Borrowing ideas from natural immunity, Artificial Immune Systems (AIS) offer a novel
approach to solving many diagnosis, optimization and control problems. In the course of
this research this paradigm was applied to the problem of optimizing urban traffic. The
traffic was micro-simulated with each car on a two junction road system modeled
individually. The cars themselves were programmed with 'personalities' to better
simulate real traffic. A novel AIS was developed to detect, predict, and control
anomalous traffic conditions. It was also used to optimize the flow of traffic through the
road network. Benchmarking was performed against the well accepted TRANSYT
traffic control system. Though the TRANSYT system performed better initially, the AIS
control showed marked improvement over time as it adapted better to changing traffic
conditions. This change was expected as TRANSYT is optimized for specific initial
conditions unlike the AIS system which adapts to changes.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/5764 |
| Date | 17 September 2007 |
| Creators | Negi, Pallav |
| Contributors | Langari, Reza |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | 703214 bytes, electronic, application/pdf, born digital |
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