Artificial Immune System based urban traffic control

Abstract

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.