SMART AND SCALABLE URBAN SIGNAL NETWORKS: METHODS AND SYSTEMS FOR ADAPTIVE TRAFFIC SIGNAL CONTROL

摘要

Scalable urban traffic control system has been developed to address current challenges and offers a new approach to real-time, adaptive control of traffic signal networks. The methods and system described herein exploit a novel conceptualization of the signal network control problem as a decentralized process, where each intersection in the network independently and asynchronously solves a single-machine scheduling problem in a rolling horizon fashion to allocate green time to its local traffic, and intersections communicate planned outflows to their downstream neighbors to increase visibility of future incoming traffic and achieve coordinated behavior. The novel formulation of the intersection control problem as a single-machine scheduling problem abstracts flows of vehicles into clusters, which enables orders-of-magnitude speedup over previous time-based formulations and is what allows truly real-time (second-by-second) response to changing conditions.

主权项

1. An adaptive traffic control method comprising:
providing a local adaptive traffic control processor in communication with one or more neighboring adaptive traffic control processors, one or more traffic flow sensors, and a local intersection controller, wherein the local adaptive traffic control processor executes the following steps of the method: receiving traffic signal status from the local intersection controller; receiving current traffic flows from the one or more traffic flow sensors, wherein the current traffic flows comprises vehicle mode data; receiving planned traffic inflows from the one or more neighboring adaptive traffic control processors; merging the current traffic flows and the planned traffic inflows to form an aggregate traffic inflows; generating an optimal phase schedule based on the traffic signal status and the aggregate traffic inflows; and transmitting the optimal phase schedule to the one or more neighboring adaptive traffic control processors.