Information processing apparatus, onboard device, information processing system, and information processing method

According to one embodiment, in general, an information processing apparatus includes one or more processors. The one or more processors receive from an onboard device of a probe vehicle an image showing a vehicle group of one or more vehicles stopping on the same lane, imaging time of the image, and a position of the probe vehicle at the imaging time. The one or more processors select vehicle groups according to the imaging time and an imaging position. The one or more processors identify the selected vehicle groups as a vehicle queue. The one or more processors calculate a stopping vehicle-queue evaluation value. The one or more processors calculate a parking vehicle-queue evaluation value. The one or more processors determine whether the identified vehicle queue is the stopping vehicle queue or the parking vehicle queue.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2018-013048, filed Jan. 29, 2019, the entire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate generally to an information processing apparatus, an onboard device, an information processing system, and an information processing method.

BACKGROUND

Conventionally, acquiring and analyzing information from a probe vehicle in order to understand traffic conditions such as road congestion or to find on-street parking is known. By such a technique, stopping vehicles are detected on the road from an image of the surroundings generated by an imaging device mounted on the probe vehicle, for example.

In view of traffic information management, it is useful to determine whether a detected vehicle has stopped for a certain period or longer or is temporarily stopping, waiting for a traffic light.

Conventionally, there have been demands reducing processing load for determining the status of stopping vehicles, i.e., whether the vehicle has stopped for a certain period or longer or is temporarily stopping on the road.

DETAILED DESCRIPTION

According to one embodiment, in general, an information processing apparatus includes one or more processors. The one or more processors receive from an onboard device f a probe vehicle, en image, imaging time, and a position of the probe vehicle at the imaging time, the image showing a vehicle group including one or more vehicles at a stop on the same lane, the imaging time at which the image is generated. The one or more processors select a plurality of vehicle groups in accordance with the imaging time and the position of the probe vehicle at the imaging time. The one or more processors identify the selected vehicle groups as a vehicle queue. The one or more processors calculate a stopping vehicle-queue evaluation value on the basis of a plurality of stopping vehicle-queue conditions, the stopping vehicle-queue evaluation value that indicates a level of possibility of the identified vehicle queue being a topping vehicle queue that has stopped for a period less than a threshold, the stopping vehicle-queue conditions that define characteristics of the stopping vehicle queue. The one or more processors calculate a parking vehicle-queue evaluation value on the basis of a plurality of parking vehicle-queue conditions, the parking vehicle-queue evaluation value that indicates a level of possibility of the identified vehicle queue being a parking vehicle queue that has stopped for a period not less than the threshold, the parking vehicle-queue conditions that define characteristics of the parking vehicle queue. The one or more processors determine whether the identified vehicle queue is the stopping vehicle queue or the parking vehicle queue, according to the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value.

FIG. 1is a diagram of an exemplary overall configuration of an information processing system S according to the present embodiment. As illustrated inFIG. 1, the information processing system S includes a probe vehicle1and an information processing apparatus B.

The probe vehicle1incorporates an imaging device, a GPS antenna and transmits images and location information thereof to the information processing apparatus8, while traveling on the road. The imaging device of the probe vehicle images vehicles2ato2clocated on the adjacent lane, for example. The vehicles2ato2care referred to as the vehicles2unless they need to be discriminated from each other. AlthoughFIG. 1shows one probe vehicle1alone, the information processing system S includes a plurality of probe vehicles1.

The information processing apparatus8identifies a vehicle queue being at a stop on the road from the image and the location of the probe vehicle1received from the probe vehicle1to determine whether the vehicle queue is stopping or parking. The information processing apparatus8transmits a result of the determination on the vehicle queue, i.e., stopping or parking, and data on the location of the vehicle queue to a traffic information provider9.

In the present embodiment the vehicle queue refers to a plurality of consecutive vehicles2located on the same lane. The inter-vehicle distance between the vehicles2in the queue is defined as two times the length of a standard vehicle2or less, for example. The inter-vehicle distance between the vehicles2in the queue is not limited to this example.

Parking vehicle queue refers to a vehicle queue stopping for a period equal to or above a threshold. Stopping vehicle queue refers to a vehicle queue stopping for a period less than the threshold. The stopping vehicle queue includes a vehicle queue temporarily stopping, waiting for a traffic light or because of traffic congestion, for example. In the present embodiment the threshold for the stopping time is set to 5 minutes, for example, but is not limited thereto. The stopping vehicle queue may be referred to as a temporarily stopping vehicle queue, a vehicle queue waiting for a traffic light, a vehicle queue in traffic congestion.

The probe vehicle1and the information processing apparatus8wirelessly transmit and receive information via a base station7. Information communication means is not limited to this example. A global positioning system (GPS) satellite4transmits GPS radio waves to the probe vehicle1.

The traffic information provider9receives information from the information processing apparatus8and provides drivers and business enterprises with traffic information based on the received information.

FIG. 2is a diagram of an exemplary configuration of the probe vehicle1around a cockpit (a driver's seat according to the present embodiment. The probe vehicle1includes a controller10, imaging devices11aand11b, a rearview mirror BM, and a GPS antenna13. The GPS antenna13receives GPS signals from the GPS satellite4.

The controller10controls the entire probe vehicle1. The controller10is an exemplary onboard device in the present embodiment.

The imaging devices11aand11bconstitute a stereo camera and image the vehicles2ato2clocated ahead of the probe vehicle1at different angles. In the following, the imaging devices11aand11bare collectively referred to as the imaging devices11unless they need to be discriminated from each other. In the present embodiment the angle of view (imaging range) of the imaging devices11is set to cover about three vehicles located on the adjacent lane but is not limited thereto. Also, the imaging devices11generate moving images but may generate still images. The number and location of installation of the imaging devices11are not limited to the ones illustrated inFIG. 2. The imaging devices11may be a monocular camera or a camera that can image a 360-degree range.

FIG. 3is a diagram of an exemplary hardware configuration of the controller10of the probe vehicle according to the present embodiment. The controller10includes a central processing unit (CPU)101, a memory102, a hard disk drive (HUD)103, a tool interface (I/F)104, a GPS module105, a clock circuit106, and a communication interface (I/F)107. The controller10may include a storage medium such as a flash memory in place of the HDD103.

The tool interface104is an interface for connecting to various kinds of tools of the probe vehicle1. The tools include the imaging devices11, an engine control unit (ECU), various kinds of sensors such as a vehicle wheel-speed sensor, a car navigation system, and a smartphone.

The GPS module105calculates a current position (latitude and longitude) of the probe vehicle1based on GPS radio waves received from a plurality of satellites4via the GPS antenna13. The clock circuit106is a circuit having a clock function. The clock circuit106is a real time clock (RTC), for example, but is not limited thereto.

The communication I/F107is an interface for transmitting and receiving information via a network. The communication I/F107is connected to the base station7via a wireless network to transmit and receive information to and from the information processing apparatus8, for example.

FIG. 4is a block diagram of exemplary functions of the controller10of the probe vehicle1according to the present embodiment. As illustrated inFIG. 4, the controller10includes an acquirer110, a vehicle detector111, a measurer112, a vehicle-speed calculator113, a travel determiner114, a vehicle-group identifier115, an attribute detector116, an ID determiner117, and a transmitter118.

The acquirer110acquires various kinds of information via the tool interface104. Specifically, the acquirer110acquires images generated by the imaging devices11at regular time intervals via the tool interface104. The acquirer110of the present embodiment acquires a moving image including a plurality of frames at once but may acquire a still image including one frame at once.

When acquiring the image, the acquirer110acquires, as imaging time, current time at which the image is generated from the clock circuit106. The acquirer110further acquires the position (latitude and longitude) of the probe vehicle at the imaging time of the image as an imaging position from the GPS module105.

The vehicle detector111detects the vehicles2ato2cfrom the image acquired by the acquirer110. Specifically, the vehicle detector111detects the vehicles2ato2cfrom the frames of the image through image processing such as pattern recognition on the frames. The vehicle detection method is not limited to this example.

The measurer112measures the inter-vehicle distance (lengthwise distance) between the probe vehicle1and each of the vehicles2ato2c, the inter-vehicle distances among the vehicles2ato2c, and the lateral distances between the probe vehicle1and the vehicles2ato2cin each frame of the image. In the present embodiment, the lateral distances among the vehicles2ato2care defined as a distance between the centers of the widths of two of the vehicles2. Alternatively, the lateral distance between two of the vehicles2may be set to the distance of a right or left-side space between the two vehicles2.

The measurer112measures the inter-vehicle distances and the lateral distances from stereographic parallax of the imaging devices11aand11b, for example, however, it may use other known methods. The measurer112may generate a depth map based on stereographic parallax and correct the inter-vehicle distances and the lateral distances, referring to the depth map. The measurer112measures the length and width of a vehicle group identified by the vehicle-group identifier115described below and the lateral distance between the probe vehicle1and the vehicle group.

The vehicle-speed calculator113calculates a speed of the vehicle2aclosest to the probe vehicle1among the vehicles2ato2cappearing in the image. Specifically, the vehicle-speed calculator113calculates a relative speed of the vehicle2afrom a change in the inter-vehicle distance between the probe vehicle1and the vehicle2awithin a certain period and calculates the speed of the vehicle2afrom the relative speed of the vehicle2aand the speed of the probe vehicle1.

The travel determiner114determines that the vehicle2ais at a stop or not traveling when the speed of the vehicle2ais 0 km/hour. The travel determiner114may determine that the vehicle2ais not traveling when the vehicle speed is less than a threshold.

The vehicle-group identifier115determines that the vehicles2band2cahead of the vehicle2aon the same lane in the image are also stopping, when the travel determiner114determines that the vehicle2aclosest to the probe vehicle1is stopping. In this case, the vehicle-group identifier115identifies the vehicle2aand the vehicles2band2cas a vehicle group. The vehicles2band2care examples of other vehicles in the present embodiment.

The vehicle group includes one or more vehicles that are located in the imaging range of one imaging by the imaging devices11and at a stop on the same lane. The vehicle-group identifier115determines that the vehicles2band2care present on the same lane as the vehicle2awhen the lateral distance between the vehicle and each of the vehicles2band2cis a threshold or less. The number of the vehicles2of the vehicle group is not limited to three.

The vehicle-group identifier115determines a vehicle group ID of the identified vehicle group. The vehicle-group identifier115counts the number of the vehicles2of the identified vehicle group. The vehicle group is also referred to as a vehicle queue let.

When the travel determiner114determines that one of the vehicles2ato2c, not hidden by the other vehicles and the entire vehicle body of which is shown in the image, is stopping, the vehicle-group identifier115may determine that the other vehicles2are also stopping.

The attribute detector116detects colors and heights of the vehicles2of the vehicle group as attribute information of the vehicles2.

The ID determiner117sets a vehicle ID (identification information) of each of the vehicles2that enables identification of each of the vehicles2detected by the vehicle detector111. The vehicle IDs are numbers such as 1 and 2, for example, but is not limited thereto, and may be alphabets. The ID determiner117of the present embodiment determines consecutive numbers or alphabets as the vehicle IDs of the vehicles2consecutively detected by the vehicle detector111. The ID determiner117uniquely determines the vehicle ID for each vehicle2in at least one image. When determining that the vehicles2detected from different images are the same vehicle2by known image processing or according to the imaging time and the imaging position, the ID determiner117assigns the same vehicle ID to the vehicles2. The ID determiner117is an exemplary identification information determiner in the present embodiment.

The transmitter119associates, for each vehicle group5, the image, the imaging position, the imaging time, the vehicle group ID, the vehicle IDs of the vehicles2of the vehicle group, the various distances measured by the measurer112, the attribute information (color and height) of the vehicles2of the vehicle group, IDs of the imaging devices11, and an ID of the probe vehicle1with one another, to transmit such information to the information processing apparatus8. The information transmitted by the transmitter118is not limited to these examples.

The following describes the details of the information processing apparatus8. The information processing apparatus8represents a server or a personal computer (PC) and has a hardware configuration of a general computer including a CPU, a memory, an HDD, and a communication interface (I/F).

FIG. 5is a block diagram of exemplary functions of the information processing apparatus8according to the present embodiment. As illustrated inFIG. 5, the information processing apparatus8includes a receiver801, a position corrector802, a vehicle-queue identifier903, a stopping evaluator804, a parking evaluator305, a determiner806, an image generator807, a transmitter808, and a storage850.

The storage850stores therein a lane database (CB)851, a digital map852, a history database (DB)853, a stop-position database (DB)854, a parkable-section database (DR)855, a traffic-light position database (DB)856, and a railroad-crossing position database (DB)957. The storage850is an HDD, for example.

The lane database851is a database of registered position (latitudes and longitudes) information of lanes on roads. The digital map852represents map information in the form of digital data.

The history database853is a database that stores therein previous results of the determination by the determiner806as a history, as described below.

The stop-position database854is a database of registered positions (latitudes and longitudes) of bus stops. The parkable-section database855is a database of registered parkable locations in roads such as locations of parking meters. The traffic-light position database856is a database of registered positions (latitudes and longitudes) of traffic lights. The railroad-crossing position database857is a database of registered positions (latitudes and longitudes) of railroad crossings.

The receiver801receives, from the controller10, the image, the imaging position, the imaging time, the vehicle group ID, the vehicle IDs of the vehicles2of the vehicle group, the various distances measured by the measurer112, the attribute information of the vehicles2of the vehicle group, the IDs of the imaging devices11, and the ID of the probe vehicle1.

The position corrector802corrects the imaging position (the position of the probe vehicle1at the time of generation of the image) received by the receiver801to position on each lane of a road, referring to the lane database851and the digital map852. The position corrector802identifies positions (latitudes and longitudes) of the forefront and the rear end of the vehicle group according to the corrected imaging position, the inter-vehicle distances and the lateral distances among the probe vehicle1and the vehicles2, and the length and width of the vehicle group.

The vehicle-queue identifier803selects a plurality of vehicle groups on the basis of the imaging time, the corrected imaging position, the attribute information of the vehicles2of the vehicle group, and the vehicle IDs of the vehicles2of the vehicle group, and identifies the selected vehicle groups as one vehicle queue. The details of the vehicle-queue identification method will be described later.

The stopping evaluator804calculates stopping vehicle-queue evaluation values on the basis of stopping vehicle-queue conditions. The topping vehicle-queue conditions define the characteristics of the stopping vehicle queue. The stopping vehicle-queue conditions are also referred to as conditions for determining the vehicle queue as a stopping vehicle queue. The stopping vehicle-queue evaluation values indicate the level of possibility of the vehicle queue identified by the vehicle queue identifier803being the stopping vehicle queue. The stopping vehicle-queue evaluation value is also referred to as likeliness of a stopping vehicle queue.

The parking evaluator805calculates parking vehicle-queue evaluation values based on parking vehicle-queue conditions. The parking vehicle-queue conditions define the characteristics of the parking vehicle queue. The parking vehicle-queue conditions are also referred to as conditions for determining the vehicle queue as a parking vehicle queue. The parking vehicle-queue evaluation values indicate the level of possibility of the vehicle queue identified by the vehicle-queue identifier803being a parking vehicle queue. The parking vehicle-queue evaluation values are also referred to as likeliness of a parking vehicle queue. In the following, the stopping vehicle-queue conditions and the parking vehicle-queue conditions are referred to simply as the conditions unless they need to be discriminated from each other. The details of the conditions will be described later.

The determiner806determines whether the identified vehicle queue is a stopping vehicle queue, a parking vehicle queue, or an unidentifiable vehicle queue as stopping or parking, from the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value.

The image generator807generates a display image that shows the position of the vehicle group or the vehicle queue on a map. Specifically, the image generator807maps the positions of the vehicle groups on a map and generates an image that shows an overlapping area of the positions of the vehicle groups in a highlighted manner, as the display image.

The transmitter808transmits a result of the determination on the vehicle queue by the determiner806data such as the image to the traffic information provider9. The transmitter808transmits the display image generated by the image generator807to the traffic information provider9.

The following describes a flow of processing in the present embodiment.

FIG. 6is a flowchart of exemplary vehicle-group detection processing executed by the controller10according to the embodiment. The controller10executes the processing in the flowchart at regular time intervals while the probe vehicle1is traveling.

First, the acquirer110acquires an image from the imaging devices11. The acquirer110acquires current time from the clock circuit106as imaging time. The acquirer110acquires the position of the probe vehicle1at the imaging time from the GPS module105as an imaging position. The acquirer110acquires a current speed of the probe vehicle1from the ECU (S1). The acquirer110may calculate the speed of the probe vehicle1from a wheel speed acquired from a wheel speed sensor or a change in the position of the probe vehicle1based on GPS radio waves.

Next, the vehicle detector111detects the vehicles m the acquired image (S2).

FIG. 7illustrate the vehicles2detected by the controller10according to the present embodiment, by way of example. When the probe vehicle1is located at the position illustrated inFIG. 7, the image generated by the imaging devices11includes the vehicles2ato2con the adjacent lane on the left side of the probe vehicle1. In this case, the vehicle detector111detects the vehicles2ato2cfrom the image.

Next, the ID determiner117determines the vehicle IDs of the detected vehicles2ato2c. The ID determiner117determines the vehicle IDs of the vehicles2ato2cto be “1”, “2”, and “3”, respectively, for example.

Next, the measurer112measures an inter-vehicle distance3between the probe vehicle1and the vehicle2aclosest to the probe vehicle1among the vehicles2ato2cappearing on the image (S4). The vehicle-speed calculator113calculates the relative speed of the vehicle2afrom change in the inter-vehicle distance3within a certain period, and calculates the speed of the vehicle2afrom the relative speed of the vehicle2aand the speed of the probe vehicle1(S5).

The travel determiner114determines whether the speed of the vehicle2ais 0 km/h (S6). If the speed of the vehicle2ais not 0 km/h (No at S6), the travel determiner114determines that the vehicle2ais travelling. This completes the processing.

If the speed of the vehicle2ais 0 km/h (YES at S6), the travel determiner114determines that the vehicle2ais at a stop. In this case, the measurer112measures the lateral distance of the vehicles2ato2cdetected from the image (S7). In the example ofFIG. 7, longitudinal (fore-and-aft) centers35ato35cof the vehicles2ato2csubstantially match one another, therefore, the lateral distance of the vehicles2ato2cis zero meter.

Next, the vehicle-group identifier115determines whether the lateral distance between the vehicle2adetermined to be stopping and each of the vehicles2band is a threshold or less (S8). If the lateral distances between the vehicle2aand the vehicles2band2care the threshold or less (YES at S8), the vehicle-group identifier115determines that the vehicles2band2care located on the same lane as the vehicle2a. In this case, the vehicle-group identifier115identifies the vehicle2adetermined to be stopping and the other vehicles2band2cas one vehicle group5(S9). The vehicle-group identifier115sets the vehicle group ID for the identified vehicle group.

Vehicles2dto2ginFIG. 7do not appear on the image when the probe vehicle1is located at the position illustrated inFIG. 7, but they appear thereon along with the travel of the probe vehicle1. The vehicle-group identifier115thus identifies a different vehicle group5including different vehicles along with the movement of the probe vehicle1.

Next, the measurer112measures the inter-vehicle distances among the vehicles2ato2cof the identified vehicle group5(S10). The measurer112also measures the inter-vehicle distance between the probe vehicle1and each of the vehicles2band2c. The measurer112measures the distance between the forefront of the vehicle2cat the head of the vehicle group5and the rear end of the vehicle2aat the end of the vehicle group5as a vehicle group length37. The measurer112measures the width of the vehicle2aat the end of the vehicle group5as a vehicle group width36and measures the distance the center of the width of the vehicle2aat the end of the vehicle group5to the probe vehicle1as a lateral distance36between the probe vehicle1and the vehicle group5.

If the lateral distance between the vehicle2aand each of the vehicles2band2cis longer than the threshold (NO at S6), the vehicle-group identifier115determines that the vehicles2band2care not located on the same lane as the vehicle2a. In this case, the vehicle-group identifier115identifies the vehicle2aalone as one vehicle group5(S11). With only one vehicle2detected from the image at S2, the processing proceeds to S11after S7without execution of S8to S10.

After the identification of the vehicle group5through S10or S11, the attribute detector116detects the color and the height of the vehicle2aor each of the vehicles2ato2cof the identified vehicle group5as the attribute information (S12).

The transmitter transmits, to the information processing apparatus8, for each vehicle group5, the image, the imaging position, the imaging time, the vehicle group ID of the vehicle group5, the vehicle IDs of the vehicles2of the vehicle group5, the inter-vehicle distance between the probe vehicle1and one or two or more vehicles2of the vehicle group5, the vehicle group length37, the vehicle group width38, the lateral distance36between the probe vehicle1and the vehicle group5, the attribute information of the vehicles2of the vehicle group5, the ID of the imaging device, and the probe-vehicle ID, in association with one another (S13). The transmitter118may transmit not the entire image showing the vehicle group5but a selected frame.

When the vehicle group5includes two or more vehicles2, the transmitter118may further transmit the inter-vehicle distances between or among the vehicles2of the vehicle group5to the information processing apparatus8. The transmitter118may further transmit the lateral distances among the vehicles2of the vehicle group5and information such as the number of the vehicles2of the vehicle group to the information processing apparatus8.

FIG. 8is a flowchart of exemplary determination processing executed by the information processing apparatus8according to the embodiment.

The receiver801receives, from the controller10of the probe vehicle1, the image, the imaging position, the imaging time, the vehicle group ID of the vehicle group5, the vehicle IDs of the vehicle group5, the inter-vehicle distance, the vehicle group length37, the vehicle group width38, the lateral distance36between the probe vehicle1and the vehicle group5, the attribute information of the vehicles2of the vehicle group5, the imaging-device ID, and the probe-vehicle ID (S21).

Next, the position corrector802corrects the imaging position received by the receiver801to a position on the lane of the road, referring to the lane database851and the digital map852(S22).

The position corrector802identifies the positions (latitudes and longitudes) of the forefront, the rear end, the longitudinal center of the vehicle group5according to the corrected imaging position, the inter-vehicle distance between the probe vehicle1and each of the vehicles2ato2cof the vehicle group5, the vehicle group length37, the vehicle group width38, the lateral distance36between the probe vehicle1and the vehicle group5(S23).

Next, the vehicle-queue identifier803selects plurality of vehicle groups5identified by the controller10of the probe vehicle1and identifies the selected vehicle groups5as a vehicle queue (S24).

FIG. 9is a diagram of a vehicle queue50identified by the information processing apparatus8according to the present embodiment by way of example.FIG. 9shows vehicle groups5ato5dof vehicle queues50aand50bidentified by the probe vehicle1in time-series.

The vehicle-queue identifier803identifies, as a vehicle queue50, vehicle groups5of vehicles2that are located on the same lane in the inter-vehicle distance two times the length of the standard vehicle2or less on the basis of the imaging time, the corrected imaging position, the attribute information of the vehicles2of the vehicle group5, and the vehicle IDs of the vehicles2of the vehicle group5. The vehicle-queue identifier803selects one or more vehicle groups5having the corrected imaging positions in a certain distance or less from the vehicle groups5having a difference in the imaging time being a certain period or less, for example. Further, the vehicle-queue identifier803identifies the same vehicle2from different vehicle groups5in accordance with the vehicle ID and the attribute information (color and height), and identifies the vehicle groups5including the same vehicle2as a vehicle queue50.

In the example ofFIG. 9, the vehicle2cat the head of the vehicle group5aand the vehicle2cat the end of the vehicle group5bhave the same ID “3”. A vehicle2eat the head of the vehicle group5band a vehicle2eat the end of the vehicle group5chave the same vehicle ID “5”. The vehicle2cof the vehicle group5aand the vehicle2cof the vehicle group5bare the same in color and height. The vehicle2eof the vehicle group5band the vehicle2eof the vehicle group5care the same in color and height. In this case, the vehicle-queue identifier803determines that the vehicle2cof the vehicle group5aand the vehicle2cof the vehicle group5bare the same vehicle2. The vehicle-queue identifier803determines that the vehicle2eof the vehicle group5band the vehicle2eof the vehicle Group5care the same vehicle2.

That is, the vehicles2at the head and end of each vehicle group5are the same, so that the vehicle-queue identifier903determines that the vehicle groups5ato5care consecutively located on the same lane. In this case, the vehicle-queue identifier803identifies the vehicle groups5ato5cas a vehicle queue50a.

In the vehicle group5cand the vehicle group5dno vehicles2have the same vehicle ID. In the example ofFIG. 9, the head of the vehicle group5cand the end of the vehicle group5dis apart in distance more than two times the length of the standard vehicle2. In such a case, the vehicle-queue identifier803determines that the vehicle group5dis a vehicle queue50bdifferent from the vehicle queue50a.

In the above example, the vehicle-queue identifier803identifies the same vehicle2on the basis of both the vehicle IDs and the attribute information, however, the identification may be based on either of them. The vehicle-queue identifier603may identify the vehicle queue50in accordance with either the color or the vehicle height in the attribute information. The vehicle-queue identifier803may determine the vehicles2different in color or height as the same vehicle2as long as the vehicles2are sufficiently similar in a certain criterion or above. The vehicle-queue identifier803may determine a positional relationship among the vehicle groups5ato5dfrom the imaging time and the corrected imaging position without considering the vehicle IDs and the attribute information, to select consecutive vehicle groups5. The vehicle-queue identifier803may select a plurality of vehicle groups5of the vehicles2in the inter-vehicle distance two times the length of the standard vehicle2or less, on the basis of the inter-vehicle distances between the vehicles2of the vehicle groups5, to determine the selected vehicle groups5as a vehicle queue50.

The vehicle groups5ato5dillustrated inFIG. 9may be identified by controllers10of different probe vehicles1. In this case, the vehicle-queue identifier803determines the vehicle groups5identified by the controllers10of the different probe vehicles1as one vehicle queue50.

Upon determination of the vehicle groups5ato5das stopping by the controller10, the vehicle-queue identifier803determines that the identified vehicle queue50is stopping.

Referring back to the flowchart inFIG. 8, the stopping evaluator804determines whether the identified vehicle queue50satisfies the stopping vehicle-queue conditions to calculate the sum of points assigned to the satisfied stopping vehicle-queue conditions as the stopping vehicle-queue evaluation value (S25).

FIG. 10is a diagram of exemplary conditions according to the embodiment.FIG. 10illustrates classification of the stopping vehicle-queue conditions or the parking vehicle-queue conditions. Condition IDs are numbers for identifying the conditions. Each of the conditions is assigned with a point. The points represent values indicating level of importance of the conditions. The higher the level of the importance is, the larger the value assigned to is, for example. In the present embodiment, the storage850stores the details of the respective conditions and the values of the points assigned to the conditions in advance.

Specifically, the stopping vehicle-queue conditions include such conditions that the vehicle queue50is located near the center of a lane condition ID “1”), that the motion of the stopping vehicle queue50is detected, (condition ID “2”), that the distance from the forefront of the vehicle queue50to a traffic light or a railroad-crossing located ahead of the vehicle queue50is a threshold or less, (condition ID “3”), that the distance from the forefront of the vehicle queue50to a parking meter is longer than a threshold, (condition ID “4”), that the distance from the forefront of the vehicle queue50to a bus stop is a threshold or less (condition ID “5”), and that the proportion at which in previously detected vehicle queues, vehicle queues50having the same forefront or end position as a currently detected vehicle queue50were stopping vehicle queues is a threshold or more (condition ID “6”).

The stopping evaluator804determines to which of the center of the lane and the road shoulder the vehicle queue50is closer, from the longitudinal centers of the respective vehicle groups5of the vehicle queue50and information on positions of lanes registered in the lane database851. When determining that the vehicle queue50is closer to the center of the lane, the stopping evaluator804determines that the vehicle queue50satisfies the stopping vehicle-queue condition with the condition ID “1”.

When the motion of the vehicle queue50is detected within a certain period or when the attribution information of the vehicles2of the vehicle queue50greatly changes within a certain period, the stopping evaluator804determines that the vehicle queue50has moved and chanced in order, and determines that the vehicle queue50satisfies the stopping vehicle-queue condition with the condition ID “2”.

The stopping evaluator804calculates the distance from the forefront of the vehicle queue50to a traffic light, a railroad crossing, a parking meter, or a bus stop registered in the traffic-light position database856, the railroad-crossing position database857, the parkable-section database855, or the stop-position database854, to determine whether the vehicle queue50satisfies the stopping vehicle-queue condition with the condition ID “3”, “4”, or “5”. The threshold of the condition ID “3” is set to 50 meters, the threshold of the condition ID “4” is set to 20 meters, and the threshold of the condition ID “5” is set to 30 meters, for example.

The stopping evaluator604calculates the proportion at which vehicle queues50having the same forefront or d position a currently detected vehicle queue50were the stopping vehicle queues, from results of previous determination stored in the history database853, to determine whether the vehicle queue50satisfies the stopping vehicle-queue condition with the condition ID “6”.

Next, the parking evaluator805determines whether the identified vehicle queue50satisfies the parking vehicle-queue conditions, and calculates the sum of points assigned to the satisfied parking vehicle-queue conditions as the parking vehicle-queue evaluation value (S26).

The parking vehicle-queue conditions include such conditions that the vehicle queue50is closer to a road shoulder than to the center of a lane, (condition ID “101”), that the distances from the forefront of the vehicle queue50to a traffic light and a railroad crossing are longer than a threshold, (condition ID “102”), that the distance from the forefront of the vehicle queue50to a parking meter is a threshold or less, (condition ID “103”), that the distance from the forefront of the vehicle queue50to a bus stop is longer than a threshold, (condition ID “104”), that the proportion at which in previously detected vehicle queues, vehicle queues50having the same forefront or end position as a currently detected vehicle queue50were the parking vehicle queues is a threshold or more, (condition ID “105”), and that the vehicle queue50having the same forefront or end position as a detected vehicle queue50and of which the vehicle2having similar attribution information are detected by another probe vehicle (condition ID “106”).

When determining that the vehicle queue50is closer to the road shoulder than the center of the lane, the parking evaluator905determines that the vehicle queue50satisfies the parking vehicle-queue condition with the condition ID “101”. The threshold of the condition ID “102” is set to 100, for example, larger than the threshold of the condition ID “3”. The threshold of the condition ID “103” is set to 10 meters, for example, smaller than the threshold of the condition ID “4”. The threshold of the condition ID “104” is set to 80 meters, for example, larger than the threshold of the condition ID “5”. The stopping evaluator834and the parking evaluator805perform the determination using different thresholds for the stopping vehicle-queue conditions and the parking vehicle-queue conditions, preventing the addition of points to the vehicle queue50that does not include the characteristics of the stopping vehicle queue and the parking vehicle queue.

Next, the determiner806subtracts the parking vehicle-queue evaluation value from the stopping vehicle-queue evaluation value to find a difference (S27). The determiner806determines whether the difference between the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value is 10 or more (S28).

With the difference being 10 or more (YES at S28), the determiner806determines the vehicle queue50as the stopping vehicle queue (S29). In this case, the transmitter609transmits a result of the determination, the imaging time, the forefront and end positions of the vehicle queue50, the condition IDs of the conditions satisfied by the vehicle queue50, and the distance from the stopping vehicle queue to a traffic light, for example, to the traffic information provider9(S30).

With the difference between the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value being less than 10 (NO at S28), the determiner806determines whether the difference is −10 or less (S31). With the difference being −10 or less (YES at S31), the determiner806determines the vehicle queue50as the parking vehicle queue (S32). In this case, the transmitter808transmits a result of the determination, the image, the imaging time, the forefront and end positions of the vehicle queue50, and the condition IDs of the conditions satisfied by the vehicle queue50to the traffic information provider9(S33). The transmitter808transmits different images and different imaging times associated with the vehicle groups5of the vehicle queue50at S30and S33.

With the difference between the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value being less than 10 and larger than −10 (NO at S28and NO at S31), the determiner806determines the vehicle queue50as an unidentifiable vehicle queue50as the stopping vehicle queue or the parking vehicle queue (S34).

After any of the operations at S30, S33, and S34, the determiner806stores the result of determination in the history database853(S35). Specifically, the determiner806stores, in the history database853, the result of determination, the condition IDs of the conditions satisfied by the vehicle queue50, the forefront and end positions of the vehicle queue50, the attribute information of the vehicles2of the vehicle groups5of the vehicle queue50, the probe-vehicle ID of the probe vehicle1that has detected the vehicle groups5of the vehicle queue50, the images and the imaging times associated with the vehicle groups5of the vehicle queue50, and the inter-vehicle distances among the vehicles2of the vehicle groups5of the vehicle queue50, in association with one another. The determiner806may further store the depth map and the corrected imaging position in the history database853.

Next, the image generator807generates a display image that shows positions of the vehicle groups5of the identified vehicle queue50on a map (S36).

FIG. 11is a diagram of an exemplary display image according to the embodiment. As illustrated inFIG. 11, the image generator807displays the positions of the vehicle groups5ato5con the map. Among each of the vehicle groups5, vehicles closer to the probe vehicle1at the imaging time are more accurately detected. For this reason, the image generator807displays the vehicle groups5in different color densities by the length of the standard vehicle2such that the vehicle groups5closer to the probe vehicle at the imaging time1are displayed in darker color in a highlighted manner.

The image generator307displays an overlapping area of the positions of the vehicle groups5in a highlighted manner on the map. As illustrated inFIG. 11, the image generator807displays the overlapping areas of the vehicle groups5in darker color, for example.FIG. 11shows positions (imaging positions)1-1to1-3of the probe vehicle when the vehicle groups5ato5care imaged, respectively.

The image generator807may display the vehicle groups5not in different color densities by the vehicle length of the standard vehicle2but in color gradation. Alternatively, the image generator807may display the stopping vehicle queue and the parking vehicle queue in different display forms on the display image.

The transmitter808transmits the display image generated by the image generator807to the traffic information provider9(S37).

Conventionally, determination on whether the vehicle2has stopped for a certain period or longer or is temporarily stopping is made, upon every detection of a single stopping vehicle2on the road. This may, however, increase a processing load since the determination needs to be made a number of times equal to the number of stopping vehicles2on the road. In contrast, the information processing apparatus H of the present embodiment identifies two or more vehicle groups5as a vehicle queue50to determine whether the vehicle queue50is the stopping vehicle queue or the parking vehicle queue. Thereby, the information processing apparatus8of the present embodiment can determine the vehicle queue50including a plurality of stopping or parking vehicles2through a single operation, enabling reduction in processing load for the determination, in comparison with the individual determinations for the topping vehicles2.

The information processing apparatus8of the present embodiment calculates the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value for each vehicle queue50according to the stopping vehicle-queue conditions and the parking vehicle-queue conditions. Thereby, the information processing apparatus of the present embodiment can accurately identify the stopping vehicle queue or the parking vehicle queue on the road without the necessity to detect all the vehicles2of the vehicle queue50.

The information processing apparatus8of the present embodiment identifies the same vehicle2from different vehicle groups5on the basis of the imaging time, the imaging position, and the attribute information of the vehicles2of the vehicle group5, and identifies the vehicle groups5including the same vehicle2as a vehicle queue50. Thereby, the information processing apparatus8of the present embodiment can identify consecutive vehicle groups5and accurately identify the vehicle queue50.

In the present embodiment, the attribute information of the vehicles2includes the colors and the heights of the vehicles2, and the information processing apparatus8of the present embodiment can identify the vehicles2with similar appearance on the basis of the attribute information.

The information processing apparatus8of the present embodiment further identifies the same vehicle2from different vehicle groups5in accordance with the vehicle ID, and identifies the vehicle groups5including the same vehicle2as a vehicle queue53. Thereby, the information processing apparatus8of the present embodiment can accurately identify the same vehicle2and accurately identify the vehicle queue50.

The information processing apparatus8of the present embodiment adds the stopping vehicle-queue evaluation value when the forefront or end position of the vehicle queue50satisfies any of the stopping vehicle-queue conditions, and adds the parking vehicle-queue evaluation value when the forefront or end position of the vehicle queue50satisfies any of the parking vehicle-queue conditions. Thereby, the information processing apparatus8of the present embodiment can determine whether the vehicle queue50as a whole is the stopping vehicle queue or the parking vehicle queue even when the stop positions of the individual vehicles2cannot be accurately detected due to erroneous detection, for example.

The information processing apparatus8of the present embodiment can generate the display image that shows the overlapping area of the positions of the vehicle groups5in a highlighted manner on the map, and can thus show the positions where vehicles2are likely to be at a stop, on the display image.

Upon determining that the vehicle2adetected from the image is stopping, the controller10of the present embodiment identifies the vehicle2aand the vehicles2band located on the same lane on the image as the vehicle group5. Thereby, the controller10of the present embodiment can reduce a processing load and a length of processing time for determining whether the vehicle group5appearing in the image is stopping. Owing to the reduction in processing time, the controller10of the present embodiment can shorten a detection cycle and thus reduce the occurrence of erroneous detection due to the change in the positions of the vehicles in the group during the detection operation.

The controller10of the present embodiment detects the colors and the heights of the vehicles2ato2cof the vehicle groups5as the attribute information. The information processing apparatus8can thus select the vehicle groups5including the same vehicle2in accordance with the colors and the heights to accurately identify the vehicle queue50.

The controller10of the present embodiment sets the vehicle ID that enables identification of the detected vehicle2. Owing to such features of the controller10, the information processing apparatus8of the present embodiment can accurately select the vehicle groups5including the same vehicle2and identify the vehicle queue50.

The present embodiment has described the thresholds, the contents of the data stored in the respective databases by wave of example only, and they are not limited to such examples.

First Modification

In the first embodiment the image generator807of the information processing apparatus8displays the vehicle groups5identified by one probe vehicle1. The image generator807may further display, in a superimposed manner, vehicle groups5identified by the probe vehicle1traveling on the opposite lane.

FIG. 12is a diagram of an exemplary display image according to a first modification. The image generator807generates a display image that shows a vehicle queue50c, including vehicle groups5dto5gidentified by a probe vehicle1btraveling on the opposite lane as the probe vehicle1travels, superimposed on a vehicle queue50aincluding the vehicle groups5ato5cidentified by the probe vehicle1.FIG. 12shows the positions1b-1to1b-3of the probe vehicle1bat the time when the vehicle groups5dto5gare imaged, respectively by superimposition of the vehicle groups5identified by the probe vehicle1btraveling on the opposite lane on the display image, the image generator807can accurately display the position of the stopping vehicle queue50on the lane.

Second Modification

The image generator807may display the vehicle groups5identified from an image generated by a front camera of the probe vehicle1and the vehicle groups5identified from an image generated by a rear camera in a superimposed manner.

FIG. 13is a diagram of an exemplary display image according to a second modification. The probe vehicle1of the present modification includes another imaging device (rear camera) that images the area behind the probe vehicle1in addition, to the imaging devices11(front cameras) that image the area ahead of the probe vehicle1. The rear camera and the front cameras have different imaging-device IDs. The image generator807generates a display image that shows a vehicle queue50a-2, including vehicle groups5a-2to5c-2identified from the image generated by the rear camera of the probe vehicle1, superimposed on the vehicle queue50aincluding the vehicle groups5ato5cidentified from the image generated by the front cameras of the probe vehicleFIG. 13shows the positions1-4to1-6of the probe vehicle1bat the time when the vehicle groups5a-2to5c-2are imaged, respectively.

The information processing apparatus8of the present modification can accurately display the position of the vehicle queue50identified from the image generated by the single probe vehicle1.

According to the present modification, the vehicle-queue identifier803may also identify, as the vehicle queues50, thio vehicle groups5identified from the image by the front cameras and the vehicle groups5identified from the image by the rear camera. The probe vehicle1may additionally include imaging devices that image the lateral sides of the probe vehicle1. The image generator807may further superimpose the vehicle groups5appearing in an image of the lateral side on the display image.

Third Modification

The probe vehicle1may be a tram vehicle, a motorcycle, an autonomous vehicle traveling on the road. The vehicles2as a subject of the determination may also be tram vehicles.

Fourth Modification

The stopping evaluator804and the parking evaluator805may determine whether each vehicle group5satisfies the conditions, to calculate the stopping vehicle-queue evaluation value and the parking vehicle-queue evaluation value. The determiner806may determine whether each vehicle group stopping or parking.

Fifth Modification

The information processing apparatus8may include any or all of the vehicle detector111, the measurer112, the vehicle-speed calculator113, the travel determiner114, the vehicle-group identifier115, the attribute detector116, and the ID determiner117of the controller10of the embodiment. According to such configuration, the transmitter118of the controller10transmits the image, the imaging position, and the imaging time to the information processing apparatus8, for example.

Sixth Modification

When the vehicle queue50determined as the parking vehicle queue by the determiner806satisfies the condition with the condition ID “3” or “5”, the vehicle queue50may be parked in a no-parking cone such as in the vicinity of a traffic light, a railroad crossing, or a bus stop. In this case, the transmitter808may transmit information representing high possibility of the vehicle queue50being parked in a no-parking zone to the traffic information provider9.

Other Modifications

The conditions illustrated inFIG. 10are merely exemplary. The stopping vehicle-queue conditions and the parking vehicle-queue conditions may further include a condition based on the temperature of a muffler of the vehicle2detected with an infrared camera, for example. The thresholds used in the respective conditions may vary depending on time, the day of the week (including weekdays, Saturday, Sunday, and national holidays), or the time of sunrise or sunset in each month, for example. The conditions and the points may be changed after the start of operation of the information processing system S. The information processing apparatus8may download the conditions from an external device.

The position corrector802may correct the imaging position according to a positional history of the probe vehicle1acquired at intervals of a few seconds. The controller10may correct the imaging position on the basis of information acquired from the car navigation system of the probe vehicle1. The position corrector802may detect lanes from an image by a known image processing method.

The various kinds of databases may be stored in a cloud environment in place of the storage850. The digital map852, the parkable-section database855, the traffic-light position database856may be updated to new information at regular time intervals.

The information processing apparatus8may calculate the ratio between the stopping vehicle queues and the parking vehicle queues in the past history in advance. Upon each storage of a result of determination in the history database853, the determiner806may calculate the ratio between the stopping vehicle queues and the parking vehicle queues for storage, for example. The determiner806may calculate, as background processing, the ratio therebetween in a time slot with a low processing load. The ratio therebetween may be calculated in an external cloud environment.

Computer programs executed by the controller10or the information processing apparatus8of the embodiment are recorded in installable or executable file format on a computer-readable recording medium such as a compact disc read only memory (CD-ROM), a flexible disk (FD), a compact disc recordable (CD-R), and a digital versatile disc (DVD). The computer programs executed by the controller10or the information processing apparatus8of the embodiment may be stored in a computer connected to a network such as the Internet and downloaded via the network. The computer programs executed by the controller10or the information processing apparatus8of the embodiment may be provided or distributed via a network such as the Internet. The computer programs executed by the controller10or the information processing apparatus8of the embodiment may be embedded in a ROM, for example.

The computer programs executed by the controller10of the embodiment include a module configuration including the above elements (acquirer, vehicle detector, measurer, vehicle-speed calculator, travel determiner, vehicle-group identifier, attribute detector, ID determiner, and transmitter). As actual hardware, a CPU (processor) reads and executes the computer programs from the ROM, to load the elements on a main storage device to generate the acquirer, the vehicle detector, the measurer, the vehicle-speed calculator, the travel determiner, the vehicle-group identifier, the attribute detector, the ID determiner, and the transmitter the main storage device.

The computer programs executed by the information processing apparatus8of the embodiment include a module configuration including the above elements (receiver, position corrector, vehicle-queue identifier, stopping evaluator, parking evaluator, image generator, and transmitter). As actual hardware, a CPU reads and executes the computer programs from the storage medium to load the elements on a main storage device to generate the receiver, the position corrector, the vehicle-queue identifier, the stopping evaluator, the parking evaluator, the image generator, and the transmitter on the main storage device.