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Enhanced Perception for Autonomous Vehicles at Obstructed Intersections: An Implementation of Vehicle to

Yanghui Mo1, Roshan Vijay1, Raphael Rufus1

  • 1Energy Research Institute, Nanyang Technological University, Singapore 637141, Singapore.

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Summary
This summary is machine-generated.

This study introduces a LiDAR Infrastructure System to improve the safety of connected automated vehicles (CAVs) at urban intersections with visual obstructions. The system enables early obstacle detection, enhancing autonomous driving robustness.

Keywords:
V2X communicationscollaborative autonomous drivingobstructed scenariosroadside sensing systemvehicle–infrastructure cooperative perception

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Area of Science:

  • Robotics and Intelligent Systems
  • Transportation Engineering
  • Computer Vision

Background:

  • Autonomous vehicles (AVs) face significant safety challenges in urban environments due to visual obstructions at intersections.
  • Limited sensory input hinders the robust operation of AVs in complex traffic scenarios.
  • Enhancing perception capabilities is crucial for safe and reliable autonomous driving.

Purpose of the Study:

  • To implement and evaluate a novel LiDAR Infrastructure System for roadside sensing to improve the safety and robustness of Connected Automated Vehicles (CAVs).
  • To address the challenge of occluded visibility at urban intersections for autonomous driving systems.
  • To integrate roadside perception enhancement with existing autonomous driving and V2X communication platforms.

Main Methods:

  • Development of a LiDAR Infrastructure System for roadside sensing.
  • Integration with Baidu Apollo's Automated Driving System (ADS) and Cohda Wireless V2X communication hardware.
  • Field testing at the Singapore CETRAN autonomous vehicle test track adhering to SAE J2735 V2X standards.

Main Results:

  • The integrated system demonstrated enhanced perception capabilities for CAVs in occluded urban scenarios.
  • Analysis of communication latency and packet delivery ratio confirmed system viability.
  • Successful advance detection of obstacles under challenging visibility conditions was achieved.

Conclusions:

  • The proposed LiDAR Infrastructure System effectively enhances the situational awareness of CAVs in urban intersections with occluded visibility.
  • The integration of roadside sensing and V2X communication offers a promising solution for improving autonomous driving safety.
  • This implementation study provides a foundation for deploying advanced perception systems in real-world autonomous driving applications.