Project

# Title Team Members TA Documents Sponsor
91 Automatic Bike Collision Prevention System
Charlie Wang
Nathan Zhu
Rahul Nayak
Frey Zhao design_document1.pdf
proposal1.pdf
# Automatic Bike Collision Prevention System

Team Members:
- Rahul Nayak (rn8)
- Charlie Wang (cgwang3)
- Nathan Zhu (nyzhu2)

# Problem

Active pathways like campus sidewalks create high risk scenarios for cyclists and passerby due to oblivious pedestrians and distracted riding. Traditional bicycle bells are reactive rather than proactive, requiring both the cyclist to recognize a potential collision and react by ringing the bell, and pedestrians to acknowledge the bell and move out of the way. The total time to prevent collision can be lengthened if the cyclist’s reaction time was not a consideration. As such, there is a need for an automated alert system that is able to identify and distinguish potential collision hazards before they occur.

# Solution

We will create a handlebar-mounted safety system using three mmWave radar sensors to act as a peripheral vision of sorts. The sensors will be set up such that we have a center sensor, and left and right sensors. The system performs spatial gating, where detections transitioning from peripheral radar sectors into the forward sector are classified as hazards, while detections only in the peripheral radar sectors are ignored. We estimate a time to collision depending on the current distance detected and the distance from past readings, and ring the bell at different volumes accordingly.

# Solution Components

## Subsystem 1: Power

Provide regulated power and system status feedback.

Components:

- Li-ion 18650 Battery: High capacity power source.
- Buck-Boost Converter: Stable 5V/3.3V regulation.
- Status LEDs: Indicators to indicate if the system is on, sensitivity level, and if an object is detected.
- Sensitivity Potentiometer: Allows the rider to adjust the magnitude threshold for different environments.

## Subsystem 2: Radar Sensor Array

Function: Detect object distance.

Components:

- Three HLK-LD2410 24GHz mmWave Radar Modules
- Configuration: 1 center (0°), 2 side angled (30°)
- To create distinct sensors, small 3D printed shields will be set to limit field of view and prevent cross-talking.
- This triangular configuration allows for section-based filtering.
- Due to limited UARTs on the ESP32, the radars should be checked one at a time in a very fast, cyclical manner, which would also help prevent crosstalking.

## Subsystem 3: Processing

Function: Filter noise and determine collision likeliness.

Components:
- ESP32 Microcontroller: UART connection with Radar sensors
- Magnitude thresholding: Ignore low energy reflections such as from pavement or small non-collision objects.
- Time-To-Collision algorithm: Estimate how long it will take until a collision occurs.

## Subsystem 4: Alert System

Function: Create a gradually audible ringing sound depending on the expected collision time.

Components:
- Piezo Buzzer (PS1240): Use Pulse Width Modulation to increase beep frequency
- Three alert stages

# Criterion For Success

The project will be considered successful if all criteria below are met:
- Range performance: Reliably detect objects from 5 meters away.
- Low latency: Detection to audio output is less than 150ms.
- Form factor: Device is compact enough to mount on handlebars.
- False-positive mitigation: Thresholding prevents alarm from triggering for ground objects and other non hazards.
- Peripheral vision: Device is able to detect objects in peripheral vision and keep track of these objects moving into the sight of the center sensor.
- Battery life: Battery should last at least 8 hours on a single charge.

Iron Man Mouse

Jeff Chang, Yayati Pahuja, Zhiyuan Yang

Featured Project

# Problem:

Being an ECE student means that there is a high chance we are gonna sit in front of a computer for the majority of the day, especially during COVID times. This situation may lead to neck and lower back issues due to a long time of sedentary lifestyle. Therefore, it would be beneficial for us to get up and stretch for a while every now and then. However, exercising for a bit may distract us from working or studying and it might take some time to refocus. To control mice using our arm movements or hand gestures would be a way to enable us to get up and work at the same time. It is similar to the movie Iron Man when Tony Stark is working but without the hologram.

# Solution Overview:

The device would have a wrist band portion that acts as the tracker of the mouse pointer (implemented by accelerometer and perhaps optical sensors). A set of 3 finger cots with gyroscope or accelerometer are attached to the wrist band. These sensors as a whole would send data to a black box device (connected to the computer by USB) via bluetooth. The box would contain circuits to compute these translational/rotational data to imitate a mouse or trackpad movements with possible custom operation. Alternatively, we could have the wristband connected to a PC by bluetooth. In this case, a device driver on the OS is needed for the project to work.

# Solution Components:

Sensors (finger cots and wrist band):

1. 3-axis accelerometer attached to the wrist band portion of the device to collect translational movement (for mouse cursor tracking)

2. gyroscope attached to 3 finger cots portion to collect angular motion when user bend their fingers in different angles (for different clicking/zoom-in/etc operations)

3. (optional) optical sensors to help with accuracy if the accelerometer is not accurate enough. We could have infrared emitters set up around the screen and optical sensors on the wristband to help pinpoint cursor location.

4. (optional) flex sensors could also be used for finger cots to perform clicks in case the gyroscope proves to be inaccurate.

Power:

Lithium-ion battery with USB charging

Transmitter component:

1. A microcontroller to pre-process the data received from the 4 sensors. It can sort of integrate and synchronize the data before transmitting it.

2. A bluetooth chip that transmits the data to either the blackbox or the PC directly.

Receiver component:

1. Plan A: A box plugged into USB-A on PC. It has a bluetooth chip to receive data from the wristband, and a microcontroller to process the data into USB human interface device signals.

2. Plan B: the wristband is directly connected to the PC and we develop a device driver on the PC to process the data.

# Criterion for Success:

1. Basic Functionalities supported (left click, right click, scroll, cursor movement)

2. Advanced Functionalities supported(zoom in/out, custom operations eg. volume control)

3. Performance (accuracy & response time)

4. Physical qualities (easy to wear, durable, and battery life)