- Harou Xue - Electrical Engineering
- Yuhan Zhang - Electrical Engineering
- Cheyenne Herrera - Math/Engineering
The goal of our project is to create a miniature version of a Tesla. We wanted to increase the safety of the self-driving car by implementing rear-end collision prevention as well as apply the lane change safety. The Donkey RoboCar will stop itself when approaching an object in the front using a TOF sensor mounted to it. Additionally, the car will speed up if a vehicle/object is approaching it from behind. Furthermore, the RoboCar will implement lane change on command.
- Jetson Nano with fan and wirless card installed
- PCA9685 PWM (control servo and ESC)
- Steering Servo (control steering)
- Electronic speed controller (ESC) (control throttle)
- Relay (provide emergency stop)
- LED (show emergency stop status)
- USB camera
- Arduino (for connecting ToF sensor)
- Time-of-flight sensor (ToF)
- Lidar and USB controller
Donkey and parts
We use the Donkey Car framework for car control. With the framework, we can easily train deep learning autonomous driving models by recording manual driving. The frameworks use modularized "parts" to manage all the components in a car. When the car runs, it loops through all parts that have been added to it. Not only sensors can be Donkey parts, controllers and actuators are also Donkey parts.
Our project involves new sensors, ToF and Lidar, that have not been included in Donkey. They should be added to Donkey in the form of parts.
We connect the Lidar and ToF(Arduino) using serial ports. We need to add our user to a group that has access to serial ports.
sudo usermod -a -G dialout jetson
To use the PyLidar3 library
Create an instance and connect
lidar = YdLidarX4("/dev/ttyUSB0") lidar.Connect()
scans = self.lidar.StartScanning() for scan in scans: for i in range(360): self.scan[i] = scan[i]
Stop Lidar and disconnect
We use Adruino to connect to the ToF sensor.
myArduino = serial.Serial('/dev/ttyACM0', 115200)
Get sensor reads
myArduino.flushInput() ser_bytes = myArduino.readline() try: distance = float(ser_bytes[0:len(ser_bytes) - 2].decode("utf-8"))
Donkey uses a dictionary to save data that flow through each part. The data used as input or output of parts should be defined when adding parts.
Example: adding Lidar to Vehicle in manage.py V.add(lidar, outputs=['lidar/scan', 'lidar/time'], threaded=True)
Lane changing behavior training
Donkey framework supports training different behavior states. We can use that to train a model that is able to perform lane changing. https://docs.donkeycar.com/guide/train_autopilot/#training-behavior-models
Rear collision prevention
Our first goal is to provide rear collision prevention. When another car is going to crash into the back of our car and there is no obstacle in front of our car. We can accelerate forward to prevent a collision. To use Lidar to detect objects in the back. The car is 25 centimeters in width so if we want to detect something that wide 20 centimeters away from the back, we need about 60 degrees of Lidar measurement.
Safe lane changing
When changing lane, it is not safe to just look at mirrors. Using Lidar we can detect cars in the blind spot and override steering control to prevent unsafe lane changing.
More specifically, we divide Lidar scan into regions