Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Methodology and Algorithms for Pedestrian Network Construction

Kasemsuppakorn, Piyawan (2011) Methodology and Algorithms for Pedestrian Network Construction. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

Primary Text

Download (5MB) | Preview


With the advanced capabilities of mobile devices and the success of car navigation systems, interest in pedestrian navigation systems is on the rise. A critical component of any navigation system is a map database which represents a network (e.g., road networks in car navigation systems) and supports key functionality such as map display, geocoding, and routing. Road networks, mainly due to the popularity of car navigation systems, are well defined and publicly available. However, in pedestrian navigation systems, as well as other applications including urban planning and physical activities studies, road networks do not adequately represent the paths that pedestrians usually travel. Currently, there are no techniques to automatically construct pedestrian networks, impeding research and development of applications requiring pedestrian data. This coupled with the increased demand for pedestrian networks is the prime motivation for this dissertation which is focused on development of a methodology and algorithms that can construct pedestrian networks automatically.
A methodology, which involves three independent approaches, network buffering (using existing road networks), collaborative mapping (using GPS traces collected by volunteers), and image processing (using high-resolution satellite and laser imageries) was developed. Experiments were conducted to evaluate the pedestrian networks constructed by these approaches with a pedestrian network baseline as a ground truth. The results of the experiments indicate that these three approaches, while differing in complexity and outcome, are viable for automatically constructing pedestrian networks.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Kasemsuppakorn, Piyawanpik2@pitt.eduPIK2
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairKarimi, Hassan A.hkarimi@sis.pitt.eduHKARIMI
Committee MemberAkinci,
Committee MemberDing, DAD5
Committee MemberHirtle, Stephen HIRTLE
Committee MemberZadorozhny, Vladimirvladimir@sis.pitt.eduVIZ
Date: 18 November 2011
Date Type: Publication
Defense Date: 8 September 2011
Approval Date: 18 November 2011
Submission Date: 14 November 2011
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 187
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Pedestrian Network, Spatial Database, Pedestrian Navigation Services, Network Buffering, Collaborative Mapping, Image Processing
Date Deposited: 18 Nov 2011 15:46
Last Modified: 15 Nov 2016 13:35


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item