        • Idempotent matrix
        • Identity matrix
        • Incremental object detection
        • Inertial Measurement Unit
        • Inner product
        • Inverse of a matrix
        • Invertibility of a matrix
        • Jetson AGX Xavier
        • Kolmogorov–Smirnov test
        • Limit and Continuity of Functions with Several Variables
        • Linear Algebra
        • Linear combination
        • Linear equations
        • Linear independence
        • Linear Models
        • Linear regression model
        • Linearity
        • Mahalanobis Distance
        • Matrices of functions
        • Matrix
        • Matrix functions
        • Maximum likelihood estimation
        • Mean squared error of an estimator
        • Method of moments
        • Minor of a Matrix
        • Modulus of a complex number
        • Moments
        • Multiple linear regression
        • Multivariate Analysis
        • Multivariate normal distribution
        • Non-parametric Statistics
        • Normal Matrix
        • One-hat encoding
        • Ordinary differential equation
        • Orthogonal
        • Orthogonal matrix
        • Partial differential equation
        • Pearson correlation coefficient
        • Power of a matrix
        • Precision matrix
        • Principle of superposition
        • Probability Distribution
        • Quadratic form
        • Random variable
        • Rank of matrix
        • Removing outliers
        • Repicrocal of a complex number
        • Runge-Kutta method
        • Scaling the data
        • Separable equations
        • Simple linear regression
        • Singular matrix
        • Skew symmetric matrix
        • Spectral Decomposition
        • Square Matrix
        • Statistic
        • Statistical Design of Experiments
        • Statistical Inference
        • Stream-based DAL
        • Symmetric matrix
        • Systems of first order ODE's
        • Systems of linear equations
        • Topology
        • Trace of a matrix
        • Transformer-base Object Detection
        • Unbiased estimator
        • Uniformly minimum variance unbiased estimator
        • Variance & Covariance
        • Wronskian
          • Data Parallelism, How to Train Deep Learning Models on Multiple GPU's
          • Fundamentals of Deep Learning
            • Autonomous Checklist
            • Autonomous Mission Indicator
            • Autonomous System Brake
            • Autonomous System Master Switch
            • Autonomous System Status Indicator
            • Data Logger
            • Electronical Control Unit
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            • Ready to Drive
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            • Sensors
            • Shutdown Circuit
            • System Critical Signal
          • Formula Student
          • Formula Student Driverless
          • METU Formula Racing
          • Wheelie Roadmap
          • Wheelie: An End-to-End Autonomous Racing Framework for Formula Student Driverless Competition
          • KOBOT
          • Dealing with missing values
          • How to select the device in PyTorch
          • learnpytorch.io
          • NovoGrad Optimizer
          • PyTorch
          • PyTorch Fundamentals
          • PyTorch Tensors
        • Adaptive ASHA Searcher
        • Determined.AI Hyperparameter Tuning
        • DeterminedAI
        • DevrimCAN Structure
        • Foxglove CLI
        • How to clear Jupyter kernel
        • How to flash Jetson AGX Xavier
        • How to install onnxruntime_gpu Jetson
        • How to install REALTEK RTL88x2B USB Linux Driver
        • Hyperparameter Tuning
        • MCAP CLI
        • Object Oriented Programming with Java
        • Obsidian
        • Obsidian Callouts
        • pd.cut
        • Quartz

    Recent writing

    • Wheelie Roadmap

      Nov 21, 2025

      • wheelie
      • formula-student-driverless
    • Invertibility of a matrix

      Nov 21, 2025

      • linear-algebra
      • mathematics
    • About me

      Nov 21, 2025

      Home

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      METU Formula Racing

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      Autonomous System Master Switch

      Autonomous System Master Switch

      Nov 21, 20251 min read

      ASMS is basically just a Master Switch, thus it should satisfy MS rules.

      T 14.5.3 The ASMS must be marked with “AS”.

      Supply of the autonomous actuators must be directly connect by the ASMS. FSG25 AS Beginner's Guide. Check FSG25 Rules T.1.3.1

      One has to use forcibly guided relay with ASMS to bypass RES. FSG25 AS Beginner's Guide


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