"Investigation of Traffic Counter Accuracy for Horse-Drawn Vehicles" by Ellie McCauley and Jay Grossman
 

Investigation of Traffic Counter Accuracy for Horse-Drawn Vehicles

Level of Education of Students Involved

Undergraduate

Faculty Sponsor

Jay Grossman

College

College of Engineering (COE)

Discipline(s)

Transportation Engineering

ORCID Identifier(s)

0000-0002-6090-9174

Presentation Type

Poster Presentation

Symposium Date

Spring 4-24-2025

Abstract

In transportation engineering, accurate traffic counts are essential for transportation planning and infrastructure design, enabling policymakers and designers to make informed decisions about future development plans, safety improvements, and resource allocation. This research project investigates the ability of traditional traffic counting devices, counting tubes, to effectively count horse and buggy traffic. Traffic counting tubes, commonly used for monitoring vehicle flow, detect vehicles based on tire contact with a pneumatic tube. Lighter or slower vehicles are known to be miss-counted by these devices. This research focuses on the ability of traffic counters to recognize horse and buggy traffic, with data collected on local county roads in Elkhart County, Indiana, particularly County Road 37, which is centered in an Amish community where horse-drawn transportation remains an integral part of the local lifestyle. Elkhart County has a significant Amish population resulting in a high volume of horse and buggy traffic along certain corridors. Counting and differentiating buggy traffic allows the county to plan and prioritize road repairs and improvements to better address this user base. In order to assess the capabilities of traffic tube counters, data collected from the tube counters was compared to manual traffic counts derived from video of the count locations. The results of this study aim to provide insight for Elkhart County into the reliability of current traffic counting practices. Ultimately, this research will contribute to the ongoing effort to improve traffic data accuracy and provide more inclusive and comprehensive data collection techniques.

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