Enlarging Stability Region of Urban Networks with Imminent Supply Prediction

Stability region is a key index to characterize a dynamic processing system's ability to handle incoming demands. It is a multidimensional space when the system has multiple OD pairs where their service rates interact. Urban traffic network is such a system. Traffic congestion appears when its demand approaches or exceeds the upper frontier of its stability region. In this decade, with the rapid development of traffic sense technology, real-time traffic operations, e.g., BackPressure (BP) control, have gained lots of research attention. Urban network's mobility could be further improved with these timely demand-responding strategies. However, most studies on real-time controls continue with traditional supply assumptions and ignore an important fact -- imminent saturation flow rate (I-SFR), i.e., the system's real-time service rate under green, is neither fixed nor given, but hard to be precisely known. It is unknown how the knowledge level of I-SFR would influence the stability region. This paper proves that knowing more accurate I-SFR can enlarge the upper frontier of the network's stability region. Furthermore, BP policy with predicted I-SFR can stabilize the network within the enlarged stability region and relieve the congestion level of the traffic network. Therefore, improving the I-SFR's prediction accuracy is meaningful for traffic operations.