Abstract:
A vehicular traffic control system was designed with an inexpensive OOPIC micro controller. The
information on vehicular traffic at the junction was simulated and fed to the microcontroller and was
used as the primary input for the decision-making algorithms.
The adoptive algorithm first compares the number of vehicles in a chosen lane with those present in
all other lanes at any given moment. The ratio between number of vehicles was calculated and the
moment the ratio fell below a pre-defined threshold value, changes in traffic signal times were sought
through a fuzzy sub-system. The algorithm ‘learns’ continuously and converges to the most
acceptable switching time for each lane on a particular day at a particular time.
The pilot tests indicated that the system efficiency improves with time as it continues to learn from
experience. It was observed that on average the system adapts itself to a new situation within two or
three cycles. Even when the change in traffic pattern is small, 20%-30% efficiency improvement was
seen in this system compared to a programmed time system. For a large change, the improvement
was about 60%. In worse case scenario, (such as a failure of a sensor), the system behaves as a
programmed time system.
