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Automated Lane Centering: An Off-the-Shelf Computer Vision Product vs. Infrastructure-Based Chip-Enabled Raised

Parth Kadav1, Sachin Sharma1, Johan Fanas Rojas2

  • 1Department of Mechanical and Aerospace Engineering, Western Michigan University, 4601 Campus Dr, Kalamazoo, MI 49008, USA.

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|April 13, 2024
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Summary
This summary is machine-generated.

Chip-enabled raised pavement markers (CERPMs) offer a cost-effective solution for autonomous vehicles (AVs), transmitting crucial data directly to vehicles. This technology enhances AV operational robustness and energy efficiency, outperforming traditional systems in challenging conditions.

Keywords:
Mobileyeadvanced driver assistance systems (ADAS)autonomous vehicles (AV)chip enabled raised pavement marker (CERPM)computer visioncontrolsinfrastructure sensorslane centeringperceptionvehicle-to-infrastructure (V2I)

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Area of Science:

  • Autonomous Systems
  • Infrastructure Technology
  • Robotics and AI

Background:

  • Safe autonomous vehicle (AV) operation relies on accurate environmental perception via sensors, leading to high computational loads.
  • Traditional lane markings are unreliable due to fading, construction zones, and limitations in adverse conditions.
  • Existing direct data transmission methods like high-definition maps and roadside units (RSUs) are expensive to implement and maintain.

Purpose of the Study:

  • To introduce and evaluate chip-enabled raised pavement markers (CERPMs) as a novel, cost-effective infrastructure information source (IIS) for AVs.
  • To assess the performance of CERPMs in reducing AV computational load and energy consumption.
  • To compare the detection and reliability of CERPMs against traditional computer vision-based lane detection systems.

Main Methods:

  • CERPMs were installed along lane lines, transmitting geospatial data and speed limits via LoRaWAN protocol directly to AVs.
  • A perception subsystem processed data from both CERPMs and a Mobileye computer vision system for lane centering (LC) applications.
  • System performance was evaluated across three test routes with varying road curvatures and conditions.

Main Results:

  • The Mobileye system failed to detect lane markings at road curvatures exceeding ±0.016 m⁻¹, with only 6.7% detection in steep curvature scenarios.
  • CERPMs successfully generated reference trajectories for vehicle control in all tested scenarios, demonstrating high reliability.
  • CERPMs provided reliable detection up to 340 meters, significantly enhancing AV perception range and robustness.

Conclusions:

  • CERPM technology presents a viable and cost-effective solution for improving AV operational robustness and energy efficiency.
  • CERPMs effectively address the limitations of traditional lane markings and computer vision systems, particularly in complex driving environments.
  • This passive IIS has the potential to overcome current challenges in AV perception and control systems.