Abstract:
The present disclosure teaches a software and hardware system capable of operating on a signal controller platform which detects and records individual vehicle data including but not limited to dangerous driving behavior such as red light running and speeding. The disclosure teaches sharing of the computing platform and infrastructure of the traffic control system. The disclosure also teaches receiving, interpreting, and organizing data collected through the traffic control system&#39;s vehicle detection infrastructure, and driving cameras, video, or other recording devices to provide additional evidence of an individual vehicle&#39;s behavior.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is a divisional of U.S. patent application Ser. No. 10/557,915, filed Nov. 21, 2005, which is a national stage entry of PCT application PCT/US04/15714, filed May 19,  2004 , and which claims priority from U.S. Provisional Patent Application 60/471,685, filed May 19, 2003. This Application claims priority to each of those prior applications, which are hereby incorporated by reference. The content of the present application is not necessarily identical to the parent applications. 
     
    
     TECHNICAL FIELD 
       [0002]    This invention relates to traffic control systems, specifically providing the means to enable traffic signal controllers to collect individual vehicle data for safety analysis, automated enforcement, traffic control system assessment, and traffic condition assessment. 
       BACKGROUND OF THE DISCLOSURE 
       [0003]    Traffic signal controllers typically collect data concerning traffic count, occupancy, and average speed. Current state of the art is for the signal controller to collect data, and bin or aggregate it into predefined time increments, for example fifteen minute or one-hour intervals. Traffic information available from the controller, then, is based strictly on these aggregations. Information on individual vehicles traveling through the intersection is not available. 
         [0004]    Municipalities, other government agencies, and traffic researchers have long sought an efficient way to identify and analyze dangerous driving behavior in order to improve intersection safety (through signal timing, intersection re-engineering, or improved enforcement). Red light running and speeding are the behaviors most often researched. 
         [0005]    Because traffic signal controllers present only aggregate data, it is impossible to identify events associated with individual vehicles. Further, vehicle data that are tracked (occupancy and count) do not have either time or signal status associated with them For example, vehicle counts and occupancy data do not include the dimension of signal status—when the light was red, green, or amber. The result is that it is impossible to analyze traffic signal controller data to determine the number, frequency, time phasing, or severity of dangerous driving behavior such as red light running and speeding. Severity can be determined by analyzing a combination of speed, acceleration, vehicle type, and intersection clearance time. 
         [0006]    Current methods to analyze red light running include hand counts, video taping, and collecting data from automated enforcement systems. These methods suffer from several flaws: Hand counts are inaccurate, and liable to miss scenarios where multiple violations occur. Hand counts are impossible to validate—there is no empirical evidence of a violation. Further, hand counts typically collect only a fraction of the data required to fully analyze driver behavior. Hand counts cannot collect information relating to speed, acceleration, length into the red light cycle, or intersection clearance time. Video data collection improves only on accuracy of hand count, but not on the quality of related data (speed, acceleration, etc.). 
         [0007]    Automated enforcement devices are capable of collecting much of the information needed for safety research. Red light enforcement systems operate in conjunction with traffic signal controllers. The enforcement device receives status input and uses vehicle detection devices to determine when a violation is occurring. Automated speed enforcement systems use laser or radar to calculate vehicle speed, and do not require a connection to a signal controller to determine a violation. In both cases however, data is typically collected only in the process of active enforcement. The data collected by such devices is directly affected by the visibility of the enforcement device to the drivers being monitored, much the same way the presence of a police cruiser at an intersection win have an effect on speeding and red light running. 
         [0008]    Additionally, most, if not all, data analysis is done looking at single approaches to intersections with the remote (from the intersection) analysis of historical data. This precludes the collection and analysis of data from multiple vehicles and multiple approaches concurrently, providing results (to the traffic control system, for example) in near real time. 
         [0009]    In conclusion, no traffic signal controller can identify and record dangerous driving behavior, and no automated enforcement device is capable of operating as a traffic signal controller and unobtrusively collecting intersection safety information. Further, because they cannot identify individual vehicle events, and capture information related to those events, current traffic signal controllers are not capable of operating as automated enforcement systems in addition to their function of traffic control. 
       SUMMARY OF THE DISCLOSURE 
       [0010]    The present disclosure teaches a software and hardware system capable of operating on a signal controller platform which detects and records individual vehicle data including but not limited to dangerous driving behavior such as red light running and speeding. The disclosure teaches sharing of the computing platform and infrastructure of the traffic control system. The disclosure also teaches receiving, interpreting, and organizing data collected through the traffic control system&#39;s vehicle detection infrastructure, and driving cameras, video, or other recording devices to provide additional evidence of an individual vehicle&#39;s behavior. 
         [0011]    Aspects of the invention may be found in a system for collecting and analyzing data relating to individual vehicles as they approach or pass through an intersection. The system may include sensors for detecting vehicles, sensor input receivers, a traffic signal, a traffic control computer, an image acquisition system, and a network device. The system may also include a traffic control application, other internal applications, and a data collection and analysis application. Each of these applications may jointly operate on the traffic control computer. 
         [0012]    Vehicle data may be acquired by the sensors and communicated to the traffic control computer through the sensor input receiver. The traffic control application may communicate with the traffic signal and determine its state. The traffic control application may also communicate with the data collection and analysis application, providing both vehicle detection data and traffic signal state data. 
         [0013]    Further aspects of the invention may be found in the system combining vehicle and signal state data for the purpose of analysis and event detection or prediction. For example, the data collection and analysis application may associate a timestamp with each vehicle detection event. Furthermore, the data collection and analysis application may associate a timestamp with each traffic signal state change event, note the traffic signal state relative to each vehicle detection event, and may combine this information to create a record of the vehicle&#39;s passage through the intersection. 
         [0014]    Other aspects of the invention may be found in a method for detecting traffic violations or other safety hazards at the intersections. The method may include analyzing sensor data to determine or predict a vehicle&#39;s path up to and through the intersection. For example, the sensors may detect a vehicle moving towards the intersection. The data collection and analysis application may use the data to calculate the speed of the vehicle, and determine that it is exceeding the speed limit. 
         [0015]    The method may also include analyzing sensor data combined with signal state data to determine if a traffic signal violation has occurred or will occur. For example, the sensors may detect a vehicle moving towards the intersection at which the light is red. The data collection and analysis application may determine, after calculating the speed, acceleration, proximity to the intersection, and traffic signal state, that the vehicle is running or is likely to run the light. 
         [0016]    The method may also include analyzing sensor data from multiple vehicles and multiple approaches to the intersection to determine the likelihood of a collision or near collision. For example, the sensors may detect two vehicles approaching the intersection at the same time on different paths of travel. The data collection and analysis application may determine that, after calculating the speed, acceleration, and location of the two vehicles, their paths of travel may result in a collision. The integration of the data collection and analysis function with the traffic control system enables the invention to collect and analyze data from multiple vehicles and multiple approaches concurrently, providing results (to the traffic control system, for example) in near real time. 
         [0017]    Other aspects of the invention may be found in a system for acquiring images of desired events, combining the images with other data collected and calculated relative to the events, and transferring the data and/or images through an interconnected network. For example, the sensors may detect vehicles approaching the intersection, and the data collection and analysis application may detect or predict speeding or red light violations, or an imminent collision. The data collection and analysis application may then schedule an image or images to be taken of each of these vehicles or events as they occur at or near the intersection. Furthermore, the data collection and analysis application may combine the images and data relating to each event, and transfer them to a remote storage device or external applications using the network device. 
         [0018]    Further aspects of the invention may be found in a system locally transferring data and or analysis from the data collection and analysis application to either the traffic control application or to another application running on the traffic control computer. For example, the sensors may detect a vehicle approaching the intersection, and the data collection and analysis application may relate that data with the current signal state to predict a red light violation. Further, the data collection and analysis application may communicate that prediction to the traffic control application which in turn may communicate with the traffic signal to extend the red condition for the lanes of cross traffic. 
         [0019]    Further aspects of the invention may be found in a system for analyzing the traffic signal state to determine if it is in concurrence with the parameters defined by the traffic control application. For example, the data collection and analysis application may communicate with the traffic control application to determine the parameters for the signal timing. The data collection and analysis application may also analyze the number of seconds a particular signal displays an amber light over a period of hours, days, or weeks. Further, the data collection and analysis application may determine that the length of the amber signal has declined to the point where it is out of specification and communicate this information either to the traffic control application, to an external application, or both. 
         [0020]    Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words or phrases used throughout this patent document: the terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation; the term “or” is inclusive, meaning and/or; the phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, or the like; and the term “controller” means any device, system or part thereof that controls at least one operation, whether such a device is implemented in hardware, firmware, software or some combination of at least two of the same. It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. Definitions for certain words and phrases are provided throughout this patent document, and those of ordinary skill in the art will understand that such definitions apply in many, if not most, instances to prior as well as future uses of such defined words and phrases. While some terms may include a wide variety of embodiments, the appended claims may expressly limit these terms to specific embodiments. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0021]    For a more complete understanding of the present disclosure, and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, wherein like numbers designate like objects, and in which: 
           [0022]      FIG. 1  is a schematic block diagram of a system for collecting and analyzing vehicle data according to the disclosed embodiments; 
           [0023]      FIG. 2  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 ; 
           [0024]      FIG. 3  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 ; 
           [0025]      FIG. 4  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 ; 
           [0026]      FIG. 5  is a block flow diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 ; 
           [0027]      FIG. 6  is a block flow diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 ; and 
           [0028]      FIG. 7  is a block diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 . 
       
    
    
     DETAILED DESCRIPTION 
       [0029]      FIGS. 1 through 7 , discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged device. The numerous innovative teachings of the present application will be described with reference to exemplary non-limiting embodiments. 
         [0030]      FIG. 1  is a schematic block diagram of a system for collecting and analyzing vehicle data according to the invention. The system  1  includes a traffic control application  2  and a data collection and analysis application  3  which both operate on a traffic control computer  4 . The traffic control computer  4  may reside in a traffic control system enclosure  5 . The traffic control computer  4  may be connected to a traffic signal  6  and sensor input receiver  8 . Further, the sensor input receiver  8  may receive inputs from the vehicle detection sensors  7 . Similarly, the data collection and analysis application  3  may be connected to an image acquisition system  9 . The traffic control computer may include a network device  10  that allows connection to a remote storage device  11  and support of external applications  12 . 
         [0031]    The vehicle detection sensors  7  may detect a vehicle or vehicles. The sensors  7  may communicate data associated with the vehicle or vehicles through the sensor input receiver  8  to the traffic control computer  4 . The traffic control computer  4  and/or the traffic control application  2  may communicate data from sensors  7  and traffic signal  6  to the data collection and analysis application  3 . The data collection and analysis application  3  may analyze data received to predict the vehicle&#39;s path through the intersection, including but not limited to determining whether a traffic violation or other safety hazard has occurred or is likely to occur. Further, the data collection and analysis application  3  may schedule a time for the acquisition of one or more images associated with an event relating to the vehicle&#39;s travel path using the image acquisition  9 . Furthermore, the data collection and analysis application  3  may combine data received from the image acquisition system  9 , the vehicle detection sensors  7 , and the traffic signal  6  in the process of creating a record of the vehicle&#39;s travel up to and through the intersection, as well as temporarily storing the record on the traffic control computer  6  before making the data available to internal applications  13 , or accessing the network device  10  for transmission to either remote storage  11  or external applications  12 . 
         [0032]      FIG. 2  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 . In this exemplary embodiment  14  an intersection is shown  15 . On at least one approach to the intersection  15 , vehicle detection sensors  16  may define detection zones  17 A and  17 B. The vehicle detection sensors may be placed, for example, in, on, under, or above the road. The sensors may detect one or more vehicles  18  and  19  approaching the intersection. The sensors  16  may signal the traffic control computer  20  with the data associated with the vehicles  18  and  19 . Furthermore, the traffic control computer  20  may provide the data associated with the vehicles  18  and  19  to the data collection and analysis application  22 . The data collection and analysis application  22  may receive signal state data either directly from the traffic signal  21  or from the traffic control computer  20 . The data collection and analysis application may analyze data associated with the vehicles  18  and  19  in conjunction with the signal state data and predict or detect the vehicle&#39;s path of travel up to and through the intersection. The data collection and analysis application may timestamp and record each of the detection events, signal states, and signal change events associated with the vehicle&#39;s travel up to and through the intersection. 
         [0033]    In another exemplary embodiment, the data collection and analysis application  22  may analyze the data relating to a vehicle&#39;s approach to the intersection to determine if a traffic violation or other safety hazard has occurred or is likely to occur. If the analysis indicates that such a violation or hazard is likely to occur, the data can be characterized as falling within a “violation” or “hazard” classification. Furthermore, the data collection and analysis application  22  may capture, or schedule a time for the acquisition of, one or more images associated with the traffic violation or safety hazard using the image acquisition system  23 . Images created with the image acquisition system  23  and data collected and analyzed by the data collection and analysis application  22  may be combined and transmitted to a remote storage device  24 . 
         [0034]    For example, vehicle  18  may approach the intersection  15 . The vehicle  18  may pass through detection zone  17 A, and may cause a detection event or events to be sent through the vehicle detection sensor  16  to the traffic control computer  20 . Furthermore, the data collection and analysis application  22  may receive the detection data associated with vehicle  18  from the traffic control computer  20 . The data collection and analysis application  22  may also receive data from the traffic control computer  20  regarding the status of the traffic signal  21  which may be red. The data collection and analysis application  22  may then associate the traffic signal  21  status with the detection data and analysis relating to vehicle  18 . The data collection and analysis application  22  may determine that a violation has occurred or is likely to occur. For example, the data collection and analysis application  22  may measure or determine the location, speed, and or magnitude of acceleration of vehicle  20 , relate this data to the status of the traffic signal  21 , and ascertain the likelihood of vehicle  18  running a red light. Furthermore, the data collection and analysis application  22  may schedule images to be acquired of the red light violation using the image acquisition system  23 . Images and data associated with the red light violation may then be transferred to a remote storage device  24 . 
         [0035]    In another example, vehicle  19  may approach the intersection  15 . The vehicle  19  may pass through detection zone  17 B, and may cause a detection event or events to be sent through the vehicle detection sensor  16  to the traffic control computer  20 . Furthermore, the data collection and analysis application  22  may receive the detection data associated with vehicle  19  from the traffic control computer  20 . The data collection and analysis application  22  may also receive data from the traffic control computer  20  regarding the status of the traffic signal  21  and associate that status with the detection data associated with vehicle  19 . Based on its analysis, the data collection and analysis application  22  may record and store the data, transfer the data to a remote storage device  24 , or schedule images to be recorded using the image acquisition system  23 . 
         [0036]    In another example, vehicle  18  may approach the intersection  15 . The vehicle  18  may pass through detection zone  17 A, and may cause a detection event or events to be sent through the vehicle detection sensor  16  to the traffic control computer  20 . The data collection and analysis application  22  may receive the detection data associated with the vehicle  18 , calculate the speed of vehicle  18 , and determine that a speeding violation has occurred. Furthermore, the data collection and analysis application  22  may schedule images to be acquired of the speeding violation using the image acquisition system  23 . Images and data associated with the speeding violation may then be transferred to a remote storage device  24 . 
         [0037]      FIG. 3  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 . In this exemplary embodiment  25 , an intersection is shown  26 . On multiple approaches to the intersection  26 , one or more detection sensors  27  may define detection zones  28 A,  28 B,  28 C,  28 D,  28 E,  28 F,  28 G, and  28 H. The vehicle detection sensors may be placed, for example, in, on, under, or above the road. The sensors may detect one or more vehicles  29 ,  30 ,  31 ,  32 , and  33  approaching the intersection. The sensors  27  may signal the traffic control computer  34  with the data associated with the vehicles  29 ,  30 ,  31 ,  32 , and  33 . Furthermore, the traffic control computer  34  may provide the data associated with the vehicles  29 ,  30 ,  31 ,  32 , and  33  to the data collection and analysis application  35 . In this example, two vehicles  29  and  30  approach the intersection. The vehicle  29  may pass through detection zone  28 B and vehicle  30  may pass through the detection zone  28 C resulting in detection events recorded by the sensors  27 . The detection events may be transferred to the traffic control computer  34  and then to the data collection and analysis application  35 . Using the detection event data, the data collection and analysis application  35  may determine location, speed, and acceleration of both vehicles  29  and  30 . The data collection and analysis application  35  may also analyze signal state data based on the state of the traffic signals  36 . Furthermore, the data collection and analysis application may predict a path of travel for both vehicles  29  and  30 , based on the analysis of the detection event data and signal state data, to determine if there is a potential for a collision or a near collision of the two vehicles. In the event of detecting a collision or near collision, the data collection and analysis application  35  may schedule the acquisition of images of the event using an image acquisition system  37 . 
         [0038]    In another example, two vehicles  31  and  33  approach the intersection. Vehicle  31  may be an emergency vehicle, and vehicle  33  may be a privately owned vehicle. Vehicle  31  may travel through the detection zone  28 E and vehicle  33  may travel through the detection zone  28 H, with sensors  27  recording the detection events. The detection events may be transferred to the traffic control computer  34  and then to the data collection and analysis application  35 . Furthermore, the emergency vehicle  31  may communicate information to the traffic control computer  34  about its status as an emergency vehicle. The data collection and analysis application  35  may analyze traffic signal  36  status in conjunction with the detection events related to vehicles  31  and  33 . Further, the data collection and analysis application  35  may predict or detect a red light violation by vehicle  33 , and notify the traffic control computer  34  of the detection. The traffic control computer  34  may then communicate the impending or occurring red light violation of vehicle  33  to the emergency vehicle  31 , thereby reducing the likelihood of a collision. 
         [0039]    In another example, two vehicles  32  and  33  approach the intersection. Vehicle  32  may travel through the detection zone  28 F and vehicle  33  may travel through the detection zone  28 H. Sensors  27  may record the detection events. The detection events may be transferred to the traffic control computer  34  and then to the data collection and analysis application  35 . The data collection and analysis application  35  may analyze and relate traffic signal  36  status to the detection events related to vehicles  32  and  33  and may further predict travel paths of the two vehicles. The signal phasing may be such that both vehicles  32  and  33  are approaching the intersection with the traffic signal  36  showing a red light. The next planned phase of the traffic signal  36  may be to display a green light to vehicle  32  and to continue to display a red light to vehicle  33 . The data collection and analysis application  35  may, after analysis, predict or detect a red light violation either occurring or about to occur based on the location, travel path, speed, or acceleration of vehicle  33 . The data collection and analysis application  35  may also communicate the likelihood or actuality of this red light violation to the traffic control computer  34 . The traffic control computer  34  may then preempt the planned change of status of the traffic signal  36  that is facing vehicle  32  and hold the traffic signal  36  in the red display condition until vehicle  33  is clear of the intersection. 
         [0040]      FIG. 4  is a schematic block diagram of an exemplary embodiment of the system according to  FIG. 1 . In this exemplary embodiment  37 , a defined roadway area  38  is shown. Markers, signs, or striping areas  39 A and  39 B may define the boundaries of the area  38 . The zone may be a school zone, construction zone, neighborhood or other roadway zone defined by boundaries. A vehicle detection sensor  40  may define detection zones  41 A,  41 B,  41 C, and  41 D. The vehicle detection sensor  40  may detect vehicles  42  and  43  as they pass through detection zones  41 A,  41 B,  41 C, or  41 D. Further, the vehicle detection sensor  40  may communicate detection events to the traffic zone controller  44 . The traffic zone controller  44  may communicate with indicator lamps  45  to notify passing vehicles  42  and  43  that they are traveling through a defined roadway area  38 , and that, as a result, special conditions such as speed limits may apply. In this example, vehicle  42  may travel through detection zone  41 A and vehicle  43  may travel through detection zone  41 C. Vehicle detection sensor  40  may detect vehicles  42  and  43  as they pass through detection zones  41 A and  41 C respectively. Vehicle detection sensor  40  may communicate these detection events to the traffic zone controller  44 , and the traffic zone controller  44  may further communicate the detection events to the data collection and analysis application  47 . The traffic zone controller  44  may also communicate the status of the indicator lamps  45  to the data collection and analysis application  47 . Furthermore, the data collection and analysis application  47  may calculate the speed and location of vehicles  42  and  43  and correlate this data with the status of the indicator lamps  45 . The data collection and analysis application  47  may then determine that vehicles  42  and  43  are in violation of the speed limit defined by the indicator lamps  45  being illuminated for the roadway area  38 . Further, the data collection and analysis application  47  may schedule images to be captured of the violations using image capture systems  46 A and  46 B. In this example, the data collection and analysis application  47  may schedule images specifically for vehicle  42  and may use image capture system  46 A, and may use image capture system  46 B to schedule and record images of vehicle  43 . 
         [0041]      FIG. 5  is a block flow diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 . In this exemplary method  48 , the data collection and analysis system may collect a first set of individual vehicle data  49  and a second set of individual vehicle data  50 . Furthermore, the data collection and analysis system may analyze the combination of the first set, the second set, and the differences or similarities between the two sets  51 . Finally, the data collection and analysis system may provide the result of the analysis  52  to interested local or external applications. For example, the data collection and analysis system may collect data over the course of a month to determine average traffic volume by hour of the day. The data collection and analysis system may further collect the same set of data in a different month. Finally, the data collection and analysis system may compare the two sets of data to either define a historical model to be used for future reference, or to determine differences in traffic volume on a monthly basis. 
         [0042]    In another example, the data collection and analysis system may collect a set of individual vehicle data  49 , review a model (historical or preferred) set of data  50 , and analyze the similarities and differences in the data sets  51 . The result of the analysis  52  may be made known to interested external or internal applications. For example, the data collection and analysis system may collect data on vehicle volumes for different times of day. It may compare actual volumes to historical volumes and determine that volume for the current hour is 10% of the historical average. The data collection and analysis system may then generate a notice of this condition and deliver it to interested local or external applications. 
         [0043]      FIG. 6  is a block flow diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 . In this exemplary method  53 , the data collection and analysis system may collect a set of signal state data  54  and a second set of signal state data  55 . Furthermore, the data collection and analysis system may analyze the combination of the first set, the second set, and the differences or similarities between the two sets  56 . Finally, the data collection and analysis system may provide the result of the analysis  57  to interested local or external applications. For example, the data collection and analysis system may collect data over the course of a month to determine average green, amber, and red timing. The data collection and analysis system may further collect the same set of data in a different month. Finally, the data collection and analysis system may compare the two sets of data to determine if the signal timing has changed in an allowable range. If the change in signal timing is outside of the allowable range, the data collection and analysis application may send a notice to an interested local or external application. 
         [0044]    In another example, the data collection and analysis system may collect a set of signal state data  54  and review a model (preferred or historical) set of signal state data  55 . Furthermore, the data collection and analysis system may analyze the combination of the first set, the second set, and the differences or similarities between the two sets  56 . Finally, the data collection and analysis system may provide the result of the analysis  57  to interested local or external applications. For example, the data collection and analysis system may collect signal state data  54  on green, amber, and red signal display times for each phase change during the course of the day. The data collection and analysis system may review the green, amber, and red signal display times as provided by the model data  55 . Further, the data collection and analysis application may compare the model and actual data  56 , may determine that the amber signal display times  54  are different from the model  55 , and may record the differences over time. Additionally, the data collection and analysis application may determine that the difference between the actual amber signal display time  54  and the model display time  55  is increasing, and may predict that the signal timing will soon be out of specification as determined by the signal timing model. Finally, the data collection and analysis application may communicate the out of specification prediction results  57  interested local or external applications. 
         [0045]      FIG. 7  is a block diagram of an exemplary embodiment of a method for use in a system as seen in  FIG. 1 . In this exemplary method  58 , the data collection and analysis application may collect, combine, and analyze a set of individual vehicle and signal state data  59 . The data collection and analysis application may also collect, combine, and analyze a different set of individual vehicle and signal state data  60 . Furthermore, the data collection and analysis application may compare the two sets of data  61 , and provide results  62  to interested internal or external applications. For example, the data collection and analysis application may collect, combine, and analyze a set of individual vehicle and signal state data to determine the number of red light violations occurring in a particular time period  59 . The data collection and analysis application may collect the same type of data over a different time period  60 . The data collection and analysis application may compare the data sets  61 , and determine that the number of red light violations has increased over the time period, and may report the results  62  to interested internal or external applications. 
         [0046]    In another example, the data collection and analysis application may collect, combine, and analyze a set individual vehicle and signal state data  59 . The data collection and analysis application may review a second model (preferred or historical) set of data  60 . Furthermore, the data collection and analysis application may compare the two sets of data  61 , and provide results  62  to interested internal or external applications. For example, the data collection and analysis application may collect, combine, and analyze a set of individual vehicle and signal state data to determine the number of red light violations occurring in a particular time period  59 . The data collection and analysis application may review the number of red light running violations in a like time period from the model data  60 . The data collection and analysis application may compare the data sets  61 , and determine that the number of red light violations from the actual data  59  exceeds the number of violations expected by the model  60 , and may report the results  62  in the form of a notice, alarm, or other communication to interested internal or external applications. 
         [0047]    The term “communication,” as used in the present disclosure, includes direct and indirect transfer of information. For example, the case of a first agent writing a set of data to and a second agent reading the set of data from a shared memory would be included. The case of multiple agents utilizing a common source or conduit for receiving or transmitting data, such as a shared driver which outputs vehicle detection information to two applications, would also be included. 
         [0048]    Those skilled in the art will recognize that, for simplicity and clarity, the full structure and operation of all systems or circuitry suitable for use with the present disclosure is not being depicted or described herein. Instead, only so much of the systems or circuitry as is unique to the present disclosure or necessary for an understanding of the present disclosure is depicted and described. The remainder of the construction and operation of the embodiments disclosed herein may conform to any of the various current implementations and practices known in the art. 
         [0049]    Although an exemplary embodiment of the present disclosure has been described in detail, those skilled in the art will understand that various changes, substitutions, variations, and improvements disclosed herein may be made without departing from the spirit and scope of the disclosure in its broadest form. 
         [0050]    None of the description in the present application should be read as implying that any particular element, step, or function is an essential element which must be included in the claim scope: the scope of patented subject matter is defined only by the allowed claims. Moreover, none of these claims are intended to invoke paragraph six of 35 USC §112 unless the exact words “means for” are followed by a participle.