JP2007241429A - Traffic flow parameter calculation system, method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately calculate a traffic flow parameter in simple system configurations. <P>SOLUTION: This traffic flow parameter calculation system is configured to acquire vehicle location data from an on-vehicle device loaded on at least two vehicles traveling on a target road entering an intersection, and to calculate the number S of passing vehicles interposed between passage time t11 and t21 of the vehicle sensors of two vehicles, and to calculate an inter-stop vehicle distance Lh, a saturated traffic flow rate Qs, a saturated start time interval Ts and an inter-line start time interval Tq at the intersection based on locations Lt1 and Lt2 included in the vehicle location data and the number S of the passing vehicle. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a traffic flow parameter estimation technique required for realizing signal control on a ground system, safe driving support and environmental countermeasure support on a vehicle system. Here, “traffic flow parameters” are data that universally express the behavioral characteristics of traffic and do not change on average if the environmental conditions (vehicle, weather, regional conditions) are the same. is there. For example, there are in-matrix travel speed Vq, start wave propagation speed Vw, saturated traffic flow rate Qs, stop-to-head distance Lh, saturation start time interval Ts, and in-matrix start time interval Tq.

Regarding the technology for estimating traffic flow parameters, in the past known technology,
In either case, a vehicle detector or the like is installed on the road, and the behavior of the vehicle is analyzed to calculate specific traffic flow parameters.
As an example of the traffic flow parameter, a saturated traffic flow rate will be described.
The saturated traffic flow rate is the maximum number of vehicles that can pass through an intersection at a green light. It is a very important traffic flow parameter in traffic management. When there is sufficient traffic demand upstream of the intersection, the traffic volume per unit blue hour is the number of traffic per hour.

For example, in Patent Document 1, a saturated traffic flow rate is directly calculated by measuring the number of vehicles flowing into the intersection when the signal of the inflow path is blue, for example, by installing a sensor near the stop line at the intersection. ing.
JP 2002-109681 A

  Saturated traffic flow rate includes traffic conditions (turn right / left, oncoming straight car, crossing pedestrian, vehicle type, driving quality), road conditions (lane width, road gradient, intersection shape), weather conditions (heavy rain, clear weather, snowfall / snow cover) ), Time conditions (morning, noon, evening, night), regional conditions (whether there are bus stops, parking stops, regional characteristics), etc. Used.

This modification, while appropriate based on sensory experience, is very expensive and expensive. In addition, it is not possible to cope with a location that fluctuates depending on conditions, and there is a problem in terms of accuracy.
Therefore, an object of the present invention is to provide a traffic flow parameter calculation system, method and program capable of accurately calculating a traffic flow parameter with a simple system configuration.

In this section, reference numerals used in the “best mode for carrying out the invention” are added and described.
The traffic flow parameter calculation system of the present invention includes probe data acquisition means for acquiring data including vehicle position data measured multiple times in time series from an in-vehicle device mounted on a vehicle entering an intersection,
Based on the vehicle position data acquired by the probe data acquisition means, the in-matrix running speed Vq, the starting wave propagation speed Vw, the saturated traffic flow rate Qs, the stop-to-head distance Lh, the saturated starting time interval Ts, the in-matrix starting And processing means for calculating at least one of the time intervals Tq.

In this system, the vehicle position data collected by the in-vehicle device is used to drive the traffic flow parameters in-matrix travel speed Vq, starting wave propagation speed Vw, saturation traffic flow rate Qs, stop head distance Lh, saturation start. At least one of the time interval Ts and the in-matrix start time interval Tq is calculated.
Many traffic flow parameters can be calculated based on the vehicle position data collected by the in-vehicle device, which is very advantageous in terms of cost.

For example, the traffic flow parameter calculation system can calculate the in-matrix travel speed Vq based on information of the vehicle stop position Lt1, the stop end time t1, and the intersection passage time t2 extracted from the vehicle position data. .
Further, if the signal lamp color control data acquisition means for acquiring the signal lamp color control data including the green signal start time is further provided, the vehicle stop position Lt1 and the stop at the intersection extracted from the vehicle position data and the green signal start time tg. Based on the end time t1, the propagation velocity Vw of the starting wave can be calculated.

  The traffic flow parameter calculation system according to the present invention includes vehicle detection data acquisition means for acquiring vehicle detection data from a vehicle detector installed upstream of the intersection, and signal lamp color control for acquiring signal lamp color control data including a green signal start time. If further provided with data acquisition means, the probe data acquisition means acquires vehicle position data from an in-vehicle device mounted on at least two vehicles traveling on the target road entering the intersection, and the processing means Calculates the passing vehicle number S of vehicles sandwiched between the passing times t11 and t21 of the vehicle detector of the two vehicles extracted from the vehicle position data using the vehicle detection data, and the vehicle position data Based on the stop positions Lt1 and Lt2 of the vehicle, the number S of passing vehicles of the vehicle, and the green signal start time tg at the intersection extracted from Distance Lh, saturation flow rate Qs, saturated starting time interval Ts, can be calculated at least one matrix in the starting time interval Tq.

In this system, vehicle sensing data measured by the ground system and signal light color control data are used, vehicle position data is acquired from an in-vehicle device mounted on at least two vehicles, and vehicles of the two vehicles are obtained. By calculating the passing vehicle number S of vehicles sandwiched between the passing times t11 and t21 of the sensor, the traffic flow parameters can be calculated more accurately.
For example, when the two vehicles are vehicles passing through an intersection with a red light in between, the number S of vehicles passing between the two vehicles is determined as the first of the two vehicles. After passing the intersection, the number of vehicles that passed during the green light is equal to the sum of the number of vehicles that have stopped at the next red light and queued in front of the second vehicle. It is possible to estimate at least one of the distance Lh between the stop heads, the saturation traffic flow rate Qs, the saturation start time interval Ts, and the in-matrix start time interval Tq.

  Further, when the two vehicles are vehicles passing through an intersection within the same green light time, the number S of vehicles passing between the two vehicles is determined as the first of the two vehicles. Supposing that it is equal to the sum of the number of vehicles queued between the vehicle and the second vehicle, the distance Lh between the stop heads, the saturation traffic flow rate Qs, the saturation start time interval Ts, the start time interval in the queue At least one of Tq can be estimated.

  Further, the traffic flow parameter calculation system of the present invention is obtained by the vehicle sensor if it further comprises vehicle detection data acquisition means for acquiring vehicle detection data from a vehicle detector installed upstream of the intersection, The average vehicle length is estimated using the data on the occupancy time or occupancy rate of the passing vehicle and the speed of the vehicle. It is also possible to calculate at least one of Ts and the in-matrix start time interval Tq.

Further, the average vehicle length is estimated by using the data of the occupation time or the occupation rate of the passing vehicle obtained by the vehicle sensor and the vehicle speed data obtained by the probe data acquisition means, and the average vehicle length is calculated. It is also possible to calculate at least one of the distance Lh between the stopped vehicle heads, the saturated traffic flow rate Qs, the saturated start time interval Ts, and the in-matrix start time interval Tq.
In addition, when the target road entering the intersection is a road having a branch road with inflow / outflow, the target road with inflow / outflow entering the intersection from an in-vehicle device mounted on three or more vehicles. Vehicle position data for traveling is obtained, and the processing means includes a number obtained by subtracting the inflow / outflow traffic volume from the number of vehicles passing between two vehicles out of the three or more vehicles, Using the number of passing vehicles of the vehicle sandwiched between the other two of the three or more vehicles minus the inflow / outflow traffic volume, the inflow / outflow deduction traffic volume, It is possible to estimate at least one of the stop head-to-head distance Lh, the saturated traffic flow rate Qs, the saturated start time interval Ts, and the in-matrix start time interval Tq.

  For example, if the two vehicles out of the three or more vehicles are vehicles passing through an intersection with a red light in between, the inflow and outflow of vehicles passing between the two vehicles The number of vehicles excluding deducted traffic is the number of vehicles passing during the green light after the first vehicle of the two vehicles passes the intersection, and the second vehicle stopped at the next red light. Is equal to the sum of the number of vehicles queuing in front of the vehicle, and the other two of the three or more vehicles are vehicles passing the intersection within the same green light time, The number obtained by subtracting the inflow / outflow traffic from the number of vehicles passing between the two vehicles is calculated between the first vehicle and the second vehicle of the two vehicles. Subtracting the inflow and outflow, assuming that it is equal to the sum of the number of vehicles in the queue. The amount can be estimated stop headway distance Lh, saturation flow rate Qs, saturated starting time interval Ts, at least one of the matrix in the starting time interval Tq.

The “two vehicles” and the “other two vehicles” are vehicles selected from any combination of three or more probe vehicles. There may be a plurality of combinations. If there are multiple combinations, an equation can be established for each. Thereby, traffic flow parameters can be calculated with good accuracy.
In addition, one of the selected “two vehicles” and one of the “other two vehicles” may be a common vehicle, and “two vehicles” and “the other two vehicles” All of the “vehicles” may be completely different vehicles.

  The method and program for calculating traffic flow parameters at an intersection according to the present invention are a method and program according to the substantially same invention as that of the traffic flow parameter calculation system.

  Conventionally, traffic quantities (traffic volume, occupancy time, speed) using existing sensors installed for signal control, such as optical beacons, ultrasonic detectors, loop detectors, image detectors, etc. However, according to the present invention, the saturation traffic flow rate, which is a basic parameter of traffic flow, is obtained by using probe data (position, speed, and time data) that is collected on the vehicle. , Saturation start time interval, distance between heads at stop (minimum head distance), time interval at start, running speed in matrix, start wave propagation speed, etc. can be calculated efficiently and accurately, which is very useful in terms of cost. It is.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
First, terms are defined.
“Traffic volume”: Number of vehicles passing per unit time.
“Occupied time”: The total time that the vehicle exists in the detection area of the vehicle detector per unit time.
“Occupancy rate”: Occupation time / (unit time)
“Probe vehicle”: A vehicle equipped with an in-vehicle device capable of transmitting data such as a vehicle position, speed, and time required for carrying out the present invention.

“Probe data”: vehicle position, speed, and time data obtained from an in-vehicle device. The probe data is data of the vehicle position, speed, and time every predetermined time, every predetermined distance traveling, every predetermined acceleration / deceleration, or every predetermined azimuth change, and when the vehicle is stopped, the vehicle position when the vehicle starts, Includes speed and time data.
“Queue”: A queue of vehicles waiting for a signal.

“Signal lamp color switching information”: Information related to the switching time of red, blue, and yellow at the intersection.
“Saturated traffic flow rate (Qs)”: The maximum number of vehicles that can pass through the intersection per unit time of green light.
“Traveling speed in queue”: When the vehicles that have formed the queue start from the front in order from the start of the green light, the vehicles that have formed the queue until the stop line is reached. Average speed.

FIG. 1 is a map showing a target intersection and a road flowing into the intersection.
The vehicle detector 1 is installed at a distance Ls from the stop line upstream of the road flowing into the intersection. Moreover, the downstream vehicle detector 2 is installed at the exit of the intersection. As these vehicle sensors 1 and 2, an optical beacon, an ultrasonic sensor, a loop sensor, an image sensor, a far infrared sensor, an infrared sensor, or the like can be used. The vehicle detectors 1 and 2 are often installed for existing signal control.

These vehicle detectors 1 measure traffic volume, occupation time, vehicle speed, and the like.
It is assumed that the road flowing into the intersection has no branch road where the vehicle flows in and out from another road between the intersection and the vehicle detector 1 (if there is a branch road, it will be described later).
FIG. 2 is a graph showing the running behavior of the vehicle at the intersection, where the horizontal axis represents time and the vertical axis represents the distance from the stop line of the intersection.

As the vehicle travels, a travel locus of the vehicle is represented as shown in FIG.
A triangular portion represented by a vertical line represents a queue. The upper side of the triangle represents the stop position of the vehicle that has entered the queue. In the example of FIG. 2, the vehicle first stops at the end of the red signal queue (which may include a yellow signal; the same applies hereinafter). The lower side of the triangle represents a start position of a vehicle that turns green and starts from an intersection. When the light turns green, the vehicle starts from the top of the queue.

Since the stop position and the start position each extend upstream with time, each has a propagation velocity. These are called stop wave and start wave.
The time point at which the stop wave and the start wave cross represents a boundary time point when the stopped vehicle disappears in the queue, and the queue gradually decreases as the vehicle travels. Vehicles entering the intersection after this time will join the running queue.

FIG. 3 is a block diagram showing the overall configuration of the traffic flow parameter calculation system of the present invention.
The traffic flow parameter calculation system includes a ground traffic center 3, a signal control device 4, a road device 5, and a vehicle detector 1.
The ground traffic center 3 includes a processing device 31.
As shown in FIG. 3, the processing device 31 is installed in the same place as the road device 5, but is not necessarily installed in the same place, and is installed in a location different from the road device 5. May be.

The in-vehicle device 6 is mounted on the probe vehicle. The in-vehicle device 6 includes a position detection device such as a GPS receiver, and can detect the position of the host vehicle for each time. The position data acquired by the in-vehicle device 6 is transmitted as probe data from the in-vehicle communication device. The transmitted data is received by the road device 5 and sent to the processing device 31.
As a system for road-to-vehicle communication between the in-vehicle device 6 and the on-road device 5, an optical beacon, wireless LAN, or DSRC (Dedicated Short Range Communication) can be used. Further, communication that directly connects the vehicle and the ground transportation center 3 may be used by a mobile phone, a dedicated radio, or the like.

The signal control device 4 is a device that controls switching of signals at intersections. In the case of using a cellular phone, a dedicated radio, or the like, information on the signal lamp color switching time is sent from the signal control device 4 to the ground traffic center 3.
When the processing device 31 of the ground traffic center 3 acquires the probe data from the in-vehicle device 6, the traveling speed Vq in the queue, the propagation speed Vw of the starting wave, from the vehicle position data and the information of the signal lamp color switching time, At least one of the saturated traffic flow rate Qs, the saturation start time interval Ts, and the in-matrix start time interval Tq is calculated.

FIG. 4 is a flowchart showing the overall procedure of the traffic flow parameter calculation processing of the present invention performed by the processing device 31 of the ground traffic center 3.
All or part of the processing described below is realized by the computer of the processing device 31 executing a program recorded on a predetermined medium such as a CD-ROM or a hard disk.

First, the processing device 31 acquires probe data of a probe vehicle (denoted by C1), and grasps the position and speed for each time (speed may be obtained by differentiating the position) and time (step S1). ).
Next, the time when the probe vehicle C1 stops at the end of the queue, the position, the start time when it starts moving, the time when it stops in the queue, and the time when it passes the stop line at the intersection are calculated (step S2). ).

It is determined whether or not the stop time in the queue is longer than the predetermined time (step S3), and if it is shorter, the process is terminated. This is because it is considered that the position, speed, etc. cannot be measured accurately when the time during which the process is stopped in the matrix is short.
It is determined whether or not the distance between the stop position in the matrix and the stop line is longer than the threshold value (step S4). This is also because it is considered that the position, speed, etc. cannot be measured with high accuracy when the position stopped in the matrix is close to the intersection.

  Next, it is determined whether there is a clogged intersection (step S5). “Clogged” means that the road just downstream of the intersection is congested. If there is a clog, the traffic flow parameters may not be determined accurately, so the process is stopped. Whether there is a clog is determined based on the speed of the probe vehicle after passing through the intersection or the occupation rate or speed measured by the vehicle detector 2 downstream of the intersection.

If there is no clogging, signal light color control data is acquired from the signal control device 4, and vehicle detection data such as traffic volume, occupation rate, and speed are acquired from the vehicle detector 1 (step S6).
Next, the vehicle traveling speed (referred to as the in-queue traveling speed) Vq and the starting wave propagation speed Vw after the start of the green light are calculated (step S7). This calculation method will be described with reference to FIG.
FIG. 5 is a graph showing the behavior of the vehicle at the intersection, where the horizontal axis represents time and the vertical axis represents the distance to the intersection.

The probe data of the probe vehicle that has passed through the stop line of the intersection through the target road is received by the road device 5 and accumulated in the ground traffic center 3.
When this is analyzed, the time when the probe vehicle passes through each point of the target road and the speed at each time are obtained. The travel locus is plotted in FIG.
The green signal start time is tg, the time when the probe vehicle hits the queue is t0, and the time when the vehicle starts from the head of the queue is t1. Let t2 be the time of arrival at the stop line at the intersection. Let Lt1 be the distance to the stop position of the intersection when the probe vehicle is stopped.

The starting speed Vq and the starting wave propagation speed Vw can be obtained by the following equations based on geometric considerations.
Vq = Lt1 / (t2-t1) (1 set)
Vw = Lt1 / (t1-tg) (2 formulas)
Next, the stop head-to-head distance Lh is calculated, and using this stop head-to-head distance Lh, the saturated traffic flow rate Qs, the saturation start time interval Ts, and the in-matrix start time interval Tq are calculated (step S8). ).

Hereinafter, a method for calculating these traffic flow parameters will be described in detail.
If the number of vehicles in the queue from the stop line to the distance Lt1 is Et1, and the distance between the stop heads of the queue (the distance between the front and rear vehicle heads; see FIG. 6) is the stop head distance Lh, then Lt1 = Et1Lh A relationship is established.
The saturated traffic flow rate Qs, which is the maximum number of vehicles that can pass through the intersection per green light unit time, is expressed as follows, where the unit of time t is seconds (where the road immediately downstream from the intersection is congested): It is assumed that there is no clogging of the intersection, and “maximum” of the maximum number of passable vehicles means that there is no clogging of the intersection).

Qs = 3600Et1 / (t2-tg) = 3600Lt1 / {Lh (t2-tg)} (3 formulas)
The saturation start time interval Ts that is the reciprocal of the saturated traffic flow rate Qs is as follows.
Ts = 3600 / Qs = (t2-tg) / Et1 = Lh (t2-tg) / Lt1 (4 formulas)
The in-matrix start time interval Tq of a vehicle stopped in the matrix is obtained from the following equation.
Tq = Lh / Vw (5 formulas)
In order to obtain the saturated traffic flow rate Qs, the saturation start time interval Ts, and the in-matrix start time interval Tq, it is necessary to know the distance Lh between the stopped vehicle heads.

However, the distance Lh between the stop heads cannot be set to a constant value because it changes depending on the ratio of large vehicles in the queue.
Therefore, the distance Lh between the stop heads is obtained by the methods (a) to (c) described below.
(A) Method of using the number of passing vehicles measured by the vehicle detector 1 and the probe data of two probe vehicles
(a-1) When a red signal time exists between two probe vehicles passing through the intersection FIG. 7 shows a vehicle trajectory in which two probe vehicles C1 and C2 travel on the target road. The time when these two vehicles C1 and C2 pass the installation point of the vehicle detector 1 upstream of the intersection is defined as t11 and t21.

The number S of passing vehicles between these times t11 and t21 can be measured by the vehicle detector 1.
A position where the vehicle C1 stops in the queue is represented by Lt1, and a position where the vehicle C2 stops in the queue is represented by Lt2. The time when the vehicle C1 passes the stop line at the intersection is t12, and the time when the vehicle C2 passes the stop line at the intersection is t22.

Each vehicle that has passed the vehicle detector 1 during this time t11, t21 has already passed the stop line at the intersection when the vehicle C2 arrives at the end of the queue, or exists in the queue in front of the vehicle C2. Either.
When traffic flows out without any gaps during the green hours, the traffic volume at the green traffic light is saturated (this is the case when there is a traffic jam where there is more than one traffic signal waiting at the intersection).

When the amount of traffic passing by the green light is saturated, the number S of passing vehicles is expressed by the following equation, where Tg is the time from the start to the end of the green light.
S = Qs (tg + Tg-t12) / 3600 + Lt2 / Lh (6 formulas)
The first term on the right side of (Expression 6) represents the number of vehicles that have passed through the stop line at the intersection between time t21 when the first probe vehicle has passed the stop line at the intersection and until the green light ends. ing. The second term on the right side represents the number of vehicles that stopped at the next red light without passing the stop line at the intersection during the blue hour.

Substituting the equation of the saturated traffic flow rate Qs shown in (Equation 3) into (Equation 6),
S = Lt1 (tg + Tg-t12) / {Lh (t12-tg)} + Lt2 / Lh
(Formula 6 ')
It becomes. However, t2 in (Expression 3) is replaced with t12.
The stop positions Lt1 and Lt2 are included in the data rising from both probe vehicles, and the passing vehicle number S is an amount that can be measured by the vehicle detector 1, so the distance Lh between the stop vehicle heads is calculated from the equation (6 ′). it can.

If the distance Lh between the stopped vehicle heads can be calculated, the saturated traffic flow rate Qs can be calculated from (Expression 3), the saturated start time interval Ts can be calculated from (Expression 4), and the in-matrix start time interval Tq can be calculated from (Expression 5). .
It can be determined as follows whether the traffic volume at the green light is saturated, that is, whether there is a traffic congestion so that there is a vehicle that waits more than twice at the intersection.

A distance (for example, about 150 m upstream from the intersection) is set so that when the signal queue is extended so far, the signal will wait twice or more, and a vehicle detector 1 for traffic jam detection is separately installed at this point. If the occupation time or the occupation rate obtained by the vehicle sensor 1 is higher than a predetermined threshold, it can be determined that the traffic jam has spread to this point.
(a-2) When two probe vehicles are able to pass through the intersection within the same green light time FIG. 8 is a graph showing a travel locus when two probe vehicles exist in the same queue.

In FIG. 7, the rear vehicle C2 of the two probe vehicles C1 and C2 is caught by a red signal on the target road, but both of the two vehicles C1 and C2 can pass through the green signal.
A method for obtaining the distance Lh between the stopped vehicle heads in this case is shown below.
In FIG. 8, the time when these two vehicles C1 and C2 pass the installation point of the vehicle detector 1 upstream of the intersection is defined as t11 and t21.

The number of passing vehicles between these times t11 and t21 is S '. The passing vehicle number S ′ can be measured by the vehicle detector 1.
The position where the vehicle C1 stops in the queue is denoted by Lt1 ′, and the position where the vehicle C2 stops in the queue is denoted by Lt2 ′. Let t12 be the time when the vehicle C1 has passed the stop line at the intersection, and t22 be the time when the vehicle C2 has passed the stop line at the intersection.

Since the two vehicles C1 and C2 exist in the same queue, the following (Expression 7) holds instead of (Expression 6).
S ′ = (Lt2′−Lt1 ′) / Lh (7 formulas)
This (Equation 7) indicates that the number of vehicles S ′ can be obtained by dividing the queue length between the two vehicles C 1 and C 2 by the distance Lh between the stop heads. Using this (Expression 7), the distance Lh between the stopped vehicle heads can be obtained directly from the number of vehicles S ′ and Lt2 ′ and Lt1 ′.

If the distance Lh between the stopped vehicle heads can be calculated, the saturated traffic flow rate Qs can be calculated from (Expression 3), the saturated start time interval Ts can be calculated from (Expression 4), and the in-matrix start time interval Tq can be calculated from (Expression 5). .
(B) Method of using the average vehicle length obtained by the vehicle detector 1 By using the vehicle detector 1 installed on the ground, the occupancy time t (seconds) of the passing vehicle and the vehicle speed v (m / second) are obtained. If it can be measured, the distance Lh between the stopped vehicle heads can be obtained by the following method.

The average vehicle length Lc is obtained as follows.
Lc = E [t · v] (Equation 8)
Here, E [*] indicates an average operation of * for a plurality of vehicles passing through the vehicle detector 1.
The average inter-vehicle distance of the stopped vehicles in the queue (distance between the tail of the front vehicle and the head of the rear vehicle; see FIG. 6) Ld may be considered as a constant. can get.

Lh = Lc + Ld (9 formulas)
In this way, since the distance Lh between the stop heads is obtained from the average vehicle length Lc and the average inter-vehicle distance Ld, thereafter, as in (a), the saturated traffic flow rate Qs, the saturated start time interval Ts, the matrix The internal start time interval Tq can be calculated.
(C) A method of using the average vehicle length obtained from the occupancy time of the vehicle detector 1 and the speed obtained by road-to-vehicle communication The occupancy time t (seconds) of each individual vehicle is detected by the vehicle detector 1 installed on the ground. ) Is obtained and the vehicle speed v (m / sec) is not obtained, the average vehicle length is estimated as follows using the speed included in the probe data uplinked from the in-vehicle device 6 .

In this case, since the number of probe vehicles that can uplink the vehicle speed v is limited, the number of samples of the speed v is smaller than that in (b), but the data of the velocity v can still be acquired from a plurality of probe vehicles. Consider the case.
Each probe vehicle is represented by a subscript i (i = 1, 2, 3,...). The average value of the speed data vi is E [vi], the average value of the occupation time ti is E [ti], and deviations from the average values of the respective data are Δvi and Δti.

When expressed with the subscript omitted, the average vehicle length Lc is as follows. However, E [Δv] = E [Δt] = 0.
Lc = E [(E [t] + Δt) (E [v] + Δv)]
= E [t] E [v] + E [t] E [Δv] + E [Δt] E [v] + E [ΔtΔv]
= E [t] E [v] + E [ΔtΔv] (Equation 10)
When it is quiet, there is a large variation in speed, and each probe vehicle does not always run on average. In addition, the accuracy cannot be obtained because the speed changes greatly every time when the traffic is low.

Therefore, a calculation at the time of near saturation where the velocity data hardly changes between the probe vehicle and the vehicles before and after the probe vehicle is considered.
Near-saturation means that the traffic volume is gradually increasing, the traffic density is high, and it is difficult to run or overtake at any speed.
FIG. 9 is a graph for determining near saturation, with the horizontal axis representing the occupation ratio and the vertical axis representing the traffic volume. If the occupancy increases, it becomes near saturation from the non-saturated state, and if the occupancy increases further, it becomes supersaturated.

Whether it is near-saturation can be determined by comparing the occupation rate and the threshold value as shown in FIG. An occupation time may be used instead of the occupation ratio.
Since Δv≈0 at near saturation, E [ΔtΔv] ≈0, and it is considered that the speed vp of the probe vehicle represents the speed of the preceding and following vehicles. Therefore, the average vehicle length can be obtained by the following equation. it can.

Lc = E [t] E [vp] (Formula 11)
The distance Lh between the stop heads at the time of stop is obtained by (Equation 9) as in (b), and the saturated traffic flow rates Qs, Ts, Tq can also be obtained using this.
In the case described above, using the probe data of the two probe vehicles, various traffic flow parameters such as the distance Lh between the stop heads, the saturation traffic flow rate Qs, the saturation start time interval Ts, and the in-matrix start time interval Tq are obtained. However, in order to improve the calculation accuracy of the traffic flow parameter, a plurality of (Expression 1) to (Expression 7) may be used by using three or more probe data. If there are a plurality of equations, a plurality of solutions can be obtained. Therefore, the calculation accuracy can be improved by performing statistical processing such as averaging the solutions.

Since various parameters do not change greatly in a short time, they may be averaged or smoothed in consideration of data calculated in the past.
Further, when a large amount of probe data is obtained, data indicating an abnormal value of the speed of the non-congested portion may be removed, or only data around the median speed may be used.
In the description so far, it has been assumed that the road flowing into the intersection has no branch road between the intersection and the vehicle detector 1 where vehicles flow in and out from other roads. The road that flows into the road may have a branch road between the intersection and the vehicle detector 1 from which the vehicle flows in and out from another road.

Next, how to obtain the traffic flow parameters in this case will be described.
FIG. 10 is a map showing an intersection and a road flowing into the intersection.
The road flowing into the intersection has a branch road between the intersection and the vehicle detector 1 through which vehicles flow in and out from other roads.
When there is traffic inflow / outflow on the target road, the methods (b) and (c) can be handled without any influence, but the vehicle detector 1 counts the number of passing vehicles with the vehicle detector 1 and the vehicle counted. Since some of them flow into and out of the branch road, they cannot be handled as they are.

For this reason, the following assumptions are used to modify (Equation 6) and (Equation 7).
That is, it is assumed that the deducted traffic volume flowing into and out of the target road is constant when averaged over a time range longer than the threshold.
Therefore, the subtracted traffic volume (inflow traffic volume-outflow traffic volume) per unit time on the target road is defined as Qio.

Assume that three probe vehicles C1, C2, and C3 pass through the intersection, of which two probe vehicles, for example, C1 and C2, pass through the intersection with a red signal time in between, and two probe vehicles, for example, C2 Suppose C3 did not pinch a red signal.
Based on the probe data of the probe vehicles C1 and C2 that sandwich the red signal, the equation (6 ′) can be modified as follows.
S-Qio (t21-t11) ≈Lt1 (tg + Tg-t12) / {Lh (t12-tg)} + Lt2 / Lh (Equation 12)
Here, the position where the vehicle C1 stops in the queue is denoted by Lt1, and the position where the vehicle C2 stops in the queue is denoted by Lt2. The time when the vehicle C1 passes the stop line at the intersection is t12, and the time when the vehicle C2 passes the stop line at the intersection is t22. t11 and t21 are times when two vehicles C1 and C2 pass the installation point of the vehicle detector 1 upstream of the intersection. S is the number of vehicles passing between these times t11 and t21.

Further, based on the probe data of the two probe vehicles C2 and C3 that do not sandwich the red signal, (Expression 7) can be similarly approximated as follows.
S′−Qio (t21′−t11 ′) ≈ (Lt2′−Lt1 ′) / Lh (13 formulas)
Here, the position where the vehicle C1 stops in the queue is represented by Lt1 ′, and the position where the vehicle C2 stops in the queue is represented by Lt2 ′. The time at which the vehicle C1 has passed the stop line at the intersection is t12 ', and the time at which the vehicle C2 has passed the stop line at the intersection is t22'.

Accordingly, Qio and the stop-to-head distance Lh can be calculated by solving (Equation 12) and (13) as an equation with Qio and the stop-to-head distance Lh as unknowns.
Using this, saturated traffic flow rates Qs, Ts, and Tq can also be obtained.
Of the three probe vehicles C1, C2, and C3, for example, C1 and C2 pass through the intersection with a red signal time in between, and C3 passes through the intersection with a red signal time after C2. Then, (Equation 12) is obtained two. Even if these two (Equation 12) are solved as equations with Qio and the distance Lh between the stopped vehicle heads as unknowns, Qio and the distance Lh between the stopped vehicle heads can be calculated, and using this, the saturated traffic flow rate Qs, Ts and Tq can also be obtained.

Furthermore, if the three probe vehicles C1, C2, and C3 pass through the same blue signal without sandwiching a red signal, two (13) are obtained. Even if these two (Equation 13) are solved as equations with Qio and the distance Lh between the stopped vehicle heads as unknowns, Qio and the distance Lh between the stopped vehicle heads can be calculated, and the saturated traffic flow rate Qs, Ts and Tq can also be obtained.
It is also possible to create simultaneous equations based on probe data of more probe vehicles. For example, there are four probe vehicles C1, C2, C3, and C4, and two sets of two vehicles are made by arbitrarily combining them, and from the first set (12 formulas) or (13 formulas) If (Equation 12) or (Equation 13) is obtained from another set and two equations in total can be obtained, the distance Lh between stop vehicle heads can be calculated, and using this, the saturated traffic flow The rates Qs, Ts, and Tq can also be obtained.

It is a map depicting an intersection and a target road without a branch road that enters the intersection. It is a graph showing the behavior of the vehicle which approachs an intersection. It is a whole block diagram which shows the calculation system of a traffic flow parameter. It is a flowchart which shows the whole traffic flow parameter calculation process of this invention which the processing apparatus 31 of the ground traffic center 3 performs. It is a graph showing the behavior of the vehicle which approachs an intersection. It is a schematic diagram for demonstrating the distance Lh between stop vehicle heads. It is a graph showing the behavior of a vehicle when two probe vehicles C1 and C2 each passing through an intersection on a target road with a red light in between travel. It is a graph showing the behavior of the vehicle when two probe vehicles C1 and C2 passing through the intersection within the same green light time travel on the target road. It is a graph for judging near saturation of traffic. It is a map depicting an intersection and a target road with a branch road that enters the intersection.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Vehicle detector 2 Downstream vehicle detector 3 Ground traffic center 4 Signal control apparatus 5 Roadside apparatus 6 In-vehicle apparatus 31 Processing apparatus

Claims (12)

A system for calculating traffic flow parameters at an intersection,
Probe data acquisition means for acquiring data including vehicle position data measured multiple times in time series from an in-vehicle device mounted on a vehicle entering the intersection;
Based on the vehicle position data acquired by the probe data acquisition means, at least one of in-matrix travel speed, start wave propagation speed, saturated traffic flow rate, stop-to-head distance, saturation start time interval, and in-matrix start time interval And a traffic flow parameter calculation system at an intersection.   The traffic flow parameter calculation system according to claim 1, wherein the processing means calculates the in-matrix travel speed based on a vehicle stop position, stop end time, and intersection passage time at an intersection extracted from the vehicle position data. It further comprises signal lamp color control data acquisition means for acquiring signal lamp color control data including the blue signal start time,
2. The traffic flow parameter calculation according to claim 1, wherein the processing means calculates a propagation speed of a start wave based on the green light start time and a stop position and stop end time of a vehicle at an intersection extracted from the vehicle position data. system. Vehicle detection data acquisition means for acquiring vehicle detection data from a vehicle detector installed upstream of the intersection, and signal lamp color control data acquisition means for acquiring signal lamp color control data including a green signal start time,
The probe data acquisition means acquires vehicle position data from an in-vehicle device mounted on at least two vehicles traveling on a target road entering the intersection,
The processing means uses the vehicle detection data to calculate the number of vehicles passing between the two vehicles extracted from the vehicle position data and the vehicle detector passing time, and from the vehicle position data Based on the stop position of the vehicle at the extracted intersection, the number of passing vehicles of the vehicle, and the green signal start time, at least the distance between the stop heads, the saturated traffic flow rate, the saturation start time interval, and the in-matrix start time interval The system for calculating traffic flow parameters at an intersection according to claim 1, wherein one is calculated. The two vehicles are vehicles that respectively pass through an intersection with a red light in between.
The processing means includes the number of vehicles passing between the two vehicles, the number of vehicles passing between the green lights after the first vehicle of the two vehicles passes through the intersection. If it is equal to the sum of the number of vehicles that have stopped at the next red light and queued in front of the second vehicle, the distance between the stop heads, the saturation traffic flow rate, the saturation start time interval, and the start in the queue The traffic flow parameter calculation system according to claim 4, wherein at least one of the time intervals is estimated. The two vehicles are vehicles that pass an intersection within the same green light time,
The processing means is a vehicle that forms a queue between the first vehicle and the second vehicle of the two vehicles for the number of vehicles passing between the two vehicles. The traffic flow parameter calculation system according to claim 4, wherein at least one of a stop head distance, a saturated traffic flow rate, a saturated start time interval, and an in-matrix start time interval is estimated assuming that it is equal to the sum of the number of vehicles. Vehicle detection data acquisition means for acquiring vehicle detection data from a vehicle detector installed upstream of the intersection,
The processing means includes
The average vehicle length is estimated by using the data of the occupation time or occupation rate of the passing vehicle obtained by the vehicle sensor and the vehicle speed, and the average vehicle length is used to determine the distance between the stop head and the saturated traffic. The traffic flow parameter calculation system according to claim 1, wherein at least one of a flow rate, a saturation start time interval, and an in-matrix start time interval is calculated. Vehicle detection data acquisition means for acquiring vehicle detection data from a vehicle detector installed upstream of the intersection,
The processing means estimates the average vehicle length using the data on the occupation time or occupation ratio of the passing vehicle obtained by the vehicle sensor and the vehicle speed data obtained by the probe data acquisition means, and calculates the average vehicle length. The traffic flow parameter calculation system according to claim 1, wherein at least one of a stop head distance, a saturated traffic flow rate, a saturation start time interval, and a start time interval in a matrix is calculated using a vehicle length. The probe data acquisition means acquires vehicle position data that travels on an inflow / outflow target road that enters the intersection from an in-vehicle device mounted on three or more vehicles,
The processing means includes a number obtained by subtracting the inflow / outflow traffic volume from the number of vehicles passing between two vehicles among the three or more vehicles, and the number of the three or more vehicles. Using the number of vehicles passing between two other vehicles minus the inflow / outflow traffic volume, the inflow / outflow traffic volume, the distance between the stop heads, and the saturated traffic flow rate The traffic flow parameter calculation system according to claim 4, wherein at least one of a saturation start time interval and an in-matrix start time interval is estimated. When the two vehicles out of the three or more vehicles are vehicles that respectively pass through an intersection with a red light in between,
In the processing means, the first vehicle out of the two vehicles has passed the intersection by subtracting the inflow / outflow traffic volume from the number of vehicles passing between the two vehicles. Later, it is set equal to the sum of the number of vehicles passing during the green light and the number of vehicles queued in front of the second vehicle stopped at the next red light,
When the other two vehicles out of the three or more vehicles are vehicles that pass an intersection within the same green light time,
The processing means obtains the number obtained by subtracting the inflow / outflow traffic volume from the number of vehicles passing between the two vehicles, and the first vehicle and the second vehicle among the two vehicles. Putting it equal to the sum of the number of vehicles queuing between vehicles,
The traffic flow parameter calculation according to claim 9, wherein at least one of the subtracted traffic volume of inflow and outflow, the distance between the stop heads, the saturated traffic flow rate, the saturation start time interval, and the in-matrix start time interval is estimated. system. A method for calculating traffic flow parameters at an intersection,
Acquire data including vehicle position data measured multiple times in time series from an in-vehicle device mounted on a vehicle entering the intersection,
Based on the acquired vehicle position data, at least one of in-matrix traveling speed, starting wave propagation speed, saturated traffic flow rate, stop-to-head distance, saturated starting time interval, in-matrix starting time interval is calculated. How to calculate traffic flow parameters at intersections. A program for calculating traffic flow parameters at an intersection,
A procedure for acquiring data including vehicle position data measured multiple times in time series from an in-vehicle device mounted on a vehicle entering the intersection;
A procedure for calculating at least one of in-matrix travel speed, start wave propagation speed, saturated traffic flow rate, stop-to-head distance, saturation start time interval, and in-matrix start time interval based on the acquired vehicle position data. A program for calculating traffic flow parameters at intersections.

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