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SAILing CAVs: Speed-Adaptive Infrastructure-Linked Connected and Automated Vehicles

Matthew Nice, Matthew Bunting, George Gunter, William Barbour, Jonathan Sprinkle, Dan Work

TL;DR

A lightly modified vehicle is developed and deployed that is able to dynamically adjust the vehicle speed in response to posted variable speed limit messages generated by the infrastructure using LTE connectivity.

Abstract

This work demonstrates a new capability in roadway control: Speed-adaptive, infrastructure-linked connected and automated vehicles. We develop and deploy a lightly modified vehicle that is able to dynamically adjust the vehicle speed in response to posted variable speed limit messages generated by the infrastructure using LTE connectivity. This work describes the open source hardware and software platform that enables integration between infrastructure-based variable posted speed limits, and existing vehicle platforms for automated control. The vehicle is deployed in heavy morning traffic on I-24 in Nashville, TN. The control vehicle follows the posted variable speed limits, resulting in as much as a 25% reduction in speed variability compared to a human-piloted vehicle in the same traffic stream.

SAILing CAVs: Speed-Adaptive Infrastructure-Linked Connected and Automated Vehicles

TL;DR

A lightly modified vehicle is developed and deployed that is able to dynamically adjust the vehicle speed in response to posted variable speed limit messages generated by the infrastructure using LTE connectivity.

Abstract

This work demonstrates a new capability in roadway control: Speed-adaptive, infrastructure-linked connected and automated vehicles. We develop and deploy a lightly modified vehicle that is able to dynamically adjust the vehicle speed in response to posted variable speed limit messages generated by the infrastructure using LTE connectivity. This work describes the open source hardware and software platform that enables integration between infrastructure-based variable posted speed limits, and existing vehicle platforms for automated control. The vehicle is deployed in heavy morning traffic on I-24 in Nashville, TN. The control vehicle follows the posted variable speed limits, resulting in as much as a 25% reduction in speed variability compared to a human-piloted vehicle in the same traffic stream.
Paper Structure (16 sections, 3 equations, 12 figures, 1 table)

This paper contains 16 sections, 3 equations, 12 figures, 1 table.

Table of Contents

  1. Introduction
  2. Methods
  3. Active Traffic Management Infrastructure
  4. Vehicle System Architecture
  5. Vehicle Interfaces
  6. Data Integration from Public Infrastructure
  7. Web-based service to establish speed at each gantry
  8. Models for gps2vsl
  9. Controllers
  10. Hardware Instrumentation
  11. Experimental Design
  12. Results
  13. Performance of CAV for VSL-Following
  14. Potential Benefits
  15. Practical Findings for Future Deployments
  16. ...and 1 more sections

Figures (12)

  • Figure 1: Variable speed limit (VSL) system activated and posting 30 mph speed limit during congested traffic. Photo taken from the ego vehicle which automatically adjusts its velocity to 30 mph in response to the VSL system.
  • Figure 2: Control vehicle (right) preparing to deploy as a VSL-following CAV on I-24 behind pilot vehicle (left) for trajectory comparison.
  • Figure 3: Three networks interact in the VSL-compliant CAV: SMART Corridor (fixed sensor network), OEM Vehicle Network (e.g. radar sensor, drive-by-wire), and the ROS message passing network. Vehicle proprioception, speed recommendations, and safety control actions are handled here.
  • Figure 4: The multiplexer decides which signals are used for the desired velocity using two switches. If libpandabunting2021libpanda is not allowing control, then the desired speed is output as the velocity signal; this feature avoids discontinuities in desired velocities in entry/exit states. If libpanda is allowing control, then the input from a second switch is passed through. In the second switch, if the vehicle is inside the SMART Corridor then the speed recommended by the VSL is the desired speed; otherwise (i.e. if you are anywhere else in the world), the desired speed is set to the set point on the driver dashboard controlled by steering wheel buttons.
  • Figure 5: High level flowchart showing how our implementation starts with GPS data and produces a vehicle's desired velocity (also called a set point). See Figures \ref{['fig:gantry']} and \ref{['fig:setpoint']} for more detail on the Gantry Identification and Identify Posted Speed components, respectively.
  • ...and 7 more figures