TITLE:
Methodology for Automatically Setting Camera View to Mile Marker for Traffic Incident Management
AUTHORS:
Jijo K. Mathew, Haydn A. Malackowski, Christopher M. Gartner, Jairaj Desai, Edward D. Cox, Ayman F. Habib, Darcy M. Bullock
KEYWORDS:
Roadside Cameras, Traffic Incident Management, Connected Vehicles, Trajectory
JOURNAL NAME:
Journal of Transportation Technologies,
Vol.13 No.4,
October
13,
2023
ABSTRACT: Traffic incident
management (TIM) is a FHWA Every Day Counts initiative with the objective of
reducing secondary crashes, improving travel reliability, and ensuring safety
of responders. Agency roadside cameras play a critical role in TIM by helping
dispatchers quickly identify the precise location of incidents when receiving
reports from motorists with varying levels of spatial accuracy. Reconciling
position reports that are often mile marker based, with cameras that operate in
a Pan-Tilt-Zoom coordinate system relies on dispatchers having detailed
knowledge for hundreds of cameras and perhaps some presets. During real-time
incident dispatching, reducing the time it takes to identify the most relevant
cameras and setting their view on the incident is an important opportunity to
improve incident management dispatch times. This research develops a
camera-to-mile marker mapping technique that automatically sets the camera view
to a specified mile marker within the field-of-view of the camera. Over 350
traffic cameras along Indiana’s 2250 directional miles of interstate were
mapped to approximately 5000 discrete locations that correspond to
approximately 780 directional miles (~35% of interstate) of camera coverage.
This newly developed technique will allow operators to quickly identify the
nearest camera and set them to the reported location. This research also
identifies segments on the interstate system with limited or no camera coverage
for decision makers to prioritize future capital investments. This paper concludes
with brief discussion on future research to automate the mapping using LiDAR
data and to set the cameras after automatically detecting the events using
connected vehicle trajectory data.