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Related Concept Videos

Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

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Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
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Collisions in Multiple Dimensions: Problem Solving01:06

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Three-Dimensional Force System:Problem Solving01:30

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A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
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Rolling Resistance: Problem Solving01:17

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Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
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PD Controller: Design01:26

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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
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A Dynamic Path-Planning Method for Obstacle Avoidance Based on the Driving Safety Field.

Ke Liu1, Honglin Wang1, Yao Fu1

  • 1State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China.

Sensors (Basel, Switzerland)
|November 25, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a dual-layered dynamic path-planning method for obstacle avoidance, enhancing driving safety field (DSF) models. The new approach generates smoother, safer paths for intelligent vehicles by optimizing risk assessment and vehicle kinematics.

Keywords:
driving safety fieldintelligent vehicleobstacle avoidancepath planning

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Area of Science:

  • Robotics and Autonomous Systems
  • Intelligent Transportation Systems
  • Control Theory

Background:

  • Accurate and efficient driving risk assessment is critical for safe autonomous navigation.
  • Existing path-planning methods struggle with integrating vehicle motion states and kinematic constraints for obstacle avoidance.
  • The development of adaptable and smooth paths remains a challenge for intelligent vehicles in dynamic environments.

Purpose of the Study:

  • To propose a novel dual-layered dynamic path-planning method for obstacle avoidance based on the driving safety field (DSF).
  • To enhance the accuracy of driving risk modeling and the adaptability to vehicle kinematic characteristics.
  • To generate collision-free, curvature-continuous, and dynamically adjustable obstacle avoidance paths.

Main Methods:

  • Constructed a comprehensive driving safety field (DSF) integrating potential fields (static obstacles, lane boundaries, target position) and a kinetic field (dynamic obstacles).
  • Utilized resultant force direction from the DSF to guide ego-vehicle motion, generating an initial path respecting kinematic and dynamic constraints.
  • Employed quadratic programming (QP) for path smoothing, optimizing waypoints and fitting polynomial curves for curvature continuity.

Main Results:

  • The proposed path-planning algorithm significantly outperformed the improved artificial potential field (APF) method.
  • Achieved substantial reductions in path curvature (62.29%–87.32%) and heading angle (34.11%–72.06%).
  • Demonstrated dynamic adjustment of obstacle avoidance maneuver initiation based on relative vehicle velocities for proactive avoidance.

Conclusions:

  • The dual-layered dynamic path-planning method effectively generates safe, comfortable, and stable obstacle avoidance paths for intelligent vehicles.
  • The approach successfully addresses challenges in driving risk modeling, path smoothing, and kinematic adaptability.
  • The method ensures collision-free, curvature-continuous trajectories suitable for complex driving scenarios.