Device, System and Method for Traffic Prediction

Abstract

A method is provided for predicting load of traffic of vehicles that are travelling according to non reference route plan, provided with Dynamic Route Guidance capability of their PMMS, in a Forward Time Interval related Route Segment and according to a predetermined protocol between mobile systems and a non mobile system of a SODMS. Using mobile units, a traffic prediction query is receiving according to a predetermined differential traffic load match process. A match process is performed by each of the mobile units and, according to a match, a predetermined response procedure is enabled, wherein a response procedure in each mobile unit uses a predetermined random process to select an allocated slot in which to transmit a predetermined signal, which provides an improved way to predict traffic in conjunction with off line database statistics, preferably with such that are being adaptively corrected by prior data and method to predict traffic which do not include, or lack sufficient erratic traffic information.

1 - 4 . (canceled) 
     
     
         5 . A method to adjust traffic prediction, the method comprising a plurality of iterations, wherein at least one iteration of the plurality of iterations comprises:
 providing a traffic prediction update for route planning associated with a plurality of vehicles, wherein said traffic prediction update is based, at least in part, on route plan modifications resulting from give-up processes performed in a prior iteration, wherein said give-up process comprises modification of a route plan, in accordance with a give-up criterion, to exclude from the route plan a congested route segment, which is expected to have traffic congestion, and wherein said traffic prediction update includes a prediction, in a forward time interval, of congested traffic on a route segment that is still congested with respect to traffic predicted on said route segment in said prior iteration; and   in response to the traffic prediction update, receiving an indication that a vehicle of said vehicles has modified its route plan from a planned route that includes said still congested route segment to a modified route that does not include said still congested route segment.   
     
     
         6 . The method of  claim 5 , wherein the traffic prediction update is further based on statistical traffic data. 
     
     
         7 . The method of  claim 6  including updating a statistical database according to the indication. 
     
     
         8 . The method of  claim 5 , wherein the give-up process comprises a give-up process utilizing one or more give-up criterion levels. 
     
     
         9 . The method of  claim 8 , wherein a give-up criterion level of the give-up criterion levels includes a threshold to modify a route plan to a route having lower priority than the route plan of the prior iteration. 
     
     
         10 . The method of  claim 8 , wherein a give-up criterion level of the give-up criterion levels includes a threshold to modify a route plan to a route plan having a higher travel time than the route plan of the prior iteration. 
     
     
         11 . The method of  claim 8 , wherein a give-up criterion level of the give-up criterion levels includes a threshold to modify a route plan to an earlier, more preferable, route. 
     
     
         12 . The method of  claim 8 , wherein a give-up criterion level of the give-up criterion levels includes a threshold to modify a route plan to a route having a-priori lower priority than the route plan of the prior iteration. 
     
     
         13 . The method of  claim 5 , wherein one or more of the iterations is based on one or more random parameters. 
     
     
         14 . The method of  claim 5 , wherein the give-up process in a successive iteration to a prior iteration modifies planned routes at a higher grade of give-up criterion level than the route plan of the prior iteration. 
     
     
         15 . The method of  claim 5 , wherein a length of the modified route is greater than a length of the planned route. 
     
     
         16 . The method of  claim 5  comprising:
 if the traffic prediction update indicates that too many mobile units gave up on said still congested route segment in the prior iteration, 
 receiving one or more signals from one or more of said vehicles, indicating that said one or more vehicles modify their current routes to routes previously-used in the previous iteration. 
 
     
     
         17 . The method of  claim 16  comprising:
 receiving a signal indicating that at least one of said vehicles returns to a previously-used route by re-making a prior give-up process with a lower grade of give-up level criterion. 
 
     
     
         18 . The method of  claim 16 , wherein the previously-used routes are shorter than the current routes. 
     
     
         19 . The method of  claim 16 , wherein modification of said current routes to previously-used routes comprises performing the modification based on randomly selected values of at least one parameter. 
     
     
         20 . The method of  claim 5  comprising:
 performing a plurality of iterations until reaching a sufficient level of convergence. 
 
     
     
         21 . The method of  claim 20  comprising:
 performing said plurality of iterations by taking into account a trade-off between low levels of give-up grades and high levels of give-up grades. 
 
     
     
         22 . The method of  claim 5  including broadcasting said traffic prediction update to the plurality of vehicles. 
     
     
         23 . The method of  claim 5 , including, at a vehicle of the vehicles:
 receiving positioning signals,   planning a route according to traffic updates and according to a respective give-up process,   transmitting radio signals to update a mapping system about route modification, and   receiving radio signals of traffic updates.   
     
     
         24 . The method of  claim 5 , wherein said route modification comprises modification to exclude from route plans one or more route segments affected by predicted traffic congestion.