TY - GEN
T1 - CrowdPath
T2 - 13th International Symposium on Spatial and Temporal Databases, SSTD 2013
AU - Hendawi, Abdeltawab M.
AU - Sturm, Eugene
AU - Oliver, Dev
AU - Shekhar, Shashi
PY - 2013
Y1 - 2013
N2 - Our proposed system CrowdPath is based on the hypothesis that people know their commute area better than conventional routing services that use traditional digital roadmaps and shortest path algorithms. The knowledge and experiences of drivers reflected in volunteered commute routes may provide better routes. By leveraging such available volunteered geographic information (VGI), our goal is to investigate next-generation routing services to further reduce travel time, fuel consumption, and improve navigation. Previous related work summarizes GPS tracks into a landmark graph which is used for answering routing queries. In contrast, CrowdPath directly queries a collection of map-matched GPS tracks to recommend paths from a source location to a destination. Our evaluation using real GPS tracks illustrates the promise of CrowdPath in significantly reducing travel time compared to routes from common routing providers. In the future, CrowdPath may be extended to adapt route recommendations by start time and provide safe paths using volunteered crime and accident reports.
AB - Our proposed system CrowdPath is based on the hypothesis that people know their commute area better than conventional routing services that use traditional digital roadmaps and shortest path algorithms. The knowledge and experiences of drivers reflected in volunteered commute routes may provide better routes. By leveraging such available volunteered geographic information (VGI), our goal is to investigate next-generation routing services to further reduce travel time, fuel consumption, and improve navigation. Previous related work summarizes GPS tracks into a landmark graph which is used for answering routing queries. In contrast, CrowdPath directly queries a collection of map-matched GPS tracks to recommend paths from a source location to a destination. Our evaluation using real GPS tracks illustrates the promise of CrowdPath in significantly reducing travel time compared to routes from common routing providers. In the future, CrowdPath may be extended to adapt route recommendations by start time and provide safe paths using volunteered crime and accident reports.
UR - http://www.scopus.com/inward/record.url?scp=84881258060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881258060&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40235-7_28
DO - 10.1007/978-3-642-40235-7_28
M3 - Conference contribution
AN - SCOPUS:84881258060
SN - 9783642402340
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 456
EP - 461
BT - Advances in Spatial and Temporal Databases - 13th International Symposium, SSTD 2013, Proceedings
Y2 - 21 August 2013 through 23 August 2013
ER -