Benefit

Evaluation of an In-Vehicle Active Traffic and Demand Management System finds that 73 percent of participants favor the technology

Human factors evaluation study of an in-vehicle ATDM device that delivered HOV, lane management, speed limit, and VMS information to drivers traveling on a portion of I-66.


04/04/2016
Virginia,United States


Summary Information

Research out of Virginia Tech focused on the development and subsequent evaluation of an in-vehicle Active Traffic and Demand Management (ATDM) system deployed on I-66, an interstate running west from Washington, D.C into Northern Virginia. Specifically, the purpose of this research was to determine if in-vehicle signage, coupled with ATDM, had the potential to successfully manage traffic by drawing inferences from individual subjects.

Methodology

An approximately 40-mile segment of I-66 between Manassas and Falls Church (both Eastbound and Westbound) was used for the study. There were four Variable Message Signs (VMS) along the route. Data collection occurred from July – August 2015.

Forty participants recruited from the Northern Virginia area were asked to drive along the corridor while following route guidance provided by the in-vehicle device (IVD). The participants were accompanied by a member of the research team and were provided with the following information through the IVD:
  1. Speed limits
  2. Lane availability
  3. High Occupancy Vehicle (HOV) restrictions
  4. Messages related to traffic conditions, including accidents ahead, detours, etc.
This system was equipped with auditory and visual alerts to notify the driver when relevant information was updated.

Participant data was collected from hardware in the instrumented vehicle, including four in-vehicle cameras, a Data Acquisition System (DAS), an on-board equipment (OBE), and a Differential GPS (DGPS). During the driving portion, participants were asked a series of questions regarding each alert from the IVD. The participants then completed a post-drive questionnaire that aimed to capture the participant’s overall impressions of the in-vehicle system, including attributes such as: desirability, distractibility, driver behavior, general concerns, and areas of improvement. Statistical analysis methods were performed to analyze participant eye glance durations towards the IVD and instrument cluster. Participant speed data and survey responses were also utilized to answer research questions.

Key Findings

Distraction
  • Overall, participants did not feel the in-vehicle alerts were distracting or annoying based on in-vehicle and post-drive survey responses.
  • Participants believed that the IVD gave them relevant, clear information based on the in-vehicle questionnaire.

Desirability
  • When asked if they would use an in-vehicle device that provided HOV, lane management, speed limit, and VMS if such a system existed, 98 percent of participants said they would use the device on both the pre-drive and post-drive surveys.
  • Furthermore, 73 percent of participants indicated they would want the in-vehicle technology in their next vehicle while 25 percent signified a “neutral? feeling towards the IVD.

Driver Behavior
  • According to the speed data, participants who were traveling above the new speed limit at the time of the alert were found to be traveling at a reduced speed 10 seconds after the alert.
  • On average, significantly longer glances to the instrument cluster occurred following speed limit alerts when compared against VMS alert.
  • The research team recorded confirming/reminding 27 out of 40 participants (67.5 percent) to follow the IVD exit instructions for at least one of the two required exits, signifying that participants may not have been trustworthy of the information presented on the IVD.

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Source

Human Factors Evaluation of an In-Vehicle Active Traffic and Demand Management (ATDM) System

Author: Kayla Paris Sykes

Published By: Virginia Polytechnic Institute and State University

Source Date: 04/04/2016

URL: https://vtechworks.lib.vt.edu/handle/10919/65003

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Benefit ID: 2016-01099