UVU Computer Engineering Capstone Project

Universal Smart Car Kit

Team Members: Bridger Miles and Chance Cochrane

Faulty Advisor: Dr. Afsaneh Minaie

Someone Driving inside a car brochure for Universal Smart Car Kit

In 2019, a study done by the National Highway Traffic Safety Administration concluded that 94% of the serious vehicle accidents that occurred in 2018 were due to human error. They believe that with the incorporation of autonomous vehicles in American society we can save the lives of the nearly 36,560 people that died in 2018 [1]. They support this claim with the evidence that lane-assist, blind-spot monitoring, and brake assist have helped decrease the deaths per 100,000 people from approximately 23 people in 1980 to 11 deaths per 100,000 people in 2018 [2]. With these new components in technology, vehicles can avoid accidents caused by drowsy or distracted drivers. They also believe that with fully autonomous vehicles we can cut down on roughly $190 billion every year just in health care costs [3]. They admit that with enough advancement in autonomous vehicles they can become completely driverless avoiding accidents indefinitely allowing for faster travel time and increased efficiency in traffic flow. As you can see adding a level of automation to the driving experience can drastically reduce these statistics and improve the life of the general public in multiple ways.

In this project a universal smart car kit was developed to give older cars with less technology modern features. This kit is compatible with any car manufactured after 1996 as long as it supports OBDII. This kit includes a backup camera, blind-spot monitoring system, and a live engine monitoring system. The kit was prototyped using a 2002 Lexus Is300, which has very limited technology for its time. This was accomplished using a Raspberry Pi 4, Raspberry Pi Pico, Elm327 Microcontroller, USB camera, and some HC-SR04 ultrasonic sensors. These features are all output to an interactive touchscreen for the driver. The kit will be sold for under $200 and will be available to purchase online. The kit is an easy DIY install and will take under 20 minutes for the average consumer to install and setup requiring no vehicle modifications. To install the kit the user will simply plug in the ELM327 microcontroller into the cars OBDII port. Mount the screen to the dash using the provided Velcro strips. Supply power to the system by plugging it into the cars cigarettes lighter. Plug in the fuse for the reverse lights. Mount the backup camera to the rear of the vehicle as well as the 2 ultrasonic sensors. To setup the system the user simply starts the car and the device will automatically connect and initialize all of the systems.

The Raspberry Pi 4 acts as the main hub for the system. The source code is run here that drives the GUI as well as the main application which was written in Python using multi-threading for the different modules. This is connected to the ELM327 Microcontroller over a Bluetooth serial communication which is connected to the car's OBDII port for receiving data from the car’s engine control module in real-time. This data isrelayed to the Raspberry Pi and printed to the GUI. The blind-spot monitoring system is comprised of a Raspberry Pi Pico microcontroller running micro Python. This MCU runs a simple algorithm that gathers input data from the left and right HC-SR04 ultrasonic sensors mounted to the rear of the car every few microseconds. Once the data is gathered it’s filtered and processed on the microcontroller and sent over GPIO wires to the Raspberry Pi to be output to the touchscreen. The touchscreen then lights up a side of the screen if a car is present in the blind spot. Lastly, the backup camera is comprised of a DSI camera and a relay. The backup camera is mounted to the rear of the car and is powered as well as transmits data through the onboard DSI port on the Raspberry Pi. The coil of the relay is wired in parallel with the cars reverse lights so when the car is in reverse the relay will switch to the normally closed position which will allow for our trigger signal to flow from the GPIO output Raspberry Pi pin back to the input GPIO pin of the Raspberry Pi. Using this signal the system knows when to toggle the backup camera on and off

The significance of this project was to show that as we wait for a society filled with autonomous cars we can build and install kits into our very own personal cars to assist in a safer, more efficient transportation experience.

Students' Presentation