self-driving-car-sim | A self-driving car simulator built with Unity | Learning library

 by   udacity C# Version: v1.45 License: MIT

kandi X-RAY | self-driving-car-sim Summary

kandi X-RAY | self-driving-car-sim Summary

self-driving-car-sim is a C# library typically used in Manufacturing, Utilities, Automotive, Tutorial, Learning, Unity applications. self-driving-car-sim has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

This simulator was built for Udacity's Self-Driving Car Nanodegree, to teach students how to train cars how to navigate road courses using deep learning. See more project details here. All the assets in this repository require Unity. Please follow the instructions below for the full setup.
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            kandi-support Support

              self-driving-car-sim has a medium active ecosystem.
              It has 3793 star(s) with 1466 fork(s). There are 226 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 53 open issues and 70 have been closed. On average issues are closed in 217 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of self-driving-car-sim is v1.45

            kandi-Quality Quality

              self-driving-car-sim has 0 bugs and 0 code smells.

            kandi-Security Security

              self-driving-car-sim has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              self-driving-car-sim code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              self-driving-car-sim is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              self-driving-car-sim releases are available to install and integrate.

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            self-driving-car-sim Key Features

            No Key Features are available at this moment for self-driving-car-sim.

            self-driving-car-sim Examples and Code Snippets

            No Code Snippets are available at this moment for self-driving-car-sim.

            Community Discussions

            Trending Discussions on self-driving-car-sim

            QUESTION

            How to prevent a lazy Convolutional Neural Network?
            Asked 2017-Dec-22 at 15:12

            How to prevent a lazy Convolutional Neural Network? I end with a ‘lazy CNN’ after training it with KERAS. Whatever the input is, the output is constant. What do you think the problem is?

            I try to repeat an experiment of NVIDIA’s End to End Learning for Self-Driving Cars the paper. Absolutely, I do not have a real car but a Udacity’s simulator . The simulator generates figures about the foreground of a car.

            A CNN receives the figure, and it gives the steering angle to keep the car in the track. The rule of the game is to keep the simulated car runs in the track safely. It is not very difficult.

            The strange thing is sometimes I end with a lazy CNN after training it with KERAS, which gives constant steering angles. The simulated car will go off the trick, but the output of the CNN has no change. Especially the layer gets deeper, e.g. the CNN in the paper.

            If I use a CNN like this, I can get a useful model after training.

            ...

            ANSWER

            Answered 2017-Dec-22 at 15:12

            I can't run your model, because neither the question not the GitHub repo contains the data. That's why I am 90% sure of my answer.

            But I think the main problem of your network is the sigmoid activation function after dense layers. I assume, it will train well when there's just two of them, but four is too much.

            Unfortunately, NVidia's End to End Learning for Self-Driving Cars paper doesn't specify it explicitly, but these days the default activation is no longer sigmoid (as it once was), but relu. See this discussion if you're interested why that is so. So the solution I'm proposing is try this model:

            Source https://stackoverflow.com/questions/47846824

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install self-driving-car-sim

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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