Introduction In this final part, we will integrate all components to measure the speed of vehicles in front of you. We will also use GPS data to enhance accuracy.

1. Calculating Speed To calculate the speed, you need to measure the distance traveled by the vehicle over time.

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import time

previous_time = time.time()
previous_distance = None

def calculate_distance(bbox):
    # Custom function to calculate distance based on bbox size
    # This is a placeholder for the actual distance calculation logic
    return bbox[2] - bbox[0]

def calculate_speed(distance_initial, distance_final, time_elapsed):
    distance_change = distance_final - distance_initial
    speed_m_s = distance_change / time_elapsed
    speed_kmh = speed_m_s * 3.6
    return speed_kmh

2. Integrating GPS Data Use the smartphone’s GPS to get your vehicle’s speed. This can be done through various Android APIs or libraries.

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# Placeholder for getting the vehicle's speed from GPS
def get_my_vehicle_speed():
    return 50  # Assume a constant speed for demonstration

3. Combining Everything Combine all the components to calculate the relative speed of the vehicle in front.

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while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break

    results = model.predict(source=frame)
    bboxes = extract_bboxes(results)
    outputs = deepsort.update(bboxes)

    current_time = time.time()

    for output in outputs:
        bbox = output[:4]
        track_id = output[4]

        current_distance = calculate_distance(bbox)
        if previous_distance is not None:
            time_elapsed = current_time - previous_time
            relative_speed = calculate_speed(previous_distance, current_distance, time_elapsed)
            my_vehicle_speed = get_my_vehicle_speed()
            front_vehicle_speed = my_vehicle_speed + relative_speed
            print(f'Front Vehicle Speed: {front_vehicle_speed} km/h')

        previous_time = current_time
        previous_distance = current_distance

4. Enhancing Accuracy

  • Calibration: Calibrate your system to improve accuracy.
  • Frame Rate: Ensure the video processing frame rate is high to minimize latency. Conclusion By following this series, you have learned how to build a system to measure the speed of vehicles in front of you using a smartphone. This involves capturing video, detecting and tracking vehicles, and calculating their speed using real-time data.

FAQ

  1. How do I calculate the speed of a vehicle? Speed is calculated by measuring the distance traveled over a period and then dividing this distance by the time taken.
  2. How can I integrate GPS data into my system? You can use GPS data to get the speed of your vehicle and then calculate the relative speed of the vehicle in front by comparing positional changes over time.
  3. What are the challenges in real-time speed calculation? The main challenges include ensuring low latency, accurate distance measurement, and handling varying frame rates and environmental conditions.
  4. How do I enhance the accuracy of my system? Calibrating your system, ensuring high frame rates, and using precise distance measurement methods can significantly enhance accuracy. References

By following this structure, each part of the series will provide a comprehensive overview, practical implementation steps, and additional resources for further learning. This approach ensures that readers of all levels, including high school students, can understand and apply the concepts.