Methods and systems for reducing vehicle data transmission

Abstract

A method for reducing the transmission of detected vehicle data over a network is provided. The method includes receiving a first set of detected vehicle data from a vehicle at one or more processors located remotely from the vehicle, wherein the first set of detected vehicle data includes a triggering event from a first time period. The processor determines that no additional set of detected vehicle data is received during a second time interval. The processor also determines, based on the determination that no additional set of detected vehicle data was received, that no triggering event occurred during the second time interval. The processor further estimates estimated detected vehicle data for the vehicle during the second time interval based on the first set of detected vehicle data and the no-trigger assumption.

Description

Technical Field

[0001] This invention generally relates to the field of traffic tracking and prediction, and more specifically to using triggered events to reduce the amount and frequency of probe vehicle data transmitted over a network. Background Technology

[0002] Detection vehicle data includes location and speed data collected by vehicles as they move. Vehicle manufacturers are producing more and more cars with internal sensors, such as GPS units that collect detection vehicle data. These vehicles can help determine traffic speed, congestion, accidents, or other issues on the road. Vehicles can also transmit this information to remote servers that track traffic, calculate travel times, and generate traffic reports. These remote servers can use cellular network data to collect detection vehicle data from vehicles. When using cellular networks, every phone in traffic becomes an anonymous source of potential traffic detection and information. The location of each phone can be tracked, and algorithms can be used to extract high-quality data. Therefore, this detection vehicle data can be used without infrastructure or special hardware installed in vehicles or along roads. Summary of the Invention

[0003] In one embodiment, the present invention discloses a computer-implemented method for reducing the transmission of detected vehicle data over a network. The method includes receiving a first set of detected vehicle data from a vehicle at a server located remotely from the vehicle, wherein the first set of detected vehicle data includes a triggering event from a first time interval. The method further includes detecting at the server that a second set of detected vehicle data from a second time interval was not transmitted from the vehicle. The method further includes determining that the second set of detected vehicle data does not include the triggering event. The method further includes estimating estimated detected vehicle data for the vehicle in the second time interval based on the first set of detected vehicle data and a no-trigger assumption.

[0004] The estimated vehicle data for the second time interval includes: calculating the estimated travel distance of the vehicle since the trigger event interval; calculating the estimated heading range of the vehicle, wherein the estimated heading range includes the current heading received at the processor plus or minus a heading threshold, within which the vehicle will not trigger the trigger event; and comparing the estimated travel distance and the estimated heading range with map data stored on a remote server.

[0005] In another embodiment, the present invention provides a computer program product for reducing the transmission of detected vehicle data over a network. The computer program product includes one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media. The program instructions include instructions for receiving a first set of detected vehicle data from a vehicle at a server located remotely from the vehicle, wherein the first set of detected vehicle data includes a triggering event from a first time period. The program instructions also include instructions for detecting at the server that a second set of detected vehicle data from a second time interval has not been transmitted from the vehicle. The program instructions further include instructions for determining that the second set of detected vehicle data does not include a triggering event. The program instructions also include instructions for estimating estimated detected vehicle data of the vehicle in the second time interval based on the first set of detected vehicle data and a no-trigger assumption.

[0006] In another embodiment, the present invention provides a computer system for reducing the transmission of detected vehicle data over a network. The computer system includes one or more computer processors, one or more computer-readable storage media, and program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors. The program instructions include instructions for receiving a first set of detected vehicle data from a vehicle at a server located remotely from the vehicle, wherein the first set of detected vehicle data includes a triggering event from a first time interval. The program instructions also include instructions for detecting at the server that a second set of detected vehicle data from a second time interval has not been transmitted from the vehicle. The program instructions further include instructions for determining that the second set of detected vehicle data does not include a triggering event. The program instructions also include instructions for estimating estimated detected vehicle data for the vehicle in the second time interval based on the first set of detected vehicle data and a no-trigger assumption. Attached Figure Description

[0007] Figure 1 A simplified diagram of a vehicle monitoring system according to an embodiment of the present invention is depicted.

[0008] Figure 2 An embodiment of the invention is depicted in Figure 1 A flowchart of the steps of the vehicle sensor monitoring program executed within the system;

[0009] Figure 3 An embodiment of the invention is depicted in Figure 1 A graph showing the change in vehicle acceleration over time within the system;

[0010] Figure 4 A schematic representation of a vehicle agent mapped to a road according to an embodiment of the present invention is depicted; and

[0011] Figure 5 A block diagram depicts components of a monitoring server and a vehicle according to an illustrative embodiment of the present invention. Detailed Implementation

[0012] When collecting probed vehicle data over cellular networks, the amount of data transmitted can be expensive and cumbersome. Therefore, the embodiments disclosed herein selectively transmit probed vehicle data so that the vehicle's position, speed, acceleration, heading, or other data can be tracked, estimated, or interpolated without requiring constant, continuous monitoring by a server over the network. The embodiments described herein rely on triggering events to determine when to send / receive probed vehicle data. The triggering events are selected such that the reduced data points still provide sufficient information for vehicle tracking.

[0013] Figure 1 A simplified diagram of a vehicle monitoring system 100 according to an embodiment of the present invention is depicted. System 100 includes a server 102 connected via a network 106 to a vehicle 104 (i.e., sensors / devices connected to a processor within the vehicle 104). The vehicle 104 includes a processor (CPU) that receives and processes signals from sensors in the vehicle 104-1 to determine the condition of the vehicle 104-1 and its surrounding environment. The processor is generally described herein as a common part of the vehicle 104, and references to the vehicle 104-1 should be understood to include the processor for processing sensor signals and transmitting data via the network 106.

[0014] For example, network 106 may be a telecommunications network, a local area network (LAN), a wide area network (WAN) (such as the Internet), or a combination of all three, and the combination may include wired, wireless, or fiber optic connections. Network 106 may include one or more wired and / or wireless networks capable of receiving and transmitting data, voice, and / or video signals (including multimedia signals that include voice, data, and video information). Generally, network 106 may be any combination of connections and protocols that support communication between monitoring server 102 and other computing devices, such as vehicle 104 within vehicle monitoring system 100. In various embodiments, network 106 operates locally via wired, wireless, or optical connections and may be any combination of connections and protocols (e.g., personal area network (PAN), near field communication (NFC), laser, infrared, ultrasonic, etc.). Monitoring server 102 may include any suitable computer architecture for receiving and storing data. For example, monitoring server 102 may include a computer-readable storage medium (or medium) having computer-readable program instructions thereon for causing a processor to execute aspects of the present invention.

[0015] Vehicle 104 includes sensors for recording and / or collecting vehicle detection data as vehicle 104 drives along road 108. These sensors may include GPS positioning devices, speedometers, odometers, clocks, accelerometers, compasses, pressure sensors, or other sensors for detecting conditions inside or outside (i.e., the environment) of vehicle 104-1. Therefore, vehicle detection data includes current data on position, speed, distance, time, acceleration, heading, pressure, markings, or other information about vehicle 104-1 that can be detected by sensors. Vehicle detection data can also be detected by devices / sensors not directly installed in the vehicle. For example, a smartphone or stand-alone GPS device belonging to a user inside vehicle 104-1 can collect vehicle detection data. For simplicity, this application describes all devices that collect and transmit vehicle detection data as vehicle 104-1.

[0016] In addition to sensor data, vehicle 104-1 collects and / or computes preprocessed data as part of the detected vehicle data. For example, vehicle 104-1 may take the detected location and match that location with an onboard map or road markings, thereby making the set of detected vehicle data include map matching data or road marking data. Alternatively, vehicle 104-1 may measure the distance from the starting point and include this information in the set of detected vehicle data. Vehicle 104-1 may collect detected vehicle data from all sensors and all computations at a given time interval as a set of detected vehicle data. This time interval can be customized for the driver but is typically a short interval of about one second. Other time intervals may be used according to embodiments of the invention. Once the set of detected vehicle data has been collected and / or preprocessed, vehicle 104 includes a network connection that can transmit the set of detected vehicle data to network 106 and monitoring server 102.

[0017] Monitoring server 102 includes vehicle monitoring program 110, which receives the set of probe car data, monitors the condition of vehicle 104, and makes determinations about road 108 based on these conditions. To accurately monitor conditions, vehicle monitoring program 110 can receive sets of probe car data detected and preprocessed by vehicle 104. However, the short time intervals between sets of probe car data increase congestion on network 106 and the cost of monitoring road 108. To reduce pressure on network 106, vehicle monitoring program 110 can receive probe car data only when a triggering event has occurred. That is, while vehicle 104-1 may collect a set of probe car data per second or other short time intervals, vehicle monitoring program 110 can receive only one set of triggering event probe car data 112 whenever a triggering event occurs at vehicle 104-1. This reduces the amount of data transmitted over the network, increasing speed and reducing cost. Vehicle monitoring program 110 uses the triggering event probe car data 112 to store a vehicle agent 114 representing vehicle 104 and its associated position, speed, heading, etc., on monitoring server 102. As explained in detail below, the vehicle monitoring program 110 estimates the estimated time interval during which the vehicle monitoring program 110 has not received actual detected vehicle data 116.

[0018] Triggering event detection vehicle data 112 and estimated detection vehicle data 116 can be delivered to a post-processor 118, which can be used to optimize the driver journey by managing fleet operations, monitoring driver behavior, and simplifying car sharing. Furthermore, the post-processor 118 can predict vehicle malfunctions by monitoring usage, fuel consumption, safety, and in-vehicle activities to reduce maintenance of vehicle 104-1. The post-processor 118 can communicate back to the driver in vehicle 104-1 to provide them with data that adds context and situational awareness, and to provide insights into the movement and driving behavior of each vehicle 104. The post-processor 118 can also evaluate real-time interval data from multiple sources, including weather, geolocation, traffic, social media, and other data systems, to derive a holistic model of vehicle 104-1 and road 108.

[0019] Figure 2 An embodiment of the invention is depicted in Figure 1The flowchart illustrates the steps of the vehicle monitoring procedure 110 executed within system 100. During operation of system 100, vehicle monitoring procedure 110 receives a first set of detected vehicle data from one of vehicles 104 (e.g., vehicle 104-1) via network 106 (block 202). The first set of detected vehicle data includes a set of triggered event detected vehicle data 112 from a first time interval having a trigger event and other sensor data already detected by vehicle 104-1. Vehicle 104-1 will not send a set of detected vehicle data to network 106 if no trigger event is experienced. Trigger events are conditions detected by vehicle 104-1 that are predefined to trigger the transmission of detected vehicle data. Such conditions can be categorized as "global events" or "notification events."

[0020] Global events can include those capable of detecting trigger differences between two probe vehicle data over long time intervals. For example, if the angle of road 108 changes by one degree in one second, this one-degree change will not cause vehicle 104-1 to send trigger event probe vehicle data 112. However, if road 108 continues to change at one degree per second for 30 seconds, vehicle 104 recognizes the significant change of 30 degrees and triggers both a global event and the transmission of trigger event probe vehicle data 112. Vehicle 104-1 will also trigger a global event after a predefined duration has expired. Cue events can be detected more immediately using only cue data (e.g., the current derivative of acceleration). For example, vehicle 104-1 can monitor the absolute value of the acceleration difference between two consecutive time intervals to determine if the difference is greater than an acceleration trigger threshold.

[0021] Figure 3 An embodiment of the present invention is depicted. Figure 1 A graph 300 shows the derivative of the acceleration 302 of vehicle 104 within system 100 at time interval 304. Vehicle 104-1 tracks the current derivative of acceleration 306 and compares it to a threshold 308. If the absolute value of the current derivative of acceleration 306 is detected to be outside the threshold 308 (e.g., at time interval 310), vehicle 104-1 identifies a trigger event, and a set of trigger event detection vehicle data 112 is sent to network 106 and received by vehicle monitoring program 110. Acceleration changes outside the threshold 308 (e.g., at time interval 312) do not trigger the transmission of trigger event detection vehicle data 112. Similar tracking is maintained for speed, heading, or other sensor data that may indicate trigger events. The threshold can be programmed from known general operating conditions and can be customized based on vehicle type, driver's driving habits, road characteristics 108, or other details related to a particular vehicle 104.

[0022] See back Figure 2Vehicle monitoring program 110 monitors incoming signals from vehicle 104 and detects that a second set of probe vehicle data from a second time period has not been sent from vehicle 104-1 (block 204). Vehicle monitoring program 110 may have a minimum waiting time interval before which it does not receive a set of probe vehicle data. However, the minimum waiting time interval may be short (e.g., the time interval for collecting probe vehicle data: 1.5 seconds to 2 seconds), and its expiration enables vehicle monitoring program 110 to detect the absence of the second set of probe vehicle data and determine that the second set of probe vehicle data does not include the triggering event (block 206).

[0023] In the absence of a second set of probe vehicle data, vehicle monitoring program 110 estimates estimated probe vehicle data 116 (box 208) for vehicle 104-1. Estimating the estimated probe vehicle data 116 involves using probe vehicle data 112 triggered by an event and a no-trigger assumption (i.e., the event did not occur at the second time interval). For example, this means that changes in heading angle, speed, acceleration, etc., do not exceed ranges allowed by heading thresholds and / or speed thresholds. In some embodiments, vehicle monitoring program 110 estimates changes in acceleration whose absolute value is not outside the threshold. For example, if acceleration increases from zero and trigger event probe vehicle data 112 is transmitted, vehicle monitoring program 110 calculates the current acceleration using a constant decay rate. That is, vehicle monitoring program 110 is programmed to recognize that as vehicle 104-1 approaches its cruising speed, the acceleration of vehicle 104-1 will decrease, and a constant decay rate has been found to accurately measure the behavior of many vehicles 104.

[0024] Figure 4A schematic representation of a vehicle agent 414 mapped to road 408 according to an embodiment of the present invention is depicted. This schematic representation does not necessarily reflect the actual implementation of the vehicle agent in all embodiments, but is merely an example for illustrative purposes. In the illustrated embodiment, vehicle monitoring program 110 receives trigger event detection vehicle data for a first time interval. The trigger event detection vehicle data includes (among other potential data) position, heading angle, and speed, which are graphically represented (for illustrative purposes only) by a first vehicle agent 422 having position relative to the road, arrow direction, and arrow length, respectively. In a second time interval, vehicle monitoring program 110 does not receive trigger event detection vehicle data and estimates estimated detection vehicle data (represented by a second vehicle agent 424) using the trigger event detection vehicle data (represented by the first vehicle agent 422) and the no-trigger assumption that the heading angle and speed are within associated thresholds. Similarly, vehicle monitoring program 110 does not receive trigger event detection vehicle data for a third or fourth time interval and estimates estimated detection vehicle data (represented by third and fourth vehicle agents 426 and 428).

[0025] Vehicle monitoring program 110 can estimate the estimated probed vehicle data by eliminating potential paths based on the configuration of road 408. That is, vehicle monitoring program 110 can identify alternative paths (represented by the hypothetical vehicle agent 430), but eliminate these paths due to the necessary heading change and subsequent reception of triggering event probed vehicle data that will accompany vehicle 104-1 traveling the alternative path in a third time interval. Since vehicle monitoring program 110 does not receive triggering event probed vehicle data, vehicle monitoring program 110 estimates the straight-line route of the vehicle (i.e., third vehicle agent 426 and fourth vehicle agent 428).

[0026] Figure 4 Two options for a triggering event that may occur at the fifth time are shown. One option is that vehicle 104-1 turns slightly to the left along the left fork 408a. Because the heading change 430 between the fourth heading (i.e., the heading of the fourth vehicle agent 428) and the fifth heading (i.e., the heading of the fifth vehicle agent 432a) is greater than a threshold, vehicle 104-1 sends triggering event detection vehicle data. Therefore, vehicle monitoring program 110 does not estimate the detection vehicle data, but instead records the detection vehicle data as vehicle agent 432. Figure 4 The second option shown is that vehicle 104-1 takes a straighter path along the right fork 408b, but still sends trigger event detection vehicle data because the speed change exceeds a threshold. If vehicle 104-1 uses this option in the fourth time interval, vehicle monitoring program 110 represents vehicle 104-1 as vehicle agent 432b.

[0027] Some embodiments of the invention may also include interpolating the detected vehicle data instead of estimating it in advance. Figure 4 In this context, the interpolation performed by the vehicle monitoring program 110 includes waiting between a first time interval (vehicle agent 422) and a fifth time interval (vehicle agents 432a, 432b). When trigger event detection vehicle data is received at the fifth time interval, the vehicle monitoring program 110 interpolates the most likely detection vehicle data that occurred between the first and fifth time intervals. In the example shown, since vehicle 104-1 is unlikely to make any turn indicated by the hypothetical vehicle agent 430 and return to the received position by the fifth time interval, the hypothetical vehicle agent 430 is eliminated. Therefore, the vehicle monitoring program 110 interpolates vehicle 104-1 as it travels on the road as indicated by vehicle agents 424, 426, and 428.

[0028] In some embodiments, vehicle monitoring program 110 can determine traffic conditions and estimate the detected vehicle data (block 210) of vehicle 104 along road 108. Determining traffic conditions can be based on triggered event detected vehicle data or estimated detected vehicle data estimated by vehicle monitoring program 110. For example, if one or more vehicles experience acceleration changes at a location on road 108 where such acceleration changes are not normally present, vehicle monitoring program 110 can determine that an accident has occurred at that location, or that there is an obstruction in the road, or that some other event has occurred. If many vehicles 104 exhibit regular deceleration along a section of road 108, vehicle monitoring program 110 can determine that an obstruction, such as a pothole, crack, or bump, has appeared in that section. Similarly, temporary obstructions, such as debris on the road, can be identified based on the detected vehicle data received by vehicle monitoring program 110. Vehicle 104 can help determine traffic conditions by sending wave indicators (indicating wave-like speed and / or traffic movement) instead of triggered event detected vehicle data. In other words, if vehicle 104-1 encounters traffic congestion along road 108, vehicle 104-1 can stop relying on trigger events to send probe car data and instead periodically send wavy indicators and its current location. Vehicle monitoring program 110 determines whether a wavy indicator is present (box 212), and if so, determines that the road condition includes traffic congestion (box 212, "Yes"). For vehicle 104 sending a wavy indicator, vehicle monitoring program 110 can completely disregard the estimated probe car data 116 and simply track the congestion on road 108. If vehicle monitoring program 110 does not receive a wavy indicator (box 212, "No"), it determines whether vehicle 104-1 is still operating. If vehicle 104-1 is still operating (box 214, "Yes"), vehicle monitoring program 110 receives another set of trigger event probe car data. If vehicle 104-1 does not operate (box 214, "No"), the method used by vehicle monitoring program 110 ends until the next iteration.

[0029] Figure 5 A block diagram depicts components of a monitoring server 102 and a vehicle 104 according to an illustrative embodiment of the present invention. It should be understood that... Figure 5 This is merely an illustration of an implementation and does not imply any limitation regarding the environment in which different embodiments may be implemented. Many modifications can be made to the depicted environment.

[0030] Both the monitoring server 102 and the vehicle 104 include a communication structure 502 that provides communication between a computer processor 504, a memory 506, a persistent storage device 508, a communication unit 510, and an input / output (I / O) interface 512. The communication structure 502 can be implemented using any architecture designed to transfer data and / or control information between processors (such as microprocessors, communication and network processors, etc.), system memory, peripheral devices, and any other hardware components within the system. For example, the communication structure 502 can be implemented using one or more buses.

[0031] Memory 506 and persistent storage device 508 are computer-readable storage media. In this embodiment, memory 506 includes random access memory (RAM) 514 and cache memory 516. Generally, memory 506 may include any suitable volatile or non-volatile computer-readable storage medium.

[0032] The vehicle monitoring program 110 is stored in a persistent storage device 508 of the monitoring server 102 for execution and / or access by one or more corresponding computer processors 504 of the monitoring server 102 via one or more memories of the memory 506 of the monitoring server 102. In this embodiment, the persistent storage device 508 includes a magnetic hard disk drive. Alternatively, or in addition to a magnetic hard disk drive, the persistent storage device 508 may include a solid-state hard disk drive, a semiconductor storage device, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), flash memory, or any other computer-readable storage medium capable of storing computer-readable program instructions or digital information.

[0033] The media used in persistent storage device 508 can also be removable. For example, a removable hard disk drive can be used in persistent storage device 508. Other examples include optical discs and disks, thumb drives, and smart cards, which are inserted into the drive for transfer to another computer-readable storage medium that is also part of persistent storage device 508.

[0034] In these examples, communication unit 510 provides communication with other data processing systems or devices. In these examples, communication unit 510 includes one or more network interface cards. Communication unit 510 can provide communication using either or both physical and wireless communication links. Vehicle monitoring program 110 can be downloaded to permanent storage device 508 of monitoring server 102 via communication unit 510 of monitoring server 102.

[0035] I / O interface 512 allows for data input and output to other devices that can be connected to monitoring server 102 and / or vehicle 104-1. For example, I / O interface 512 may provide connectivity to external device 518 (such as a keyboard, keypad, touchscreen, and / or other suitable input devices). External device 518 may also include portable computer-readable storage media, such as thumb drives, portable optical discs or disks, and memory cards. Software and data used to implement embodiments of the invention (e.g., vehicle monitoring program 110) may be stored on such portable computer-readable storage media and may be loaded onto permanent storage device 508 of monitoring server 102 via I / O interface 512 of monitoring server 102. I / O interface 512 is also connected to display 520.

[0036] The display 520 provides a mechanism for displaying data to the user and may be, for example, a computer monitor.

[0037] The programs described herein are identified based on their application in specific embodiments of the invention. However, it should be understood that any specific procedural terminology used herein is for convenience only, and therefore the invention should not be limited to use only in any specific application identified and / or implied by such terminology.

[0038] This invention can be any possible system, method, and / or computer program product at any level of integration technical detail. The computer program product may include a computer-readable storage medium (or medium) having computer-readable program instructions thereon for causing a processor to execute aspects of the invention.

[0039] Computer-readable storage media can be tangible devices that can hold and store instructions for use by an instruction execution device. For example, a computer-readable storage medium can be, but is not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable optical disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices such as punch cards or structures with protrusions in grooves on which instructions are recorded, and any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0040] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device or to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to a computer-readable storage medium within the corresponding computing / processing device.

[0041] Computer-readable program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​(such as Smalltalk, C++, or similar languages) and procedural programming languages ​​(such as the "C" programming language or similar programming languages). The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network (including a local area network (LAN) or a wide area network (WAN)) or may be connected to an external computer (e.g., using an internet service provider via the internet). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute the computer-readable program instructions by utilizing state information from the computer-readable program instructions to personalize the electronic circuitry in order to perform aspects of this invention.

[0042] This document describes aspects of the invention with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0043] These computer-readable program instructions may be provided to a processor of a computer or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium that can instruct a computer, programmable data processing apparatus, and / or other device to operate in a particular manner, such that the computer-readable storage medium storing the instructions includes an article of manufacture comprising instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0044] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce a computer-implemented process, such that the instructions, which execute on the computer, other programmable apparatus, or other device, perform the functions / actions specified in one or more blocks of a flowchart and / or block diagram.

[0045] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the figures. For example, two blocks shown consecutively may actually be completed as a single step, executed simultaneously, substantially simultaneously, in a manner that partially or completely overlaps in time, or these blocks may sometimes be executed in reverse order, depending on the functions involved. It will also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a special-purpose hardware-based system that performs the specified function or action or performs a combination of special-purpose hardware and computer instructions.

Claims

1. A computer-implemented method for reducing the transmission of vehicle data, comprising: One or more processors located away from a vehicle traveling along the road receive a first set of vehicle detection data via a network, wherein the first set of vehicle detection data includes triggering events from a first time interval; It was determined that no additional probe vehicle data sets were received during the second time interval; Based on the determination that no additional probe vehicle data set was received during the second time interval, it was determined that no triggering event occurred during the second time interval; as well as Based on the first set of vehicle detection data, the road configuration, and the no-trigger assumption that no triggering event occurred during the second time interval, estimated vehicle detection data for the vehicle during the second time interval is estimated, wherein the estimated vehicle detection data includes a change in one of heading, speed, and acceleration less than a threshold.

2. The method of claim 1, wherein the first set of detected vehicle data comprises selection from the group consisting of: location, speed, time, heading, and vehicle identification.

3. The method of claim 1, wherein the first set of detected vehicle data includes preprocessed data selected from the group consisting of: map matching data, road sign data, and distances measured from the starting point.

4. The method of claim 1, wherein the first set of detected vehicle data includes a first heading and a first speed, and wherein the no-trigger assumption includes selection from the group consisting of: a current heading within a heading threshold from the first heading and a current speed within a speed threshold from the first speed.

5. The method of claim 1, wherein estimating the estimated detection vehicle data of the vehicle in the second time interval includes calculating the current acceleration using a constant decay rate of acceleration.

6. The method according to claim 1, comprising: The location of the vehicle and a wave sign are received at a third time interval, wherein the wave sign includes an indication of the wave-like movement of traffic. as well as In response to receiving the wave sign, road conditions are determined, including traffic congestion, without estimating the estimated detection vehicle data for the third time interval.

7. The method according to claim 1, comprising: A third set of vehicle detection data is received by one or more processors located remotely from the vehicle, wherein the third set of vehicle detection data includes trigger events from a third time interval; as well as The position of the vehicle in the second time interval is interpolated based on the first set of vehicle detection data and the third set of vehicle detection data.

8. The method of claim 1, wherein the triggering event comprises the absolute value of the acceleration difference between two consecutive time intervals greater than the acceleration triggering threshold.

9. The method of claim 1, wherein estimating the estimated detection vehicle data of the vehicle in the second time interval comprises: Calculate the estimated travel distance of the vehicle since the interval from the triggering event; Calculate the estimated heading range of the vehicle, wherein the estimated heading range includes the current heading received at the processor plus or minus a heading threshold, within which the vehicle will not trigger a triggering event; as well as The estimated driving distance and the estimated heading range are compared with map data stored on a remote server.

10. A computer program product for reducing the transmission of vehicle data, the computer program product comprising program instructions, the program instructions including: Program instructions for receiving, via a network, a first set of vehicle detection data from a vehicle traveling remotely along the road, wherein the first set of vehicle detection data includes a triggering event from a first moment. The program instructions used to determine that no additional probe vehicle data sets were received during the second time interval; Program instructions for determining that no additional detection vehicle data was received during the second time interval and that no triggering event occurred during the second time interval; as well as Program instructions for estimating estimated vehicle data of the vehicle in the second time interval based on the first set of detected vehicle data, the configuration of the road, and the no-trigger assumption that no triggering event occurred during the second time interval, wherein the estimated detected vehicle data includes a change in one of heading, speed, and acceleration less than a threshold.

11. The computer program product of claim 10, wherein the first set of detected vehicle data comprises selected from the group consisting of: position, speed, time, heading, and vehicle identification.

12. The computer program product of claim 10, wherein the first set of detected vehicle data includes preprocessed data selected from the group consisting of: map matching data, road sign data, and distances measured from the starting point.

13. The computer program product of claim 10, wherein the first set of detected vehicle data includes a first heading and a first speed, and wherein the no-trigger assumption includes selection from the group consisting of: a current heading within a heading threshold from the first heading and a current speed within a speed threshold from the first speed.

14. The computer program product of claim 10, wherein estimating the estimated detection vehicle data of the vehicle in the second time interval includes calculating the current acceleration using a constant rate of decay of acceleration.

15. The computer program product according to claim 10, comprising: Program instructions for receiving wave signs and the location of the vehicle at a third time interval, wherein the wave signs include indications of the wave-like movement of traffic. as well as Program instructions for responding to receiving the wave sign and determining road conditions, including traffic congestion, without estimating the estimated detection vehicle data of the third time interval.

16. The computer program product of claim 10, wherein estimating the estimated detection vehicle data for the vehicle during the second time interval comprises: Program instructions for calculating the estimated travel distance of the vehicle from the interval between the triggered events; Program instructions for calculating an estimated heading range for the vehicle, wherein the estimated heading range includes the current heading received at the processor plus or minus a heading threshold, within which the vehicle will not trigger a triggering event; as well as Program instructions for comparing the estimated travel distance and the estimated heading range with map data stored on a remote server.

17. A computer system for reducing the transmission of vehicle detection data, the computer system comprising: One or more computer processors, one or more computer-readable storage media, and program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: Program instructions for receiving, via a network, a first set of vehicle detection data from a vehicle traveling remotely along the road, wherein the first set of vehicle detection data includes a triggering event from a first moment. Program instructions used to determine that no additional probe vehicle data was received during the second time interval; Program instructions for determining that no additional detection vehicle data was received during the second time interval and that no triggering event occurred during the second time interval; and Program instructions for estimating estimated vehicle data of the vehicle in the second time interval based on the first set of detected vehicle data, the configuration of the road, and the no-trigger assumption that no triggering event occurred during the second time interval, wherein the estimated detected vehicle data includes a change in one of heading, speed, and acceleration less than a threshold.

18. The computer system of claim 17, wherein the first set of detected vehicle data includes a first heading and a first speed, and wherein the no-trigger assumption includes selection from the group consisting of: a current heading within a heading threshold from the first heading and a current speed within a speed threshold from the first speed.

19. The computer system according to claim 17, comprising: Program instructions for receiving wave signs and the location of the vehicle at a third time interval, wherein the wave signs include indications of the wave-like movement of traffic. as well as In response to receiving the wave sign, program instructions are used to determine road conditions, including traffic congestion, without estimating the estimated detection vehicle data for the third time interval.

20. The computer system of claim 17, wherein estimating the estimated detection vehicle data for the vehicle in the second time interval comprises: Program instructions for calculating the estimated travel distance of the vehicle from the interval between the triggered events; Program instructions for calculating an estimated heading range for the vehicle, wherein the estimated heading range includes the current heading received at the processor plus or minus a heading threshold, within which the vehicle will not trigger a triggering event; as well as Program instructions for comparing the estimated travel distance and the estimated heading range with map data stored on a remote server.

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