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Title:

Modeling Visit Probabilities Within Network Time Prisms Using Continuous-Time Semi-Markov Techniques

Accession Number:

01553675

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

The space-time prism is a key concept in time geography and geographic information science that captures both spatial and temporal constraints on an object’s potential mobility. For mobility within spatial networks such as transportation systems, network-time prisms (NTPs) delimit accessible locations in network space with respect to time given scheduling constraints, movement constraints and speed limits imposed by the network. The boundary of a NTP has been used as a measure of individuals’ accessibility to a network and opportunities in that network. However, the interior structure of NTPs has lacked quantitative characterization, including the distribution of visit probabilities at accessible locations. Intuitively, locations along the shorter routes are more likely to be visited than those along circuitous routes, since they provide more available time and higher flexibility. This paper models visit probabilities within NTPs using the continuous-time semi-Markov process. The authors simulate visit probabilities using Python and ArcPy, visualize these distributions using ESRI ArcGIS, and compare them with empirical probabilities derived from GPS trajectories in New York City, USA. The visit probabilities provide a quantitative description of individuals’ potential mobility within a NTP and a foundation for developing the refined accessibility benefit and cost measures that go beyond the binary nature of classical NTPs.

Supplemental Notes:

This paper was sponsored by TRB committee ABJ50 Information Systems and Technology.

Monograph Accession #:

01550057

Report/Paper Numbers:

15-4241

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Song, Ying
Miller, Harvey J
Zhou, Xuesong

Pagination:

20p

Publication Date:

2015

Conference:

Transportation Research Board 94th Annual Meeting

Location: Washington DC, United States
Date: 2015-1-11 to 2015-1-15
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Geographic Terms:

New York (New York)

Subject Areas:

Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2015 Paper #15-4241

Files:

TRIS, TRB, ATRI

Created Date:

Dec 30 2014 1:23PM