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One-Degree-of-Freedom System01:24

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In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
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Accuracy-Power Controllable LiDAR Sensor System with 3D Object Recognition for Autonomous Vehicle.

Sanghoon Lee1,2, Dongkyu Lee2, Pyung Choi2

  • 1Carnavicom Co., Ltd., Incheon 21984, Korea.

Sensors (Basel, Switzerland)
|October 10, 2020
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Summary

This study introduces new algorithms to reduce power consumption in LiDAR sensors for autonomous vehicles. By adjusting laser transmission and using a sleep mode, significant energy savings are achieved, benefiting electric vehicles.

Keywords:
3D object recognitionLiDAR sensor processorautonomous vehiclelow-power circuit design

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Area of Science:

  • Automotive Engineering
  • Sensor Technology
  • Robotics

Background:

  • Conventional Light Detection and Ranging (LiDAR) sensors consume significant power due to continuous laser transmission for environmental detection.
  • Inefficient power consumption in LiDAR is a critical issue for battery-dependent autonomous and electric vehicles.
  • Improving LiDAR power efficiency is essential for the viability and performance of autonomous driving systems.

Purpose of the Study:

  • To propose novel algorithms for reducing the power consumption of LiDAR sensors in autonomous vehicles.
  • To enhance the energy efficiency of LiDAR systems without compromising their object detection capabilities.
  • To address the limitations of current LiDAR technology regarding power usage in electric and autonomous vehicles.

Main Methods:

  • Implementing a horizontal angular resolution (HAR) control algorithm to dynamically adjust the laser transmission period (TP) based on vehicle speed.
  • Developing a sleep mode algorithm that reduces static power consumption by sensing the surrounding environment.
  • Testing the proposed algorithms on a commercial processor and designing an integrated circuit (IC) using the Global Foundries 55 nm CMOS process.

Main Results:

  • The HAR control algorithm reduced laser diode (LD) power consumption by 6.92% to 32.43% relative to maximum laser transmissions (Nx.max), varying with vehicle speed.
  • The sleep mode algorithm achieved a substantial power reduction of 61.09%.
  • The integrated processor design demonstrates the practical implementation of the proposed power-saving algorithms.

Conclusions:

  • The developed algorithms significantly improve LiDAR power consumption efficiency for autonomous vehicles.
  • Dynamic HAR control and environment-aware sleep modes are effective strategies for reducing energy usage.
  • The successful integration and testing pave the way for more energy-efficient LiDAR systems in future automotive applications.