Patent Publication Number: US-11663909-B1

Title: Traffic jam avoidance system that assigns vehicles to lanes based on driver comfort levels

Description:
BACKGROUND OF THE INVENTION 
     Field of the Invention 
     One or more embodiments of the invention are related to the field of traffic control systems for vehicles on roadways. More particularly, but not by way of limitation, one or more embodiments of the invention enable a traffic jam avoidance system that assigns vehicles to lanes based on driver comfort levels. 
     Description of the Related Art 
     Freeway congestion is a serious and increasing problem with enormous costs to society and to drivers. Because of the limitations and errors of human drivers, today&#39;s traffic configurations tend to break down under elevated traffic loads resulting in excessively long travel times. Existing traffic management solutions such as carpool lanes and traffic metering have had relatively limited effect on congestion. Moreover, these existing solutions do not take advantage of the capabilities of modern vehicles, which are generally equipped with multiple sensors and control systems. There are no known systems that obtain data from vehicles to characterize the behavior of individual drivers, and that then use that data to manage the flow of traffic on roadways. 
     For at least the limitations described above there is a need for a traffic jam avoidance system that assigns vehicles to lanes based on driver comfort levels. 
     BRIEF SUMMARY OF THE INVENTION 
     One or more embodiments described in the specification are related to a traffic jam avoidance system that assigns vehicles to lanes based on driver comfort levels. Embodiments of the invention may calculate a driver comfort level (DCL) factor for a vehicle based on data measured by the vehicle&#39;s sensors, and may guide the vehicle to a specific lane that is appropriate for that vehicle&#39;s measured DCL. 
     One or more embodiments of the invention may include one or more processors that are coupled via a network to multiple vehicles. Each vehicle may have a velocity sensor that measures the vehicle&#39;s velocity, a distance sensor that measures the following distance between the vehicle and another vehicle immediately in front of it, and a navigation system that provides navigation messages to the vehicle. The processors may collect sample data pairs from each vehicle while the vehicle is moving on one or more roadways, where a sample data pair includes the vehicle&#39;s velocity and the vehicle&#39;s following distance. They may calculate a driver comfort level for each vehicle from the sample data pairs, and store the driver comfort level for each vehicle in a memory. The processors may manage lane assignments on a multi-lane road based on the driver comfort levels. Managing lane assignments may include assigning a driver comfort level range to two or more lanes of the multi-lane road, where the driver comfort level ranges of different lanes do not overlap. For each vehicle moving on this multi-lane road, the processors may retrieve the driver comfort level associated with the vehicle from the memory, select an assigned lane with an associated driver comfort level range that contains the vehicle&#39;s driver comfort level, and transmit a message to the vehicle&#39;s navigation system instructing the vehicle to drive in the assigned lane. 
     In one or more embodiments, calculation of a vehicle&#39;s driver comfort level may include selecting at least one sample data pair that represents a minimum following distance at a maximum velocity, calculating vehicle spacing for the selected sample data pairs as the following distance plus a vehicle length, and calculating the driver comfort level as the square of the velocity divided by the vehicle spacing. 
     In one or more embodiments higher driver comfort level ranges may be assigned to lanes closer to the center of a multi-lane road. 
     In one or more embodiments the processors may also assign a lane velocity to two or more lanes of a multi-lane road. In one or more embodiments a higher velocity may be assigned to lanes with higher DCL ranges. In one or more embodiments the processors may send a second message to the navigation system of each vehicle instructing it to drive at the lane velocity associated with its assigned lane. 
     In one or more embodiments the vehicles may also have a cruise control system. The cruise control system may receive a target driver comfort level from the processor(s). It may obtain the vehicle&#39;s velocity from the velocity sensor, obtain the following distance from the distance sensor, calculate vehicle spacing as the sum of the following distance and a vehicle length, calculate an actual driver comfort level as the ratio of the velocity squared to the vehicle spacing, and adjust the vehicle velocity to maintain the actual driver comfort level with a range near the target driver comfort level. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The above and other aspects, features and advantages of the invention will be more apparent from the following more particular description thereof, presented in conjunction with the following drawings wherein: 
         FIG.  1    shows an observed relationship between the velocity of a vehicle and the spacing the driver tries to maintain between his vehicle and the vehicle in front; while this relationship is generally quadratic for most drivers, drivers differ in their driver comfort levels (DCLs), which determine how much space is desired at each velocity. 
         FIG.  2    shows how mixing vehicles with different DCLs on the same lane can lead to traffic jams, for example when high-DCL drivers try to occupy the space in front of a low-DCL driver. 
         FIG.  3    shows how one or more embodiments of the invention prevent the situation of  FIG.  2    by assigning specific non-overlapping DCL ranges to each lane. 
         FIG.  4    illustrates the relationship between lane throughput and DCL, and it shows that lane throughputs can be equalized across lanes if vehicles on higher-DCL lanes travel at higher velocities. 
         FIG.  5    shows an extension of the embodiment of  FIG.  3    that assigns lane velocities in addition to lane DCL ranges. 
         FIG.  6    illustrates communication between a processor (or collection of processors) and sensor and control systems in a vehicle; the processor obtains sample pairs of vehicle velocities and following distances from the vehicle&#39;s speed and distance sensors, respectively. 
         FIG.  7    shows how vehicle following distance may be converted to inter-vehicle spacing (measured for example between vehicle centers) in one or more embodiments of the invention. 
         FIG.  8    shows illustrative steps that may be performed to calculate a vehicle DCL from the velocity and distance sample pairs of  FIG.  6   . 
         FIG.  9    illustrates how a processor may transmit messages to the navigation system of a vehicle to move the vehicle to its assigned lane based on its DCL, and potentially to also set the vehicle&#39;s target velocity based on the assigned lane. 
         FIG.  10    shows how one or more embodiments of the invention may interact with a vehicle&#39;s cruise control system to set a target DCL for the vehicle. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     A traffic jam avoidance system that assigns vehicles to lanes based on driver comfort levels will now be described. In the following exemplary description, numerous specific details are set forth in order to provide a more thorough understanding of embodiments of the invention. It will be apparent, however, to an artisan of ordinary skill that the present invention may be practiced without incorporating all aspects of the specific details described herein. In other instances, specific features, quantities, or measurements well known to those of ordinary skill in the art have not been described in detail so as not to obscure the invention. Readers should note that although examples of the invention are set forth herein, the claims, and the full scope of any equivalents, are what define the metes and bounds of the invention. 
     The dynamics of freeway traffic and the conditions that lead to traffic jams are greatly affected by the relationships between vehicle velocities and the inter-vehicle spacing that drivers attempt to maintain at different speeds. Most drivers realize that braking distance increases as vehicle velocity increases, and they increase their following distances accordingly at higher speeds. Empirically many drivers display a quadratic relationship between the velocity of their vehicle and the spacing between their vehicle and the next vehicle ahead of them on a freeway, as shown in  FIG.  1   . This quadratic relationship, where spacing is proportional to the square of the vehicle velocity, may reflect drivers&#39; intuitive understanding that the vehicle&#39;s kinetic energy increases with the square of its velocity, and that the braking distance needed to bring the vehicle to a stop is therefore also proportional to the square of the velocity. However, drivers differ substantially in how conservative they are in setting their following distances to the vehicle immediately ahead of them. A driver&#39;s desired following distance may be based on vehicle technical characteristics such as the vehicle&#39;s weight and braking force, and on whether the vehicle has automated assistance to detect a slowdown of the vehicle ahead and automatically apply braking. It may also be based on the driver&#39;s knowledge of the vehicle&#39;s capabilities; for example, some drivers may be unaware of the vehicle&#39;s automated assistance features and may therefore set following distances higher than the distances that are technically necessary. 
     In this application we use the term “driver comfort level” (DCL) to represent a general relationship between vehicle velocity and inter-vehicle spacing for an individual driver. An illustrative DCL may be defined for example as: DCL=(Vehicle Velocity) 2 /(Inter-vehicle Spacing). For a driver that follows a quadratic relationship between spacing and velocity, the spacing at a given velocity is therefore: Inter-vehicle Spacing=(1/DCL)*(Vehicle Velocity) 2 . This illustrative DCL is therefore the inverse of the proportionality factor between squared velocity and spacing. A driver with a higher DCL is comfortable with a smaller inter-vehicle spacing at any given velocity than is a driver with a lower DCL. The DCL factor represents the combined effects of automotive hardware technology, software technology in the form of electronic assistance, and the individual driver&#39;s awareness of these technologies, including his/her perception of the safety provided by the technologies. The specific formula for driver DCL given above is illustrative; any definition of DCL that measures how comfortable a specific driver is with smaller inter-vehicle spacing as a function of velocity is in keeping with the spirit of the invention. 
       FIG.  1    shows graph  100  with three illustrative curves  115 ,  130 , and  145  for three illustrative drivers with DCLs of 15, 30, and 45, respectively, where these DCLs are measured in units of mph 2 /ft. (One or more embodiments may measure and use DCL values in any desired units.) Each curve shows the desired spacing  101  for the driver between the driver&#39;s vehicle and the vehicle immediately ahead, as a function of the vehicle&#39;s velocity  102 . Drivers with higher DCLs require less spacing at a given velocity; for example, at a velocity of 50 mph, a driver with a DCL of 45 requires an inter-vehicle spacing of 56 feet, while a driver with a DCL of 15 requires an inter-vehicle spacing of 167 feet. For all drivers, regardless of their DCL, spacing increases with the square of the velocity. 
     The inventor&#39;s analysis of traffic flow and traffic jams indicates that mixing drivers with substantially different DCLs on the same traffic lane can create conditions that lead to traffic jams. An example scenario illustrating this problem is shown in  FIG.  2   . A two-lane highway  200  has a mix of high-DCL vehicles (shown as white rectangles) and low-DCL vehicles (shown as black rectangles) (refer to legend  230 ). Initially in the snapshot shown at the top of  FIG.  2   , a high DCL vehicle  201  in lane 1 is followed by three low DCL vehicles  210 ,  211 , and  212 . Vehicle  210  establishes a large following distance  220  between it and vehicle  201 , consistent with the low DCL of this vehicle. In adjacent lane 2, two high DCL vehicles  202  and  203  are following closely behind another vehicle. These vehicles  202  and  203  observe the large gap  220  in lane 1, and because they are high-DCL vehicles, they are comfortable moving from lane 2 into lane 1 to occupy this gap. The snapshot shown at the bottom of  FIG.  2    shows the consequences of vehicles  202  and  203  moving into this gap in lane 1. Low-DCL vehicle  210  is not comfortable with the reduced following distance  221  when vehicles  202  and  203  occupy gap  220 , and therefore vehicle  210  brakes heavily to decelerate to increase its following distance. This sudden deceleration of vehicle  210  then reduces the gap between vehicle  210  and vehicle  211 , which causes vehicle  211  to decelerate; this in turn causes vehicle  212  to decelerate. This chain reaction may continue and may lead to the formation of a traffic jam  222 . The traffic flow that was stable in the top snapshot has now become unstable due to the movement of a high-DCL vehicle into a gap in front of a low-DCL vehicle. 
     The inventor has discovered that a solution to the traffic jam formation situation illustrated in  FIG.  2    is to prevent or reduce mixing of vehicles with substantially different DCLs in the same lane. When lanes contain exclusively or primarily vehicles with similar DCLs, traffic flow stability is improved, and the likelihood of traffic jams is greatly reduced.  FIG.  3    illustrates this approach for a 4-lane highway  300 . This highway has 4 lanes in each direction (with only the lanes of one direction shown in  FIG.  3   ). Embodiments of the invention may be used with any multi-lane roadway of any type, and with roadways having any number of lanes. A processor (or any collection of processors)  320  may perform an assignment  321  of DCL ranges to some or all of the lanes of highway  300 . To prevent the type of traffic jam formation scenario illustrated in  FIG.  2   , the DCL ranges assigned to different lanes may be non-overlapping, so that each DCL value is assigned only one lane.  FIG.  3    shows illustrative DCL ranges  310  for lanes 1 through 3 of highway  300 . (Lanes are numbered starting from the center of the road closest to the median.) In this example, range  311  containing the highest DCL vehicles is assigned to lane 1 (closest to the center), range  312  with moderate DCL vehicles is assigned to lane 2, and range  313  with the lowest DCL vehicles is assigned to lane 3. In this example, lane 4 is unmanaged by processor  320 , so lane 4 may contain a mix of vehicles with different DCLs; for example, vehicles whose DCL has not been measured may drive in lane 4, and lane 4 may also be used for vehicles entering and exiting the highway. In one or more embodiments of the invention any subset of the lanes of a roadway may have DCL ranges assigned, and any number of other lanes may be unmanaged. As in  FIG.  3   , in one or more embodiments the DCL ranges for lanes closer to the center (such as lane 1) may be higher than the DCL ranges for lanes further from the center (such as lane 3). The DCL ranges  310  are illustrative; in one or more embodiments of the invention any DCL ranges may be assigned to any lanes. 
     Processor or processors  320  may perform any type of analyses to determine the DCL ranges  310  assigned to the lanes of the highway. For example, the ranges assigned to each lane may be based on the distribution of vehicle DCL values on the freeway, and on traffic conditions at any point in time. DCL ranges assigned to lanes may change over time as traffic conditions change. 
     In one or more embodiments of the invention, processor  320  may also assign target velocities to each managed lane of a roadway. Traffic flow may be improved if all vehicles in a lane move at approximately the same velocity, for example. However, different lanes may have different target velocities. In one or more embodiments, lanes with higher DCLs may for example be assigned higher velocities. This approach may have two potential benefits. First, the prospect of traveling at a higher velocity (thereby shortening travel time) may encourage drivers to increase their DCL. Second, assigning higher velocities to higher DCL lanes may equalize traffic throughput across lanes, as shown in  FIG.  4   . As illustrated in  FIG.  4   , the spacing  402  between vehicles on a lane equals the square of velocity  401  divided by the DCL of vehicles on the lane (which may be an average across the assigned DCL range for the lane, for example). The density  403  of vehicles in the lane is the inverse of the spacing  402  (rescaled by factor  5280  to express density in vehicles per mile.) Lane throughput  404  is the product of lane velocity  401  and vehicle density  403 , and is therefore proportional to DCL/V. This expression implies that the vehicle throughput of different lanes will be equal if vehicle velocities on each lane are proportional to the DCL assigned to the lane. 
     In an illustrative embodiment shown in  FIG.  5   , processor  320  performs both DCL assignment  321  and velocity assignment  501  for lanes 1 through 3 of highway  300 . For simplicity of exposition, the DCL  310  assigned to each lane is shown as a single value; in practice the DCL for a lane may be a range of values. In this example the velocity  502  assigned to each lane is proportional to the DCL, as described above with respect to  FIG.  4   ; therefore lane 1 contains vehicles with the highest DCLs, and these vehicles travel at the highest velocities. Throughput  503  is equalized across lanes 1 through 3 by assigning velocities proportional to DCLs. In one or more embodiments the processor  320  may assign lane velocities but may not make these velocities strictly proportional to lane DCLs. Embodiments that assign lane velocities may set the velocity of any lane to any value and may assign velocities to any subset of the lanes of a multi-lane roadway. Lanes closer to the center of the roadway (such as lane 1) may be assigned higher velocities in one or more embodiments. 
     We now describe how one or more embodiments of the invention may interact with vehicles to determine a vehicle&#39;s DCL and to accomplish assignment of the vehicle to a specific lane based on its DCL. As illustrated in  FIG.  6   , processor  320  (or one or more processors of a collection of processors) may interact with one or more sensors or control systems in a vehicle  601 . The processor or processors may be connected via one or more network connections to the vehicle subsystems, for example. Network connections may be wireless, wired, or any combination. In one or more embodiments processor  320  may communication for example with onboard vehicle computers that in turn are connected to the various vehicle subsystems. In one or more embodiments a collection of processors  320  may also include processors embedded in one or more vehicles, and some or all of the calculations or actions performed by processors  320  may be performed by in-vehicle processors. Illustrative sensors on vehicle  601  may include a speedometer  603  that measures the vehicle&#39;s velocity  613 , and a distance sensor  602  that measures the following distance  612  between the front of the vehicle and the back of a vehicle  611  immediately in front of vehicle  601  on a roadway. Processor  320  may obtain data captured from these sensors while vehicle  601  is moving on one or more roadways, and it may store sample data pairs with measured velocities  621  and corresponding measured following distances  622  in a database  620 . The velocity and distance data  620  may be used to calculate a vehicle&#39;s DCL, as described below. 
     In one or more embodiments processor  320  may also communicate with a vehicle navigation system  604 . This navigation system may for example have a screen or an audio output that communicates with the driver of the vehicle to provide instructions on where and how to navigate. In one or more embodiments the vehicle may be autonomous or semi-autonomous, and the navigation system may directly control the movement of the vehicle without driver interaction. In one or more embodiments processor  320  may also communication a vehicle cruise control system  605  that may for example interact with the vehicle&#39;s engine  606  and brakes  607  to maintain the speed of the vehicle at a setpoint value. 
       FIG.  7    and  FIG.  8    illustrate a method that may be used in one or more embodiments to calculate a vehicle&#39;s DCL from sample velocity and following distance data  620 . As shown in  FIG.  7   , in one or more embodiments the following distance information captured from the vehicle sensor(s) may first be converted into inter-vehicle spacing data. The spacing  701  between vehicles  601  and  611  may be defined for example as the distance between vehicle centers  601   c  and  611   c . The inter-vehicle spacing  701  equals the following distance  612  plus the offsets  702   a  and  702   b  between the ends of the vehicles and the centers of the vehicles. For uniform vehicle lengths, the sum of these offsets equals the length of the vehicle. Therefore, in one or more embodiments the inter-vehicle spacing may be derived from the following distance by adding a vehicle length (either an actual length or an estimated average vehicle length) to the following distance. 
       FIG.  8    shows illustrative steps that may be used by processor or processors  320  in one or more embodiments to perform calculation  800  of a DCL for each vehicle for which velocity and distance data has been captured. In one or more embodiments the DCL calculations may be performed by multiple processors, including for example by processors integrated into some or all of the vehicles. Step  801  of collecting sample data pairs  620  with velocity and following distance is described above with respect to  FIG.  6   . A vehicle&#39;s DCL or a range of DCLs may be calculated using this data  620 . In one or more embodiments the primary focus of the traffic jam avoidance system may be the vehicle&#39;s best (highest) DCL at high speeds. Therefore, a selection  802  may be performed to select a subset  812  of velocity/distance sample pairs that correspond to high velocities and low distances. This selection may be based on any desired criteria. For example, sample data pairs may be selected with velocity higher than some threshold and following distance below some threshold. In one or more embodiments the samples with maximum velocities (or with a range of the maximum velocities) may be selected, and then a further subset may be selected from those samples with the smallest following distances. In the example shown in  FIG.  8   , two sample data pairs  812  are selected from data  620 . Step  803  then converts following distance data to inter-vehicle spacing, as described with respect to  FIG.  7   , resulting in velocity and spacing data pairs  813 . Step  804  then calculates the DCL as a ratio of squared velocity to spacing for each of the selected velocity/spacing pairs, resulting in a set of one or more DCL values  814 . If there are multiple values in DCL data  814 , step  805  may aggregate the DCL values into a single DCL estimate  815  for the vehicle. Aggregation may for example use an average, a median, a maximum, or any other function applied to data  814 . In step  820 , processor  320  may store the vehicle&#39;s calculated DCL in a memory  821 , along with an identifier of the vehicle. Memory  821  may be a database coupled to the processor, or it may be distributed within each vehicle, where each vehicle stores its own associated DCL. 
       FIG.  9    illustrates how one or more embodiments may use the DCLs calculated for each vehicle to implement the assignment of vehicles to lanes based on DCL values. As described above with respect to  FIG.  3    and  FIG.  5   , lanes 1 to 3 of freeway  300  are assigned DCL ranges and may also potentially be assigned target velocities in one or more embodiments. Processor  320  (which may the same processor as the processor that calculates DCLs and assigns lane DCLs, or it may be one or more additional processors that manage roadway traffic) first performs or obtains a detection  901  that a vehicle  601  is entering roadway  300 . This detection may be based for example on location tracking of the vehicle, or may for example occur when a receiver on or near the roadway receives a message from the vehicle. Processor  320  then performs retrieval  902  of the DCL associated with vehicle  601  from the database or other memory  821 . Based on the vehicle&#39;s DCL and on the DCL ranges assigned to one or more lanes of the roadway, the processor then performs assignment  903  of vehicle  601  to a specific lane. To accomplish the lane assignment, processor  320  may for example perform transmission  904  of a message to the navigation system of the vehicle indicating which lane the vehicle should move to. This message may for example be shown on a display  604  of the vehicle&#39;s navigation system, or an audio message may be played for the driver. For an autonomous vehicle the message may direct the vehicle to move to the desired lane. For an embodiment that also assigns target velocities to one or more lanes, processor  320  may also perform assignment  905  of a target velocity to vehicle  601  based on the lane to which the vehicle is assigned. Transmission  906  of a second message to navigation system  604  may inform the vehicle of its assigned target velocity. In one or more embodiments the messages with lane assignment and target velocity may be combined into a single transmission. 
     In one or more embodiments of the invention, the DCL of a vehicle may be input into the vehicle&#39;s cruise control system, and the cruise control system may then modify the vehicle&#39;s velocity to maintain the desired DCL. This feature may be used on either managed roadways where lanes are assigned DCL ranges (as described above) or on unmanaged roadways.  FIG.  10    shows an illustrative example for vehicle  601 , which has a cruise control system  605 . Processor  320  performs step  1001  to transmit the vehicle&#39;s target DCL  1002  to the cruise control system  605 . (In one or more embodiments the vehicle control system may already have access to the vehicle&#39;s target DCL  1002 , and it may directly set the DCL of the cruise control system.) Cruise control system  605  may then execute a feedback control loop to adjust the vehicle&#39;s velocity so that the actual DCL is within a desired range near the target DCL. Illustrative repeated steps of this control loop may include step  1011  to obtain the vehicle&#39;s velocity and following distance from speedometer  603  and distance sensor  602 , step  1012  to calculate the inter-vehicle spacing from the following distance, step  1013  to calculate the vehicle&#39;s actual DCL as the square of the velocity divided by the spacing, step  1014  to calculate the difference between the actual DCL and the target DCL  1002 , and step  1015  to adjust the vehicle&#39;s velocity (by transmitting commands to the engine  606  or brakes  607 ) based on this difference. One or more embodiments may use any desired feedback control algorithm or steps to adjust the vehicle&#39;s velocity based on the target DCL  1002 . 
     While the invention herein disclosed has been described by means of specific embodiments and applications thereof, numerous modifications and variations could be made thereto by those skilled in the art without departing from the scope of the invention set forth in the claims.