Accuracy–Power Controllable LiDAR Sensor System with 3D Object Recognition for Autonomous Vehicle

Author:

Lee SanghoonORCID,Lee DongkyuORCID,Choi Pyung,Park DaejinORCID

Abstract

Light detection and ranging (LiDAR) sensors help autonomous vehicles detect the surrounding environment and the exact distance to an object’s position. Conventional LiDAR sensors require a certain amount of power consumption because they detect objects by transmitting lasers at a regular interval according to a horizontal angular resolution (HAR). However, because the LiDAR sensors, which continuously consume power inefficiently, have a fatal effect on autonomous and electric vehicles using battery power, power consumption efficiency needs to be improved. In this paper, we propose algorithms to improve the inefficient power consumption of conventional LiDAR sensors, and efficiently reduce power consumption in two ways: (a) controlling the HAR to vary the laser transmission period (TP) of a laser diode (LD) depending on the vehicle’s speed and (b) reducing the static power consumption using a sleep mode, depending on the surrounding environment. The proposed LiDAR sensor with the HAR control algorithm reduces the power consumption of the LD by 6.92% to 32.43% depending on the vehicle’s speed, compared to the maximum number of laser transmissions (Nx.max). The sleep mode with a surrounding environment-sensing algorithm reduces the power consumption by 61.09%. The algorithm of the proposed LiDAR sensor was tested on a commercial processor chip, and the integrated processor was designed as an IC using the Global Foundries 55 nm CMOS process.

Funder

Ministry of Education

Ministry of Science and ICT

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference38 articles.

1. Overview of Electric Vehicles (EVs) and EV Sensors;Basu,2019

2. The energy footprint of automotive electronic sensors;Armstrong;Sustain. Mater. Technol.,2020

3. Handbook of Driver Assistance Systems;Winner,2014

4. Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions

5. Development of Autonomous Car—Part I: Distributed System Architecture and Development Process

Cited by 29 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The Impact of Automotive Radar Configuration on Power Consumption: The Case of TI AWR1843;2024 IEEE International Workshop on Metrology for Automotive (MetroAutomotive);2024-06-26

2. Adaptive sensor management for UGV monitoring based on risk maps;Robotics and Autonomous Systems;2024-02

3. Parallel Processing of 3D Object Recognition by Fusion of 2D Images and LiDAR for Autonomous Driving;2024 International Conference on Electronics, Information, and Communication (ICEIC);2024-01-28

4. Optimal Driving Control for Autonomous Electric Vehicles Based on In-Wheel Motors Using an Artificial Potential Field;IEEE Access;2024

5. Tcl-based Simulation Platform for Light-weight ResNet Implementation;2023 20th International SoC Design Conference (ISOCC);2023-10-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3