PROJECT TITLE

An Investigation of Drivers’ Adaptation Behavior and Decision Making When Interacting with Automated and Connected Vehicle Technologies

PRIMARY INVESTIGATOR

Shan Bao, PhD
Assistant Research Scientist, Human Factors Group, U-M Transportation Research Institute

PROJECT DATES

May 2015 – April 2017

PROJECT TEAM

Carol Flannagan, PhD
Associate Research Scientist, Biosciences Group, U-M Transportation Research Institute; co-director, Center for the Management of Information for Safe and Sustainable Transportation (CMISST)

Anuj Pradhan, PhD
Assistant Research Scientist, Human Factors Group, U-M Transportation Research Institute

John Sullivan, PhD
Associate Research Scientist, Head, Human Factors Group, U-M Transportation Research Institute

OBJECTIVE

To assess and quantify factors associated with how drivers’ adaptively interact with automated and connected vehicle technologies.

APPROACH

Comprehensive data mining work will be conducted on UMTRI existing naturalistic driving data related to automated (i.e., Adaptive Cruise Control) and connected vehicle (i.e., Vehicle to Vehicle) technologies. Both stochastic (Hidden Markov Model and Neural Network) and statistical (Mixed Models) analytical modeling methods will be applied and developed.

OUTCOME

Computational models to predict drivers’ decision making in adapting automated and connected vehicles safety systems; and quantification of safety consequences from drivers’ adaptation behavior

RELATED LINK

https://www.cmisst.org/


CATEGORY: HUMAN FACTORS
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