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A Direct Demand Model for Commuter R...

Kwong, Jennifer.

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A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area./
Author:	Kwong, Jennifer.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	61 p.
Notes:	Source: Masters Abstracts International, Volume: 80-09.
Contained By:	Masters Abstracts International80-09.
Subject:	Regional Studies. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10936962
ISBN:	9781392001165

A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area.
Kwong, Jennifer.

A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 61 p.

Source: Masters Abstracts International, Volume: 80-09.

Thesis (M.S.)--University of California, Irvine, 2019.

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

This thesis documents the development of a direct travel demand model for commuter rail in the San Francisco Bay Area. A direct demand model simultaneously estimates trip generation and attraction, which for this thesis would be trips between an origin-destination pair of stations. In the model, the number of trips assigned to an origin-destination pair of stations is dependent on land use characteristics at the origin and destination stations in combination with travel time on the network during congested peak periods and via transit. The model uses a multiplicative direct demand model to estimate ordinary least square regression parameters for the origin-destination trips. From the model form, the resultant estimated regression parameters are elasticities, and as such, can be used to postulate the effects of the selected land use characteristics and network travel times upon the number of trips made. At both the origin and destination, the location of the station within the central business districts of the San Francisco Bay region had the largest effect on trip generation and attraction. Higher employment density at the destination and a larger number of workers per household at the origin had a positive effect on trips, while the total number of industrial workers at the destination and an increased number of two car households had a negative effect on trips. Longer travel times on transit appeared to have a positive effect on trips, yet longer travel times in congested peak periods appeared to have a negative effect on trips.

ISBN: 9781392001165Subjects--Topical Terms:

1672379
Regional Studies.

A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area.
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506 $a This item must not be sold to any third party vendors.
520 $a This thesis documents the development of a direct travel demand model for commuter rail in the San Francisco Bay Area. A direct demand model simultaneously estimates trip generation and attraction, which for this thesis would be trips between an origin-destination pair of stations. In the model, the number of trips assigned to an origin-destination pair of stations is dependent on land use characteristics at the origin and destination stations in combination with travel time on the network during congested peak periods and via transit. The model uses a multiplicative direct demand model to estimate ordinary least square regression parameters for the origin-destination trips. From the model form, the resultant estimated regression parameters are elasticities, and as such, can be used to postulate the effects of the selected land use characteristics and network travel times upon the number of trips made. At both the origin and destination, the location of the station within the central business districts of the San Francisco Bay region had the largest effect on trip generation and attraction. Higher employment density at the destination and a larger number of workers per household at the origin had a positive effect on trips, while the total number of industrial workers at the destination and an increased number of two car households had a negative effect on trips. Longer travel times on transit appeared to have a positive effect on trips, yet longer travel times in congested peak periods appeared to have a negative effect on trips.
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