  We introduce a heuristic scheduling algorithm for real-time adaptive traffic
signal control to reduce traffic congestion. This algorithm adopts a lane-based
model that estimates the arrival time of all vehicles approaching an
intersection through different lanes, and then computes a schedule (i.e., a
signal timing plan) that minimizes the cumulative delay incurred by all
approaching vehicles. State space, pruning checks and an admissible heuristic
for A* search are described and shown to be capable of generating an
intersection schedule in real-time (i.e., every second). Due to the
effectiveness of the heuristics, the proposed approach outperforms a less
expressive Dynamic Programming approach and previous A*-based approaches in
run-time performance, both in simulated test environments and actual field
tests.
