Account for Variations in Driver Population When Assessing Driving Interactions with Automated Vehicles.

Simulator Study in Oregon Assessed Car-Following Behavior for Automated and Human Driven Lead Vehicles.

Date Posted
04/30/2022
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Identifier
2022-L01111

Integrating Driving Simulator Experiment Data with a Multi-Agent Connected Automated Vehicles Simulation (MA-CAVs) Platform to Quantify Improved Capacity

Summary Information

Automated vehicles (AVs) are expected to improve the performance of the transportation network as market penetration rates increase. In order to estimate their impacts, researchers conducted a driving simulator study to assess how human-driven vehicles (HVs) will interact with AVs. Driving simulator data from 36 participants were used to measure HV headways when they followed an AV. Researchers then integrated the data into a multi-agent simulation to quantify highway travel time and flow predictions at varying AV market penetration levels. Several hard-braking scenarios were included to compare driver stress levels and determine how drivers interpret blame for collisions. Galvanic skin response (GSR) data were collected from participants during the experiment to quantify drivers’ levels of stress.

Lessons Learned

  • Implement education programs and campaigns to reinforce safe following distances regardless of the lead vehicle type. Study results revealed that younger drivers generally followed vehicles with shorter headways than other age groups, and selected headways were even shorter when following AVs than HVs. Participants younger than age 34 followed AVs with 18 percent shorter headway than when following HVs, while participants over age 34 followed AVs with a 2 percent longer headway.  Education on safe following distances may be warranted as increasing interactions with AVs emerge.
  • Recognize driver behavior will differ based on familiarity with AV technology. Those participants that had not previously interacted with Society of Automotive Engineers (SAE) level 5 (Full Driving Automation) vehicles may exhibit different driving behavior and perceptions with increased exposure to automated vehicles.
  • Further research drivers’ level of stress during hard-braking scenarios when following an AV or HV. The level of confidence may change if the participant is aware that an AV will exhibit safe driving behavior. Researchers found that the driver’s level of stress was higher in the hard braking scenario when following an HV in comparison to following an AV.
  • Plan for synchronizing simulator data with GSR data when conducting experiments. The synchronization should include connecting the GSR sensor and host computer more reliably during data collection. Weak wireless connectivity between the GSR sensor and host computer had resulted in partial data loss during the study.

Integrating Driving Simulator Experiment Data with a Multi-Agent Connected Automated Vehicles Simulation (MA-CAVs) Platform to Quantify Improved Capacity

Integrating Driving Simulator Experiment Data with a Multi-Agent Connected Automated Vehicles Simulation (MA-CAVs) Platform to Quantify Improved Capacity
Source Publication Date
06/15/2020
Author
Wang, Haizhong; David Hurwitz; Cadell Chand; Hisham Jashami; and Charles Koll
Publisher
Pacific Northwest Transportation Consortium (PacTrans) University Transportation Center

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