WO2006125291A1 - Système et procédé d’évaluation des temps de parcours d’une sonde de circulation - Google Patents

Système et procédé d’évaluation des temps de parcours d’une sonde de circulation Download PDF

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Publication number
WO2006125291A1
WO2006125291A1 PCT/CA2005/000785 CA2005000785W WO2006125291A1 WO 2006125291 A1 WO2006125291 A1 WO 2006125291A1 CA 2005000785 W CA2005000785 W CA 2005000785W WO 2006125291 A1 WO2006125291 A1 WO 2006125291A1
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traffic
location
trajectory
locations
travel time
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PCT/CA2005/000785
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English (en)
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WO2006125291A9 (fr
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Hiroyuki Takada
Bruce Hellinga
Liping Fu
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Hiroyuki Takada
Bruce Hellinga
Liping Fu
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Priority to PCT/CA2005/000785 priority Critical patent/WO2006125291A1/fr
Publication of WO2006125291A1 publication Critical patent/WO2006125291A1/fr
Publication of WO2006125291A9 publication Critical patent/WO2006125291A9/fr

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    • 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
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
    • G07B15/06—Arrangements for road pricing or congestion charging of vehicles or vehicle users, e.g. automatic toll systems
    • G07B15/063—Arrangements for road pricing or congestion charging of vehicles or vehicle users, e.g. automatic toll systems using wireless information transmission between the vehicle and a fixed station

Definitions

  • This invention relates to a system and method for estimating travel times experienced by individual traffic probes in traversing traffic links of a road network, based on intermittent and possibly erroneous reports of geographical locations from the traffic probes and a database of the road network.
  • a mobile phone such as a mobile phone, a mobile terminal of a global positioning system, and an electronic tag can be used to identify locations, and therefore an inexpensive scheme for travel time data collection using traffic probes equipped with those mobile devices is theoretically possible with a wide coverage of a road network if the infrastructure for those mobile devices is already deployed around the road network.
  • the present invention provides a novel methodology of estimating travel times based on location data reported from a traffic probe. This methodology has several characteristics suitable for the use of operational traffic management.
  • candidate locations and candidate routes are determined as possibilities of true locations and true routes of the traffic probe.
  • the candidate locations are limited so as to reduce computation time and to keep sufficient accuracy for ensuing calculation of travel times.
  • the candidate routes can be obtained through a novel shortest path algorithm in order to reduce computation time while taking into account transition times defined between consecutive traffic links as well as free flow travel times uniquely assigned to each traffic link.
  • the candidate locations and the candidate routes are connected to one another, and a set of feasible trajectories are generated as possibilities of the trajectory of the traffic probe.
  • Each of the feasible trajectories is associated with an objective value mathematically combining location errors calculated from the candidate locations and a total travel time calculated from the free flow travel times and the transition times included in the sequence of the candidate routes.
  • a portion of the most likely trajectory is incorporated into a full trajectory if there is no contradiction in a provisional trajectory connecting the portion of the most likely trajectory and a portion of a precedent full trajectory.
  • the separation of trajectories into these two parts makes computation time shorter than a composition of a full trajectory from location data in each time of update.
  • the full trajectory reflects the most recent result of the estimation for the true locations and the true routes.
  • Estimates of travel times experienced by the traffic probe are assigned to each traffic link included in the full trajectory.
  • the calculation of travel times takes into account not only the ambiguity of the locations reported from the traffic probe, but also possible behavior scenarios of the traffic probe associated with stopping location, stopping time, and magnitude of traffic congestion in order to improve the accuracy of the estimates of travel times.
  • the estimated travel times can be used for average travel times or speeds of more than one traffic probe or for estimation of route travel times or speeds over more than one traffic link.
  • Fig. 1 is an illustrative representation of real elements and attributes thereof dealt with in the present invention
  • Fig. 2 is a block diagram of a typical system for estimating travel times
  • Fig. 3 is a block diagram of processes, data, and data flow working on the system of Fig.
  • Fig. 4 shows illustrative structures of road network representing a real road network by the road network data of Fig. 3;
  • Fig. 5 is a flow chart of the process for selecting candidate locations as part of the trajectory estimation of Fig. 3;
  • Fig. 6 illustrates the application of the candidate location selection process from Fig. 5;
  • Fig. 7 is an illustrative representation of data elements for determining candidate routes associated with part of the trajectory estimation of Fig. 3;
  • Fig. 8 is a flow chart of the process for determining candidate routes as part of the trajectory estimation of Fig. 3;
  • Fig. 9 is an illustrative representation of data elements associated with part of the trajectory estimation of Fig. 3 for generating the full trajectory data of Fig. 3 based on candidate locations obtained from the process illustrated in Fig. 5 and candidate routes from the process in Fig. 8;
  • Fig. 10 is a flow chart of the process for determining a full trajectory as part of the trajectory estimation of Fig. 3;
  • Fig. 11 is an illustrative representation of data elements associated with the travel time estimation of Fig. 3.
  • Fig. 12 is a flow chart of the process of generating travel time data sets of Fig. 3 as the travel time estimation of Fig. 3.
  • a traffic probe 101 which may be a pedestrian, a private vehicle, a public transit vehicle, a fleet vehicle, or some other type of vehicle, carriage, or traveler is assumed to move on a real road network 102, and to intermittently report the current locations at true locations 103.
  • Each of reported locations 104 is associated with one of the true locations 103, and may include a location error from the associated true location.
  • This invention provides estimates of the true locations 103 and true routes 105, which the traffic probe 101 takes between each pair of consecutive true locations on the real road network 102, based on the reported locations 104 and recorded information of the real road network 102. For the purpose of traffic management, this invention also provides estimates of travel times experienced by the traffic probe 101 each of which is associated with one of traffic links 106 including one or more road segments of the real road network 102.
  • the estimation of the travel times requires a system and a method implemented to the system.
  • the physical components of the system are shown as Fig. 2.
  • the system is divided into three subsystems: a location referencing system 201, an estimating system 202, and a traffic management system 203.
  • the infrastructure of the location referencing system 201 may be associated with an existing system such as a cellular phone network, a global positioning system (GPS), or an electronic toll collection system deployed on a toll road network.
  • GPS global positioning system
  • a mobile station 206 is a device physically moving with a traffic probe.
  • the mobile station 206 may be a cellular phone, a mobile terminal of a GPS, an electronic tag, or some other type of device capable of communicating with another device physically separated therefrom.
  • the attachment of the mobile station 206 to the traffic probe may be flexible; for example, a user of a cellular phone may change the type of traffic probe from a pedestrian to a private vehicle by entering the vehicle with the cellular phone.
  • a locating equipment 205 is used for measuring geographical location of the mobile station 206 intermittently. The result of the location measurement is a reported location.
  • the locating equipment 205 includes at least one base station physically remote from the mobile station 206.
  • the base station may be settled on the ground like a base station of a cellular phone network used for the purpose of telecommunication, or may move like a satellite used in a GPS.
  • the process of the location measurement utilizes radio communication between the base station and the mobile station 206. According to the requirement of applied locating technology, part of the locating equipment 205 may be physically combined with the mobile station 206.
  • a location transmitter 204 is connected to the locating equipment 205 by communications link in order to receive the reported location.
  • communications link which appears here and later in the description is defined as all types of media and devices providing the capability of data communication between two remote units, such as a wireless connection, an electronic circuit, a physical line used for computer networks, or a telephone line.
  • the location transmitter 204 also has an interface to send the received reported location. According to the applied technology of the locating equipment 205, the location transmitter 204 may be physically attached to the mobile station 206 or the base station, or may reside in some other place.
  • the number of each component included in the location referencing system 201 is not restrictive.
  • the location referencing system 201 may manage more than one mobile station like a cellular phone system.
  • the number of base stations may also be more than one, such as the number of satellites used for a GPS.
  • the location transmitter 204 may be a physically integrated device managing all mobile stations, or may be divided into multiple devices each of which manages a group of mobile stations.
  • the estimating system 202 provides a set of devices necessary for estimating travel times of a traffic probe based on reported locations obtained from the location referencing system 201.
  • the number of mobile stations managed in the estimating system 202 may be one or more.
  • the estimating system 202 contains two interfaces for data input and output.
  • a location receiver 207 includes an interface connected to the location referencing system 201 by communications link to receive the records of reported locations.
  • a travel time transmitter 218 includes another interface connected to the traffic management system 203 by communications link and outputting the estimated travel times.
  • a location memory 208, a trajectory working memory 209, a trajectory memory 211, a parameter memory 212, a travel time working memory 215, and a travel time memory 217 provide a physical or logical space for storing data used for estimating travel times. These memories may be electronic, magnetic, optical, or the like, but a dynamic memory is preferable for each of these memories. Part of these memories may be combined into the same physical component.
  • a map storage 214 stores records of a real road network. In general, these records are static and may exceed the capacity of an existing dynamic memory in total, and therefore a static and discrete memory such as a magnetic disk is preferable for the map storage 214.
  • a trajectory processor 210 and a travel time processor 216 perform arithmetical and logical calculations for the data sets stored in the trajectory working memory 209 and the travel time working memory 215 respectively. These processors may be combined into one physical processor, if this physical processor can perform all the arithmetical and logical calculations assigned to the trajectory processor 210 and the travel time processor 216.
  • a system controller 213 provides physical or logical connections by communications link between any necessary pairs of the components included in the estimating system 202, and controls the data flow for the provided connections.
  • the system controller 213 may be physically divided into a plurality of sub controllers, according to the required connections. The relationship among the components is addressed later in the description of processes and data flow.
  • the traffic management system 203 receives the data of the estimated travel times through an interface included in a travel time receiver 219.
  • the received data may be displayed or further processed, according to the purpose of the traffic management system 203. For example, if personnel working for operational management of a transit system need to know the most recent status of a specific transit vehicle, the received data associated with the transit vehicle may be displayed by connecting a monitoring unit to the travel time receiver 219.
  • the purpose of the traffic management system 203 is provision of travel time or speed information to the drivers of general vehicles on a road network
  • the received data may be aggregated into average travel times or speeds of general vehicles by connecting another computing module to the travel time receiver 219.
  • the speed information can be obtained from the travel time information by dividing the travel time into the distance of the corresponding route or traffic link on the road network.
  • a location generating process 301 is implemented in the location referencing system 201, and intermittently generates a location data set including records for a reported location.
  • the location data set includes a record of a location measured by locating equipment 205, and a time record for the moment of the location measurement.
  • the location record represents a location on a two-dimensional coordinate system.
  • the location record may not necessarily be a pair of latitude and longitude of the earth, but should be able to be associated with latitude and longitude of the earth to determine a geographical location of the mobile station 206.
  • the location record also allows a three-dimensional coordinate system, and the unit measuring the location may be meters, kilometers, feet, miles, or the like.
  • identification of a traffic probe for each reported location is assumed to be technologically possible in the location referencing system 201, and the location data set may include a record of an identification number specific to the traffic probe.
  • the location data set is sent out from the location transmitter 204.
  • the generated location data set is received and stored in the estimating process 302 implemented in the estimating system 202.
  • the location receiver 207 and the location memory 208 are the physical components corresponding to this process, and the system controller 213 manages the associated data flow.
  • Location data sets 304 include past location records and past time records as well as the most recent location and time records for the mobile station 206.
  • Road network data 305 are stored in the map storage 214 and represents a real road network.
  • the road network data 305 includes records of a traffic node 401 and a traffic link 402 on a two-dimensional plane of Cartesian coordinate system. Those two dimensions can be associated with longitude and latitude of the real road network.
  • the traffic node 401 may be one of intersections of road segments with or without traffic control, shape points, dead ends of a road segment, or changing points of some road attribute on the real road network, but the road network data 305 may not explicitly provide the distinction of these categories.
  • the traffic link 402 is the representation of one or more road segments connecting between the traffic node 401 and another traffic node 403.
  • the traffic link 402 is assumed to be a straight segment, and includes the information of direction. If the traffic link 402 allows bi-directional traveling for a traffic probe like directions 404 and 405, the road network data 305 may have two separate records for the traffic link 402. There exists at most one traffic link starting from a traffic node and ending at another traffic node. A traffic probe is assumed to travel traffic links along the direction defined for each traffic link. The road network data 305 may contain other types of information to represent more details of the real road network.
  • trajectory estimation 306 is performed in the trajectory working memory 209 and the trajectory processor 210.
  • This process retrieves part of the location data sets 304, the road network data 305, and parameters 307 stored in the parameter memory 212 into the trajectory working memory 209 under the management of data flow by the system controller 213.
  • This process generates full trajectory data 308 including estimates of true locations and true routes.
  • the full trajectory data 308 is stored in the trajectory memory 211 through the system controller 213. This process may also retrieve the full trajectory data 308 for the purpose of its renewal.
  • the process of travel time estimation 309 is performed in the travel time working memory 215 and the travel time processor 216. This process retrieves part of the location data sets 304, the road network data 305, and the parameters 307 into the travel time working memory 215 through the system controller 213. This process generates travel time data sets 310 including estimates of travel times. The travel time data sets 310 are stored in the travel time memory 217 through the system controller 213.
  • a traffic management process 303 working in the traffic management system 203 obtains part of stored travel time data sets 310 through the system controller 213 and travel time transmitter 218.
  • a reported location included in one of the location data sets 304 is defined as
  • the reported locations for the same traffic probe compose a sequence of reported locations ordered by time, , where I 0 and I ⁇ are indices representing the starting and ending locations of the sequence respectively.
  • a traffic node recorded in the road network data 305 is a location on a two-dimensional plane defined as:
  • a traffic link from traffic node a to traffic node b is uniquely defined as
  • a traffic link is regarded as a set of locations, and the locations on the traffic link are expressed parametrically by ⁇ . Accordingly as ⁇ increases, the corresponding location moves toward the downstream end of the traffic link. All the defined traffic links belong to the set of traffic links, L. Since every traffic link contains traffic nodes at the entering and exiting points, WcL .
  • Information of free flow speed for traffic link l(n a , n b ) is also recorded in the road network data 305, and is defined as $ ⁇ n a , n b ) .
  • This information may be derived from a record of road class associated with each traffic link and a set of rules associating road class with free flow speed.
  • the free flow speed is defined uniquely for each traffic link.
  • the physical length of traffic link l ⁇ n a , n b ) vasy be calculated by taking the Euclidean distance between n ⁇ and n b , or may be directly recorded as part of the road network data 305. In any case, it is defined as ⁇ l ⁇ n ⁇ , n b ) ⁇ . If the length of traffic link ⁇ l ⁇ n ⁇ , n b ) ⁇ is assumed to be an Euclidian distance, it is defined as
  • the free flow travel time of this traffic link may be calculated from the length and the free flow speed as follows:
  • the free flow travel time defines the theoretically minimum time for the traffic probe to complete a traverse of the traffic link.
  • a candidate location corresponding to the reported location ih k (t k j) is defined as
  • This candidate location is assumed to be on the represented road network
  • a candidate route between consecutive candidate locations, m k ⁇ t k ⁇ l ) and > is defined as
  • Candidate route r k (t kt l , t kt l+l ) means one of all the possible routes connecting consecutive candidate locations m k (t k ⁇ l ) and m k ⁇ t kt l+ ⁇ ) on the represented road network.
  • the candidate route can be regarded as a subset of locations on the represented road network, and it can be partitioned into a set of fractional or complete traffic links such as
  • traffic link is more relaxed in this equation.
  • every traffic link must have traffic nodes on its ends.
  • a fractional traffic link is also possible by changing one end or both ends of a traffic link into a given location on the traffic link.
  • the notation of the candidate route is redefined as follows:
  • r k(h,,> m k,,. l)> l ( m k,,, V m k, ,,2)> ⁇ ⁇ ⁇ > l(m k,hJ ⁇ k> ,y v m l:lJ(kj) ), /(JW W(M , m ki , iJ ⁇ kil)+l ) ⁇ (10) ,!' • "' where l k ⁇ l ⁇ J (j O,l,..., J ⁇ k, i)) is one of the complete or fractional traffic links included in the candidate route.
  • the method implemented for the trajectory estimation 306 is based on a minimization problem evaluating location errors of reported locations and quantified behaviors of a traffic probe. By virtue of this quantification, all candidate estimates of the true locations and the true routes can be numerically ranked, and selection of the most likely estimates of the true locations and the true routes becomes possible.
  • the formulation of the minimization problem is given by
  • the most likely estimates of true locations and the true routes are defined as Z mm , which includes the sequence of most likely candidate locations, 1 I 0 ⁇ i ⁇ J 1 J , and the sequence of most likely candidate routes,
  • Z mm provides the minimum objective value Z mm in equation (14).
  • the relationships from (6) to (10) and (13) are also applied to m k ⁇ t k> l ) and h , ⁇ + ⁇ ) 5 because these are also candidate locations and candidate routes respectively.
  • functions F and G needs to be defined in more detail in order to show concretely that the reported locations and the road network data 305 can be utilized in the minimization problem, and that smaller values of the functions can represent more likely estimates.
  • the following functions are provided as a preferable structure:
  • i is an index indicating the sequence of location sampling time for traffic probe k, which starts at I 0 and ends at I x
  • J(k, i) is the number of complete or fractional traffic links in candidate route f k (h,,' ⁇
  • Function F uses distance measurements between reported locations and candidate locations denoted as and the minimization thereof toward reference value ⁇ k> , . If most of distance errors caused by the locating equipment 205 are known to statistically appear around some average value, ⁇ k , , may be set to this average value. The definition of the reference value would be effective to explain the errors that are known in distance but unknown in direction. « 4 ; is a coefficient adjusting the evaluative weight of function F relative to function G. Indices k and i attached to ⁇ and ⁇ permit those parameters to vary by location measurement. For example, by assigning a different set of values for a different location measurement, function F can reflect different levels of location accuracy associated with different locating techniques. It is also possible to take into account other attributes specific to each location measurement by changing those values if those attributes are known in advance.
  • Parameter ⁇ reflects a statistical attribute of individual location measurements.
  • the distance error from the reference value is evaluated as its value in the minimization problem, and the total of distance errors from the reference value obtained at different sampling times is minimized.
  • ⁇ > 1 a large distance error from the reference value has an amplified value in function F, and estimates with similar distance errors from the reference value tends to be regarded as the most likely.
  • ⁇ ⁇ 1 the distance errors from the reference value for the most likely estimates separate to relatively large and small ones.
  • the value of parameter ⁇ applied to each location measurement may change by type of locating technology.
  • function G refers to the total time to travel along a sequence of candidate routes.
  • ⁇ f (l kJJ ) is the free flow travel time of complete or fractional link l kJJ as defined by equation (5) or (13), and ⁇ s (l kJJ ) corresponds to the transition time from one traffic link to another.
  • the total travel time is regarded as the sum of the free flow travel times and the transition times included in the sequence of candidate routes.
  • the total travel time is not determined only by the sum of the free flow travel times defined as equations (5) and (13). Consideration of transition times is also important in quantifying the possibilities of candidate routes, when the candidate routes are similar in terms of the sum of the free flow travel times, and a traffic probe chooses the most economical route with the minimum sum of transition times.
  • a transition time is uniquely assigned to a pair of traffic links topologically connected by a traffic node.
  • One possible way for determining each transition time is to prepare a fixed value for each pair of traffic links and to register this value to the road network data 305.
  • Another way is to apply a function reflecting transition times. The following function is an example of a systematic method for estimating the additional time required for a traffic probe to transition from one traffic link to another as a result of deceleration and acceleration in turning movements.
  • Equation (19) requires the definition of h, ⁇ ,j( k , ⁇ ) + i in order to calculate the transition time of the last traffic link in each candidate route as follows:
  • This fractional or complete traffic link is part of a candidate route after time t kj+x . Furthermore, although the records of angle for all the pairs of consecutive traffic links may be registered in the road network data 305, the calculation of cos ⁇ 4 , 7 is still possible without preparing these extra records.
  • the value of cos0 A , 7 can be calculated using the already defined variables as follows:
  • Parameter v in equation (17) functions as an evaluator of the correlation between consecutive candidate routes of a traffic probe. If v is equal to or less than one, the minimization problem regards some extreme trajectory such as an alternation between being stopped during an interval and then traveling at more than the free flow speed as the most likely in terms of a comparison between consecutive candidate routes. Meanwhile, if the actual speed of a traffic probe always changes continuously along time, a value more than one is preferable for v . ⁇ kt , is a parameter which adjusts the evaluative weight of function G toward function F The most probable factor that causes the value of y and ⁇ to change for each location measurement is fluctuation of sampling time interval for a traffic probe.
  • the parameters used in the minimization problem need to be determined and assigned with some appropriate values.
  • the optimal values for the parameters depend on the type of traffic probe, the structure of road network, and the attributes of reported location, and it is impossible to provide a unique set of values applicable for all situations.
  • the optimal values for the parameters can be obtained through a calibration process in a heuristic manner. The calibration is possible by testing a small, but statistically sufficient number of sample traffic probes for which the true results can be obtained.
  • the values of ⁇ and ⁇ can be determined from a measurement test of the locating technology used for the location referencing system 201.
  • the values of ⁇ and ⁇ can be obtained from a test of transition times for real or simulated traffic probes.
  • the values of a, v, y, and ⁇ 5 can be determined by running a test traffic probe with equipment which can measure its precise and frequent locations on a real road network such as a differential GPS, and comparing the results between the estimates obtained from the reported locations of the test traffic probe and the true trajectory obtained from the equipment of the test traffic probe.
  • Fig. 5 An algorithm determining the candidate locations is shown in Fig. 5.
  • Reported location ih k (t k ⁇ is retrieved from the location data sets 304 in step 501.
  • an allowable maximum distance d k l is determined in step 502.
  • the value of fi ⁇ r may change according to the locating technology applied to reported location m k (t k l ) , and may be stored as one of the parameters 307.
  • d k When the road network data 305 is divided into subsets by sub area associated with geographical locations of traffic nodes or traffic links, d k ; may be applied to step 503 to select the subsets used for searching the candidate locations.
  • Steps 504, 505, 506, and 507 extract part of the candidate locations from the traffic nodes included in the selected subsets. If the distance error between one of these traffic nodes n a and reported location ih k ⁇ t k j) is within the allowable maximum distance, denoted as
  • the other candidate locations are extracted from middle points of the traffic links included in the selected subsets. Each of these candidate locations is derived from an intersection of one of these traffic links and the perpendicular thereof passing reported location m k ⁇ t k j) .
  • Equations (23) and (24) contain four unknown variables (JC, y, d, and ⁇ ). If d is assumed to be a known value, then these equations can be used to solve for ⁇ by eliminating x and y. As the result of this elimination,
  • Equation (25) is a quadratic on ⁇ , and the rule of quadratic solutions leads to
  • D can be used to examine the existence of locations within an allowable maximum distance by substituting d k , for d in equation (27), and calculating the right hand side. If D ⁇ O , then there exists an intersection of the line including the traffic link 604 and its perpendicular 607 passing the reported location 601, and the coordinate of a representative location 608 at the intersection is calculated. The intersection is given by
  • ⁇ m can be obtained simply by setting D to zero in equation (26), because this intersection must be the middle point of the intersections parametrically derived from equation (26).
  • the coordinate of the representative location 608 can be obtained by substituting ⁇ m determined from equation (28) for ⁇ in equation (23).
  • the Euclidian distance between the representative location 608 and the reported location 601 can be calculated using those coordinates.
  • the representative location obtained through ⁇ m is not always on a segment represented by a traffic link used for the calculation. For example, when ⁇ m is more than 1 or less than 0 for a traffic link 609, a representative location 610 is not on the traffic link 609 as per the definition given in equation (3). In this case, the representative location 610 is not considered as a candidate location.
  • a representative location on an intermediate point of a traffic link may be relocated to the terminating traffic nodes if the representative location is near to the terminating traffic nodes.
  • some threshold value C is determined, and if ⁇ m satisfies either of
  • Inequalities (29) and (30) are the conditions of relocation to the entering traffic node and the exiting traffic node respectively.
  • C the representative location 612 is relocated to the traffic node 602.
  • the value of C might need to be calibrated to some value by taking into account the distance error of reported locations and the structure of represented road network. However, this constant does not necessarily have an exact optimal value for the purpose of estimating travel times.
  • Algorithmic selection of the candidate locations from the representative locations as shown in Fig. 5 is based on the result of these calculations.
  • the discriminant for this traffic link is provided by equation (27) in step 509. If the discriminant is determined to be zero or positive in step 510, the coordinates of the representative location are calculated using equations (23) and (28) in step 511. If the representative location is determined within the segment of the traffic link defined by equation (3) in step 512, the possibilities of ithe relocation of the representative location is examined in step 513. After step 514 calculates the distance error between the reported location and the examined representative location, the examined representative location is stored as one of the candidate locations with the calculated distance error in step 515. The selection of the candidate locations is repeated for another traffic link until step 516 recognizes that all the traffic links included in the selected subsets have been examined.
  • the determination of candidate locations for a reported location ends by pruning the records of stored locations indicating the same traffic node or the same location on the same traffic link to one record.
  • the efficiency of the trajectory estimation 306 also depends on the way by which a candidate route between a pair of consecutive candidate locations is identified. Factors determining candidate routes are illustrated in Fig. 7. On a represented road network 701, an origin location 702 and a destination location 703, which form a pair of consecutive candidate locations, may have a plurality of possible routes 704 and 705 connected with part of traffic nodes 706 and traffic links 707, and a fractional traffic link 708.
  • the traffic links 707 have free flow travel times 709 defined by equation (5) respectively.
  • the definition of free flow travel time 710 follows equation (13). Pairs of the traffic links 707 connected at one of the traffic nodes 706 have transition times 711.
  • the minimum travel time of a possible route is the sum of the free flow travel times and the transition times included in the possible route. If the minimum travel time of the possible route 704 is smaller than the minimum travel time of any other possible route, then the possible route 704 is the candidate route connecting the origin location 702 and the destination location 703.
  • a candidate route may be identified in a round-robin manner, which examines all routes connecting a pair of consecutive candidate locations.
  • the more efficient way of route search is using a shortest path algorithm.
  • the shortest path algorithm described later is an algorithm improved from the Dijkstra's algorithm, and maintains more than one label for each traffic node so that the transition times can be taken into account in searching the candidate route.
  • T max Upper bound of minimum travel time allowed for route search Firstly, an origin location, a destination location and other variables are initialized in step 801 as follows:
  • Step 802 monitors a condition of terminating the route search by examining subset of traffic nodes N q . If this subset is empty, the process of route search terminates; otherwise, step 803 selects a traffic node with minimum label in the subset as follows:
  • This traffic node is eliminated from the subset W q in step 804 as follows to avoid a double search for the same traffic node:
  • step 805 The process of route search is terminated in step 805, if the selected traffic node n a coincides with « dst .
  • the step 806 recognizes that it is physically impossible for a traffic probe to travel from the selected traffic node to « dst even at the anticipated highest speed of the traffic probe on a represented road network, and the selected node is not searched any further.
  • T max needs to be larger to some extent than the exact time interval corresponding to a pair of consecutive reported locations, if a traffic probe may run at more than free flow speed, or if the origin location and the destination location derived from candidate locations may have location errors from true locations.
  • step 807 selects a traffic node from adjacent traffic nodes defined as
  • step 808 assigns new labels. These labels are allowed to change until the turn to examine the selected adjacent traffic node in the step 803 comes later in the algorithm.
  • the transition time assigned to the selected traffic node between the connected traffic links is calculated when the selected adjacent traffic node is searched.
  • the computation applied to the step 808 depends on the status of the selected adjacent traffic node and the labels thereof, shown as follows:
  • n b n dst then n b ))+ ⁇ g (l(Y ,(w ⁇ ), w ⁇ ))+ ⁇ g (Z( w ⁇ , n b )) ⁇ ⁇ arg min ⁇ A,(w e )+T f (Z(w fl , » 5 ))+ ⁇ g (/ [Y 1 (ItJ, n a ))+r g ⁇ l ⁇ n a , n b )) ⁇ otherwise
  • the selected adjacent traffic node is added to the subset of traffic nodes as follows:
  • step 812 recognizes that all the adjacent traffic nodes are examined, the algorithm goes back to the step 802; otherwise, another adjacent traffic node is selected to repeat the steps from 807.
  • the minimum travel time is obtained in step 813 by adding the free flow travel time of l ⁇ n ⁇ sV w dst ) to the first label of « dst .
  • the candidate route is also obtained by tracking pointers defined for precedent location and ascending label from the first pointers of « dst .
  • the number of labels assigned to each traffic node is sufficient with two labels if most traffic nodes are not more complicated than an intersection of two bi-directional flows.
  • Fig. 9 The integrative process of the trajectory estimation 306 is illustrated in Fig. 9.
  • candidate locations 902 and candidate routes 903 are obtained through the methods described earlier.
  • a feasible trajectory is a continuous route on a represented road network connecting some or all of the candidate locations 902 and some or all of the candidate routes 903.
  • the feasible trajectory may substitute another candidate route 904 for one of the candidate routes 903, if the substitute candidate route 904 gives the resulting feasible trajectory a smaller total travel time.
  • a most likely trajectory 905 is selected from the feasible trajectories derived from the sequence of the reported locations 901, and has the minimum value among the feasible trajectories in the meaning of the minimization problem (14) and (15).
  • a provisional trajectory 906 includes part of the most likely trajectory 905, part of a previously stored full trajectory 907, and a route connecting these two partial trajectories.
  • the part of the most likely trajectory 905 is referred to as a first sequence of locations and routes
  • the part of the previously stored full trajectory 907 is referred to as a second sequence of locations and routes.
  • the connecting route may coincide with one of the candidate routes 903. If the provisional trajectory 906 is determined to be consistent in terms of a trajectory of a traffic probe, then the additional part of the provisional trajectory 906 to the previously stored full trajectory 907 is stored as an additional part of the full trajectory data 308.
  • Fig. 10 An algorithm for obtaining a provisional trajectory and determining the consistency thereof is shown in Fig. 10.
  • the algorithm initially sets a range of trajectory history in step 1001, which defines the number of consecutive candidate locations and candidate routes from which to compose feasible trajectories.
  • the range of trajectory history is preferably small like an inclusion of three or four consecutive candidate locations; otherwise, the amount of calculations for obtaining feasible trajectories would considerably increase, being useless for practical purposes.
  • the candidate locations and the candidate routes included in the range of trajectory history are prepared in step 1002.
  • Step 1003 composes connected trajectories using the candidate locations and the candidate routes prepared in the step 1002.
  • the included candidate locations connect the included candidate routes with a correct sequence of time.
  • the possible route 704 is the candidate route as long as the destination location 703 is a candidate location at the latest end of trajectory history. However, if another reported location is provided and the destination location 703 and a candidate location 712 for the another reported location have a candidate route 713, transition times 714 and 715 need to be taken into account. If the transition time 714 is much larger than the transition time 715, the possible route 705 and the candidate route 713 constitute the feasible trajectory connecting the origin location 702 and the candidate location 712 via the previous destination location 703.
  • This type of connected trajectory is revised in step 1004 to determine the feasible trajectories corresponding to the defined range of trajectory history.
  • This revision is performed by replacing several procedures of the shortest path algorithm described earlier with new ones and running this modified algorithm. If route r k (t k ⁇ l , t k ⁇ +1 ) needs to be checked for the validity as a candidate route in a feasible trajectory starting at time **, / founded and ending at time t k I ⁇ (I 0 ⁇ i ⁇ I ⁇ ) , then, at the definition of variables, f « org and m ⁇ sX sxe redefined as the adjacently previous and the next traffic nodes out of * * *(?* , ,> ?; t, , + i) in the connected trajectory respectively.
  • N out another subset of traffic nodes including all the traffic nodes in the connected trajectory except for the traffic nodes included in route r h (h,i> h,i + ⁇ ) is defined as N out , and the line with (*) of the route search algorithm is modified as follows:
  • the free flow travel times and the transition times between the original and the redefined m o ⁇ g and between the original and the redefined m dst need to be subtracted from the value obtained from the modified algorithm, because the redefined m org and m dst should not be included in the revised route.
  • An objective value is assigned to each of the feasible trajectories in step 1005. This value is obtained through the calculation of F(M k , M k )+G(R k ) for each of the feasible trajectories.
  • the location errors for the feasible trajectories used in F(M k , M k ) can be obtained in determining the candidate locations.
  • the total travel time used in G(R k ) can be obtained in determining the revised routes.
  • the parameters used in these functions can be stored as part of the parameters 307.
  • the most likely trajectory can be determined in step 1006 by searching the feasible trajectory with the minimum objective value. This most likely trajectory represents a computational approximation of Z min in equation (15).
  • Step 1007 extracts a first sequence of locations and routes from the most likely trajectory.
  • the candidate locations and the candidate routes connected with the other candidate locations or routes in the middle of the most likely trajectory are more preferable for this extraction than the candidate locations or routes at the ends.
  • a second sequence of locations and routes is extracted from the full trajectory data 308 in step 1008.
  • This extracted sequence covers a different time interval from that of the first sequence of locations and routes, and may contain nothing when the trajectory estimation 306 is first applied to the location data sets 304.
  • a provisional trajectory is formed in step 1009 by connecting the extracted two sequences with a route on the represented road network.
  • the modified algorithm used in the step 1004 is applicable to obtain this route by setting /w org and m dst to the ending location of the second sequence and the starting location of the first sequence respectively, and, if available, by setting « org and « dst to the entering traffic node of the ending traffic link in the second sequence and the exiting traffic node of the starting traffic link in the first sequence respectively.
  • the consistency of the provisional trajectory is evaluated in step 1010.
  • a set of rules is applied to find contradictions within the provisional trajectory.
  • the rules of contradiction need to cover all the possible cases, but may include redundant ones.
  • the rules can be defined mathematically as follows:
  • I 0 index of the starting time for which the consistency should be maintained
  • I 1 index of the ending time of the first sequence
  • /is index of the ending time of the second sequence therefore, r k ⁇ t kJ , t kJ+ ⁇ ) is the route connecting the end of the second sequence and the beginning of the first sequence.
  • Inequalities (31) and (32) examine the distance between a reported location and a candidate location in the provisional trajectory. If this distance is larger than C 1 or smaller than C 2 , then the candidate location at time t kJ+l in the first sequence is determined to be doubtful.
  • the values of C 1 and C 2 can be determined from the statistical attributes of distance error specific to the locating technology.
  • Formula (33) examines the first sequence and the connecting route for irregular concentration of the included candidate locations as a moving traffic probe. When this part of the provisional trajectory indicates that the movement of the traffic probe is restricted to within one traffic link, this sequence is revised to obtain more likely estimates. Inequalities (34) and (35) examine the minimum travel time of connecting route * k (h , i> h,i + ⁇ ) • If the minimum travel time is longer than the time interval of the corresponding consecutive reported locations, the estimated trajectory is incorrect for this time interval unless the traffic probe has violated one or more traffic rules. In any case, this kind of trajectory is regarded as a doubtful result.
  • the value of C 3 preferably takes into account the attributes of the distance error of the locating technology.
  • Inequality (36) examines the candidate locations included in the connecting route.
  • a value less than or equal to C 4 on the left hand side of inequality (36) means a sharp turn, such as a U-turn, at the connected candidate locations. If sharp turns are prohibited or rare, satisfaction of this inequality means a possible contradiction.
  • C 4 is set to zero or some negative value larger than -1 according to definition (19).
  • Formula (37) checks a cyclic sub path brought by the first sequence or the connecting route. This formula means that, if there is no cyclic sub path between the second sequence and the other part of the provisional trajectory, the common subset of these sub trajectories must be limited to the connected location thereof.
  • the connecting route and the first sequence are regarded as part of the true locations and true routes, and are stored as part of the full trajectory data 308 in step 1011.
  • step 1012 checks the range of trajectory history. If the current range of trajectory history is less than a predefined maximum, and more candidate locations and candidate routes are available outside of the current range of trajectory history, then the process of the trajectory estimation 306 continues to make the contradictions resolved; otherwise, this process has no way of obtaining more likely estimates of true locations and true routes, and ends after storing the additional part of the provisional trajectory in the step 1011.
  • step 1013 deletes the most recent part of the full trajectory data 308.
  • the deleted part of the full trajectory is re-estimated in the minimization problem by expanding the range of trajectory history in step 1014 and repeating the process from the step 1002.
  • each of the feasible trajectories should have an objective value in the step 1005. If the objective value of a feasible trajectory is much larger than the minimum pre-specified in the step 1006, then this feasible trajectory can be regarded as an unlikely trajectory. Therefore, it is possible to filter feasible trajectories with a large objective value in step 1015, and to compute a new set of feasible trajectories derived from the renewed range of trajectory history by adding the expanded part of candidate locations and candidate routes to the filtered feasible trajectories.
  • a trajectory 1101 extracted from part of the full trajectory data 308 includes a first location 1102 corresponding to a first reported location 1103 and a route 1104 connecting the first location 1102 and a second location 1105 corresponding to a second reported location 1106.
  • the process defines first likely locations 1107 and second likely locations 1108 for the first location 1102 and the second location 1105 on the trajectory 1101 respectively.
  • a likely route 1109 is defined as a route on the trajectory 1101 which connects one of the first likely locations 1107 and one of the second likely locations 1108 with traffic nodes 1110 and fractional or complete traffic links 1111. This process further determines a set of possible behavior scenarios of a traffic probe for the likely route 1109.
  • Each of the possible behavior scenarios has a different combination of stopping probabilities assigned to each of the traffic links 1111 and a magnitude of traffic congestion uniquely defined through the likely route 1109. Travel times assigned to traffic links 1111 are determined from an integration of these possible behavior scenarios and all the possible likely routes between the first likely locations 1107 and the second likely locations 1108.
  • step 1201 initializes a time interval used through the algorithm.
  • Index of starting time I 0 and index of ending time Z 1 are associated with a pair of reported locations stored as location data sets 304 for the same traffic probe. These indices are not necessarily the same as those used in the trajectory estimation 306, but the time interval needs to be longer than the anticipated maximum travel time of the traffic probe on any traffic link for which a travel time is estimated.
  • Reported locations of the traffic probe included in this time interval are extracted from location data sets 304 in step 1202. These locations are denoted as [m k ⁇ t k>l )
  • a continuous trajectory of the traffic probe corresponding to this time interval is extracted from the full trajectory data 308 in step 1203.
  • This trajectory includes estimates of true locations ⁇ t k (t k l ) ⁇ I 0 ⁇ i ⁇ I ⁇ ⁇ and estimates of true routes
  • each of the estimates of true routes can be decomposed to complete or fractional traffic links as r k (t k l , t k ⁇ + ⁇ )— ⁇ l k ⁇ l:J ⁇ 0 ⁇ j ⁇ J(k, i) ⁇ .
  • the travel times of the traffic links included in the extracted trajectory are accumulated through recursive travel time assignments calculated for pairs of locations each of which corresponds to estimates of two consecutive true locations. One of the pairs is selected in step 1204.
  • Step 1205 determines possible sequences of likely locations and likely routes for the selected pair of locations.
  • One of these sequences, z, and an objecitve value assigned to this sequence, z, are defined as follows:
  • Z 4 (Z 0 , Z 1 ) is a set of sequences of likely locations and likely routes completely included in the extracted trajectory, and ⁇ n ⁇ k z (t k ⁇ ) ⁇ and ⁇ r z k (t k ⁇ l , t k ⁇ l+ ⁇ ) ⁇ are likely locations and likely routes included in z respectively.
  • the locations on traffic nodes are not included in the likely locations.
  • the likely locations may be further restricted to the vicinity of the estimates of true locations as follows:
  • I p (i) is the largest integer less than / such that ⁇ f ⁇ l ⁇ ,i p ( ⁇ ,j(k,i r (,))) + ⁇ g ( l k ,/ admir(,) ,j(t , / perhaps(,))) is positive
  • I n ⁇ i) is the smallest integer more than or equal to / such that ⁇ f( ⁇ ,/ n (;),o)+ ⁇ g('yfc,/ 0 (,),o) is positive
  • C is the same threshold value used in inequalities (29) and (30).
  • / p (z) and / n (z) exclude the estimates of true routes containing zero free flow travel times and zero transition times from the sequence of traffic links.
  • a certain number of discrete locations are extracted to assign travel times to the likely route uniquely determined by a sequence of the extracted locations. The possible resolution for these discrete locations depends on the computational capacity of the travel time estimation 309.
  • the process of travel time assignment would be more efficient by restricting derivation of likely locations to those for t k j and t k ;+1 , and by using only estimates of true locations for the other times. In this case, based on the assumption that the traffic probe never proceeds backward on the same traffic link, the estimates of true locations at the times between t Ir ⁇ i) and t ⁇ or between t i+2 and
  • ⁇ /n (, + i) may be moved backward or forward respectively, when i"l(t k ⁇ i , t kti+ ⁇ ) expands the estimate of true route for the same time interval backward or forward.
  • the set of sequences resulting from this restriction is defined as Z ⁇ 1 (I 01 I 1 ) , and can be substituted for
  • Step 1206 selects one of the sequences of likely locations and likely routes.
  • the set of the selected likely routes is denoted as ⁇ r k z (t kJ , t kJ+ ⁇ ) ⁇ I 0 ⁇ i ⁇ I 1 —l ⁇
  • each of the selected likely routes can be decomposed as iJ ⁇ O ⁇ j ⁇ J z ⁇ k, i) ⁇
  • J z (k, i) is the maximum number of complete or fractional traffic links included in r z k (t kJ , t k j+l ) .
  • a probability for the existence of the selected sequence is determined on the basis of exponential deviation from the redefined Z mjn as follows:
  • Step 1207 determines travel times of the traffic links included in the selected likely route between a pair of consecutive likely locations. This step requires a series of definitions. Suppose that the time indices of these consecutive likely locations are / and /+1, and that z is the unique sequence included in Z k j (l o , l ⁇ ) , the time interval of these consecutive likely locations are decomposed as follows:
  • ⁇ s (l z k l ⁇ J ) is the time consumed for stopping on complete or fractional link ll tliJ in- response to traffic control
  • ⁇ c is the time consumed for traffic congestion on the likely route.
  • Time for deceleration and acceleration of the traffic probe required in association with traffic control is assumed to be included in ⁇ s ⁇ l z k l J ) as well as the time for a complete stop of the traffic probe.
  • the traffic congestion is assumed to be uniform for any part of the same likely route, and therefore the time consumed for traffic congestion is not separated into the level of traffic link in equation (43).
  • T 0 The possible minimum value of T 0 is zero in any case. This situation corresponds to no congestion in actual traffic flow. Meanwhile, the maximum value of ⁇ 0 is realized when the traffic probe does not include any stopping movement due to traffic control on the likely route. This maximum value is obtained by substituting zero for ⁇ s (l z k hJ ) in equation (43), and defined as follows:
  • the traffic probe is assumed to travel the likely route constantly at a speed slower than the maximum.
  • the magnitude of traffic congestion over the likely route can be determined as follows:
  • w z k ,( ⁇ c ) takes its value between 0 and 1 for any possible value of ⁇ c .
  • the minimum value of w z kJ ( ⁇ c ) is zero when ⁇ c is equal to zero, and the maximum is less than one when ⁇ c is equal to T z c (k, i) (i.e. no stopping time).
  • An exceptional case occurs when the likely route indicates that the traffic probe is stopped at a location during the whole time interval between consecutive likely locations. This exceptional case is handled separately as per the following description.
  • equation (45) implies that a unique value of ⁇ c can be determined when a value of initially given.
  • T 0 is provided as a function of magnitude of traffic congestion:
  • the maximum value of the magnitude of traffic congestion may be affected by other values of magnitude of traffic congestion obtained from the likely routes outside of the time interval between t k i and t k>l+l , if the magnitude of traffic congestion is not considered to change suddenly between consecutive likely routes separated by likely locations.
  • a definition of probability that traffic congestion at the level of w occurs would make the evaluation of possible traffic probe behavior scenarios more reasonable. This definition is given as follows:
  • Equation (47) implies that the value of P z w (k, i, w) is determined through relative comparison of w with the maximum magnitude of traffic congestion in the likely routes involving the i th likely route in wider range, and that a heavy traffic congestion represented by a larger value of w is unlikely to occur when these routes indicate light traffic flow. If this kind of assumption is not applicable, then P z w (k, i, w) may be set to one in any case.
  • Equation (47) creates a time lag for the travel time estimation 309. If such a time lag is not allowable or desirable, then this time lag can be eliminated by setting the second term of the right hand side of equation (47) to one. Equation (47) is applicable when the i th likely route indicates a location.
  • the stopping probability of traffic links is calculated for different scenarios of stopping times and stopping locations with a hypothetically fixed value of w, and then travel times are assigned to the traffic links in the likely route, reflecting all the cases with different values of w. For simplicity of computation, it is preferable to assume that the traffic probe stops only once in each likely route for any possible value of w.
  • Determination of the stopping probability needs a definition of stopping likelihood applied to each location on a traffic link.
  • a knowledge-based definition using the road network data 305, or a simple step function of ⁇ defined in equation (3) may be applicable.
  • the location of stopping tends to be near to the exiting traffic node for low traffic flow, and to exist regardless of the vicinity of the exiting traffic node in heavy traffic flow, then the following function is more preferable for the stopping likelihood:
  • This function can be applied when the value of w is positive and less than one.
  • the stopping likelihood in the traffic link exponentially increases as ⁇ increases, and the stopping likelihood at the upstream end of the traffic link is significantly smaller than at the downstream end.
  • the stopping likelihood is similar regardless of the location on the traffic link.
  • the stopping likelihood has a mixed structure of those two boundary conditions. It should be noted that h( ⁇ , w) always takes its value between 0 and 1 for any possible combination of ⁇ and w.
  • Variable p relates to an equivalent point of stopping likelihood.
  • the stopping likelihood is always equal to half for any value of w when 1— ⁇ is equal to w, that is, when the parametric location on the traffic link measured from its exiting node coincides to the magnitude of traffic congestion.
  • the conditional probability of stopping on a complete or fractional traffic link included in the likely route is given as the average of the stopping likelihood for the locations covered by the traffic link.
  • conditional stopping probability becomes equivalent to the stopping likelihood when A 1 is equal to ⁇ 2 (i.e. a likely route indicating a complete stop at a location).
  • ⁇ 2 i.e. a likely route indicating a complete stop at a location.
  • the upper case of definition (50) corresponds to a likely route composed of only one traffic link or only a location.
  • ⁇ ( ⁇ , z) is the sum of probabilities accounting for all the likely routes associated with the pair of locations selected in the step 1204 and all the possible behavior scenarios derived from these likely routes, given by
  • Equation (54) implies that the time due to traffic congestion in a likely route is divided according to the proportion of the sum of the free flow travel time and the transition time of the traffic link to that of all traffic links in the likely route.
  • the same definition as equation (55) is applied to this case.
  • the travel times assigned to the traffic links in the likely route is given by the sum of the probabilistic free flow travel time, probabilistic transition time, probabilistic stopping time, and probabilistic time for traffic congestion as follows:
  • This probabilistic travel time is accumulated by traffic link as the result of the step 1207.
  • Step 1208 makes the steps 1206 and 1207 repeated until p ⁇ l z k:ltJ ) is determined for all the traffic links included in all the likely routes derived from the pair of consecutive locations selected in the step 1204.
  • step 1209 makes the computation from the step 1204 repeated with one of the unselected pairs of consecutive locations; otherwise, the computation of travel time assignment ends.
  • the accumulated probabilistic travel times assigned to a traffic link are stored as one of the travel time data sets 310 in step 1210, if all the sequences used for travel time assignment internally cover this traffic link.
  • the travel time included in this data set is calculated as follows:
  • 1[A] is an index function, which is equal to one when statement A is true, and zero when it is false.
  • a travel completion time defined as the time when a traffic probe finishes traversing a traffic link. This time also means the time when this traffic probe enters the consecutive traffic link.
  • a travel completion time may be associated with one of the travel time data sets 310.
  • the travel completion time for a traffic link included in the full trajectory data 308 can be given by the sum of the time of a past estimate of true location and the travel times for part of the full trajectory connecting this past estimate of true location and the exiting location of this traffic link.
  • this part of the full trajectory is defined as an empty set ⁇ .
  • the travel completion time for this traffic link can be calculated by using definition (63) as follows:
  • a traffic probe refers to any type of vehicle, carriage, and traveler moving on a real road network, such as a pedestrian, a private vehicle, a public transit vehicle, a fleet vehicle, and the like.
  • a mobile station refers to any type of device that can physically move with a traffic probe, measure a geographical location thereof, and communicate with another device physically separated, such as a cellular phone, a mobile terminal implementing a GPS, an electronic tag, and the like.
  • Another equivalent system may be possible by physically separating or integrating part of the individual components of the described system, or by modifying the number of components included in the described system.
  • the process of trajectory estimation is formulated as a minimization problem, but this approach is not indispensable in obtaining the estimates of true locations and true routes.
  • Another formulation by minimizing or maximizing an alternative objective function or some other types of optimization problem may also be possible.
  • the point is to fuse both the location measurements and the feasible trajectories through quantification so that the feasible trajectories can be objectively ranked and that the most likely trajectory can be selected.
  • the definitions of free flow travel time and transition time can be replaced with values obtained from the road network data, from the traffic management system, or from a combination thereof, as long as the former and the latter are specific to each traffic link and each pair of traffic links respectively.
  • the formulae including the rules of contradiction applied to a provisional trajectory and the stopping likelihood function are changeable in accordance with the characteristics of traffic probe and mobile station.
  • Another equivalent algorithm achieving the same functionality as one of the described algorithms may be possible by altering the order of computations.

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Abstract

L’invention concerne un système et un procédé d’évaluation des temps de parcours de sondes de circulation en évaluant les véritables emplacements et les véritables itinéraires d’une sonde de circulation. Le système comporte : un système de référencement d’emplacement qui envoie de manière intermittente un ensemble de données d’emplacement ; un récepteur d’emplacement ; une mémoire d’emplacement ; un système de stockage de carte représentant un véritable réseau routier utilisant des nœuds de circulation et un ensemble de liaisons de circulation, chaque liaison de circulation étant associée à une connexion entre deux desdits nœuds de circulation ; une mémoire de paramètres stockant des paramètres servant à évaluer les véritables emplacements et les véritables itinéraires ; un processeur de trajectoire permettant de déterminer les trajectoires possibles ; une mémoire de travail de trajectoire ; un processeur de temps de parcours permettant de traiter les ensembles de données d’emplacement, une partie des données de réseau routier, une partie des données complètes de trajectoire, et de déterminer un ensemble de temps de parcours évalués, chaque temps de parcours étant associé à l’une des liaisons de circulation ; une mémoire de travail de temps de parcours et une mémoire ; un émetteur de temps de parcours ; un contrôleur de système permettant d’assigner des connexions de liaison de communication ; et un système de gestion de circulation avec un récepteur de temps de parcours pour recevoir une partie des ensembles de données de temps de parcours stockés. Le procédé d’évaluation des véritables emplacements et des véritables itinéraires englobe la génération intermittente d’un ensemble de données d’emplacement associé à une latitude et une longitude de la terre et d'un enregistrement de temps ; le stockage en outre de l’ensemble de données d’emplacement dans une mémoire ; la génération de la trajectoire la plus probable ; la rétention de données complètes de trajectoire dans une mémoire de trajectoire ; la génération et le stockage d’ensembles de données de temps de parcours associées aux liaisons de circulation enregistrées ; et la réception d’ensembles de données de temps de parcours.
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