Patent Grant
9779621
Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Some vehicles are configured to operate in an autonomous mode in which the vehicle navigates through an environment with little or no input from a driver. Such a vehicle typically includes one or more sensors that are configured to sense information about the environment. The vehicle can use the sensed information to navigate through the environment. For example, if the sensors sense that the vehicle is approaching an obstacle, the vehicle can navigate around the obstacle.
In a first appearance, a method is provided. A server receives one or more reports from a plurality of information sources associated with a road feature. Each respective report includes source data indicative of one or more aspects of the road feature at a respective time. The road feature includes a road intersection. At least the source data from the one or more reports is stored at the server. The server constructs a phase map for the road feature from at least the source data. The phase map is configured to represent a status of the road feature at one or more times. The server receives an information request related to the road feature at a specified time. In response to the information request, the server generates an information response including a prediction of a status related to the road feature at the specified time. The prediction is provided by the phase map and is based on the information request. The information response is sent from the server.
In another appearance, an article of manufacture including a non-transitory computer readable medium having stored thereon program instructions is provided. The program instructions, upon execution by a computing device, cause the computing device to perform operations. The operations include: (a) receiving one or more reports from a plurality of information sources associated with a road feature, each respective report including source data indicative of one or more aspects of the road feature at a respective time, where the road feature includes a road intersection, (b) storing at least the source data from the one or more reports, (c) constructing a phase map for the road feature from at least the source data using the server, where the phase map is configured to represent a status of the road feature at one or more times, (d) receiving an information request related to the road feature at a specified time, (e) in response to the information request, generating an information response including a prediction of a status related to the road feature at the specified time, where the prediction is provided by the phase map and is based on the information request, and (f) sending the information response.
In yet another appearance, a server is provided. The server includes a processor and a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium stores at least source data, a phase map and instructions. The instructions, when executed by the processor, cause the server to perform operations. The operations include: (a) receiving one or more reports from a plurality of information sources associated with a road feature, each respective report comprising source data indicative of one or more aspects of the road feature at a respective time, where the road feature includes a road intersection, (b) storing at least the source data from the one or more reports, (c) constructing the phase map for the road feature from at least the source data, where the phase map is configured to represent a status of the road feature at one or more times, (d) receiving an information request related to the road feature at a specified time, (e) in response to the information request, generating an information response including a prediction of a status related to the road feature at the specified time, where the prediction is provided by the phase map and is based on the information request, and (f) sending the information response.
The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, appearances, embodiments, and features described above, further aspects, appearances, embodiments, and features will become apparent by reference to the figures and the following detailed description.
Overview
Example embodiments disclosed herein relate to methods and systems for gathering information about “road features”, such as, but not limited to, part or all of a road, road intersections, bridges, tunnels, interchanges/junctions, road/railroad intersections, entrances to roads (e.g., on-ramps), exits from roads (e.g., off-ramps), and “condition features” related to road features, such as, but not limited to traffic conditions, construction-related conditions, weather-related conditions, and accident-related conditions. The information about road features and condition features can be gathered using “information sources” that are on, near, or otherwise related to one or more of the road features. These information sources can include, but are not limited to: vehicles, mobile devices carried by pedestrians, “signals”, such as traffic signals or traffic lights, crosswalk timers, and traffic signal timers. Information sources can provide information about a road, road features, motor vehicles, non-motor vehicles (e.g., bicycles), pedestrians, signals and signal timers. Condition features can include information about a status of a road feature at a time—e.g., an open road, an intersection with permitting traffic to move north/south, but not east/west, an icy bridge—and/or a status of an information source; e.g., a yellow traffic signal, a pedestrian walking north. In general, an “aspect” is a term for a road feature, condition feature, or information source; e.g., aspects include a portion of a road, the status of the road at 5 PM, a truck near the road, and/or the status of the truck, such as idle, moving, traveling west at 30 kilometers/hour, etc.
An information source can send one or more reports about a road feature to a “relaying server” that generates a representation of the road feature termed a “phase map” of the road feature from the data from the one or more reports. The phase map can include computer software and/or hardware configured at least to retrieve the stored data from the one or more reports and to generate the representation of the road feature. The phase map can provide responses to queries associated with a road feature, condition feature, information source, trends, and/or based on other associations. These queries can include requests about behavior of the road feature (or condition feature, information source, etc.) at one or more specific times; e.g., a time or time range involving past time(s), a current time, and/or future time(s). That is, the requests can include predictions of future behavior of the road feature, requests to monitor status of the road feature at the current time, and/or requests for retrieval of information about past behavior of the road feature. Other types of queries and/or to the phase map are possible as well.
Data stored in the phase map is considered to be time sensitive, that is, in some contexts, responses to queries can be based on data that is no older than a threshold age. For example, information about vehicles at an intersection that is several hours old is not likely to indicate the current status of the intersection. However, data older than the threshold age can be retained in the phase map so that the phase map can determine trends about the road and condition features; e.g., signal patterns, traffic flows at intersections and/or on roads during specific times of the day/days of the week, trends on accident occurrences at a location, average vehicle speed on an road during a given time of day, etc.
The relaying server can, upon request, provide information from the phase map to one or more “information consumers” (e.g., vehicles, mobile devices, other information sources) that can benefit from a better understanding of the road features. For example, an information consumer can send a query to the relaying server, which can pass the query on to the phase map as necessary. Based on any results provided by the phase map, the relaying server can provide a query response, such as a report, to the information source that sent the query.
In some embodiments, the phase map can store data beyond data available to an individual driver. For example, the phase map can maintain one or more “snapshots” of a given road feature, or a state that thoroughly describes a given road feature at a specific time based on a combination of source data in reports from a plurality of information sources about aspect(s) of the given road feature.
Example queries can include a “GetReports” query to get all reports about one or more pre-determined aspects for some amount of time. Reports can be “aged out” or subject to time and/or constraints. Aging out can happen directly or indirectly. As an example of direct aging out, a first report can be received that indicates a pedestrian P is at an intersection of 1st and Main Streets and is headed toward 2nd St. Then, a later report can indicate that P is on Main St. halfway between 1st and 2nd Streets. As the pedestrian has moved past the intersection of 1st and Main Streets, the first report about pedestrian P can be aged out and no longer reported.
As an example of indirect aging out, suppose first reports indicate a vehicle V is reported stopped on Main St. near the intersection of 1st and Main Streets and that a traffic signal on Main St. is red. Later, a second report(s) indicate that the traffic signal on Main St. is green and V is moving on Main St. at 15 miles/hour. As V has moved to some yet unknown location, the phase map and/or relaying server can infer that V is no longer near the intersection of 1st and Main Streets, and indirectly age out the first reports about vehicle V.
Another example type of query can be a “ClearPath” query to indicate whether a proposed path is or will be free of obstructions. Yet another example type of query can be a “PredictSignal” query to predict which light of a traffic signal (e.g., red, green, or yellow) will be active at a given time. Other types of reports are possible as well.
This use of phase maps and relaying servers can, thus, increase the knowledge available to information sources interested in the road(s) and/or road feature(s) modeled by the phase map. Knowledge from the phase map can be used to augment vehicle behavior during autonomous driving or to alert the driver of an impending situation. Vehicles and other entities can apply the knowledge provided by the phase maps to operate more efficiently, safely, and cooperatively.
Example Operations
In some embodiments, the one or more reports additionally can include information about a condition feature associated with the road feature. The condition feature includes at least one condition selected from the group consisting of: a traffic condition, a construction condition, a weather-related condition, and an accident-related condition. In other embodiments, the source data can include data selected from the group consisting of: data about a vehicle, data about a pedestrian, data about a traffic signal, data about road construction, data about a timer associated with the intersection, and data about a blockage of the intersection.
At block 120, the server can store at least the source data from the one or more reports.
At block 130, the server can construct a phase map for the road feature from at least the source data. The phase map can be configured to represent a status of the road feature at one or more times.
At block 140, the server can receive an information request related to the road feature at a specified time.
At block 150, in response to the information request, the server can generate an information response including a prediction of a status related to the road feature at the specified time. The information response can be provided by the phase map and can be based on the information request.
In some embodiments, the at least one information source of the plurality of information sources can include a signal, and the prediction of the status related to the road feature can include a predicted red/yellow/green-light status of the signal at the specified time. In other embodiments, the prediction of the status related to the road feature can include a prediction of whether the at least one information source is in a path at the specified time, where the path is associated with the road feature.
In yet other embodiments, generating the information response to the information request can include: (i) obtaining one or more data items from the source data and (ii) for each data item of the one or more data items: (a) determining an age of the data item, (b) comparing the age of the data item to a threshold age, and (c) in response to the age of the data item being less than the threshold age, using the data item to determine the response data. In particular embodiments, the threshold age can be based on the road feature. In more particular embodiments, the road feature is associated with a traffic signal, where the traffic signal is configured to sequence through a series of signals during a predetermined traffic-cycle time, and where the threshold age is based on the traffic-cycle time.
At block 160, the server can send the information response.
Example Scenarios and Use Cases of Phase Maps
In scenario 200, some of motor vehicles 210, 212, 214, and 216 can be configured with sensors that gather data about intersection 202. For example, motor vehicle 214 can be configured with camera(s) that capture signal data about some or all of traffic signals 220, 222, 224, and 226. This signal data can include data such as, but not limited to red/yellow/green light status, walk/don't walk signal status, crosswalk timer values, and/or flashing/not-flashing light data. After capturing this data, motor vehicle 214 can generate a report about the status of one or more traffic signals. An example report about traffic signal 222 can include information about motor vehicle 214 such as an identifier and/or location information for motor vehicle 214, information about traffic signal 212, such as an identifier, signal data, and/or location information about traffic signal 222, and perhaps other information, such as timing information or information about related traffic signals, such as traffic signal 220, and/or information about other objects at or near intersection 216, such as bicycle 230, pedestrian 202, and/or motor vehicle(s) 210, 212, and/or 216.
People can provide reports to relaying servers using software executing on computing devices. For example, in scenario 200, pedestrian 232 has a mobile device executing a software application that can provide reports to phase map 242 maintained by relaying server 240 and receive information from phase map 242. The received information can be conveyed as text, diagrams, images, video, and/or audible information.
Phase map image 280 includes status information for the aspect associated with application 270, as status 274a graphically depicting a location of “ped232” and showing the aspect as a pedestrian. Phase map image 280 also includes status information for other aspects at or near the intersection of Main St. and Oak Dr. For example,
As another example of aspect status shown by phase map image 280, a vehicle at location 284a on Oak Drive just beginning to cross Main Street with status information 284b and 284c indicating is “truck 214” moving at 5 MPH northbound. Road indicators (RI) 286a, 286b each indicate a name of a road shown in
Application 270 can provide information about possible hazards to the aspect associated with the application. For example, suppose the “unknown bike” shown in
All five vehicles—the four vehicles in front of Vehicle 1 and Vehicle 1 itself—can communicate with relaying server 340 to get information about the traffic signals at the intersection from phase map 342. For example, vehicle V1 310 and the four vehicles V2 312, V3 314, V4 316, and V5 318 in front of V1 310 can each send a GetReports query at 8:02:01 PM to relaying server 340 to learn about traffic signals controlled by traffic signal controller 320, such as the example query for Vehicle 1 shown in Table 1 below:
The example query for V1 310 is shown graphically as message 350 of
During use case 300, the red light changes to green at 8:02:07 PM.
Traffic signal controller 320, which controls all four signals at the intersection, can send reports, such as those shown in Table 2 below to relaying server 340 and phase map 342.
Relaying server 340 and phase map 342 can send these reports to each of vehicles V1 310, V2 312, V3 314, V4 316, and V5 318 in response to the respective GetReports queries discussed above. These reports are shown graphically on
Each report from an aspect can be associated with a time, such as the time the report is sent, and a location. Each report can be subject to “aging out” due to time and/or location constraints that invalidate the report. Once a report has been aged out, the report can be discarded, not reported, and/or stored. Aged out reports that are stored can be used to determine trends, such as traffic flows, aspect counts on a daily, weekly, monthly or other basis, traffic cycles, and/or other trends related to roads, road features, and/or aspects.
Aging out can happen directly or indirectly. As an example of direct aging out, a first report can be received that indicates a pedestrian P is at an intersection of 1st and Main Streets and is headed toward 2nd St. Then, a later report can indicate that P is on Main St. halfway between 1st and 2nd Streets. As the pedestrian has moved past the intersection of 1st and Main Streets, the first report about pedestrian P can be aged out.
As another example, suppose P is halfway between 1st and 2nd Streets at 10:00 PM and sends a report at that time and location. Then, a threshold age; e.g., 30 seconds, 60 seconds, etc., can be used to determine if the data in the 10:00 PM report is “stale” or out of date. If the threshold age is 60 seconds, then the report sent at 10:00 PM will be stale at 10:01 PM. Stale reports can then be aged out.
As an example of indirect aging out, suppose first reports indicate a vehicle V is reported stopped on Main St. near the intersection of 1st and Main Streets and that a traffic signal on Main St. is red. Later, a second report(s) indicate that the traffic signal on Main St. is green and V is moving on Main St. at 15 miles/hour. As V has moved to some yet unknown location, the phase map and/or relaying server can infer that V is no longer near the intersection of 1st and Main Streets, and indirectly age out the first reports about vehicle V. Many other examples of aging out, including direct and/or indirect aging out, are possible as well.
Subsequently, all five vehicles can receive the above reports from phase map 342 and/or relaying server 340. Based on the information in these reports, all five vehicles can begin moving forward, as shown in
In some scenarios, PredictSignal queries can be used to obtain information about traffic cycles. A traffic cycle is one complete sequence of lights for a traffic signal. In some embodiments, a traffic cycle can begin with the traffic signal transitioning to a green light signal, maintaining the green light signal for a green-signal period of time, then transitioning to a yellow light signal, maintaining the yellow signal for a yellow-signal period of time, transitioning to a red light signal, and maintaining the red light signal for a red-signal period of time. A traffic cycle can end with the transition from a red light to a green light, which also begins a new traffic cycle.
A traffic-cycle time is the amount of time taken to complete a traffic cycle. For example, let the green-signal period for a traffic signal TS be 30 seconds, let the yellow-signal period for traffic signal TS be 10 seconds, and let the red-signal period for traffic signal TS be 40 seconds. Then, the traffic-cycle time for traffic signal time would be 30+10+40=80 seconds.
The PredictSignal query can be used to provide traffic cycle information for one or more signals, e.g., signal 322, 324, 326, and/or 328, and/or for signals controlled by one or more signal controllers, e.g., signal controller 320, for a period of time. For example, V1 320 can use the example PredictSignal query shown in Table 3 below to query signal controller 320 about traffic cycles that start on or before 8:02:00 PM (20:02:00 if expressed in 24-hour time) and end on or after 8:02:55 PM, at the intersection shown in
In response, phase map 342 can generate reports that predict complete traffic cycles for signals controlled by traffic signal controller 340 that begin at or before the start time; e.g., 8:02:00 PM and end at/after the end time; e.g., 8:02:55 PM. Once generated, phase map 342 can provide the reports to relaying server 340 to send to V1 310. Example reports are shown in Table 4:
The example reports of Table 4 above includes a report line with STATUSES=Green, Yellow, Red to indicate times when the signals controlled by signal controller signal320 will be green, yellow, and red, respectively. The first example report uses two CYCLE report lines to indicate two cycles occur during the period of time between 8:02:00 PM and 8:02:55 PM for eastbound and westbound signals controlled by signal controller signal320. The first CYCLE report line in the first report, with times 8:01:27 PM CDT, 8:01:57 PM CDT, 8:02:07 PM CDT indicates the eastbound and westbound signals have a first traffic cycle that starts at 8:01:27 PM Central Daylight Time (CDT) with a transition to a green light, continues with transitions at 8:01:57 PM CDT to a yellow light and 8:02:07 PM CDT to a red light. The example report indicates that the first traffic cycle begins at 8:01:27 PM CDT, which is before the 8:02:00 PM beginning of the period of time.
According to the first example report in Table 4, the first traffic cycle for the eastbound and westbound traffic signals ends just before a green light transition at 8:02:47 PM. This green light transition begins a second traffic cycle of the eastbound and westbound signals. The second CYCLE report line in the first example report, with times 8:02:47 PM CDT, 8:03:27 PM CDT, 8:03:37 PM CDT indicate that the second traffic cycle starts at 8:02:47 PM CDT with a transition to a green light and continues with transitions at 8:03:27 PM CDT to a yellow light and 8:03:37 PM CDT to a red light. The second traffic cycle is displayed as the second traffic cycle starts at 8:02:47 PM, which is before the 8:02:55 PM end of the period of time. The second report in Table 4 shows similar information for the northbound and southbound signals controlled by signal controller 320.
Phase maps can be constructed. For example, to construct a phase map, such as phase map 342: data for phase map 342 can be initialized, one or more road features can be associated with the phase map, one or more information sources can be associated, directly or indirectly, with the phase map, and source data for the information sources can be made available to the phase map. Initialized phase map 342, as shown in
Phase map 342 can use source data for a range of times to determine trends within the data. For example, let source data for signal 332 show that signal 332 had Red/Green Transitions at 8:01:00 AM, 8:02:00 AM, 8:03:00 AM, 8:04:00 AM, and 8:05:00 AM on Monday Jan. 21, 2013, and Red/Green Transitions at 8:01:02 AM and 8:02:02 AM on Tuesday, Jan. 22, 2013. By analyzing this data, phase map 342 can determine that (a) Red/Green Transitions take place on one-minute intervals on both Jan. 21 and Jan. 22, 2013 and (b) the transitions are starting at 2 seconds after the minute mark on Jan. 22, 2013. Then, in response to a query for trends in Red/Green Transitions of signal 332 between 8:03 and 8:08 AM on Jan. 22, 2013, phase map 342 can generate an output indicating a trend for Red/Green Transitions at 8:03:02 AM, 8:04:02 AM, 8:05:02 AM, 8:06:02 AM, and 8:07:02 AM on Jan. 22, 2013.
Predictions can indicate some amount of uncertainty; for example, based on the same data, in response to a query for trends in Red/Green Transitions of signal 332 between 8:03 and 8:08 AM on Wednesday Jan. 23, 2013, phase map 342 can generate an output indicating a trend for Red/Green Transitions at 8:03:01 AM+/−1 second, 8:04:01 AM+/−1 second, 8:05:01 AM+/−1 second, 8:06:01 AM+/−1 second, and 8:03:01 AM+/−1 second, on Wednesday Jan. 23, 2013.
To continue this example, suppose the source data for signal 332 also show
Then, based on this data, phase map 342 can predict that, on Wednesday, Jan. 23, 2013, signal 332 will be: green between 8:02:01 and 8:02:26 with an uncertainty of 1 second, yellow between 8:02:26 and 8:02:31 with an uncertainty of 1 second, and red between 8:02:31 and 8:03:01 with an uncertainty of 1 second.
Phase map 342 can use source data answer queries regarding the current status of a road feature; e.g., what color signal is signal 332 displaying to west-bound traffic? How long has that signal been displayed? In some scenarios, the source data may change during query processing; e.g., suppose at 3:00:00 PM a query is received to regarding the color that signal 332 is currently displaying to west-bound traffic and that immediately after receiving that query, a report from signal 332 is received indicating a red/green transition for west-bound traffic. Then, in response, phase map 342 can indicate the previous state of “red” as the current state at the time when the query is received, “green” as the current state at the time when the query is completely processed, and/or “red/green transition” to indicate the signal changed from red to green while the query was being processed.
Phase map 342 can also predict trends, such as a drift in the time of signal 332 of 2 seconds between two adjacent days. To continue this example, suppose signal 332 is configured to provide a count of cars that pass by the signal, then phase map 342 can predict which days of the week have the most or least traffic at intersection 330, amounts of traffic at specific times, traffic trends, historical traffic records, and perhaps other types of information.
By examining data from multiple information sources, phase map 342 can determine relationships between information sources. For example, suppose that each signal at intersection 330 can provide information about each lamp of each signal; e.g., signal 322 has a east lamp best seen by west-bound traffic and a south lamp best seen by north-bound traffic, and signal 326 has a east lamp best seen by west-bound traffic and a north lamp best seen by southbound traffic. Also, suppose that source data for both signals 332 and 336 include data on Red/Green (R/G), Green/Yellow (G/Y), and Yellow/Red (Y/R) transitions for each lamp, and that an example excerpt of source data from signals 332 and 336 is summarized in Table 5 below.
Based on the data in Table 5, phase map 342 can determine at least the following relationships between lamps in signals 322 and 326: (a) the south lamp of signal 322 and the north lamp of signal 326 are synchronized; that is, show the same color at the same time, (b) the west lamp of signal 322 is synchronized with the west lamp of signal 326, (c) the south lamp of signal 322 is not synchronized with either the west lamp of signal 322 or the west lamp of signal 326, and (d) the south lamp of signal 326 is not synchronized with either the west lamp of signal 322 or the west lamp of signal 326.
If a query requests historical data; e.g., a query for a color of the north lamp of signal 322 yesterday at 4 PM, then phase map 342 can access the source data for signal 322 to determine the requested color. Similarly, phase map 342 can access source data to determine historical trends, requests covering ranges of times, and other queries for historical information. In some cases, data may be unavailable; e.g., a query for 10-year old information about a 5-year old road feature or a query regarding a vehicle that has passed by a road feature, and phase map 342 can respond with an appropriate response; e.g., an error message or similar information indicating that the data unavailable to answer the input query.
Signal 422, shown as “S/T 420 NW” on the northwest corner of the intersection in
Use case 400 begins at 8:01:55 AM CDT where V1 410 sends a GetReports query, shown in
In some embodiments, the SUBSCRIBE option to GetReports query provides all reports about the specified aspect(s) of interest that are received by relaying server(s) and/or phase map(s) during the specified reporting_duration, which in the example shown in Table 6 above is set to one minute. When the prev_report option to GetReports query is set to YES, such as shown above in Table 6, the relaying server and/or phase map can provide the most recently received report(s) for the specified aspect(s) prior to the query.
The GetReports query is shown graphically in
In response, Vehicle 1 receives the reports shown in Table 7, perhaps among others. The first four reports in Table 7, shown as reports 460, 462, 464 are due to the prev_report=YES setting:
The last two reports in Table 7 are received by V1 410 at 8:02:10 AM Central time.
In other use cases, V1 410 can query phase map 442 to get information about predicted traffic cycles. For example, at 8:01:55 AM, V1 410 can send the example PredictSignal query shown in Table 8 to obtain information about signal “signal420”, perhaps instead of or along with the GetReports query previously shown in Table 6:
The PredictSignal query can be used to provide traffic cycle information for one or more signals, such as the specified signal1=signal420 shown in the example query, for a period of time. The example query uses the starttime1=NOW to specify the start of the period of time as the current time “NOW” and the endtime1=NOW+1 min parameter to specify the end of the period of time as one minute in the future. That is, the period of time in this example is the interval from 8:01:55 AM to 8:02:55 AM. The reporting=DIGEST parameter to the example query indicates the results of the query are to be provided as a digest, or summary form.
In response, V1 410 can receive the example digest report shown in Table 9 below to report prediction of the complete traffic cycles that begin at or before the start of the period of time and end at or after the end of the period of time:
The example report to the PredictSignal query shown above includes STATUSES=Green, Yellow, Red to indicate times when the eastbound signal of signal 420 will be green, yellow, and red, respectively. The example report indicates the eastbound signal has a first traffic cycle that starts at 8:01:40 AM CDT with a transition to a green light, continues with transitions at 8:02:10 AM CDT to a yellow light and 8:02:16 AM CDT to a red light. The first traffic cycle begins at 8:01:40 AM CDT, which is before the 8:01:55 AM CDT beginning of the period of time.
According to the example report in Table 9, the first traffic cycle ends just before a green light transition at 8:02:52 that begins a second traffic cycle for the eastbound signal. The second CYCLE report line in the example report indicates that the second traffic cycle starts at 8:02:52 AM CDT with a transition to a green light and continues with transitions at 8:03:22 AM CDT to a yellow light and 8:03:28 AM CDT to a red light. The second traffic cycle is displayed as the second traffic cycle starts at 8:02:52 AM, which is before the 8:02:55 AM end of the period of time.
To learn more about actual and predicted conditions at intersection 502, V1 510 can send an information request 550 to a relaying server 540 with phase map 542 maintaining information about intersection 502. An example of information request 550 is the ClearPath query shown in Table 10 below:
In the example ClearPath query shown above, the path=RIGHT_TURN parameter can indicate a proposed or predicted path to be searched when traversing the aspect intersect502 specified using the asp=intersect502 parameter. In other examples, the value of the path parameter can specify other paths to be searched; e.g., path can be set to LEFT_TURN, STRAIGHT_AHEAD, BACK_LEFT, BACK_RIGHT or BACK_UP. Other and/or additional values of the path parameter are possible as well. The pathtime=NOW+3 secs parameter indicates that V1 510 predicts that it will make the right turn at time NOW+3; that is, three seconds in the future.
Relaying server 540 can receive information request 550 and query phase map 542 to estimate the paths of aspects in and near the intersection and project where those aspects will be when Vehicle 1 wants to make the right turn. Based on a response to the query, relaying server 540 and/or phase map 542 can inform V1 510 about any aspects known by the phase map in the path. In use case 500, bike 514, with an ID=“bike514”, and pedestrian 516, with an ID=“pedestrian516”, are connected to relaying server 540 and/or phase map 542, shown in
In response, relaying server 540 and/or phase map 542 can send vehicle V1 510 a digest report responding to the ClearPath query, such as report 560 of
The above digest report can give Vehicle 1 a prediction that two aspects may be in path 512: (i) bike 514, which is a Person-Powered Vehicle (PPV), has a 45% probability of being in path 512 at time NOW+3 seconds and is moving at 5 MPH, and (ii) pedestrian 516, also a PPV, has a 95% probability of being in path 512 at time NOW+3 seconds and is moving at 3 MPH.
In response to learning about the bicyclist and pedestrian, Vehicle 1 can slow down, stop, (if autonomously driven) and/or alert the driver (if partially or completely-human driven) to let the bicyclist and pedestrian pass through the intersection before making a right hand turn.
As shown in
In use case 600, Vehicle 1, shown in
At 8:02:00, V1 610 sends the query shown in Table 12 to the relaying server to monitor a range 614 of NorthSouth Street near the intersection for the next 45 seconds:
V1 610 specified monitored range 614 using the seg1 parameter to specify a road segment, indicated in Table 12 above as: {road=NorthSouth, start=100 N. NorthSouth, end=100 S. NorthSouth}. In this example, EastWest St. is the baseline a.k.a. 0 North/0 South St. Then, 100 N. NorthSouth is one block north of EastWest St. and 100 S. NorthSouth is one block south of EastWest St. Thus, by monitoring the above-specified road segment, V1 610 has requested to learn about traffic-related events on NorthSouth St. within a block in either direction of the intersection of NorthSouth and EastWest. Use of the “reporting=SUBSCRIBE” parameter in the GetReports query enables V1 610 to receive all reports received by the reporting server, and an amount of time equal to 45 seconds for monitoring monitored range 614 is specified using the “reporting_duration=45 sec” in the GetReports query.
The GetReports query is shown graphically in
During this 45 second interval, Vehicle1 gets the following reports from the relaying server shown in Table 13 below:
These reports are also shown in
At 8:02:29 PM, the first report shown in Table 14 below is sent from V2 612 to phase map 642. Phase map 642 relays the first report and two additional reports, also shown in Table 14, to Vehicle 1:
These reports are shown in
From reports 680b, 682, and 684, V1 610 learns that at 8:02:29 PM, both (a) V2 612 is just north of the intersection and appears to be moving at 45 MPH southbound toward the intersection, and (b) the green signals on NorthSouth St. controlling northbound and southbound traffic have just turned yellow. By knowing Vehicle 2 has shown no signs of slowing despite a traffic signal likely to turn red, Vehicle 1 can remain stopped longer than it might otherwise if there was no cross traffic, or perhaps creep very slowly toward the intersection to better view Vehicle 2 approaching from Vehicle 1's left (from the north).
Example Vehicle Systems
The vehicle 700 can include various subsystems such as a propulsion system 702, a sensor system 704, a control system 706, one or more peripherals 708, as well as a power supply 710, a computer system 900, and a user interface 716. The vehicle 700 can include more or fewer subsystems and each subsystem can include multiple aspects. Further, each of the subsystems and aspects of vehicle 700 can be interconnected. Thus, one or more of the described functions of the vehicle 700 can be divided up into additional functional or physical components, or combined into fewer functional or physical components. In some further examples, additional functional and/or physical components can be added to the examples illustrated by
The propulsion system 702 can include components operable to provide powered motion for the vehicle 700. In an example embodiment, the propulsion system 702 can include an engine/motor 718, an energy source 719, a transmission 720, and wheels/tires 721. The engine/motor 718 can be any combination of an internal combustion engine, an electric motor, steam engine, Stirling engine, or other types of engines and/or motors. In some embodiments, the engine/motor 718 can be configured to convert energy source 719 into mechanical energy. In some embodiments, the propulsion system 702 can include multiple types of engines and/or motors. For instance, a gas-electric hybrid car can include a gasoline engine and an electric motor. Other examples are possible.
The energy source 719 can represent a source of energy that can, in full or in part, power the engine/motor 718. That is, the engine/motor 718 can be configured to convert the energy source 719 into mechanical energy. Examples of energy sources 719 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electrical power. The energy source(s) 719 can additionally or alternatively include any combination of fuel tanks, batteries, capacitors, and/or flywheels. The energy source 719 can also provide energy for other systems of the vehicle 700.
The transmission 720 can include aspects that are operable to transmit mechanical power from the engine/motor 718 to the wheels/tires 721. To this end, the transmission 720 can include a gearbox, clutch, differential, and drive shafts. The transmission 720 can include other aspects. The drive shafts can include one or more axles that can be coupled to the one or more wheels/tires 721.
The wheels/tires 721 of vehicle 700 can be configured in various formats, including a unicycle, bicycle/motorcycle, tricycle, or car/truck four-wheel format. Other wheel/tire geometries are possible, such as those including six or more wheels. Any combination of the wheels/tires 721 of vehicle 700 can be operable to rotate differentially with respect to other wheels/tires 721. The wheels/tires 721 can represent at least one wheel that is fixedly attached to the transmission 720 and at least one tire coupled to a rim of the wheel that can make contact with the driving surface. The wheels/tires 721 can include any combination of metal and rubber, or another combination of materials.
The sensor system 704 can include a number of sensors configured to sense information about an environment of the vehicle 700. For example, the sensor system 704 can include a Global Positioning System (GPS) 722, an inertial measurement unit (IMU) 724, a RADAR unit 726, a laser rangefinder/LIDAR unit 728, and a camera 730. The sensor system 704 can also include sensors configured to monitor internal systems of the vehicle 700 (e.g., O2 monitor, fuel gauge, engine oil temperature). Other sensors are possible as well.
One or more of the sensors included in sensor system 704 can be configured to be actuated separately and/or collectively in order to modify a position and/or an orientation of the one or more sensors.
The GPS 722 can be any sensor configured to estimate a geographic location of the vehicle 700. To this end, GPS 722 can include a transceiver operable to provide information regarding the position of the vehicle 700 with respect to the Earth.
The IMU 724 can include any combination of sensors (e.g., accelerometers and gyroscopes) configured to sense position and orientation changes of the vehicle 700 based on inertial acceleration.
The RADAR unit 726 can represent a system that utilizes radio signals to sense objects within the local environment of the vehicle 700. In some embodiments, in addition to sensing the objects, the RADAR unit 726 can additionally be configured to sense the speed and/or heading of the objects.
Similarly, the laser rangefinder or LIDAR unit 728 can be any sensor configured to sense objects in the environment in which the vehicle 700 is located using lasers. In an example embodiment, the laser rangefinder/LIDAR unit 728 can include one or more laser sources, a laser scanner, and one or more detectors, among other system components. The laser rangefinder/LIDAR unit 728 can be configured to operate in a coherent (e.g., using heterodyne detection) or an incoherent detection mode.
The camera 730 can include one or more devices configured to capture a plurality of images of the environment of the vehicle 700. The camera 730 can be a still camera or a video camera.
The control system 706 can be configured to control operation of the vehicle 700 and its components. Accordingly, the control system 706 can include various aspects include steering unit 732, throttle 734, brake unit 736, a sensor fusion algorithm 738, a computer vision system 740, a navigation/pathing system 742, and an obstacle avoidance system 744.
The steering unit 732 can represent any combination of mechanisms that can be operable to adjust the heading of vehicle 700.
The throttle 734 can be configured to control, for instance, the operating speed of the engine/motor 718 and, in turn, control the speed of the vehicle 700.
The brake unit 736 can include any combination of mechanisms configured to decelerate the vehicle 700. The brake unit 736 can use friction to slow the wheels/tires 121. In other embodiments, the brake unit 736 can convert the kinetic energy of the wheels/tires 721 to electric current. The brake unit 736 can take other forms as well.
The sensor fusion algorithm 738 can be an algorithm (or a computer program product storing an algorithm) configured to accept data from the sensor system 704 as an input. The data can include, for example, data representing information sensed at the sensors of the sensor system 704. The sensor fusion algorithm 738 can include, for instance, a Kalman filter, Bayesian network, or other algorithm. The sensor fusion algorithm 738 can further provide various assessments based on the data from sensor system 704. In an example embodiment, the assessments can include evaluations of individual objects and/or features in the environment of vehicle 700, evaluation of a particular situation, and/or evaluate possible impacts based on the particular situation. Other assessments are possible.
The computer vision system 740 can be any system operable to process and analyze images captured by camera 730 in order to identify objects and/or features in the environment of vehicle 700 that can include traffic signals, road way boundaries, and obstacles. The computer vision system 740 can use an object recognition algorithm, a Structure From Motion (SFM) algorithm, video tracking, and other computer vision techniques. In some embodiments, the computer vision system 740 can be additionally configured to map an environment, track objects, estimate the speed of objects, etc.
The navigation and pathing system 742 can be any system configured to determine a driving path for the vehicle 700. The navigation and pathing system 742 can additionally be configured to update the driving path dynamically while the vehicle 700 is in operation. In some embodiments, the navigation and pathing system 742 can be configured to incorporate data from the sensor fusion algorithm 738, the GPS 722, and one or more predetermined maps so as to determine the driving path for vehicle 700.
The obstacle avoidance system 744 can represent a control system configured to identify, evaluate, and avoid or otherwise negotiate potential obstacles in the environment of the vehicle 700.
The control system 706 can additionally or alternatively include components other than those shown and described.
Peripherals 708 can be configured to allow interaction between the vehicle 700 and external sensors, other vehicles, other computer systems, and/or a user. For example, peripherals 708 can include a wireless communication system 746, a touchscreen 748, a microphone 750, and/or a speaker 752.
In an example embodiment, the peripherals 708 can provide, for instance, means for a user of the vehicle 700 to interact with the user interface 716. To this end, the touchscreen 748 can provide information to a user of vehicle 700. The user interface 716 can also be operable to accept input from the user via the touchscreen 748. The touchscreen 748 can be configured to sense at least one of a position and a movement of a user's finger via capacitive sensing, resistance sensing, or a surface acoustic wave process, among other possibilities. The touchscreen 748 can be capable of sensing finger movement in a direction parallel or planar to the touchscreen surface, in a direction normal to the touchscreen surface, or both, and can also be capable of sensing a level of pressure applied to the touchscreen surface. The touchscreen 748 can be formed of one or more translucent or transparent insulating layers and one or more translucent or transparent conducting layers. The touchscreen 748 can take other forms as well.
In other instances, the peripherals 708 can provide means for the vehicle 700 to communicate with devices within its environment. The microphone 750 can be configured to receive audio (e.g., a voice command or other audio input) from a user of the vehicle 700. Similarly, the speakers 752 can be configured to output audio to the user of the vehicle 700.
In one example, the wireless communication system 746 can be configured to wirelessly communicate with one or more devices directly or via a communication network. For example, wireless communication system 746 can use 3G cellular communication, such as CDMA, EVDO, GSM/GPRS, or 4G cellular communication, such as WiMAX or LTE. Alternatively, wireless communication system 746 can communicate with a wireless local area network (WLAN), for example, using WiFi. In some embodiments, wireless communication system 746 can communicate directly with a device, for example, using an infrared link, Bluetooth, or ZigBee. Other wireless protocols, such as various vehicular communication systems, are possible within the context of the disclosure. For example, the wireless communication system 746 can include one or more dedicated short range communications (DSRC) devices that can include public and/or private data communications between vehicles and/or roadside stations.
The power supply 710 can provide power to various components of vehicle 700 and can represent, for example, a rechargeable lithium-ion or lead-acid battery. In some embodiments, one or more banks of such batteries can be configured to provide electrical power. Other power supply materials and configurations are possible. In some embodiments, the power supply 710 and energy source 719 can be implemented together, as in some all-electric cars.
Many or all of the functions of vehicle 700 can be controlled by computer system 900, discussed in detail below with respect to
The vehicle 700 can include a user interface 716 for providing information to or receiving input from a user of vehicle 700. The user interface 716 can control or enable control of content and/or the layout of interactive images that can be displayed on the touchscreen 748. Further, the user interface 716 can include one or more input/output devices within the set of peripherals 708, such as the wireless communication system 746, the touchscreen 748, the microphone 750, and the speaker 752.
The computer system 900 can control the function of the vehicle 700 based on inputs received from various subsystems (e.g., propulsion system 702, sensor system 704, and control system 706), as well as from the user interface 716. For example, the computer system 900 can utilize input from the control system 706 in order to control the steering unit 732 to avoid an obstacle detected by the sensor system 704 and the obstacle avoidance system 744. In an example embodiment, the computer system 900 can control many aspects of the vehicle 700 and its subsystems.
Although
In some embodiments, vehicle 800 can include a sensor unit 802, a wireless communication system 804, a LIDAR unit 806, a laser rangefinder unit 808, and a camera 810. The aspects of vehicle 800 can include some or all of the aspects described for
The sensor unit 802 can include one or more different sensors configured to capture information about an environment of the vehicle 800. For example, sensor unit 802 can include any combination of cameras, RADARs, LIDARs, range finders, and acoustic sensors. Other types of sensors are possible. In an example embodiment, the sensor unit 802 can include one or more movable mounts that can be operable to adjust the orientation of one or more sensors in the sensor unit 802. In one embodiment, the movable mount can include a rotating platform that can scan sensors so as to obtain information from each direction around the vehicle 800. In another embodiment, the movable mount of the sensor unit 802 can be moveable in a scanning fashion within a particular range of angles and/or azimuths. The sensor unit 802 can be mounted atop the roof of a car, for instance, however other mounting locations are possible. Additionally, the sensors of sensor unit 802 can be distributed in different locations and need not be collocated in a single location. Some possible sensor types and mounting locations include LIDAR unit 806 and laser rangefinder unit 808. Furthermore, each sensor of sensor unit 802 can be configured to be moved or scanned independently of other sensors of sensor unit 802.
The wireless communication system 804 can be located on a roof of the vehicle 800 as depicted in
The camera 810 can be any camera (e.g., a still camera, a video camera, etc.) configured to capture a plurality of images of the environment of the vehicle 800. To this end, the camera 810 can be configured to detect visible light, or can be configured to detect light from other portions of the spectrum, such as infrared or ultraviolet light. Other types of cameras are possible as well.
The camera 810 can be a two-dimensional detector, or can have a three-dimensional spatial range. In some embodiments, the camera 810 can be, for example, a range detector configured to generate a two-dimensional image indicating a distance from the camera 810 to a number of points in the environment. To this end, the camera 810 can use one or more range detecting techniques. For example, the camera 810 can use a structured light technique in which the vehicle 800 illuminates an object in the environment with a predetermined light pattern, such as a grid or checkerboard pattern and uses the camera 810 to detect a reflection of the predetermined light pattern off the object. Based on distortions in the reflected light pattern, the vehicle 800 can determine the distance to the points on the object. The predetermined light pattern can comprise infrared light, or light of another wavelength. As another example, the camera 810 can use a laser scanning technique in which the vehicle 800 emits a laser and scans across a number of points on an object in the environment. While scanning the object, the vehicle 800 uses the camera 810 to detect a reflection of the laser off the object for each point. Based on a length of time it takes the laser to reflect off the object at each point, the vehicle 800 can determine the distance to the points on the object. As yet another example, the camera 810 can use a time-of-flight technique in which the vehicle 800 emits a light pulse and uses the camera 810 to detect a reflection of the light pulse off an object at a number of points on the object. In particular, the camera 810 can include a number of pixels, and each pixel can detect the reflection of the light pulse from a point on the object. Based on a length of time it takes the light pulse to reflect off the object at each point, the vehicle 800 can determine the distance to the points on the object. The light pulse can be a laser pulse. Other range detecting techniques are possible as well, including stereo triangulation, sheet-of-light triangulation, interferometry, and coded aperture techniques, among others. The camera 810 can take other forms as well.
The camera 810 can be mounted inside a front windshield of the vehicle 800. Specifically, as illustrated, the camera 810 can capture images from a forward-looking view with respect to the vehicle 800. Other mounting locations and viewing angles of camera 810 are possible, either inside or outside the vehicle 800.
The camera 810 can have associated optics that can be operable to provide an adjustable field of view. Further, the camera 810 can be mounted to vehicle 800 with a movable mount that can be operable to vary a pointing angle of the camera 810.
Within the context of the present disclosure, the components of vehicle 700 and/or vehicle 800 can be configured to work in an interconnected fashion with other components within or outside their respective systems. For instance, the camera 730 can capture a plurality of images that can represent sensor data relating to an environment of the vehicle 700 operating in an autonomous mode. The environment can include another vehicle blocking a known traffic signal location ahead of the vehicle 700. Based on the plurality of images, an inference system (which can include the computer system 900, sensor system 704, and control system 706) can infer that the unobservable traffic signal is red based on sensor data from other aspects of the environment (for instance images indicating the blocking vehicle's brake lights are on). Based on the inference, the computer system 900 and propulsion system 702 can act to control the vehicle 700.
Computing Device Architecture
User interface module 901 can be operable to send data to and/or receive data from external user input/output devices. For example, user interface module 901 can be configured to send and/or receive data to and/or from user input devices such as a keyboard, a keypad, a touch screen, a computer mouse, a track ball, a joystick, a camera, a voice recognition module, and/or other similar devices. User interface module 901 can also be configured to provide output to user display devices, such as one or more cathode ray tubes (CRT), liquid crystal displays (LCD), light emitting diodes (LEDs), displays using digital light processing (DLP) technology, printers, light bulbs, and/or other similar devices, either now known or later developed. User interface module 901 can also be configured to generate audible output(s), such as a speaker, speaker jack, audio output port, audio output device, earphones, and/or other similar devices.
Network-communications interface module 902 can include one or more wireless interfaces 907 and/or one or more wireline interfaces 908 that are configurable to communicate via a network, such as network 238 shown in
In some embodiments, network communications interface module 902 can be configured to provide reliable, secured, and/or authenticated communications. For each communication described herein, information for ensuring reliable communications (i.e., guaranteed message delivery) can be provided, perhaps as part of a message header and/or footer (e.g., packet/message sequencing information, encapsulation header(s) and/or footer(s), size/time information, and transmission verification information such as CRC and/or parity check values). Communications can be made secure (e.g., be encoded or encrypted) and/or decrypted/decoded using one or more cryptographic protocols and/or algorithms, such as, but not limited to, DES, AES, RSA, Diffie-Hellman, and/or DSA. Other cryptographic protocols and/or algorithms can be used as well or in addition to those listed herein to secure (and then decrypt/decode) communications.
Processors 903 can include one or more general purpose processors and/or one or more special purpose processors (e.g., digital signal processors, application specific integrated circuits, etc.). Processors 903 can be configured to execute computer-readable program instructions 906 that are contained in the data storage 904 and/or other instructions as described herein.
Data storage 904 can include one or more computer-readable storage media that can be read and/or accessed by at least one of processors 903. The one or more computer-readable storage media can include volatile and/or non-volatile storage components, such as optical, magnetic, organic or other memory or disc storage, which can be integrated in whole or in part with at least one of processors 903. In some embodiments, data storage 904 can be implemented using a single physical device (e.g., one optical, magnetic, organic or other memory or disc storage unit), while in other embodiments, data storage 904 can be implemented using two or more physical devices.
Data storage 904 can include computer-readable program instructions 906, phase map 242, and perhaps additional data. Phase map 242 can store information about roads, road features, and aspects and respond to queries and information requests, as discussed above in the context of phase maps in
Cloud-Based Servers
In some embodiments, data and services at server devices 508 and/or 510 can be encoded as computer readable information stored in non-transitory, tangible computer readable media (or computer readable storage media) and accessible by programmable devices 504a, 504b, and 504c, and/or other computing devices. In some embodiments, data at server device 508 and/or 510 can be stored on a single disk drive or other tangible storage media, or can be implemented on multiple disk drives or other tangible storage media located at one or more diverse geographic locations.
In some embodiments, each of the computing clusters 909a, 909b, and 909c can have an equal number of computing devices, an equal number of cluster storage arrays, and an equal number of cluster routers. In other embodiments, however, each computing cluster can have different numbers of computing devices, different numbers of cluster storage arrays, and different numbers of cluster routers. The number of computing devices, cluster storage arrays, and cluster routers in each computing cluster can depend on the computing task or tasks assigned to each computing cluster.
In computing cluster 909a, for example, computing devices 900a can be configured to perform various computing tasks of relaying server 240, 340, 440, 540, 640. In one embodiment, the various functionalities of relaying server 240, 340, 440, 540, 640 can be distributed among one or more of computing devices 900a, 900b, and 900c. Computing devices 900b and 900c in computing clusters 909b and 909c can be configured similarly to computing devices 900a in computing cluster 909a. On the other hand, in some embodiments, computing devices 900a, 900b, and 900c can be configured to perform different functions.
In some embodiments, computing tasks and stored data associated with relaying server 240, 340, 440, 540, 640 and/or phase map 242, 342, 442, 542, 642 can be distributed across computing devices 900a, 900b, and 900c based at least in part on the processing requirements of relaying server 240, 340, 440, 540, 640 and/or phase map 242, 342, 442, 542, 642, the processing capabilities of computing devices 900a, 900b, and 900c, the latency of the network links between the computing devices in each computing cluster and between the computing clusters themselves, and/or other factors that can contribute to the cost, speed, fault-tolerance, resiliency, efficiency, and/or other design goals of the overall system architecture.
The cluster storage arrays 910a, 910b, and 910c of the computing clusters 909a, 909b, and 909c can be data storage arrays that include disk array controllers configured to manage read and write access to groups of hard disk drives. The disk array controllers, alone or in conjunction with their respective computing devices, can also be configured to manage backup or redundant copies of the data stored in the cluster storage arrays to protect against disk drive or other cluster storage array failures and/or network failures that prevent one or more computing devices from accessing one or more cluster storage arrays.
Similar to the manner in which the functions of server devices 508 and/or 510 can be distributed across computing devices 900a, 900b, and 900c of computing clusters 909a, 909b, and 909c, various active portions and/or backup portions of these components can be distributed across cluster storage arrays 910a, 910b, and 910c. For example, some cluster storage arrays can be configured to store the data of relaying server 240, 340, 440, 540, 640, while other cluster storage arrays can store data of phase map 242, 342, 442, 542, 642. Additionally, some cluster storage arrays can be configured to store backup versions of data stored in other cluster storage arrays.
The cluster routers 911a, 911b, and 911c in computing clusters 909a, 909b, and 909c can include networking equipment configured to provide internal and external communications for the computing clusters. For example, the cluster routers 911a in computing cluster 909a can include one or more internet switching and routing devices configured to provide (i) local area network communications between the computing devices 900a and the cluster storage arrays 901a via the local cluster network 912a, and (ii) wide area network communications between the computing cluster 909a and the computing clusters 909b and 909c via the wide area network connection 913a to network 238. Cluster routers 911b and 911c can include network equipment similar to the cluster routers 911a, and cluster routers 911b and 911c can perform similar networking functions for computing clusters 909b and 909b that cluster routers 911a perform for computing cluster 909a.
In some embodiments, the configuration of the cluster routers 911a, 911b, and 911c can be based at least in part on the data communication requirements of the computing devices and cluster storage arrays, the data communications capabilities of the network equipment in the cluster routers 911a, 911b, and 911c, the latency and throughput of local networks 912a, 912b, 912c, the latency, throughput, and cost of wide area network links 913a, 913b, and 913c, and/or other factors that can contribute to the cost, speed, fault-tolerance, resiliency, efficiency and/or other design goals of the moderation system architecture.
The above detailed description describes various features and functions of the disclosed systems, devices, and methods with reference to the accompanying figures. In the figures, similar symbols typically identify similar components, unless context dictates otherwise. The example embodiments described herein and in the figures are not meant to be limiting. Other embodiments can be utilized, and other changes can be made, without departing from the spirit or scope of the subject matter presented herein. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the figures, can be arranged, substituted, combined, separated, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.
With respect to any or all of the ladder diagrams, scenarios, and flow charts in the figures and as discussed herein, each block and/or communication may represent a processing of information and/or a transmission of information in accordance with example embodiments. Alternative embodiments are included within the scope of these example embodiments. In these alternative embodiments, for example, functions described as blocks, transmissions, communications, requests, responses, and/or messages may be executed out of order from that shown or discussed, including substantially concurrent or in reverse order, depending on the functionality involved. Further, more or fewer blocks and/or functions may be used with any of the ladder diagrams, scenarios, and flow charts discussed herein, and these ladder diagrams, scenarios, and flow charts may be combined with one another, in part or in whole.
A block that represents a processing of information may correspond to circuitry that can be configured to perform the specific logical functions of a herein-described method or technique. Alternatively or additionally, a block that represents a processing of information may correspond to a module, a segment, or a portion of program code (including related data). The program code may include one or more instructions executable by a processor for implementing specific logical functions or actions in the method or technique. The program code and/or related data may be stored on any type of computer readable medium such as a storage device including a disk or hard drive or other storage medium.
The computer readable medium may also include non-transitory computer readable media such as computer-readable media that stores data for short periods of time like register memory, processor cache, and random access memory (RAM). The computer readable media may also include non-transitory computer readable media that stores program code and/or data for longer periods of time, such as secondary or persistent long term storage, like read only memory (ROM), optical or magnetic disks, compact-disc read only memory (CD-ROM), for example. The computer readable media may also be any other volatile or non-volatile storage systems. A computer readable medium may be considered a computer readable storage medium, for example, or a tangible storage device.
Moreover, a block that represents one or more information transmissions may correspond to information transmissions between software and/or hardware modules in the same physical device. However, other information transmissions may be between software modules and/or hardware modules in different physical devices.
The particular arrangements shown in the figures should not be viewed as limiting. It should be understood that other embodiments can include more or less of each element shown in a given figure. Further, some of the illustrated elements can be combined or omitted. Yet further, an example embodiment can include elements that are not illustrated in the figures.
While various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.
This patent application is a continuation of U.S. application Ser. No. 13/834,354 which was filed on Mar. 15, 2013, the contents of which are entirely incorporated herein by reference as if fully set forth in this application.
| Number | Name | Date | Kind |
|---|---|---|---|
| 20020036571 | Takahashi | Mar 2002 | A1 |
| 20070118280 | Uhlmann | May 2007 | A1 |
| 20090212973 | Namikawa | Aug 2009 | A1 |
| 20100100324 | Caminiti | Apr 2010 | A1 |
| 20120161982 | Musachio | Jun 2012 | A1 |
| 20120242505 | Maeda | Sep 2012 | A1 |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 13834354 | Mar 2013 | US |
| Child | 15060346 | US |
