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Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

312
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
312
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

309
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
309
Acceleration Vectors01:30

Acceleration Vectors

7.9K
In everyday conversation, accelerating means speeding up. Acceleration is a vector in the same direction as the change in velocity, Δv, therefore the greater the acceleration, the greater the change in velocity over a given time. Since velocity is a vector, it can change in magnitude, direction, or both. Thus acceleration is a change in speed or direction, or both. For example, if a runner traveling at 10 km/h due east slows to a stop, reverses direction, and continues their run at 10 km/h...
7.9K
Average Acceleration01:30

Average Acceleration

9.3K
The importance of understanding acceleration spans our day-to-day experiences, as well as the vast reaches of outer space and the tiny world of subatomic physics. In everyday conversation, to accelerate means to speed up. For instance, we are familiar with the acceleration of our car; the harder we apply our foot to the gas pedal, the faster we accelerate. The greater the acceleration, the greater the change in velocity over a given time. Acceleration is widely seen in experimental physics. In...
9.3K
Direction of Acceleration Vectors01:10

Direction of Acceleration Vectors

8.0K
Acceleration occurs when velocity changes in magnitude (an increase or decrease in speed), direction, or both. Although acceleration is in the direction of the change in velocity, it is not always in the direction of motion. When an object slows down, its acceleration is opposite to the direction of its motion. This is commonly referred to as deceleration. However, the term deceleration can cause confusion in analysis because it is not a vector; it does not point to a specific direction with...
8.0K
Measuring Acceleration Due to Gravity01:12

Measuring Acceleration Due to Gravity

470
Consider a coffee mug hanging on a hook in a pantry. If the mug gets knocked, it oscillates back and forth like a pendulum until the oscillations die out.
A simple pendulum can be described as a point mass and a string. Meanwhile, a physical pendulum is any object whose oscillations are similar to a simple pendulum, but cannot be modeled as a point mass on a string because its mass is distributed over a larger area. The behavior of a physical pendulum can be modeled using the principles of...
470

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Updated: May 8, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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DAT: Deep Learning-Based Acceleration-Aware Trajectory Forecasting.

Ali Asghar Sharifi1, Ali Zoljodi1, Masoud Daneshtalab1,2

  • 1School of Innovation, Design and Technology (IDT), Mälardalen University, 72123 Västerås, Sweden.

Journal of Imaging
|December 27, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces the Deep learning-based Acceleration-aware Trajectory forecasting (DAT) model for safer autonomous driving. DAT significantly improves object trajectory forecasting accuracy by incorporating acceleration data, outperforming existing methods.

Keywords:
acceleration predictiondeep learningend-to-end trajectory forecastingperception

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Area of Science:

  • Robotics and Artificial Intelligence
  • Computer Vision
  • Machine Learning

Background:

  • Autonomous driving (AD) systems require robust safety features, with object detection and trajectory forecasting being critical for collision prevention.
  • Current AD systems face challenges in accurately predicting the future movements of surrounding vehicles and pedestrians.

Purpose of the Study:

  • To introduce the Deep learning-based Acceleration-aware Trajectory forecasting (DAT) model for enhanced object detection and trajectory forecasting in AD systems.
  • To leverage raw sensor measurements and acceleration data for more accurate prediction of agent motion.

Main Methods:

  • Developed an end-to-end deep learning model (DAT) that processes sequential sensor data for object detection and trajectory forecasting.
  • Introduced a novel forecasting module utilizing acceleration data and a method for estimating ground-truth acceleration.
  • Integrated an object detector that predicts acceleration attributes and a new trajectory forecasting method.

Main Results:

  • DAT was trained and evaluated on the NuScenes dataset, demonstrating significant improvements over state-of-the-art methods.
  • Achieved up to a 2x improvement in forecasting accuracy, particularly for objects with complex linear and nonlinear motion patterns.
  • Empirical validation confirmed the effectiveness of incorporating acceleration data into predictive models.

Conclusions:

  • The DAT model represents a substantial advancement in autonomous driving safety by improving trajectory forecasting accuracy.
  • Incorporating acceleration data is crucial for developing more reliable and safer autonomous driving systems.
  • The proposed methods for acceleration estimation and trajectory forecasting offer a robust solution for real-world AD applications.