Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Traffic analysis or control of surface vehicle
Reexamination Certificate
2000-12-18
2003-07-01
Cuchlinski, Jr., William A. (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Traffic analysis or control of surface vehicle
C701S118000, C340S901000
Reexamination Certificate
active
06587778
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to adaptive control systems and, more particularly, to adaptively controlling, in real-time, traffic signal control systems using rules and employing queue estimation.
2. Description of the Related Art
There are very few distributed fully-adaptive traffic control strategies in existence today. The processes in use typically are based on optimizing performance based on some objective function. The present invention departs from this approach by using a rule-based method for effective distributed adaptive signal control of traffic networks.
Most vehicular traffic signal control systems in the United States use time-based signal control, where a signal-timing plan is developed for a certain set of fixed traffic conditions. That is, traffic signals typically are controlled using a predetermined plan to change the traffic signal (i.e., the well-known red, yellow and green lights), where that plan is determined in advance based on historic traffic patterns and the time-of-day. That type of traffic control is not capable of responding effectively to short-term changes in traffic demand, and maintenance of such systems, which involves collecting new traffic volume data and modifying the current time-based control, is resource intensive. In addition, increasing traffic congestion is a recurring problem in most metropolitan and suburban cities, and modifications to the current infrastructure to increase capacity is typically very expensive and often not possible. However, technological advances in communications and electronics make it possible to consider advanced signal control systems that better respond to time-varying traffic demands, reduce maintenance costs, and increase the capacity of the current infrastructure.
Initial attempts at adaptive control were based on main frame computer technology of the 1970s. Typically, these systems were centralized in architecture, such as in the Split Cycle Offset Optimization Technique (e.g. SCOOT). Centralized traffic control systems compute the signal states for a region of intersections for a period of time (usually at least one cyclelength) and then download those signal states to each intersection. The number of intersections that can be served by this architecture is limited by the processing speed of the computer at the central site and the communications network that transfers the information to the intersections. In a distributed system, each intersection controller contains the control logic and decides what its signal state should be. There are of course, hybrids of the distributed/centralized architectures, since for any practical system some of the intelligence for the signal system must reside at the central site. However, distributed adaptive control can potentially serve an unlimited number of intersections, because most of the control logic is distributed locally at each intersection.
Currently there are very few distributed fully-adaptive real-time traffic control algorithms in existence. The existing algorithms (RHODES from the University of Arizona and OPAC from PB Farradyne) are based on optimizing the performance of some objective function. As a result, these algorithms are very resource intensive, and often cannot be implemented in more restrictive embedded systems.
The OPAC process does not perform any explicit queue estimation, because it is primarily based on the flow profiles within the network. The flow profiles for the network are predicted ahead for the next cyclelength and the splits and offsets for the control of traffic are computed based on those predictions. OPAC is a very conservative method. For example, it does not vary the phase order, and it also restricts the amount the cyclelength can vary from cycle to cycle.
RHODES is a predictive optimizer. It computes queue estimates for the network using activations from upstream detectors, and uses the idea of a “partial” vehicle to make those estimates. In addition, RHODES uses a dynamic program with a single state variable that tries every possible phase combination, using a particular measure of effectiveness (MOE) (e.g., travel time or delay) to arrive at the optimum phase. In order to find the optimum phase, RHODES must try every possible phase combination to identify the optimum phase. Thus, RHODES must be run on a very powerful, and hence, complex and expensive computer system. However, often the traffic controllers that are presently installed at an intersection are not powerful enough to effectively run the optimizations required by RHODES. Accordingly, there is a need for a distributed fully adaptive real-time traffic control process that can be performed using existing traffic controllers and that responds in real-time to traffic conditions.
SUMMARY OF THE INVENTION
Therefore, in light of the above, and for other reasons that will become apparent when the invention is fully described, an object of the invention is to effectively control traffic for a variety of traffic conditions and traffic networks using estimates of traffic conditions based on real-time or near real-time traffic measurements.
Another object of the invention is to estimate traffic patterns based on real-time, or near real-time, observations, while being insensitive to large short-term variations in traffic conditions.
Still another object of the invention is to select an optimal traffic signal state based on estimated real-time traffic conditions.
Yet another object of the invention is to control a traffic signal state using measurements from a minimum the number of upstream detectors installed across each lane for each approach to an intersection.
A further object of the invention is to control a traffic signal based on real-time traffic conditions including congested and uncongested traffic conditions.
A still further object of the invention is to use adaptively control the state of a traffic signal based on real-time, or near real-time traffic measurements, using existing traffic controllers already installed at numerous intersections. Accordingly, another object of the invention is to use minimal processor (CPU) speed and resources to run a real-time adaptive traffic signal control process that can be deployed in a variety of embedded environments.
Still another object of the invention is to reduce the delay drivers experience at traffic signal controlled intersections, and increase the number of trips that a network of traffic signals operating according to the invention can support.
The aforesaid objects are achieved individually and in combination, and it is not intended that the present invention be construed as requiring two or more of the objects to be combined unless expressly required by the claims attached hereto.
The present invention concerns a real-time adaptive traffic signal control method that determines the near optimal signal-state at an intersection. The invention achieves the objects described above by employing a rule-based method and queue estimation that can be used in a distributed environment and requires a minimal number of detectors. For uncongested traffic conditions the method estimates the number of approaching vehicles and the number of vehicles in queue, and uses a set of rules to effectively control traffic. The occupancy of upstream detectors on opposing approaches are used to determine if an intersection is experiencing congestion. An approach refers to a link (e.g., a southbound approach to an intersection). An opposing approach refers to approaches that intersect. For example, the opposing approaches for northbound traffic would be the east and westbound approaches. For congested intersections signal control logic creates a fixed time plan for the intersection. This method of effective real-time adaptive control can substantially increase the capacity and efficiency of a signalized intersection. The method estimates the number of vehicles stopped at the intersection and approaching the intersection. These estimates can be based on historical turning percentages
Owen Larry Evans
Stallard Charlie Monroe
Cuchlinski Jr. William A.
Edell Shapiro & Finnan LLC
Hernandez Olga
ITT Manufacturing Enterprises Inc.
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