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A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research.

Francisca Rosique1, Pedro J Navarro2, Carlos Fernández3

  • 1División de Sistemas e Ingeniería Electrónica (DSIE), Universidad Politécnica de Cartagena, Campus Muralla del Mar, s/n, 30202 Cartagena, Spain. paqui.rosique@upct.es.

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Summary
This summary is machine-generated.

This review details autonomous vehicle (AV) perception systems and simulators, covering sensor fundamentals, strengths, weaknesses, and selection criteria. It also explores simulation tools and global AV regulations for enhanced development and deployment.

Keywords:
LiDARautonomous vehiclemodel based designperception systemsimulator

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Area of Science:

  • Robotics and Artificial Intelligence
  • Sensor Technology
  • Autonomous Systems Engineering

Background:

  • Autonomous vehicles (AVs) rely heavily on sophisticated perception systems for safe operation.
  • Accurate environmental understanding and precise positioning are critical challenges in AV development.
  • Simulation plays a vital role in testing and validating AV perception systems.

Purpose of the Study:

  • To systematically review perception systems and simulators for autonomous vehicles.
  • To categorize and analyze common sensors used in AV perception.
  • To provide an overview of AV simulation tools and current global regulations.

Main Methods:

  • Systematic literature review of perception systems and simulation technologies for AVs.
  • Categorization of perception systems into environment perception and positioning estimation.
  • Analysis of sensor fundamentals, operational principles, and electromagnetic spectrum usage.
  • Evaluation of sensor strengths, weaknesses, and feature quantification using spider charts.
  • Description of various simulation approaches including model-based development, game engines, robotics simulators, and AV-specific simulators.

Main Results:

  • Perception systems are classified, and common sensors (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK) are detailed with their physical principles, functioning, and spectral usage.
  • Strengths and weaknesses of various sensors are presented, with spider charts aiding in feature-based sensor selection.
  • A comprehensive overview of simulation tools, from general game engines to specialized AV simulators, is provided.
  • The current landscape of global regulations concerning autonomous vehicle implementation is summarized.

Conclusions:

  • A thorough understanding of sensor characteristics and simulation capabilities is essential for effective AV perception system design and validation.
  • The review provides a valuable resource for researchers and developers in selecting appropriate sensors and simulation tools for autonomous vehicle applications.
  • Awareness of the evolving regulatory frameworks is crucial for the successful deployment of autonomous vehicles worldwide.