Cell phone providers have started fitting assisted global positioning system (AGPS) chips in new cell phones. The phone users travel on the roads voluntarily and if the phones can be queried anonymously at a reasonable cost, the phones can replace costly dedicated probe vehicles. The major challenge in using AGPS chips is that the phones may not always be on the roads. Even if they were on the roads, they could be in different modes of transportation. Since traffic conditions are usually monitored in terms of private automobiles, the modes of transportation the phones are in first needs to be determined in order for them to be used as traffic probes. Once the traffic data is correctly identified as coming from the private automobile mode, it is another challenge to combine the information with different information sources. This thesis develops a method to fuse the multiple sources of traffic data for more reliable estimation of traffic conditions. Traditionally, route guidance systems generally have focused on the shortest or the fastest route for a particular pair of origin and destination. However, by utilizing available three dimensional (3-D) and geospatial data, it is possible to aid route guidance systems that are optimizing for other objectives such as finding the most scenic, the most level or the safest route.
The objective of this thesis is to develop a framework of traffic monitoring and route guidance system named GISTMARG (GPS and GIS for Traffic Monitoring and Route Guidance) that deals with incorporating cell phones or mobile GPS devices as probes, fusing the traffic data from multiple sources and incorporating 3-D and geospatial data into route guidance methods.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/27572 |
| Date | 09 June 2011 |
| Creators | Byon, Young-Ji |
| Contributors | Abdulhai, Baher, Shalaby, Amer Saïd |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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