Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
  • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
  • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
  • G01C21/34—Route searching; Route guidance
  • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
  • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
  • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0125—Traffic data processing
  • G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
• • G—PHYSICS
  • G08—SIGNALLING
  • G08G—TRAFFIC CONTROL SYSTEMS
  • G08G1/00—Traffic control systems for road vehicles
  • G08G1/01—Detecting movement of traffic to be counted or controlled
  • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
  • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
  • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination

Definitions

• the present invention relates to the field of road traffic management in order to allow an accurate estimate of the travel time between an arrival place and a place of departure.
• a road network is in the form of a mesh comprising a plurality of elementary segments x.
• a database is used in a conventional manner which indicates the average speed Va of crossing a segment x as a function of the moment of crossing (morning, evening, etc. .) of the vehicle as illustrated in Figure 1.
• the database of average speeds Va is formed from algorithms that take into account, in particular, traffic conditions (congestion, work area, etc.). Such a database of average speeds Va is known to those skilled in the art.
• the database can also indicate the average crossing time of a segment x as a function of the moment of passage t of the vehicle as presented in the patent application FR2926880 of the company MEDIAMOBILE.
• a motorist can, on the one hand, choose the best route to reach his place of arrival and, on the other hand, choose the best time period to begin his journey.
• the accuracy of travel time estimation is crucial to enable a motorist to make the right choices.
• the weather conditions on the trip influence the speed of the motorist during his trip. Indeed, a motorist can not drive at the same speed when the roadway is dry than when it is covered with snow or rain. Also, it has been proposed to estimate travel time taking into account weather forecasts. A method is known in the prior art in which the speed of a motorist is penalized globally depending on the nature of the weather forecast. For example, the estimated speed of the motorist is penalized by 20% in case of snow and 10% in case of rain. Although the application of an overall penalty rate makes it possible to improve the estimate of the travel time, the accuracy of the estimate is not sufficient especially on a long distance route comprising segments of different natures.
• the invention relates to a method for estimating a journey time of a vehicle in a road network by a computer, the road network being defined in the form of a mesh comprising a plurality of segments x, each segment x being associated with a non-climatic average crossing speed of the segment which is a function of its instant of traversing t, each segment x being associated with a climatic degradation which is a function of its transit time t, which method comprises:
• a step of calculating a mean climatic crossing speed of each segment x which is a function of its transit time t, from the non-climatic average speed and climate modeling parameters defined locally for each segment x according to climate degradation;
• modeling parameters are used that are not defined globally for the entire road network but locally for each segment x as a function of the climatic degradation considered.
• this makes it possible to model in a real and precise way the speed modification following a degradation. Indeed, the impact of a deterioration is greater when a vehicle is traveling on a fast segment (motorway) than on a slower segment (road in built-up areas).
• the creation of a base of climatic speeds makes it possible not to modify the algorithms of computation of travel time, the algorithms using climatic velocities at place of non-climatic speeds.
• the estimate of the travel time can be performed very quickly, preferably in real time which is advantageous for users using embedded systems in their vehicle.
• the modeling parameters are obtained over a past measurement period in order to define them statistically by feedback.
• the modeling parameters are specific to each segment x which ensures optimal precision.
• the estimation of the modeling parameters is carried out for a large number of times of climatic degradation, which makes it possible to obtain optimal modeling parameters characteristic of the segment x considered for a degradation considered.
• the modeling parameters are specific to each segment x of the road network.
• each segment has its own modeling parameters which makes it possible to define "tailor-made” climatic speeds in order to optimally estimate the travel time on the road network.
• the method comprises a step of calculating standardized modeling parameters as a function of the fluid traffic speed FFS of said segment x.
• standardized modeling parameters as a function of the fluid traffic speed FFS of said segment x.
• each reference speed is obtained from measurements taken on a floating network of vehicles traveling on the road network.
• the floating vehicle network comprises a plurality of vehicles equipped with an on-board GPS system associating the speed of movement to a spatial position, for example, the segment of the network on which the vehicle is traveling.
• the temporal neighborhood of the climatic degradation moment is of constant period, preferably of the order of 5 minutes.
• the average climate speed is equal to the non-climatic average speed if the latter is less than a threshold speed which is a function of the modeling parameters and the fluid traffic speed FFS of the segment x considered .
• a threshold speed which is a function of the modeling parameters and the fluid traffic speed FFS of the segment x considered.
• the speed of a vehicle is not affected by climatic degradation when the latter is traveling at a slow speed. This observation is used to accelerate the calculation of the base of climatic velocities by keeping the non-climatic velocities of low value.
• the threshold speed is linked to the characteristic parameters of a segment, that is to say, its modeling parameters, which makes it possible to ensure an optimal compromise between cost and computational accuracy.
• the modification of the speed by climatic degradation is represented by a parametric model of the MARS type, preferably a linear model of the following form in the vicinity of a time of climatic degradation t 0 :
• Such linear parametric modeling makes it possible to rapidly obtain a climatic rate from a non-climatic speed obtained in a conventional manner.
• the estimation of the modeling parameters is easy for such linear parametric modeling.
• the threshold speed Vs is defined in the following manner
• the invention also relates to a device for estimating a journey time of a vehicle in a road network by a computer, the road network being defined in the form of a mesh comprising a plurality of segments x, each segment x being associated with a non-climatic average speed (Va) crossing the segment which is a function of its transit time t, each segment x being associated with a climatic degradation (M) which is a function of its transit time t, the device comprising:
• Vc mean climatic velocity crossing each segment x, which is a function of its transit time t, based on the non-climatic average speed (Va) and climatic modeling parameters ( P, P *) defined locally for each segment x as a function of climatic degradation (M);
• means for calculating the travel time (tp) from the calculation of the crossing times (tt) of the segments x characterized in that it comprises means for determining said climatic modeling parameters (P) for a given climatic degradation (M) for a given segment x comprising: means for obtaining a time base of climatic degradations (M) for a period of time (PER) on segment x of the road network,
• Vr time base of reference speeds (Vr) for the period of time (PER), each reference speed (Vr) corresponding to a speed of a vehicle traveling on segment x of the road network ,
• o means for estimating the modeling parameters (P, P *) from the pre-degradation speeds (Vad) and the degraded speeds (Vd) for all the times of climatic degradation (t 0 ).
• Figure 1 is a schematic representation of a method for estimating a travel time from a base of non-climatic speeds according to the prior art
• Figure 2 is a schematic representation of a method for estimating a travel time from a base of climatic speeds according to the invention
• Figure 3 is a schematic representation of the formation of the base of climatic velocities from a base of modeling parameters
• Figure 4 is a schematic diagram of the steps of forming the modeling parameter database
• FIG. 5 is a representation of the linear modeling of the degraded speed of a vehicle as a function of its speed before degradation
• FIG. 6 is a representation of the reference speeds measured during a time of climatic degradation t 0 ;
• Fig. 7 is a representation of the estimated modeling parameters for a plurality of segments x of the road network.
• Figure 8 is a representation of the standardized modeling parameters. It should be noted that the figures disclose the invention in detail to implement the invention, said figures can of course be used to better define the invention where appropriate.
• the method according to the invention makes it possible to estimate a journey time of a vehicle, in particular a vehicle, over a defined road network, in a conventional manner, in the form of a mesh comprising a plurality of elementary segments also called arcs.
• each segment x has a plurality of attributes to characterize it.
• a segment x may be characterized by a geographical position on the road network, a FRC parameter (Functional Road Class) indicating the functional class of the segment and a fluid traffic speed FFS.
• FRC parameter Federal Road Class
• the FRC class known to those skilled in the art, is a function of the type of road concerned as indicated in the table below. In the implementation example of the invention which will be presented later, only FRC class segments 0 to 2 are considered for the sake of clarity. Nevertheless, it goes without saying that the invention applies to any type of segment for any FRC value.
• the FFS fluid traffic speed of a segment x is defined as the most likely speed in fluid traffic on this segment. For example, a segment of the A1 highway in France has an FFS speed of 1 19 km / h. FFS is a known data for each segment x and is correlated to the FRC class of segment x.
• each segment x is associated with a non-climatic average speed Va passing through the segment which is a function of its transit time t.
• the set of speeds Va are collected in a database.
• the average speed Va crossing at any time of the day.
• the average speed Va is lower around 8am due to the movement of people going to work than to 1 1 pm. This average speed Va, which does not depend on the climatic conditions, is known to those skilled in the art and will not be detailed further.
• the travel time is estimated from a base of average climatic velocities Vc.
• Each segment x is associated with a climatic average speed Vc crossing the segment which is a function of its crossing time t.
• the non-climatic velocities Va are replaced by more relevant climatic velocities Vc.
• only the parameter relating to the average speed is modified in the algorithm.
• each climatic velocity Vc for a segment x given at a given transit time t is obtained from:
• a weather degradation M depends on the segment x considered and the time t considered.
• Weather degradation M may be, for example, a rain shower (low, medium or high), snowfall, fog, etc.
• the weather degradation M is zero for a clear time.
• the weather degradation M is updated every 15 minutes and is provided by a weather organization (Mluso France, etc.).
• a parametric model which relates a pre-degradation speed Vad and a degraded speed Vd following the climatic degradation M.
• the model includes parameters P which make it possible to define , for a given climatic degradation M, the future degraded speed Vd from a forward speed given degradation Vad.
• the non-climatic velocity Va is a speed before degradation Vad and that the climatic velocity Vc corresponds to a degraded velocity Vd.
• a first parametric model representing the evolution of the speed for a given segment x at a time of climatic degradation t 0 is the MARS model for "Multivariate Adaptive Regression Splines".
• MARS model for "Multivariate Adaptive Regression Splines”.
• a simplified expression of this model is known to those skilled in the art in the form below for a neighborhood of t 0 :
• climatic degradation M occurred at the time of climatic degradation t 0 .
• there are new modeling parameters P in order to relate the speed before degradation Vad and the degraded speed Vd Such a parametric model is complete and offers great precision.
• a second parametric model of an evolution of the mean velocity for a given segment x for a neighborhood of t 0 is the following linear model:
• the formula (Q3) has a restricted or simplified form of the parametric model MARS of formulas (Q1) and (Q2).
• the modeling parameters P are presented under the shape of two variables which depend on climatic degradation M occurred at the time of climatic degradation t 0 . In other words, for each type of degradation M (low rain, heavy rain, etc.), there are new modeling parameters P in order to relate the speed before the degradation Vad and the degraded speed Vd.
• the relation (Q3) is only valid for a pre-degradation speed Vad greater than a threshold speed Vs.
• a threshold speed Vs the speed which corresponds to the following equation:
• linear modeling is defined as follows:
• a threshold speed Vs advantageously makes it possible to limit the number of calculations to obtain degraded speeds Vd, that is to say, the base of climatic speeds Vc. Indeed, when the pre-degradation speed Vad is lower than the threshold speed Vs, it is not useful to calculate the degraded speed Vd, the latter being equal to the speed before degradation Vad. Thus, when the climate forecasts evolve very quickly, one can obtain the base of climatic velocities Vc in real time.
• Modeling parameters are unknown and will be estimated from a base of observations of reference speeds Vr over a given time period PER as represented in FIG. 4.
• Each reference speed Vr corresponding to a speed of a vehicle traveling on a segment x of the road network at a given moment t of the PER period.
• This reference speed Vr is not constant over time, in particular due to traffic conditions and weather conditions.
• the reference speed Vr is preferably obtained by a FCD source for "Floating Car Data" which makes it possible to collect the instantaneous speeds of a plurality of vehicles, traveling on the segments x of the road network, which provide, by means of a embedded GPS device, the instantaneous speed and the geographical position of the vehicle.
• the measurement instant t of each reference speed Vr is known.
• reference speeds Vr on the segments of the road network have been collected over a period of time PER of the order of 107 days.
• the evolution of the reference speeds Vr on a given segment x and on a measurement period PER during which a climatic degradation M "strong rain” has occurred at a time of climatic degradation is represented. t 0 .
• the vehicle reference speed Vr drops significantly at the onset of the climatic degradation M.
• the temporal instants of climatic degradation t 0 are determined .
• the time instant t 0 12h which corresponds to the appearance of a climatic degradation M.
• a temporal moment of change of climate t 0 can only appear every 15 minutes. It goes without saying that the frequency of updating climatic conditions could be different.
• FIG. 6 represents the time instant t 0 during the appearance of the rain.
• the temporal moment of change of climate t 0 is defined thanks to the weather degradation M which has evolved from "clear weather” to "heavy rain”.
• the reference speed Vr measured at time t 0 corresponds to the degraded speed Vd as illustrated in FIG. 6.
• the degraded speed Vd is sought in the time interval [t 0 , t 0 + 15 minutes [which corresponds to the frequency of information of the climatic deteriorations M. If, despite everything, no speed reference Vr has not been measured in this interval, this climate change will not be taken into account.
• a neighborhood is determined around the time of climatic degradation t 0 for which the reference speed Vr is considered constant on this neighborhood.
• the reference speed Vr is considered constant on this neighborhood.
• the duration h is equal to 5 minutes and makes it possible to obtain, in practice, neighborhoods in which the reference speed Vr is deemed to be constant.
• the reference speed Vr is measured at different times on the segments x of the road network by means of the FCD method previously described. For each previously defined neighborhood, the instant is determined of this neighborhood corresponding to the temporal moment of the last speed measurement V on this neighborhood Subsequently, the instant is designated tipping moment. In other words, is the last measure of speed
• FIG. 6 represents by points a plurality of speeds Vr measured in the vicinity the last point (the closest to corresponds to the speed before-degradation
• a speed before Vad degradation is determined for the neighborhood of each temporal moment of climate change t 0 .
• the same method is applied to each segment x of the road segment to obtain a plurality of parameter pairs for all the segments x of the road network for the same type of degradation M.
• a plurality of solutions is obtained microscopically. For example, the value of parameter pairs for the same type
• degradation coefficient M (heavy rain) is shown in the diagram of FIG. 7. It iser these steps so as to obtain a plurality of parameter pairs for all the segments x and for any type of climatic degradation M.
• the modeling parameters P are in the form of a pair of parameters defined for each segment x and for each type of degradation M.
• the pairs of parameters are grouped according to the FRC class of the segments x considered.
• segments of class FRC equal to 0, 1 or 2 have been considered, but it goes without saying that the invention applies to any class FRC.
• the pairs of parameters obtained for segments x of class FRC equal to 0 belong to a first group G1 of couples which is centered on a pair of average modeling parameters
• the parameter pairs obtained for segments x of class FRC equal to 1 or 2 belong to a second group G2 of couples which is centered on a pair of average modeling parameters
• average modeling parameters can be defined for each class FRC.
• the modeling parameters P are normalized as a function of the fluid traffic speed FFS which is specific to each segment x and strongly correlated with the FRC class.
• the parameter 3 ⁇ 4 is normalized as a function of the fluid traffic speed FFS of said segment x for which the parameter 3 ⁇ 4> has been obtained.
• the modeling parameters are grouped into a single group G 3 which is centered on a pair of average standardized modeling parameters. for which advantageously one obtains a
• Such standardized modeling parameters P * are general and simpler to implement on the entire road network compared to the modeling parameters P.
• the base of climatic velocities Vc is obtained quickly from the base.
• non-climatic velocities Va are obtained quickly from the base.
• the modeling parameters P, P * are updated over time to allow an accurate estimate as the road network evolves.
• the travel time tp is calculated from the calculation of the crossing times tt of the segments x of the course.
• this method is implemented by a calculator of the server or personal computer type.
• the threshold speed Vs of a segment x can also be defined according to the standardized modeling parameters and the speed of fluid traffic called FFS speed that are specific to a given segment x of the road network.
• the threshold speed Vs is defined as follows with the modeling parameters P:
• threshold speed Vs can be defined as follows:

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• 2012
  • 2012-06-19 FR FR1255722A patent/FR2992060B1/fr not_active Expired - Fee Related
• 2013
  • 2013-06-18 WO PCT/FR2013/051423 patent/WO2013190233A1/fr active Application Filing
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