Abstract:
A computer readable medium embodies a program of machine-readable instructions executable by a processing apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle, and transmitting one or more representations of the information. Another computer readable medium tangibly includes instructions for, for each of a number of vehicles, receiving one or more scores corresponding to a vehicle, and determining a ranked list containing at least a portion of the scores, and outputting the ranked list. Another computer readable medium includes instructions for, for each of a number of vehicles, receiving information corresponding to a vehicle, using one or more metrics, calculating one or more values from the received information, and communicating one or more representations of the one or more value to one or more entities.

Description:
BACKGROUND 
       [0001]    This invention relates generally to systems that communicate with units in vehicles for road user charging purposes and, more specifically, relates to anomaly detection for road user charging systems. 
         [0002]    In road user charging systems, an on-board unit (OBU) is placed in each vehicle to be charged. The charging is based on, e.g., distance traveled, zone, time of travel, and the like. For instance, a goal for this type of system may be to managing traffic congestion by setting higher costs for travel on certain roads or in certain areas. Thus, roads or areas that are typically congested have a higher cost for travel. These systems also may include variable pricing based on travel during certain times of the day. That is, it is more expensive to travel during peak hours. These systems also provide taxes for use of the roads. 
         [0003]    In many of these systems, the OBU keeps track of locations, times at those locations, and the like. At certain times, the OBU reports this data to a central location, called the “back office.” The back office then bills the user based, e.g., on a road use schedule. 
         [0004]    Because these systems are becoming more widespread, abusers of the systems are also becoming more prevalent. For example, software is available to fake user location: information can be stored in the OBU indicating that the vehicle is located in a low cost zone, when actually the vehicle is located in a high cost zone. Additionally, the OBU may also be tampered with, switched off, or put into different vehicles. 
         [0005]    Gantries typically serve as enforcement mechanisms. For example, a gantry observes a vehicle being in a high price zone but the vehicle claims to be in a low price zone at the observation time. As another example, a gantry uses automatic number plate recognition (ANPR) to determine that a license plate number viewed on a vehicle is different from a license place associated with the OBU for the vehicle. 
         [0006]    While these techniques work for certain situations, gantries are an additional cost and a vehicle might travel paths with infrequent pathways through gantries. Further, a savvy abuser could determine where the gantries are and correct the data in an OBU prior to passing through a gantry, but then create incorrect data for those times when travel is not near a gantry. In these situations, gantries may have limited effect as enforcement mechanisms. 
         [0007]    What is needed, therefore, are techniques for improving enforcement. 
       SUMMARY 
       [0008]    In an exemplary embodiment, a computer readable medium is disclosed that tangibly embodies a program of machine-readable instructions executable by a digital processing apparatus to cause the digital processing apparatus to perform operations including, for each of a number of vehicles, receiving information corresponding to a vehicle. The operations also include, using one or more metrics, calculating one or more values from the received information, and communicating one or more representations of the one or more values to one or more entities. 
         [0009]    In another exemplary embodiment, a computer readable medium is disclosed that tangibly embodies a program of machine-readable instructions executable by a digital processing apparatus to cause the digital processing apparatus to perform operations including, for each of a number of vehicles, receiving one or more scores corresponding to a vehicle. The operations also include determining a ranked list containing at least a portion of the scores, and outputting the ranked list. 
         [0010]    In yet another exemplary embodiment, a computer readable medium is disclosed that tangibly embodies a program of machine-readable instructions executable by a digital processing apparatus to cause the digital processing apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle. The operations also include transmitting one or more representations of the information. 
         [0011]    In a further exemplary embodiment, an apparatus is disclosed that includes one or more memories including instructions, and one or more processors operatively coupled to the one or more memories, the one or more processors configured by the instructions to cause the apparatus to perform operations including determining information corresponding to a number of differences in distances between ending points of journeys taken by a vehicle and starting points of consecutive journeys taken by the vehicle. The operations also include transmitting one or more representations of the information. 
     
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         [0012]    The foregoing and other aspects of embodiments of this invention are made more evident in the following Detailed Description of Exemplary Embodiments, when read in conjunction with the attached Drawing Figures, wherein: 
           [0013]      FIG. 1  is a block diagram of an exemplary road user charging system suitable for use with the invention; 
           [0014]      FIG. 2  is a block diagram illustrating an exemplary on-board unit operating in accordance with an exemplary embodiment of the invention; 
           [0015]      FIG. 3  is a block diagram of an exemplary back office processing apparatus operating in accordance with an exemplary embodiment of the invention; 
           [0016]      FIG. 4  is a block diagram of a heuristic overview of an exemplary embodiment of the invention; 
           [0017]      FIG. 5  is a diagram illustrating exemplary information flows in an exemplary embodiment of the invention; 
           [0018]      FIG. 6  is an example of a single journey metric used to determine possible fraud involving a single journey, and a ranked list of system abuse scores and their associated unique identifiers; 
           [0019]      FIG. 7  is a graph of an example of a distance difference distribution of distance values and an outlier value indicating possible fraud; 
           [0020]      FIG. 8  is an example of a multiple journeys metric used to determine possible fraud involving multiple journeys, and a ranked list of system abuse scores and their associated unique identifiers; 
           [0021]      FIG. 9  is a graph of an example of a distance difference distribution of distance values and a set of outlier values indicating possible fraud; 
           [0022]      FIG. 10  is a block diagram of actions performed by an OBU in accordance with an exemplary embodiment of the invention; and 
           [0023]      FIG. 11  is a block diagram of actions primarily performed by a back office processing apparatus in accordance with an exemplary embodiment of the invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0024]    Before proceeding with a description of exemplary embodiments of the invention, a more detailed discussion of problems with current road user charging systems is presented. As described above, there are certain situations where fraud might be performed on an OBU and a gantry might not detect the fraud. In particular, if an on-board unit (OBU) is set so that correct data is used near known gantries but incorrect data is used when not near gantries, a gantry typically cannot serve as an enforcement mechanism or has a much reduced capacity as an enforcement mechanism. For the situations where an OBU is loaded with incorrect data at some time, the OBU should be loaded again with correct data at some future time. There should therefore be a difference between the last known position, which is the ending point of the previous journey, and the position when the OBU is enabled again, which is a beginning point for a consecutive journey. Thus, one would believe that it would be a simple matter to test for fraud by having an OBU test for any difference in position between the ending point for a previous journey and a beginning point of a consecutive, new journey. For instance, the OBU may be simply switched off to prevent charging. 
         [0025]    However, there is some amount of natural variability in determination of the beginning point of a consecutive journey. For example, it is generally the case that an OBU powers down (e.g., is placed into a low power state) when a vehicle is turned off. This conserves the battery power of the vehicle. When the vehicle is turned back on, the OBU then powers on and begins recording data. There is typically a delay between power on time and when the OBU can synchronize with a global positioning system (GPS) or other positioning system in order to determine a current position. In some instances, this delay could be substantial if in a mountainous, covered, or urban area. Thus, even for normal OBUs, there will be some variability in a distance between the end point (e.g., position) of a previous journey and a beginning point (e.g., position) of a consecutive, new journey. 
         [0026]    Certain exemplary embodiments of the invention take this variability into account by collecting data about the distances between end points of previous journeys and beginning points of consecutive journeys from multiple OBUs in multiple vehicles. The OBUs collect data about their own distances and communicate this data to a central location. This data is used to determine information about what amounts to a distance difference distribution of the distances from the population of multiple OBUs. This information, such as a mean and a standard deviation, corresponding to the probability distribution is communicated to OBUs in the vehicles. It is noted that typically an actual population probability distribution is not actually determined, but the mean and standard deviation allows one to reconstruct such a distribution. The OBUs use this information to determine if their calculated distances are potentially fraudulent. Different exemplary metrics are used to determine potential fraud on a single journey or to determine potential fraud on multiple journeys. The OBUs, in an exemplary embodiment, report information about potential fraudulent activity, generally through scores determined using the metrics, to a central location. The central location accumulates the data from multiple OBUs and then ranks the data from highest to lowest probability of fraudulence. 
         [0027]    Turning now to  FIG. 1 , this figure shows a block diagram of an exemplary road user charging system  100  suitable for use with the invention. The road user charging system  100  includes N gantries, of which only gantries  110 - 1  and  110 - 2  are shown. The gantries  110  are connected to the back office  170  through a radio frequency (RF) or wired network  160  and wireless or wired network links  180 . Gantry  110 - 1  includes (in this example) two cameras  115 - 1  and  115 - 2 , two radio frequency communication systems (RF 1  and RF 2 ) and a gantry processing unit (GPU)  130 - 1 . Similarly, gantry  110 - 2  includes (in this example) two cameras  115 - 3  and  115 - 4 , two radio frequency communication systems (RF 3  and RF 4 ) and a GPU  130 - 2 . The gantry  110 - 1  is shown in RF communications with vehicles  120 - 1  and  120 - 2 . 
         [0028]    Each vehicle  120 - 1 ,  120 - 2  has an OBU  121 - 1 ,  121 - 2 , respectively. Each OBU meeting certain criteria (described below) sends flag messages to the gantries  110 . In this example, there are several flag messages  150 - 1  communicated from OBUs  121  through gantry  110 - 1 , through network  160 , and to the back office  170 . There are additionally several flag messages  150 - 2  communicated from OBUs  121  through gantry  110 - 2 , through network  160 , and to the back office  170 . The OBUs  121  also communicate data about the distances they determine between ending points of previous journeys and beginning points of consecutive, new journeys to the back office  170 , through gantries  110 . In this example, certain OBUs  121  determine a distance difference distribution and from the distance difference distribution (not shown in this figure) determine a mean, μ i , and a standard deviation, σ i , and send a representation  153 - 1  of the mean, μ i , and a standard deviation, σ i , to the back office  170 . Similarly, certain other (or potentially the same) OBUs  121  determine a distance difference distribution and from the distance difference distribution determine a mean, μ i , and a standard deviation, σ i , and send a representation  153 - 2  of the mean, μ i , and a standard deviation, σ i , to the back office  170 . 
         [0029]    The back office  170  uses the means and standard deviations to calculate a global mean, μ,  195  and a global standard deviation, σ,  196 . The back office  170  then communicates the global mean  195  and global standard deviation  196  to the OBUs  121  via the network  160  and gantries  110 . 
         [0030]    It should be noted that the OBUs  121  may be able to bypass the gantries  110  and communicate with the network  160  via a wired or wireless network link  190 . However, for simplicity, it is assumed herein that the OBUs  121  communicate only through gantries  110 , although this is not a requirement and other techniques may be used. 
         [0031]    Turning now to  FIG. 2 , a block diagram is shown illustrating an exemplary on-board unit (e.g., a digital processing apparatus) operating in accordance with an exemplary embodiment of the invention. The OBU  121  comprises one or more memories  210  coupled through one or more buses  295  to a GPS  250 , an RF transceiver  255 , a network interface  260 , and one or more processors  265 . The one or more memories  210  include instructions  270 , which when executed by the one or more processors  265  cause the OBU  121  to perform specific actions. The instructions  270  include an anomaly detection engine  271 , which contains the instructions that cause the OBU  121  to perform the actions described herein. The anomaly detection engine  271  includes a single journey metric  275  (see  FIG. 6  also) and a multiple journeys metric  280  (see  FIG. 8  also). 
         [0032]    The one or more memories  210  include a mean, μ j ,  211 , a standard deviation, σ j ,  212 , distances D 1  through D j , a global mean, μ,  215 , a global standard deviation, σ,  216 , a flag message  220 , a single journey value threshold, T SJV ,  221 , and a multiple journeys threshold, T MJV ,  222 . Also shown are journeys J 0  through J j , each of which has a starting point, SP, and an ending point, EP. The distances D 1  through D j  are shown being calculated from the corresponding ending point, EP, and starting point, SP. For instance, distance D 1  is calculated by subtracting the ending point EP 0  of a previous journey J 0  from the starting point SP 1  of a consecutive journey J 1 . Distance D j  is calculated by subtracting the ending point EP j−1  of a previous journey J j−1  from the starting point SP j  of a consecutive journey J j . In terms of subscripts, the subscript j is the current journey, and the journeys start at zero to make the subscripts easier to describe. The subscript i is used to indication one of n OBUs  121 . 
         [0033]    With regard to the thresholds  221 ,  222 , these are used in certain embodiments and not used in others. For instance, each OBU  121  could use the single journey metric  275  and/or the multiple journeys metric  280  to determine a score for each metric. The score(s) would then be sent from the OBUs  121  to the back office  170 , without regard to the value(s) for the score(s). Alternatively, OBUs  121  might send only those scores that surpass the thresholds  221 ,  222  to the back office  170 . 
         [0034]    It should be noted that typically only the ending point (EP j−1 ) of the previous journey (J j−1 ) and the starting point (SP j ) of the current journey (J j ) are kept in the one or more memories  210 , until the current journey ends, when the current ending point (EP j ) replaces the previous ending point. Additionally, the distances D 1  through D j  may be assembled into distance difference distributions, as shown in  FIGS. 7 and 9  below. Further, the operation of the OBU  121  is described in further detail below. 
         [0035]    The OBUs  121  use the metrics  275 ,  280  to determine scores (not shown in  FIG. 2  but shown in other figures, e.g., like  FIG. 3 ), which are then communicated to a central server, such as that shown in  FIG. 3 . The scores may be compared to the thresholds  221 ,  222 , and only those scores sent by the OBU  121  if the scores exceed the thresholds  221 ,  221 . Alternatively, each score could be sent by the OBU  121 . Furthermore, the highest score determined between the metrics  272 ,  280  may be sent, or both scores may be sent. Although not shown, the back office processing apparatus  300  could have one or more radio frequency transceivers. 
         [0036]    Referring now to  FIG. 3 , a block diagram is shown of an exemplary back office processing apparatus  300  (e.g., in back office  170 ) operating in accordance with an exemplary embodiment of the invention. The apparatus  300  may be considered to be a digital processing apparatus. The back office processing apparatus  300  is an example of a central server. The back office processing apparatus  300  includes one or more memories  310  coupled to one or more network interfaces  360  and one or more processors  365  through one or more buses  395 . The one or more memories  310  include n means  211  (i.e., μ 1 ,  211 - 1  through μ n ,  211 - n ) from n OBUs  121 , n standard deviations (i.e., σ 1 ,  212 - 1  through σ n ,  212 - n ), a global mean μ,  215 , a global standard deviation, σ,  216 , and z scores  320 - 1  through  320 - z  from flag messages  220 - 1  through  220 - z  (in this example, one score per flag message  220 , although this is not a requirement and there may be more than one score per flag message). The one or more memories  310  also include instructions  370 , which when executed by the one or more processors  365  cause the back office processing apparatus  300  to perform specific actions. The instructions  370  include an anomaly processing engine  371 , which contains the instructions that cause the back office processing apparatus  300  to perform the actions described herein. 
         [0037]    As is described in more detail below, the anomaly processing engine  371  determines the global mean  215  and global standard deviation  216  from the means  211  and standard deviations  212 , respectively. The anomaly processing engine  317  cause the global mean  215  and global standard deviation  216  to be communicated, using the one or more network interfaces  360 , to the OBUs  121 . Certain of the OBUs  121 , in this example in OBUs  121 , send flag messages  220 - 1  through  220 - m  to the back office processing apparatus  300 . The anomaly processing engine  371  then creates a list  368  of possible abusers using the scores  320  from the flag messages  220 . The list  368  in one example is a set of system abuse scores, typically ranked from most probable abuser to least probable abuser, as described below. The system abuse scores are the scores  320 . The scores- 320  are communicated to the apparatus  300  from the OBUs  121 . There may be z scores  320 , z less than n, where n is the number of OBUs  121 , if thresholds  221 ,  222  are used. Alternatively, z may be equal to n, if each OBU  121  reports scores  320  without using thresholds  221 ,  221 . Additionally, there could be two scores  320  per OBU  121 , one score for each metric  275 ,  280 , if desired. 
         [0038]    Referring now to  FIG. 4 , a block diagram is shown of a heuristic overview  400  of an exemplary embodiment of the invention. The heuristic overview  400  includes a local model in block  410 , a global model in block  420 , device data  430  in block  430 , a ranking function in block  440 , and system abuse scores  450 . In general, the heuristic overview  400  includes estimating a local model (block  410 ) and computing system abuse scores  450  by benchmarking against a global model (computed in block  420  and implemented in a ranking function in block  440 ). Thus, in block  410 , each device (e.g., OBU  121 ) independently estimates a distance difference distribution for the distance differences between an ending point of a previous journey and a starting point of a consecutive journey. A population distance difference distribution is estimated at a central server (e.g., the back office  170  and its processing apparatus  300 ). In block  440 , each OBU  121  uses device data (from block  430 ) to apply a ranking function that uses global model parameters to produce system abuse scores  450 . Exemplary ranking functions include the single journey metric  275  (shown, e.g., in  FIG. 6 ) and/or the multiple journeys metric  280  (shown, e.g., in  FIG. 8 ). System abuse scores  450  meeting a threshold (e.g., the single journey value threshold, T SJV ,  221 , and/or the multiple journeys threshold, T MJV ,  222 ) are communicated by an OBU  121  to the central server via a flag message  150  (in  FIG. 1 ) or  220  (in  FIGS. 2 or 3 ). Alternatively, all system abuse scores  450  determined by an OBU  121  are sent to the central server. The system abuse scores  450  would also include unique identifiers (discussed below) in order to link a system abuse score  450  with an OBU  121 , and this set of data is an example of a list  368  (see  FIG. 3 ) of possible abusers. 
         [0039]    Turning now to  FIG. 5 , a diagram is shown illustrating exemplary information flows in a exemplary embodiment of the invention. In this example, the local model for each OBU  121  (not shown in  FIG. 5 ) in each vehicle  120 - 1  through  120 - n  determines a mean, μ i ,  211 , a standard deviation, σ i ,  212  that are communicated from the OBU  121  to a central server (e.g., processing apparatus  300  of  FIG. 3 ). The global model then uses metric  515 , 
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         [0000]    to determine the global standard deviation  216 . The global mean  215  and global standard deviation  216  are sent back to each of the OBUs  121  in the vehicles  120 . 
         [0040]    It is noted that the design shown, e.g., in  FIG. 5  facilitates privacy-preserving information transfer to enable estimation of model parameters for anomaly detection. Additionally, asymptotic convergence of a sum of independent random variables to a Gaussian distribution is guaranteed by the extended CLT (central limit theorem) under the Lyapunov condition. It is also noted that the design shown in  FIG. 5  has an additional messaging cost of only four floating point numbers (approximately 16 bytes) per car, plus some cost for the flag messages. 
         [0041]      FIG. 6  is an example of a single journey metric  275  used to determine possible fraud involving a single journey, and a ranked list  368  of system abuse scores  450  and their associated unique identifiers  630 . In this example, the unique identifiers  630  are determined using a numeric identifier  610  and an alphabetic identifier  620 . However, these are examples and any identification can be used that uniquely identifies the OBU  121  (and therefore an associated user). The single journey metric  275  is the following: Φ (μ,σ)   −1 (max x ij ), where Φ (μ,σ)   −1 (•) is an inverse normal cumulative distribution function (cdf), max is a maximum function, the mean, μ, is the a global mean  215 , and the standard deviation, σ, is the global standard deviation  216 . As shown, this metric  275  is for all of the OBUs  121 , although a single OBU  121  uses the same metric  275 , over max x j . The x ji  is a distance difference for journey j of device i. 
         [0042]    The system abuse scores  450  are, in this example, ranked in terms of probability, that is, likelihood of system abuse, with values of scores arranged as follows: S 1 &gt;S 2 &gt; . . . &gt;S 18 . It is noted that each OBU  121  calculates the single journey metric  275  to determine a system abuse score  450  and can report each system abuse score  450  (or report scores based on some periodicity) or can report those scores  450  above a threshold. 
         [0043]    Referring now to  FIG. 7 , a graph is shown of an example of a distance difference distribution of distance values and an outlier value  710  indicating possible fraud in a single journey. The distance difference distribution shown is from a single OBU  121  with the unique identifier  630  of NX37. The graph shows the percentage of distances between ending points of previous journeys and starting points of consecutive journeys and the kilometers (kms) of the distances. In theory, the vast majority of these distances should be small, although there will be some normal variability. The outlier value  710  is beyond a threshold  721 , which corresponds to the single journey value threshold, T SJV ,  221 . The threshold  221  is in the same “score” domain as the output of the metric  275 , but an equivalent threshold  721  in the kilometer domain may also be calculated and is shown here for ease of reference. The OBU  121  that creates such a distance difference distribution will report the score calculated using the metric  275  to a central server (e.g., back office processing apparatus  300 ), e.g., such as through the exemplary flag message  720 , representing the information “score=X” or “single journey metric score=X”. The score may also be transmitted only if greater than the single journey value threshold, T SJV ,  221 . 
         [0044]      FIG. 8  is an example of a multiple journey metric  280  used to determine possible fraud involving multiple journeys, and a ranked list  368  of system abuse scores  450  and their associated unique identifiers  730 . In this example, the unique identifiers  730  are determined using a numeric identifier  710  and an alphabetic identifier  720 . However, these are examples and any identification can be used that uniquely identifies the OBU  121  (and therefore an associated user). The multiple journeys metric  280  is the following: Π k=1   4 Φ (μ,σ)   −1 (P k (X i )), where Π k=1   4 (•) is a product function. There are 5 journeys, so four distance differences. The 4 (four) can therefore be a K, a number of distance differences (that is, the number of x j ) for device i. The system abuse scores  450  are, in this example, ranked in terms of probability, that is, likelihood of system abuse, with values of scores arranged as follows: S 1 &gt;S 2 &gt; . . . &gt;S 18 . The X i  is a distance difference distribution for journey j of device i. It is noted that each OBU  121  calculates the multiple journeys metric  280  to determine a system abuse score  450  and reports those scores above a threshold or reports all scores (e.g., based on some periodicity). 
         [0045]      FIG. 9  is a graph of an example of a distance difference distribution of distance values and a set of outlier values indicating possible fraud. The distance difference distribution shown is from a single OBU  121  with the unique identifier  730  of NX54. The graph shows the percentage of distances between ending points of previous journeys and starting points of consecutive journeys and the kilometers (kms) of the distances. As described above, the vast majority of these distances should be small, although there will be some normal variability. The outlier values  910  (including the 25 percent at about 5 kms and the 10 percent at about 10 kms) are beyond the threshold  922 , which is related to and can be determined from the multiple journeys threshold, T MJV ,  222 . If the threshold  222  is being used, the OBU  121  that creates such a distance difference distribution will report this anomaly to a central server (e.g., back office processing apparatus  300 ). Such reporting includes in this example an exemplary flag message  920 , representing the information “Score=Y” or “multiple journeys metric score=Y”. As another example, the OBU  121  can send any score determined from the multiple journey metric  280  (e.g., on a periodic basis). 
         [0046]    Turning now to  FIG. 10 , a block diagram is shown of actions performed by an OBU  121  (e.g., as programmed by the instructions in the anomaly detection engine  271 ) or other digital processing apparatus in accordance with an exemplary embodiment of the invention. The method begins in block  10 A, and in block  10 B, the OBU  121  receives the global mean  215  and global standard deviation  216 . In block  10 C, it is determined if there is a new journey. If not (block  10 C=NO), the method continues in block  10 B. If there is a new journey (block  10 C=YES), the OBU determines a new starting point for the current journey, SP j  in block  10 D. In block  10 E, the OBU determines a distance, D j , using the current starting point, SP j , and the ending point, EP j−1 , of the previous journey. 
         [0047]    In block  10 F, the OBU determines a new mean  211  and a new standard deviation  212  using the current distance, D j , and previous distances, D j−1  through D 1 . In block  10 G, a single journey value (SJV) (e.g., a score) is calculated using the single journey metric  275 . In block  10 H, a multiple journeys value (MJV) (e.g., a score) is calculated using the multiple journeys metric  280 . If the SJV is greater than the single journey value threshold, T SJV ,  221  or the MJV is greater than the multiple journeys threshold, T MJV ,  222  (block  10 I=YES), then a flag message is sent in block  10 J. The flag message could include one or both scores of the SJV or MJV. If not (block  10 I=NO) a message is sent with the mean  211  and standard deviation  212  in block  10 K. Note that the mean  211  and standard deviation  212  might only be sent at particular times with particular periodicity. 
         [0048]    In another example, in block  10 I, the OBU  121  can determine whether it is time to send a score in a flag message. If so (block  10 I=YES), a flag message is sent in block  10 J. If not (block  10 I=NO), then the method proceeds to block  10 K. In this example, no SJV or MJV threshold is used. Also, the highest score between the two metrics  275 ,  280  or both scores could be sent. 
         [0049]    Referring now to  FIG. 11 , a block diagram is shown of actions primarily performed by a back office processing apparatus  300  (or some other central server or other digital processing apparatus) in accordance with an exemplary embodiment of the invention. The method starts in block  11 A, and in block  11 B, the apparatus  300  receives the means  211 - 1  through  211 - n  and receives the standard deviations  212 - 1  through  212 - n  from the n OBUs  121 . In block  11 C, the apparatus  300  calculates a global mean  215 , and in block  11 D the apparatus  300  calculates a global standard deviation  216 . In block  11 E, the apparatus  300  communicates the global mean  215  and the global standard deviation  216  to the OBUs  121 . 
         [0050]    In block  11 F, it is determined if the any flag messages  220  have been received. If a certain number of flag messages  220  have not been received (block  11 F=NO), processing continues in block  11 B. If a certain number of flag messages  220  have been received (block  11 F=YES), then one or more ranked lists  368  are determined in block  11 G. It should be noted that in block  11 F, the messages may include scores from all vehicles or only those vehicles whose scores meet the thresholds described above. If the messages are from all vehicles, in block  11 G, the apparatus  300  may create ranked list(s) having less than the number of vehicles. For example, the highest  100  scores may be output. Further, the scores may be mixed from each of the metrics  275 ,  280 . In other words, one ranked list could include scores from metric  275  and one ranked list could include scores from metric  280 , or a single ranked lists could include scores from both metrics  275 ,  280 . In block  11 H, the ranked lists  368  are output (or at least unique identifications are output) for enforcement. In block  11 I, enforcement is performed. It is noted that block  11 I will usually be performed by personnel at the back office  170 . However, enforcement might be performed via, e.g., automatic generation of a fine and associated letter. 
         [0051]    It should also be noted that the methods shown in  FIG. 11  might be performed by different digital processing apparatus. For instance, blocks  11 B,  11 C, and  11 D may be performed by a first computer system and blocks  11 F,  11 G, and  11 H performed by a second computer system. In this example, block  11 E is split into blocks  11 J and  11 K. In block  11 J, the first computer system communicates the global mean  215  and global standard deviation  216  another entity (e.g., the second computer system in this example). The entity then transmits the global mean  215  and global standard deviation  216  to one or more of the OBUs. 
         [0052]    Although primary emphasis herein has been placed on mean and standard deviation, other statistical measures such as median, mode, kurtosis may be used. 
         [0053]    As should be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon executable, e.g., by a digital processing apparatus. 
         [0054]    Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device, such as the digital processing apparatus shown, e.g., in  FIGS. 2 and 3 . 
         [0055]    A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device such as the digital processing apparatus shown, e.g., in  FIGS. 2 and 3 . 
         [0056]    Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. 
         [0057]    Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, or the like and conventional procedural programming languages, such as the “C” programming language or assembly language or similar programming languages. Such computer program code may also include code for field-programmable gate arrays, such as VHDL (Very-high-speed integrated circuit Hardware Description Language). 
         [0058]    Aspects of the present invention are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
         [0059]    These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
         [0060]    The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. 
         [0061]    The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. 
         [0062]    The foregoing description has provided by way of exemplary and non-limiting examples a full and informative description of the best techniques presently contemplated by the inventors for carrying out embodiments of the invention. However, various modifications and adaptations may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings and the appended claims. All such and similar modifications of the teachings of this invention will still fall within the scope of this invention. 
         [0063]    Furthermore, some of the features of exemplary embodiments of this invention could be used to advantage without the corresponding use of other features. As such, the foregoing description should be considered as merely illustrative of the principles of embodiments of the present invention, and not in limitation thereof.