Abstract:
The automated lane management assist method, data structure and system receive unprocessed lane-specific limited-access highway information, including lane use and speed limits, from traffic detectors in the roadway or from other sources, process and develop processed and/or processed predicted information from these sources and calculate the travel time savings in adjacent lanes using the threshold value for time savings set by the driver, thus improving (decreasing) the overall travel time by assisting the driver or the automated vehicle in the selection of driving lanes and target speeds for vehicles, including in partially and fully automated vehicles.

Description:
CROSS REFERENCE OF RELATED APPLICATIONS 
       [0001]    This patent application is a nonprovisional patent application of and claims priority from the provisional patent application Ser. No. 62/342,532 filed on May 27, 2016, and this patent application also claims the benefit of the provisional patent application Ser. No. 62/333,352 filed on May 9, 2016 and the nonprovisional patent application Ser. No. 15/288,333 claiming priority to the provisional patent application Ser. No. 62/333,352, both titled Prediction for Lane Guidance Assist (ALMAPR), all of which applications are hereby incorporated by reference in their entirety. 
     
    
     FIELD OF THE INVENTION 
       [0002]    This invention was not made pursuant to any federally-sponsored research and/or development. 
         [0003]    This patent application extends the usefulness of the following prior patents, specifically U.S. Pat. No. 9,053,636, titled Management Center Module for Advanced Lane Management Assist for Automated Vehicles and conventionally Driven Vehicles (“ALMAMC”) and U.S. Pat. No. 9,286,800, titled Guidance Assist Vehicle Module (“ALMAVM”). The disclosures of these patents are hereby incorporated by reference in their entirety. 
       BACKGROUND 
       [0004]    The above-identified patents and applications describe a methodology (ALMA) for using traffic management center (TMC) information to select a most appropriate freeway lane for a driver or automated vehicle and to provide a target speed for that lane. TMC information is based on roadway sensors or is derived from vehicle transmissions. Lane speed information and traffic incident information may also originate from vehicle based information sources which is collected and processed at a central site. The TMC traffic condition information, is essentially current information on traffic speed and other variables for each through traffic lane. The information is organized according to a data structure described in in the ALMAMC patent that considers the physical and functional features of the information. The ALMAPR patent application provides predicted information for certain traffic variables in place of current information, thereby improving its timeliness. Current and/or predicted information is transmitted to the vehicle where it is further processed (ALMAVM). This additional processing develops guidance for the most appropriate lane and target speed by looking at traffic speeds for several miles ahead (downstream) of the vehicle&#39;s current position. 
         [0005]    In ALMAVM, the vehicle operator&#39;s driving preferences (including driver aggressiveness) strongly influence the choice of lanes. While accounting for roadway and traffic conditions, guidance is provided to the vehicle operator or to the automated vehicle in accordance with the operator&#39;s preferences. Because conditions for several miles downstream of the vehicle are now considered, the decision on lane choice and target speed is improved from the traditional driver&#39;s observations or the connected or automated vehicle&#39;s choice based on the environment in close proximity to the vehicle. One major feature of these patents is to inhibit many lane changes that would be made without this assistance, thereby improving safety and driver comfort. 
         [0006]    As does the ALMAVM patent, the current patent application (ALMATR) also provides lane guidance to the manually operated, automated and connected vehicles. Rather than emphasizing driving preferences as does ALMAVM, ALMATR suggests lane changes only when the lane change results in meaningful travel time savings. By avoidance of lane changes that do not satisfy this criterion, in addition to the economies resulting from time savings, crashes are reduced and the accelerations and decelerations resulting from unnecessary lane changes are avoided, thus saving fuel. As lane selection guidance is more highly focused on safety and economy of operation in ALMATR, it is expected that commercial vehicles will be the primary beneficiaries of these improvements. 
         [0007]    As an example of the operation and benefits to be achieved by ALMATR, the following describes the analysis of data collected on Mar. 23, 2016 by the California Department of Transportation Performance Measurement System (PeMS) for I-880 in Fremont, Calif. PeMS data show that trucks almost exclusively drive in the lane adjacent to the right shoulder (Lane  4 ) and the lane just to its left (Lane  3 ).  FIG. 1  shows the lane speeds averaged over a four mile section of roadway for five minute data samples. The speed for Lane  3  is faster than the speed for lane  4  by varying amounts. Other roadway sections show Lane  4  to be faster for some time periods. The speed difference between the lanes shows considerable variation.  FIG. 2  shows a plot of the lane travel times and the differences in travel time between Lanes  3  and  4 . As shown in  FIG. 3 , a significant difference for this four mile section may, for example, be considered to be one minute  103 . 
         [0008]    It is generally expected that when the speed difference between lanes exceeds a particular value (THR)  104 , many motorists perceiving this from their local vantage will be induced to change lanes. The same may be true of automated vehicles if they base their decisions on the local environment.  FIG. 3  shows a plot of the travel time difference vs the speed difference for the five minute periods for the section analyzed. This example shows that when the speed differences exceed an assumed absolute value of THR of 4 MPH), the five minute periods may be divided into two groups. One of these groups (enclosed by the solid rectangle  101 ) results in significant time savings while the other group (enclosed by the dashed rectangle  102 ) may result in non-productive lane changes. ALMATR provides appropriate guidance to the motorist or automated vehicle to select the appropriate group. 
         [0009]      FIG. 4  shows the interrelationship of the ALMA family modules. The modules above the dashed line  201  are provided by the ALMA Management Center and provide same information to all of the vehicles in the region, while those below the dashed line  201  may be located in the vehicle and provide information to that vehicle. The principal functions of the modules are described in  FIG. 4 . 
       SUMMARY OF THE INVENTION 
       [0010]    The ALMATR module  204  accepts information on lane status and current traffic conditions from ALMAMC  202 . It may also accept predicted traffic conditions from ALMAPR  203 . It computes the travel time difference between candidate adjacent lanes for the desired look ahead distance. When this difference exceeds a threshold prescribed by the vehicle&#39;s operator (RTD), the operator or automated vehicle is notified of the recommended lane. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0011]    The features, aspects and advantages of the novel Lane Guidance Assistance for Efficient Operation will become further understood with reference to the following description and accompanying drawings where 
           [0012]      FIG. 1  shows an example of lane speed and lane speed differences for a four-mile section of freeway; 
           [0013]      FIG. 2  indicates lane travel times and the difference in lane travel times for the example roadway section illustrated in  FIG. 1 ; 
           [0014]      FIG. 3  depicts travel time difference and speed difference between two freeway lanes for five minute periods; 
           [0015]      FIG. 4  describes the interrelationship of the ALMA modules; 
           [0016]      FIG. 5  is the first part of a flow chart depicting the functional relationship of this invention&#39;s modules; and 
           [0017]      FIG. 6  is the second part of a flow chart of  FIG. 5  depicting the functional relationship of this invention&#39;s modules. 
       
    
    
     DESCRIPTION 
       [0018]    The modules shown in  FIGS. 5 and 6  and described below provide an example of the implementation of a methodology for identifying the difference in travel time between lanes for a section of freeway and providing lane guidance to the driver or automated vehicle when appropriate. 
         [0019]    Module  1   301 —Set desired look ahead difference in travel time (RTD) to change lanes. This parameter is established by the vehicle operator in conjunction with the setting for Module  3 . When the absolute value of this difference is exceeded, ALMATR provides guidance to change lanes when conditions established by other modules are appropriate. The example shown in  FIG. 3  uses an absolute value of one minute  103 . 
         [0020]    Module  2   302 —Download parameters from the ALMA Management Center. The lane specific parameters include speed, volume, average headway, average vehicle length, passenger car equivalent volume, density, as described in Table 3 of the ALMAMC patent, as well as incident status information and lane status information (Table 4 of the ALMAMC patent), and Static Database parameters (Table 5 of the ALMAMC patent). If prediction is used in addition to the ALMAMC parameters, the predicted parameters identified in Table B1 of the ALMAPR patent application will also be downloaded. The disclosure of the ALMAPR patent application is part of the disclosure of this patent application. 
         [0021]    Module  3   303 —Set look ahead time. The vehicle operator will set or select a time period (LAT) over which the downstream conditions are to be considered for lane guidance. This time may be set in conjunction with the look ahead difference in travel time  301 . For example, for a four minute look ahead time, the vehicle operator may opt to require a one minute travel time saving before a lane change becomes worth the effort or risk. 
         [0022]    Module  4   304 —Compute look ahead distance. Using current and/or predicted speed in conjunction with look ahead time (LAT) compute the look ahead distance (LEN). 
         [0023]    Module  5   305 —Identify zones for look ahead distance. This module identifies the zones and portions of zones that will be used for subsequent computations. Zones are a component of the ALMA data structure and represent a portion of the freeway. As described in the ALMAMC patent, zone boundaries are determined by such factors as traffic conditions, placement of variable message motorist information devices that provide advisory and regulatory information. Using zone lengths stored in the static database, the module identifies those zones included in the look ahead distance as well as the portion of the last zone that is also included. 
         [0024]    Module  6   306 —Compute average speed and travel time for look ahead distance. Compute the travel time for each zone or zone portion identified in Module  5  by dividing the zone length or applicable fraction of zone length by the current speed or predicted speed for that zone. Dividing the look ahead distance by the sum of the zone travel times or applicable portion provides the average speed. Travel time is computed as the quotient of look ahead distance and average lane speed (as developed by using the zone speed and zone length). 
         [0025]    Module  7   307 —Are other criteria for lane allowance satisfied? This module identifies the constraints on the choice of lane which are influenced by factors other than lane speed. Details for these factors are provided in the ALMAVM patent as noted in Table 1. 
         [0000]    
       
         
               
               
             
               
               
             
           
               
                 TABLE 1 
               
               
                   
               
               
                   
                 Appropriate 
               
               
                 Factor 
                 ALMAVM Module 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 Does number of vehicle occupants meet lane 
                 2.1 
               
               
                 requirements 
               
               
                 Does vehicle meet height limitations for 
                 2.2 
               
               
                 barrel 
               
               
                 Does vehicle meet weight limitations for 
                 2.3 
               
               
                 barrel 
               
               
                 Is vehicle class permitted in lane 
                 2.4 
               
               
                 Adjustment for vehicle exit 
                 3 
               
               
                   
               
             
          
         
       
     
         [0026]    Module  8   308 —Eliminate non-compliant lanes from further consideration. This module removes the lanes that have been found, in Module  7  to be non-compliant lanes from further consideration. 
         [0027]    Module  9   401  Set maximum speed desired. The operator may optionally enter a speed that he does not desire to exceed for safety or fuel rate consumption purposes. 
         [0028]    Module  10   402  Desire to remain within speed limit. The operator may elect to remain within the speed limits or not through a manual data entry capability. 
         [0029]    Module  11   403  Automatic speed enforcement? A message from the ALMAMC module will provide information as to the presence of automatic speed enforcement. This will direct the computation sequence to other modules. 
         [0030]    Module  12   404  Select candidate alternative lanes for further consideration. This module corresponds to Module  2  in the ALMAVM patent. Using data entry from the vehicle operator it eliminates lanes based on the following: 
         [0031]    Number of allowable vehicle occupants for lane 
         [0032]    Vehicle height and weight limitations 
         [0033]    Vehicle type classification 
         [0000]    In addition, this module implements lane closure and other lane use and speed constraints originating at the TMC and provided by the ALMAMC. 
         [0034]    Module  13   405  Is speed for all candidate lanes above the speed limit? This module provides a logic test for this function. 
         [0035]    Module  14   406  Select the slowest lane. If it is desired to stay within the speed limit and no lane has a speed that satisfies this criterion, the slowest lane is selected. 
         [0036]    Module  15   407  Lane travel time difference&gt;required threshold? This filter determines whether the travel time difference between the current lane and a candidate adjacent lane is of sufficient magnitude to warrant further consideration for lane change. 
         [0037]    Module  16   408  Select lane, recommend target speed. For the remaining candidate adjacent lanes, and using the estimated travel times for the look ahead distance (Module  6 ) select the candidate adjacent lane with the largest difference between the travel time in the current lane and the candidate adjacent lanes. 
         [0038]    Module  17   409  Lane gap test OK? This module corresponds to Module 4.3R.2.12 in the ALMAVM Module. The prior modules culminating in Module  16  have established the driver or automated vehicle preference for changing lanes, selecting the lane and the target speed. In conventionally driven vehicles it is the driver&#39;s responsibility to change lanes in a safe way, or not change if conditions are not favorable. An automated vehicle must make this choice through the use of vehicle based sensors and the accompanying logic. The literature provides numerous examples of gap acceptance criteria. Examples include Wei and Dolan 1  and Ahmed 2 .  1  JUNQING WEI and JOHN M. DOLAN, A Robust Autonomous Freeway Driving Algorithm, IEEE 2009. 2  KAZI IFTEKHAR AHMED, Modeling Drivers&#39; Acceleration and Lane Changing Behavior, Doctoral Thesis, MIT, February 1999. 
         [0039]    Module  18   410  Recommend retain current lane. If the prior filters result in negative choices, the current lane is recommended for retention. 
         [0040]    Module  19   411  Recommend lane and target speed. If the prior filters result in a positive choice, the selected lane (Module  16 ) is recommended and the target speed is the current or predicted lane speed.