leads 0.8.22

Lightweight Embedded Assisted Driving System

LEADS: Lightweight Embedded Assisted Driving System

LEADS is a lightweight embedded assisted driving system. It is designed to simplify the development of the instrumentation and control system for electric vehicles. It is written in well-organized Python and C/C++ with impressive performance. It is not only plug-and-play (the VeC Project) but also fully customizable. It provides multiple abstract layers that allow users to pull out the components and rearrange them into a new project. You can either configure the existing executable module leads_vec and leads_vec_rc simply through a JSON file or write your own codes based on the framework as easily as building a LEGO.

The hardware components chosen for this project are geared towards amateur developers. It uses neither a CAN bus nor any dedicated circuit board, but generic development kits such as Raspberry Pi and Arduino instead. However, as it is a high-level system running on a host computer, the software framework has the ability to adapt to any type of hardware component if you are willing to write some codes.

This document will guide you through LEADS VeC. You will find a detailed version here.

LEADS VeC Demo

LEADS VeC Demo (Manual Mode)

:link: Docs

:link: Remote Analyst Online Dashboard

Key Features

• Modern UI design
• Auto dark mode support
• Fancy widgets
• TCP communication system
• Remote analyst
• Replaying recorded data
• Data recording system with the following components
  • A speed recording system
  • A G force recording system
  • A GPS recording system
  • A battery voltage recording system
• ESC with the following components
  • DTCS (Dynamic Traction Control System)
  • ABS (Anti-lock Braking System)
  • EBI (Emergency Braking Intervention)
  • ATBS (Automatic Trail Braking System)

To High School Students

The codes are never designed for average high school students to understand. You may find it hard to read the codes if you do not satisfy the following requirements of skills and knowledge.

• Advanced Python knowledge (you should be familiar with everything and even programming philosophy in Python)
• Solid knowledge of Physics (you should understand how a car moves in reality)
• Basic embedded development experience (C/C++, Raspberry Pi, Arduino, serial communication, PWM)
• Rich experience in Web development (React, Next.js, FastAPI, TCP/IP, sockets)
• Basic machine learning knowledge (linear regression, polynomial regression)

Installation

Python

Note that LEADS requires Python >= 3.12. To set up the environment on a Raspberry Pi by only a single line of command, see Environment Setup.

pip install Pillow PySDL2 customtkinter gpiozero lgpio pynmea2 pynput pysdl2-dll pyserial leads

numpy and pandas will be automatically installed with leads.

Pillow, PySDL2, customtkinter, gpiozero, lgpio, pynmea2, pynput, pysdl2-dll, and pyserial are optional.

If you only want the framework, run the following.

pip install leads

Verify

python -m leads_vec info

Arduino

You can install LEADS-Arduino from Arduino Library Manager. Note that it is named "LEADS", not "LEADS-Arduino", in the index.

LEADS Framework

See Read the Docs for the documentation of how to customize and make use of the framework in your project.

Quick Start

Main

python -m leads_vec run

Optional Arguments

Run the following to get a list of all the supported arguments.

python -m leads_vec -h

Specify a Configuration File

python -m leads_vec -c path/to/the/config/file.json run

If not specified, all configurations will be default values.

To learn about the configuration file, read Configurations.

Specify a Devices Module

python -m leads_vec -d path/to/the/devices.py run

To learn about the devices module, read Devices Module.

Generate a Configuration File

python -m leads_vec -r config run

This will generate a default "config.json" file under the current directory.

Register as a Systemd Service

python -m leads_vec -r systemd run

This will register a system service to start the program.

To enable auto-start at boot, run the following.

systemctl daemon-reload
systemctl enable leads_vec

Specify a Theme

python -m leads_vec -t path/to/the/theme.json run

To learn about themes, read Color and Themes.

Magnify Font Sizes

python -m leads_vec -mfs 1.5 run

This will magnify all font sizes by 1.5.

Use Emulation

python -m leads_vec --emu run

This will force the program to use emulation even if the environment is available.

Automatically Magnify Font Sizes

python -m leads_vec --auto-mfs run

Similar to Magnify Font Sizes, but instead of manually deciding the factor, the program will automatically calculate the best factor to keep the original proportion as designed.

Remote Analyst

python -m leads_vec_rc

Go to the online dashboard at https://leads-vec-rc.projectneura.org.

Optional Arguments

Run the following to get a list of all the supported arguments.

python -m leads_vec_rc -h

Server Port

python -m leads_vec_rc -p 80

If not specified, the port is 8000 by default.

Specify a Configuration File

python -m leads_vec_rc -c path/to/the/config/file.json

If not specified, all configurations will be default values.

To learn about the configuration file, read Configurations.

If you install Python using the scripts, you will not find python ..., python3 ..., pip ..., or pip3 ... working because you have to specify the Python version such that python3.12 ... and python3.12 -m pip ....

Environment Setup

This section helps you set up the identical environment we have for the VeC project. A more detailed guide of reproduction is available here, but first of all, we run an Ubuntu 22.04 LTS on a Raspberry Pi 4 Model B 8GB. After the OS is set up, just run the one-line commands listed below. You may also choose to clone the repository or download the scripts from releases (only stable releases provide scripts).

You can simply run "setup.sh" and it will install everything including LEADS for you. If anything goes wrong, you can also manually install everything.

/bin/sh "setup.sh$(wget -O setup.sh https://raw.githubusercontent.com/ProjectNeura/LEADS/master/scripts/setup.sh)" && rm setup.sh || rm setup.sh

We also use OBS Studio for streaming, but it is not required. If you want to install, run "obs-install.sh".

/bin/sh "obs-install.sh$(wget -O obs-install.sh https://raw.githubusercontent.com/ProjectNeura/LEADS/master/scripts/obs-install.sh)" && rm obs-install.sh || rm obs-install.sh

Do not run the OBS Studio directly, instead, use "obs-run.sh".

wget -O obs-run.sh https://raw.githubusercontent.com/ProjectNeura/LEADS/master/scripts/obs-run.sh
/bin/sh obs-run.sh

Configurations

The configuration is a JSON file that has the following settings. You can have an empty configuration file like the following as all the settings are optional.

{}

Note that a purely empty file could cause an error.

Index	Type	Usage	Used By	Default
w_debug_level	str	"DEBUG", "INFO", "WARN", "ERROR"	Main, Remote	"DEBUG"
data_seq_size	int	Buffer size of history data	Main	100
data_dir	str	The directory for the data recording system	Remote	"data"
width	int	Window width	Main	720
height	int	Window height	Main	480
fullscreen	bool	True: auto maximize; False: window mode	Main	False
no_title_bar	bool	True: no title bar; False: default title bar	Main	False
theme_mode	bool	"system", "light", "dark"	Main	False
manual_mode	bool	True: hide control system; False: show control system	Main	False
refresh_rate	int	GUI frame per second	Main	30
m_ratio	float	Meter widget size ratio	Main	0.7
font_size_small	int	Small font size	Main	14
font_size_medium	int	Medium font size	Main	28
font_size_large	int	Large font size	Main	42
font_size_x_large	int	Extra large font size	Main	56
comm_addr	str	Communication server address	Remote	"127.0.0.1"
comm_port	int	The port on which the communication system runs on	Main, Remote	16900
save_data	bool	True: save data; False: discard data	Remote	False

Devices Module

Example

from leads import controller, MAIN_CONTROLLER
from leads_emulation import RandomController


@controller(MAIN_CONTROLLER)
class MainController(RandomController):
    pass

The devices module will be executed after configuration registration. Register your devices in this module using AOP paradigm. A more detailed explanation can be found here.

Architecture

Main

Pin Configuration

Remote Analyst

Collaborations

Community

Issues

Our team management completely relies on GitHub. Tasks are published and assigned as issues. You will be notified if you are assigned to certain tasks. However, you may also join other discussions for which you are not responsible.

There are a few labels that classify the issues.

• bug reports a bug
• code review discusses a code review or comment
• documentation suggests a documentation enhancement
• duplicate marks that a similar issue has been raised
• enhancement proposes a new feature or request
• help wanted means that extra attention is needed to this issue
• invalid marks that the issue is in a valid format
• question requests further information
• report states that it is discussed in the meeting
• todo creates a new task
• wontfix marks that the issue is ignored

Label your issue with at least one of the labels above before you submit.

Projects

You can have a look at the whole schedule of each project in a timeline using the projects feature.

Code Contributions

See CONTRIBUTING.md.