Week of 9/27/2021 - Weekly Report 4

Decision Matrix

-LiDAR

-Electric RC Car

Next week plans

-Work on HW 4

-Work on getting the RC car responding to Arduino and implement CAN bus system

Milestones

Jacob

• Implement auto-parking. This includes parking in a traditional parking spot with varying tightness of the spot. The tightness of the spot will vary by increasing or decreasing inches wider than the total width of the car.

Jordyn

We agreed to separate the project into 4 different tasks. I am responsible for object detection. Last week I spoke with Dr. Smith from the mechanical engineering department about cameras that would work well with this project. We discussed using the Raspberry Pi camera module. The Raspberry Pi camera can detect objects in real-time using TensorFlow and Open CV software.

This week I will decide which model of Raspberry Pi to use for the project. I will use a decision matrix to help select the best model. Upon receiving approval from the department, I plan to purchase the camera and start working with it.

DJ

Responsible for implementing Adaptive Cruise Control (ACC). Implementing ACC to the smart car builds on the work of a previous engineering team that was able to implement basic anti-collision functionality, which allowed an electric vehicle to safely stop certain distances before hitting an object. The ACC functionality will allow the smart car to maintain a pre-determined speed while also following another vehicle from a safe distance. If the vehicle in front decreases its speed, the smart car should be able to slow itself down to maintain a safe distance. ACC will be implemented using a TFmini Lidar Module that is connected to a "SMART" node of a Controller Area Network (CAN) bus network that was used by the previous engineering team.

The plan for this week is to study the CAN bus module used by the previous year's team to get a broad sense of how it can be applied to this year's project. Also, research will be conducted on the Adaptive Cruise Control systems used in the automotive industry to see what techniques or algorithms could be used for the smart car.

The following image gives a general understanding of how adaptive cruise control works for full-sized vehicles.

Quinn

• Implement point to point autonomous driving, using the GPS functionality of an Arduino chip.

• Work with Dr. Smith to integrate this control system and ensure its functionality.

• Due to changes in group responsibilities, I will be in-charge of implementing a sensor system designed to mitigate GPS errors that reach inaccuracies up to 3 meters at given moment. These sensor will operate separately from the other sensors designed for the smart car. The end goal of these sensor is to integrate with the GPS system of the Arduino chip so that point to point navigation is accurate, and not suffering from GPS 3 meter variation.