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Understanding the Influence of Famil...

Payyanadan, Rashmi Premnath.

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Understanding the Influence of Familiarity on Route Choice among Older Drivers.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Understanding the Influence of Familiarity on Route Choice among Older Drivers./
Author:	Payyanadan, Rashmi Premnath.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	166 p.
Notes:	Source: Dissertations Abstracts International, Volume: 79-09, Section: A.
Contained By:	Dissertations Abstracts International79-09A.
Subject:	Geographic information science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10743856
ISBN:	9780355621068

Understanding the Influence of Familiarity on Route Choice among Older Drivers.
Payyanadan, Rashmi Premnath.

Understanding the Influence of Familiarity on Route Choice among Older Drivers. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 166 p.

Source: Dissertations Abstracts International, Volume: 79-09, Section: A.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018.

This item must not be sold to any third party vendors.

A number of studies have established the role of familiarity as an important factor of driving for older drivers. Familiarity is known to govern route choice, and there is a need for familiarity to be included in choice models. But very limited work has been conducted in quantifying the degree to which familiarity influences route choice, under what conditions, and how robustly models can approximate familiarity. This dissertation attempts to answer the first 2 knowledge gaps in Chapter 3, where analyses conducted on the factors that influence route choice among older adults showed that a) familiar routes were preferred as they were perceived to be shorter, direct, and had minimal traffic; b) different factors of familiarity were involved in choosing a route; and c) familiarity was the most important factor in explaining route choice after baseline route choice behavior, accounting for 26 percent of the explained variance. Additionally, extensive literature review revealed that current models of route choice that included familiarity failed to capture the multi-criteria nature of familiarity. In Chapter 4, this dissertation attempts to develop an abstraction hierarchy framework for describing the multi-criteria nature of route familiarity, and establishing a mathematical framework that can be used to calculate a new measure of familiarity-estimated route familiarity. The final chapter discusses the applications of the estimated route familiarity measure and abstraction hierarchy framework for the personalization of driver support systems and vehicle algorithm design.

ISBN: 9780355621068Subjects--Topical Terms:

3432445
Geographic information science.

Understanding the Influence of Familiarity on Route Choice among Older Drivers.
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260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 166 p.
500 $a Source: Dissertations Abstracts International, Volume: 79-09, Section: A.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Lee, John D.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a A number of studies have established the role of familiarity as an important factor of driving for older drivers. Familiarity is known to govern route choice, and there is a need for familiarity to be included in choice models. But very limited work has been conducted in quantifying the degree to which familiarity influences route choice, under what conditions, and how robustly models can approximate familiarity. This dissertation attempts to answer the first 2 knowledge gaps in Chapter 3, where analyses conducted on the factors that influence route choice among older adults showed that a) familiar routes were preferred as they were perceived to be shorter, direct, and had minimal traffic; b) different factors of familiarity were involved in choosing a route; and c) familiarity was the most important factor in explaining route choice after baseline route choice behavior, accounting for 26 percent of the explained variance. Additionally, extensive literature review revealed that current models of route choice that included familiarity failed to capture the multi-criteria nature of familiarity. In Chapter 4, this dissertation attempts to develop an abstraction hierarchy framework for describing the multi-criteria nature of route familiarity, and establishing a mathematical framework that can be used to calculate a new measure of familiarity-estimated route familiarity. The final chapter discusses the applications of the estimated route familiarity measure and abstraction hierarchy framework for the personalization of driver support systems and vehicle algorithm design.
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