Patent Publication Number: US-2016232475-A1

Title: System and method for rating drivers

Description:
This application claims the benefit of U.S. Provisional Patent Application No. 62/114,323, filed Feb. 10, 2015, which is hereby incorporated by reference. 
    
    
     BACKGROUND 
     The present invention relates to determining driver performance based on a score determined from one or more categories. It finds particular application in conjunction with determining driver performance based on a frequency of critical or safety-related events and will be described with particular reference thereto. It will be appreciated, however, that the invention is also amenable to other applications. 
     Driver scoring is a tool for grading performance of vehicle drivers. Such scoring tools are used by administrators of heavy vehicle fleets to identify driver behaviors that are consistent or inconsistent with their company policies. Typically, engine diagnostics data obtained, for example, from an engine control module (ECM) and accelerometers are used to infer driving habits and behaviors of a driver. Conventionally, driver score for a particular driver is determined based on the engine diagnostics data. 
     Difficulty associated with navigating a vehicle (e.g., a heavy vehicle such as a straight truck, an articulated truck, a bus, etc.) along different types of routes varies. For example, it is typically considered more challenging for a driver of a vehicle to navigate a relatively winding and/or narrow road at high speed (e.g., at highway speed) during nighttime as compared with a more leisurely velocity on a straighter, wider road without a lot of traffic during daytime. Because route types and conditions vary, a differentiated scoring based on the route type and conditions such as time of day and other factors is desirable. Conventional driver scoring schemes fail to score a driver based on a difficulty associated with a particular route, type of route, and/or safety-related events associated with the driver. 
     The present invention provides a new and improved apparatus and method for determining a differentiated scoring scheme for particular drivers. 
     SUMMARY 
     In one embodiment, a method for rating drivers includes associating each of a plurality of segments of a route with a respective one of a plurality of segment types. For each of the plurality of drivers, a respective segment type value associated with each of the segment types is identified, a first condition value associated with a first condition is identified, a second condition value associated with a second condition is identified, and a driver score including respective component values based on the segment type values, the first condition value, and the second condition value is identified. The drivers are rated for one of the segments based on the respective multi-component driving scores. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In the accompanying drawings which are incorporated in and constitute a part of the specification, embodiments of the invention are illustrated, which, together with a general description of the invention given above, and the detailed description given below, serve to exemplify the embodiments of this invention. 
         FIG. 1  illustrates a schematic representation of a map including routes and segments of routes from a starting location to an ending location in accordance with one embodiment of an apparatus illustrating principles of the present invention; 
         FIG. 2  illustrates a schematic representation of a system for rating drivers in accordance with one embodiment of an apparatus illustrating principles of the present invention; and 
         FIG. 3  is an exemplary methodology of rating drivers in accordance with one embodiment illustrating principles of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF ILLUSTRATED EMBODIMENT 
     With reference to  FIG. 1 , a map  10  is illustrated of an area  12 . The map  10  displays various roads  14   1 - 14   6  (collectively  14 ) in the area  12 . Some of the roads  14   1,4,5  are designated as relatively lower speed roads (e.g., roads having a speed limit less than or equal to a predetermined threshold speed), while other ones of the roads  14   2,3,6  are designated as relatively higher speed roads (e.g., roads having a speed limit greater than the predetermined threshold speed). In one embodiment, the predetermined threshold speed is 50 miles per hour (mph). However, any other predetermined threshold speed is contemplated in other embodiments. Although all of the roads in the illustrated embodiment are designated as either lower speed roads or higher speed roads, it is to be understood that other embodiments in which additional road designations are used (e.g., four designations including very slow speed roads, low speed roads, medium speed roads, and high speed roads) are also contemplated. 
     For purposes of discussion, the roads  14   1,4,5  designated as the relatively lower speed roads are referred to as city roads, and the roads  14   2,3,6  designated as the relatively higher speed roads are referred to as highway roads. In addition, the map  10  illustrates a first part of the area  12   1  and a second part of the area  12   2 . A first condition is associated with the first part of the area  12   1 , and a second condition is associated with the second part of the area  12   2 . In one embodiment, the first condition is daytime, and the second condition is nighttime. Although the first and second conditions are described as daytime and nighttime, it is to be understood that other conditions (e.g., wet roads vs. dry roads; slippery (e.g., icy) roads vs. not slippery (e.g., not icy) roads, etc.) are also contemplated. Therefore, the city roads  14   1,5  in the first area  12   1  are city roads for daytime driving, the city road  14   4  in the second area  12   2  is a city road for nighttime driving, the highway roads  14   2,3  in the first area  12   1  are highway roads for daytime driving, and the highway road  14   6  in the second area  12   2  is a highway road for nighttime driving. 
     A route  20  is a path along selected ones of the roads  14  from a starting location  22  to an ending location  24 . In the illustrated embodiment, a first route  20   1  includes four (4) segments  30   1,1-4  (collectively  30 ), where the first subscript (e.g., “1”) represents the first route  20   1 , and the second subscript (e.g., “1-4”) represents the segment of the respective route  20 . The four segments  30   1,1-4  of the first route  20   1  include the following four (4) roads: i) a city road  14   1  about five (5) miles in the first area  12   1  (e.g., daytime) (e.g., segment  30   1,1 ), ii) a highway road  14   2  about 12 miles in the first area  12   1  (e.g., daytime) (e.g., segment  30   1,2 ), iii) a highway road  14   3  about 21 miles in the second area  12   2  (e.g., nighttime) (e.g., segment  30   1,3 ), and iv) a city road  14   4  about 14 miles in the second area  12   1  (e.g., nighttime) (e.g., segment  30   1,4 ). A second route  20   2  includes two (2) segments  30   2,1-2  corresponding to two (2) roads: i) a city road  14   5  about 20 miles in the first area  12   1  (e.g., daytime) (e.g., segment  30   2,1 ) and ii) a highway road  14   6  about 18 miles in the second area  12   2  (e.g., nighttime) (e.g., segment  30   2,2 ). 
     For purposes of discussion, it is assumed the speed limit in the city road segments  30   1,1 ,  30   1,4 , and  30   2,1  is 35 mph, and the speed limit in the highway road segments  30   1,2 ,  30   1,3 , and  30   2,2  is 60 mph. Therefore, based on the speed limits and distances of the different segments, the driving time from the starting location  22  to the ending location  24  along the first route  20   1  (i.e., along the segments  30   1,1-4 ) is about 1.1 hours (i.e., (5 miles/35 mph)+(12 miles/60 mph)+(21 miles/60 mph)+(14 miles/35 mph)). The about 1.1 hours time along the first route  20   1  includes about 0.3 hours in the first area  12   1  (e.g., daytime) and about 0.8 hours in the second area  12   2  (e.g., nighttime). The about 1.1 hours time along the first route  20   1  also includes about 0.5 hours on city roads and about 0.6 hours on highway roads. The about 1.1 hours time along the first route  20   1  also includes about 0.1 hours on city roads in the first area  12   1  (e.g., daytime), about 0.2 hours on highway roads in the first area  12   1  (e.g., daytime), about 0.4 hours on city roads in the second area  12   2  (e.g., nighttime), and about 0.4 hours on highway roads in the second area  12   2  (e.g., nighttime). 
     Based on the speed limits and distances of the different segments, the driving time from the starting location  22  to the ending location  24  along the second route  20   2  (i.e., along the segments  30   2,1-2 ) is about 0.9 hours (i.e., (20 miles/35 mph)+(18 miles/60 mph)). The about 0.9 hours time along the second route  20   2  includes about  0 . 6  hours in the first area  12   1  (e.g., daytime) and about 0.3 hours in the second area  12   2  (e.g., nighttime). The about 0.9 hours time along the second route  20   2  also includes about 0.6 hours on city roads and about 0.3 hours on highway roads. The about 0.9 hours time along the second route  20   2  also includes about 0.6 hours on city roads in the first area  12   1  (e.g., daytime), zero (0) hours on highway roads in the first area  12   1  (e.g., daytime), zero (0) hours on city roads in the second area  12   2  (e.g., nighttime), and about 0.3 hours on highway roads in the second area  12   2  (e.g., nighttime). 
     With reference to  FIG. 2 , a simplified component diagram of an exemplary system  40  for rating drivers is illustrated in accordance with one embodiment of the present invention. The system  40  includes an input device  42 , a controller  44  (e.g., computer processor), and an output device  46 . The controller  44  electrically communicates with both the input device  42  and the output device  46 . In the illustrated embodiment, the controller  44  electrically communicates with the input device  42  and the output device  46  via a wired connection. However, other embodiments, in which the controller  44  electrically communicates with at least one of the input device  42  and the output device  46  via a wireless connection (e.g., via a radio frequency (RF) connection), are also contemplated. 
     With reference to  FIG. 3 , an exemplary methodology of the system shown in  FIG. 2  is illustrated. As illustrated, the blocks represent functions, actions and/or events performed therein. It will be appreciated that electronic and software systems involve dynamic and flexible processes such that the illustrated blocks and described sequences can be performed in different sequences. It will also be appreciated by one of ordinary skill in the art that elements embodied as software may be implemented using various programming approaches such as machine language, procedural, object-oriented or artificial intelligence techniques. It will further be appreciated that, if desired and appropriate, some or all of the software can be embodied as part of a device&#39;s operating system. 
     With reference to  FIGS. 1-3 , the controller  44  is adapted to associate each of the segments  30  of the routes  20  with a respective one of a plurality of segment types. In the present example, the segment types include the relatively lower speed roads  14  and the relatively higher speed roads  14 . For purposes of discussion, it is assumed the speed limits discussed above (e.g.,  35  mph for city road segments and  60  mph for highway road segments) are previously programmed into the controller  44 . In a step  110 , the controller receives respective driving scores for each of a plurality of drivers. In one embodiment, the driving scores are received by the controller  44  from the input device  42 . For example, the driving scores are manually entered into the input device  42  by a user or, alternatively, are included on a removable device that is read by the input device  42 . In one embodiment, each of the driving scores is based on a number of safety events per driven mile incurred by the driver while driving in the respective segment types  30  (e.g., driving on city roads and highway roads) and areas  12  (e.g., driving during daytime and nighttime). 
     A 1 st  driver may have a record (e.g., driving history value) of two (2) safety events in 500 miles, or 0.40% (i.e., 2/500), while driving on city roads and a record of one (1) safety event in 750 miles, or 0.13% (i.e., 1/750), while driving on highway roads. The same driver may have record of two (2) safety events in 250 miles, or 0.80% (i.e., 2/250), while driving in the first area  12   1  (i.e., daytime driving) and a record of six (6) safety events in 600 miles, or 1.00% (i.e., 6/600), while driving in the second area  12   2  (i.e., nighttime driving). In addition, the 1 st  driver may have a record of three (3) safety events in 500 miles, or 0.60% (i.e., 3/500) while driving on city roads during the daytime and a record of twelve (12) safety event in 1500 miles, or 0.8% (i.e., 12/1500) while driving on city roads at nighttime. Furthermore, the 1 st  driver may have a record of seven (7) safety events in 1500 miles, or 0.47% (i.e., 7/1500) while driving on highway roads during the daytime and a record of 17 safety event in 3000 miles, or 0.57% (i.e., 17/3000) while driving on highway roads at nighttime. Therefore, the 1 st  driver has the best driving score for driving on the highway during the daytime (i.e., 0.47%) and the worst score of driving on the city at nighttime (i.e., 0.8%). 
     A 2 nd  may have a record (e.g., driving history value) of five (5) safety events in 500 miles, or 1.00% (i.e., 5/500), while driving on city roads and a record of seven (7) safety event in 300 miles, or 2.33% (i.e., 7/300), while driving on highway roads. The same driver may have record of two (2) safety events in 400 miles, or 0.50% (i.e., 2/400), while driving in the first area  12   1  (i.e., daytime driving) and a record of three (3) safety events in 250 miles, or 1.20% (i.e., 3/250), while driving in the second area  12   2  (i.e., nighttime driving). In addition, the 2 nd  driver may have a record of three (3) safety events in 800 miles, or 0.38% (i.e., 3/800) while driving on city roads during the daytime and a record of eleven (11) safety event in 1000 miles, or 1.10% (i.e., 11/1000) while driving on city roads at nighttime. Furthermore, the 2 nd  driver may have a record of seventeen (17) safety event in 1200 miles, or 1.42% (i.e., 17/1200) while driving on highway roads during the daytime and a record of 53 safety event in 3000 miles, or 1.77% (i.e., 53/3000) while driving on highway roads at nighttime. Therefore, the 2 nd  driver has the best driving score for driving in the city during the daytime (i.e.,  0 . 38 %) and the worst score of driving on the highway at nighttime (i.e., 1.77%). 
     The driving history values for driving on the respective segments (e.g., city roads and highway roads) in the respective areas  12  (e.g., during the respective conditions such as daytime and nighttime), such as driving on a city road during the daytime, driving on a city road during the nighttime, driving on a highway road during the daytime, and driving on a highway road during the nighttime, are referred to as combined values or condition-segment values. 
     In a step  112 , for each of the drivers, the controller  44  identifies a respective segment type value associated with each of the segment types. In the example discussed above, the 1 st  driver is identified as having a score of 0.40% on city roads and 0.13% while driving on highway roads. The 2 nd  driver is identified as having a score of 1.00% on city roads and 2.33% while driving on highway roads. Then, in a step  114 , for each of the drivers, the controller  44  identifies a first condition value associated with a first condition and a second condition value associated with a second condition. In the example discussed above, the 1 st  driver is identified as having a score of 0.80% for the first condition (e.g., daytime driving) and 1.00% for the second condition (e.g., nighttime driving). The 2 nd  driver is identified as having a score of 0.50% for the first condition (e.g., daytime driving) and 1.20% for the second condition (e.g., nighttime driving). Then, in a step  116 , the combined values (e.g., condition-segment values) of city driving during the daytime, city driving during the nighttime, highway driving during the daytime, and highway driving during the nighttime, which are also discussed above, are also identified for each of the drivers. 
     In a step  120 , the input device  42  receives input data from, for example, a user. In a step  122 , the input data is transmitted from the input device  42  to the controller  44 . 
     In one example, the input data received by the input device  42  includes the starting location  22  and the ending location  24  and starting date and time. In another example, the input data includes an itinerary including at least one portion. Each of the at least one portions identifies one of the segments  30  and one of a plurality of conditions associated with each of the segments  30 . In one embodiment, the plurality of conditions includes daytime and nighttime. To determine the respective condition associated with each of the segments, the user may either input a starting day and time for the starting location  22  or, alternatively, input the respective condition (e.g., daytime or nighttime) in which the driver will is expected to drive on the segment. 
     Once the controller  44  receives the input data from the input device  42 , if the input data merely includes the starting location  22 , the ending location  24 , and starting date and time (as opposed to an itinerary), the controller  44  determines possible itineraries in a step  124 . Two (2) itineraries are illustrated as the first route  20   1  and the second route  20   2  (see  FIG. 1 ). As discussed above, the about 1.1 hours time along the first route  20   1  includes about 0.1 hours on city roads in the first area  12   1  (e.g., daytime), about 0.2 hours on highway roads in the first area  12   1  (e.g., daytime), about 0.4 hours on city roads in the second area  12   2  (e.g., nighttime), and about 0.4 hours on highway roads in the second area  12   2  (e.g., nighttime). Furthermore, the about 0.9 hours time along the second route  20   2  also includes about 0.6 hours on city roads in the first area  12   1  (e.g., daytime), zero (0) hours on highway roads in the first area  12   1  (e.g., daytime), zero (0) hours on city roads in the second area  12   2  (e.g., nighttime), and about 0.3 hours on highway roads in the second area  12   2  (e.g., nighttime). 
     In a step  126 , for each of the drivers, the controller  44  identifies a respective driver score including respective multi-component values based on the segment type values, the first condition value, and the second condition value for the routes  20  for the respective driver. The segment type values are based on segment driving history values which, in turn, are based on the number of safety event incurred by the driver while driving in the respective segment type, while driving in the first condition, and while driving in the second condition. Therefore, the multi-component values are based on the number of safety event incurred by the driver while driving in the respective segment type in the first condition, and while driving in the respective segment type in the second condition. 
     The driver score for the 1 st  driver on the first route  20   1  is identified as 0.638 (i.e., 0.1/1.1 (ratio of time on city roads in the first area  12   1  e.g., daytime)  30   1,1  to total time of the first route  20   1 )*0.60 (percentage score of 1 st  driver on city roads in the daytime)+0.2/1.1 (ratio of time on highway roads in the first area  12   1  (e.g., daytime)  30   1,2  to total time of the first route  20   1 )*0.47 (percentage score of 1 st  driver on highway roads in the daytime)+0.4/1.1 (ratio of time on city roads in the second area  12   2  (e.g., nighttime)  30   1,3  to total time of the first route  20   1 )*0.80 (percentage score of 1 st  driver on city roads in the nighttime)+0.4/1.1 (ratio of time on highway roads in the second area  12   2  (e.g., nighttime)  30   1,4  to total time of the first route  20   1 )*0.57 (percentage score of 1 st  driver on highway roads in the nighttime). 
     The driver score for the 2 nd  driver on the first route  20   1  is identified as 1.336 (i.e., 0.1/1.1 (ratio of time on city roads in the first area  12   1  (e.g., daytime)  30   1,1  to total time of the first route  20   1 )*0.38 (percentage score of 2 nd  driver on city roads in the daytime)+0.2/1.1 (ratio of time on highway roads in the first area  12   1  (e.g., daytime)  30   1,2  to total time of the first route  20   1 )*1.42 (percentage score of 2 nd  driver on highway roads in the daytime)+0.4/1.1 (ratio of time on city roads in the second area  12   2  (e.g., nighttime)  30   1,3  to total time of the first route  20   1 )*1.10 (percentage score of 2 nd  driver on city roads in the nighttime)+0.4/1.1 (ratio of time on highway roads in the second area  12   2  (e.g., nighttime)  30   1,4  to total time of the first route  20   1 )*1.77 (percentage score of 2 nd  driver on highway roads in the nighttime). 
     Since the 1 st  driver has a lower driver score than the 2 nd  driver based on the respective multi-component values (i.e., 0.638&lt;1.336), the 1 st  driver is identified by the controller  44  in a step  130  as a preferred driver for the first route  20   1 . 
     The driver score for the 1 st  driver on the second route  20   2  is identified as 0.590 (i.e., 0.6/0.9 (ratio of time on city roads in the first area  12   1  (e.g., daytime)  30   2,1  to total time of the second route  20   2 )*0.60 (percentage score of 2 nd  driver on city roads in the daytime)+0.0/0.9 (ratio of time on highway roads in the first area  12   1  (e.g., daytime) to total time of the second route  20   2 )*0.47 (percentage score of 2 nd  driver on highway roads in the daytime)+0.0/0.9 (ratio of time on city roads in the second area  12   2  (e.g., nighttime) to total time of the second route  20   2 )*0.80 (percentage score of 2 nd  driver on city roads in the nighttime)+0.3/0.9 (ratio of time on highway roads in the second area  12   2  (e.g., nighttime)  30   2,2  to total time of the second route  20   2 )*0.57 (percentage score of 1 st  driver on highway roads in the nighttime). 
     The driver score for the 2 nd  driver on the second route  20   2  is identified as 0.843 (i.e., 0.6/0.9 (ratio of time on city roads in the first area  12   1  (e.g., daytime)  30   2,1  to total time of the second route  20   2 )*0.38 (percentage score of 2 nd  driver on city roads in the daytime)+0.0/0.9 (ratio of time on highway roads in the first area  12   1  (e.g., daytime) to total time of the second route  20   2 )*1.42 (percentage score of 2 nd  driver on highway roads in the daytime)+0.0/0.9 (ratio of time on city roads in the second area  12   2  (e.g., nighttime) to total time of the second route  20   2 )*1.10 (percentage score of 2 nd  driver on city roads in the nighttime)+0.3/0.9 (ratio of time on highway roads in the second area  12   2  (e.g., nighttime)  30   2,2  to total time of the second route  20   2 )*1.77 (percentage score of 2 nd  driver on highway roads in the nighttime). 
     Since the 1 st  driver has a lower driver score than the 2 nd  driver based on the respective multi-component values (i.e., 0.590&lt;0.843), the 1 st  driver is identified by the controller  44  in the step  130  as a preferred driver for the second route  20   2 . 
     Furthermore, since the 2 nd  route  20   2  has a lowest driver score than a lowest driver score for the 1 st  route  20   1  based on the respective multi-component values (i.e., 0.590&lt;0.638), the 2 nd  route  20   2  is identified by the controller  44  in the step  130  as a preferred route. The first driver has already been identified as the preferred driver for the second route  20   2 . 
     In addition to identifying which of the drivers is preferable for the routes  20 , the controller  44  optionally identifies, in a step  132 , which of the drivers is preferable along each of the individual segments  30  of the respective routes  20 . For example, although the 1 st  driver is identified as the preferred driver for the first route  20   1 , the 2 nd  driver actually has a lower component value along the first segment  30   1,1  of the first route  20   1 . More specifically, the 1 st  driver is identified as having a component value of 0.55 (i.e., 0.1/1.1 (ratio of time on city roads in the first area  12   1  (e.g., daytime)  30   1,1  to total time of the first route  20   1 )*0.60 (percentage score of 1 st  driver on city roads in the daytime) for the first segment  30   1,1  of the first route  20   1 . The 2 nd  driver is identified as having a component value of 0.035 (i.e., 0.1/1.1 (ratio of time on city roads in the first area  12   1  (e.g., daytime)  30   1,1  to total time of the first route  20   1 )*0.38 (percentage score of 2 nd  driver on city roads in the daytime) for the first segment  30   1,1  of the first route  20   1 . Therefore, since the 2 nd  driver has a lower component score than the 1 st  driver along the first segment  30   1,1  of the first route  20   1  (i.e., 0.035&lt;0.055), the 2 nd  driver is identified as a preferred driver along the first segment  30   1,1  of the first route  20   1 . Consequently, although the controller  44  identifies the 1 st  driver as the preferred driver for the first route  20   1 , the controller  44  also identifies the 2 nd  driver as the preferred driver for first segment  30   1,1  of the first route  20   1 . 
     In another embodiment, it is also contemplated that in order to be identified as a preferred driver for any of the routes  20  and/or segments  30 , each of the respective component values for the segments  30  for a particular driver must be below a predetermined threshold. Therefore, as discussed in the above example, the 1 st  driver was identified as the preferred driver for the first route  20   1 . However, the 1 st  driver had a driver component score of 0.2909 for the segment  30   1,3  (i.e., 0.4/1.1 (ratio of time on city roads in the second area  12   2  (e.g., nighttime)  30   1,3  to total time of the first route  20   1 )*0.80 (percentage score of 1 st  driver on city roads in the nighttime)). If each of the component scores for each of the segments  30   1,1-4  is required to be less than a respective predetermined threshold (e.g., &lt;0.25 for the segment  30   1,3 ) for a driver to be identified as the preferred driver for the first route  20   1 , the 1 st  driver would not be identified as a preferred driver for the first route  20 . In this case, since the component score of the 2 nd  driver for the segment  30   1,3  is also greater than the predetermined threshold (e.g., &lt;0.25 for the segment  30   1,3 ), neither of the drivers would be identified as a preferred driver of the first route  20   1 . Therefore, in this embodiment, another driver would need to be identified for the first route  20   1 . 
     By identifying preferable drivers for the segments  30  and routes  20  in the manner discussed above, the controller  44  acts to rate the drivers for at least one of the segments  30  and at least one of the routes  20  based on the respective multi-component driving scores. In one embodiment, the controller  44  also acts to rank the drivers, in a step  134 , relative to each other for at least one of the segments  30  and at least one of the routes  20  based on the respective multi-component driving scores. 
     In a step  136 , the controller  44  transmits signals to the output device  46  for conveying (e.g., displaying) the respective preferred driver for each of the routes  20  and, optionally, each of the segments  30  via the output device  46 . In one embodiment, the respective ranks of each of the drivers for one or more of the routes  20  and segments  30  the is conveyed via the output device  46 . It is also contemplated that graphical representations of the routes  20  are displayed on the output device  46  in the step  136 . In a step  140 , the respective preferred driver for each of the routes  20  and, optionally, each of the segments  30  and driver rankings are conveyed to the user via the output device  46 . 
     As discussed above, it is to be understood that the controller  44  acts as a means for associating each of a plurality of segments  30  of a route  20  with a respective one of a plurality of segment types. The controller  44  also acts as a means for identifying, for each of the plurality of drivers, a respective segment type value associated with each of the segment types, as a means for identifying the first condition value associated with the first condition, as a means for identifying the second condition value associated with the second condition, and as a means for identifying the driver score including the respective component values based on the segment type values, the first condition value, and the second condition value. The controller  44  also acts as a means for rating the drivers for one of the segments  30  based on the respective multi-component driving scores. 
     In one embodiment, the step  130  of identifying the preferred drivers for the routes assumes the respective number of safety events per driven mile incurred by each of the drivers while driving in the respective segment types at a given time of day, under given weather conditions, with a given truck, etc. is known for each driver on the respective segments  30  on which the driver has driven. Therefore, the expected total number of safety events for each driver on a given route  20  (consisting of a series of segments  30 ) may be computed. The expected number of safety events may be viewed as a cost of assigning a particular driver to a particular route. 
     In a case where there are a plurality of routes and a plurality of possible drivers for the routes, a decision may be made which driver is assigned to which route based on the expected number of safety events each of the drivers has for the particular routes. In other words, the decision as to which driver is assigned to which route is based on the cost of assigning the respective driver to the particular route. The basis for making such a decision may be expressed using a table showing persons/drivers and their jobs/routes  20 . In one embodiment, it is desirable to minimize the total number of expected safety events for the different jobs/routes. Stated differently, it is desirable to minimize the total costs (e.g., safety costs) for the different jobs/routes. 
     Minimizing the total costs of assigning drivers to the different jobs/routes, where only a single driver may be assigned to a particular route, is generally known as an Assignment problem or as optimizing the available drivers for the routes. The Hungarian Method is a classical solution to the Assignment problem. Once the total safety costs for each driver along particular segments  30  of a route  20  are determined (as discussed above), the Hungarian Method may be used for assigning the drivers to the routes  20 . Knowing the total expected costs makes it possible to decide which driver should take which of the routes  20 . In the situation where there are more routes than drivers, it is also possible to determine which routes to do when, perhaps, a single driver could get two (2) routes—one during the day and the other during the night. In another situation where there are more drivers than routes, it is also possible to determine which drivers should not be assigned to a route (based on the high costs for that driver on the routes). 
     In one example, an assignment problem has four (4) drivers available for four different routes. Only one driver can be assigned to any one route. In this example, the step  130  of identifying the preferred drivers for the routes is based on the cost of assigning each driver to each route according to the following table: 
     
       
         
           
               
               
               
            
               
                   
                   
               
               
                   
                 Route 
                   
               
            
           
           
               
               
               
               
               
               
            
               
                   
                 Driver 
                 Route 1 
                 Route 2 
                 Route 3 
                 Route 4 
               
               
                   
                   
               
               
                   
                 Driver A 
                 20 
                 25 
                 22 
                 28 
               
               
                   
                 Driver B 
                 15 
                 18 
                 23 
                 17 
               
               
                   
                 Driver C 
                 19 
                 17 
                 21 
                 24 
               
               
                   
                 Driver D 
                 25 
                 23 
                 24 
                 24 
               
               
                   
                   
               
            
           
         
       
     
     The objective in the step  130  is for the processor  44  to optimize the assignment of drivers to the routes by assigning drivers to routes such that the total cost of assignment is a minimum. In the example illustrated in the table, the total minimum cost is achieved by: 
     
       
         
           
             
               
                 
                   
                     Total 
                      
                     
                         
                     
                      
                     Cost 
                   
                   = 
                   
                     
                       A 
                        
                       
                           
                       
                        
                       1 
                     
                     + 
                     
                       B 
                        
                       
                           
                       
                        
                       4 
                     
                     + 
                     
                       C 
                        
                       
                           
                       
                        
                       2 
                     
                     + 
                     
                       D 
                        
                       
                           
                       
                        
                       3 
                     
                   
                 
               
             
             
               
                 
                   = 
                   
                     20 
                     + 
                     17 
                     + 
                     17 
                     + 
                     24 
                   
                 
               
             
             
               
                 
                   = 
                   78 
                 
               
             
           
         
       
     
     Therefore, in the example of the step  130  illustrated in the table, to achieve the total minimum cost (e.g., the optimized assignment of drivers), Driver A is assigned to Route 1, Driver B is assigned to Route 4, Driver C is assigned to Route 2, and Driver D is assigned to Route 3. It is understood that the Hungarian Method is only one example that may be used for finding the total minimum cost of assigning drivers to routes. 
     It is also contemplated that time plays a significant role in the assignment problem and, in one embodiment, is accounted for in the assignment of the drivers to the routes. For example, the local weather report may make a route&#39;s conditions different. 
     A first route including three (3) segments (e.g., a first dry segment, a second segment expected to be snowy (very slippery) per a weather report, and a third segment expected to be wet (slippery) with melting snow). Without the snowy weather report, all three (3) of the segments may be expected to be dry driving conditions, which would be suitable to a first set of drivers that have lower total safety costs for drier driving conditions. However, with the snowy weather report making the second and third segments slippery, a second set of drivers that have lower total safety costs for driving on more slippery roads may be more suitable for optimizing the assignment of drivers to the routes. Furthermore, the weather and changed travel times (e.g., slower travel time in snowy road conditions) may change the tasks because the conditions are different. For example, because travel may be slower than usual, the final segment may be driven in nighttime conditions, and so the current hours of daylight on a particular day also play a role in assigning drivers to routes. 
     While the present invention has been illustrated by the description of embodiments thereof, and while the embodiments have been described in considerable detail, it is not the intention of the applicants to restrict or in any way limit the scope of the appended claims to such detail. Additional advantages and modifications will readily appear to those skilled in the art. Therefore, the invention, in its broader aspects, is not limited to the specific details, the representative apparatus, and illustrative examples shown and described. Accordingly, departures may be made from such details without departing from the spirit or scope of the applicant&#39;s general inventive concept.