Determining street segment headings

Embodiments of the present invention provide methods, systems, computer program products, and apparatuses for determining whether a street segment is a one-way street segment or a bi-directional segment, validating map data, and/or updating map data. In one embodiment, a method for determining whether a street segment is a one-way street segment or a bi-directional segment is provided. The method comprises receiving vehicle telematics data associated with one or more vehicles during one or more time periods, the vehicle telematics data indicating a street segment traveled by the one or more vehicles during the one or more time periods; and based at least in part on the vehicle telematics, determining whether the street segment is a one-way street segment or a bi-directional segment.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. application Ser. No. 14/708,473, filed May 11, 2015, which is hereby incorporated herein in its entirety.

FIELD

Various embodiments of the present invention described herein generally relate to efficiency management systems for analyzing heading data associated with at least one street segment traveled by at least one vehicle and determining the accuracy of map data based on the heading data.

BACKGROUND

Improving operational efficiency has become an increasingly high priority for many businesses. In particular, the increasing cost of energy resources, such as fuel, and recent trends toward improving environmental sustainability have made reducing the consumption of energy resources essential for many businesses to maintain a competitive advantage in their respective industries. Likewise, volatile economic climates have increased competition in various industry sectors and prompted competing businesses to provide better services at a lower cost. As a result, many businesses are searching for ways to improve their operational efficiency in order to reduce costs and provide improved service to customers.

As business emphasis on operational efficiency has grown, so too has the development of technology capable of monitoring various operational characteristics. For example, businesses can use GPS (or other GNSS systems) and RFID technologies to track the location of people, vehicles, and items and generate data representative of those locations in relation to time. In addition, telematics devices are currently used in vehicles to capture information relating to various vehicle dynamics, such as fuel consumption and location.

Although such technology allows businesses to capture large amounts of operational data reflecting a variety of operational characteristics, many businesses are unable to effectively utilize such data to improve efficiencies. This problem is commonly the result of an inability to effectively translate otherwise overwhelming amounts of data into a format that is meaningful in the context of analyzing a particular efficiency. Thus, there is a need in the art for improved concepts for capturing and evaluating operational data in order to improve operational efficiencies in a variety of business contexts.

Additionally, inaccuracies in data used to plan business operations may cause additional inefficiencies. Map vendors, such as Tele Atlas® and NAVTEQ®, provide digital/electronic geographical maps to a variety of clients for different purposes. For example, map vendors may provide digital maps to (a) Internet websites for providing driving directions to consumers; (b) cellular companies to include in smartphones; (c) government agencies (e.g., the United States Department of Agriculture and Environmental Protection Agency) for use in their respective government functions; and (d) transportation and logistics companies, such as United Parcel Service of America, Inc. (UPS), for determining and optimizing delivery routes. Unfortunately, the digital maps provided by vendors are not always accurate. For example, streets may be marked as one-way streets when the street is really bi-directional. By increasing the accuracy of the digital maps, business operations based on the digital maps may be more efficient. Thus, there is also a need in the art for improving the accuracy of digital maps.

BRIEF SUMMARY

Various embodiments of the present invention are generally directed to a system for determining the heading of a defined street segment traveled by at least one vehicle and/or increasing the accuracy of map data based on heading data for one or more defined street segments. Various embodiments of the present invention provide methods, systems, computer program products, and apparatuses for determining whether a street segment is a one-way street segment or a bi-directional segment, validating map data, and/or updating map data.

According to one aspect of the present invention, a method for determining whether a street segment is a one-way street segment or a bi-directional segment is provided. In one embodiment, the method comprises receiving vehicle telematics data associated with one or more vehicles during one or more time periods, the vehicle telematics data indicating a street segment traveled by the one or more vehicles during the one or more time periods; and based at least in part on the vehicle telematics, determining whether the street segment is a one-way street segment or a bi-directional segment.

According to another aspect of the present invention, a system is provided. The system comprises at least one processor and at least one memory including computer program code. In one embodiment, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least receive vehicle telematics data associated with one or more vehicles during one or more time periods, the vehicle telematics data indicating a street segment traveled by the one or more vehicles during the one or more time periods; and based at least in part on the vehicle telematics, determine whether the street segment is a one-way street segment or a bi-directional segment.

According to yet another aspect of the present invention, a computer program product is provided. In one embodiment, computer program product comprises at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein. The computer-readable program code portions comprise an executable portion configured to receive vehicle telematics data associated with one or more vehicles during one or more time periods, the vehicle telematics data indicating a street segment traveled by the one or more vehicles during the one or more time periods; and an executable portion configured to, based at least in part on the vehicle telematics, determine whether the street segment is a one-way street segment or a bi-directional segment.

According to one aspect of the present invention, a method for validating map data associated with a street segment is provided. In one embodiment, the method comprises (a) receiving vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) based at least in part on the vehicle telematics data, determining a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) identifying map data associated with the street segment, wherein the map data comprises street segment direction data indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) comparing the street segment direction data of the map data and the determined street segment direction.

According to another embodiment of the present invention, a system is provided. In one embodiment, the system comprises at least one processor and at least one memory including computer program code. The at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least (a) receive vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) based at least in part on the vehicle telematics data, determine a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) identify map data associated with the street segment, wherein the map data comprises street segment direction data indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) compare the street segment direction data of the map data and the determined street segment direction.

According to yet another aspect of the present invention, a computer program product is provided. In one embodiment, the computer program product comprises at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein. The computer-readable program code portions comprise (a) an executable portion configured to receive vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) an executable portion configured to, based at least in part on the vehicle telematics data, determine a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) an executable portion configured to identify map data associated with the street segment, wherein the map data comprises street segment direction data indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) an executable portion configured to compare the street segment direction data of the map data and the determined street segment direction.

According to one aspect of the present invention, a method for updating map data associated with a street segment is provided. In one embodiment, the method comprises (a) receiving vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) based at least in part on the vehicle telematics data, determining a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) identifying map data associated with the street segment, wherein the map data comprises street segment direction data indicator indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) updating the map data to reflect the determined street segment direction for the street segment direction.

According to another aspect of the present invention, a system is provided. In one embodiment, the system comprises at least one processor and at least one memory including computer program code. The at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least (a) receive vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) based at least in part on the vehicle telematics data, determine a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) identify map data associated with the street segment, wherein the map data comprises street segment direction data indicator indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) update the map data to reflect the determined street segment direction for the street segment direction.

According to yet another aspect of the present invention, a computer program product is provided. In one embodiment, the computer program product comprises at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein. the computer-readable program code portions comprise (a) an executable portion configured to receive vehicle telematics data indicative of a travel path of a vehicle on a street segment during one or more time periods; (b) an executable portion configured to based at least in part on the vehicle telematics data, determine a street segment direction for the street segment, the determined street segment direction indicating whether the street segment is a one-way street segment or a bidirectional street segment; (c) an executable portion configured to identify map data associated with the street segment, wherein the map data comprises street segment direction data indicator indicating whether the street segment is a one-way street segment or a bidirectional street segment; and (d) an executable portion configured to update the map data to reflect the determined street segment direction for the street segment direction.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

Computer Program Products, Methods, and Computing Entities

Overview

According to various embodiments of the present invention, an efficiency management system is provided for evaluating various operational efficiencies based on operational data.FIG. 1illustrates the high-level system architecture of an efficiency management system1according to various embodiments. As shown, the efficiency management system1includes one or more data sources2and a central server3. The data sources2may be, for example, devices configured for capturing and communicating operational data indicative of one or more operational characteristics (e.g., a telematics device capturing telematics data from a vehicle, handheld devices such as mobile phones, and/or the like). The data sources2are configured to communicate with the central server3by sending and receiving operational data over a network4(e.g., the Internet, an Intranet, or other suitable network). The central server3may be configured to process and evaluate operational data received from the data sources2in accordance with user input received via a user interface (e.g., a graphical user interface (user interface) provided on a local or remote computer). A user interface may be an application, browser, user interface, interface, and/or similar words used herein interchangeably. For example, in certain embodiments, the central server3may be configured for segmenting operational data according to various operational activities, identifying various undesirable or inefficient activities or occurrences based on the operational data, and/or generating a graphical presentation based on the operational data that displays operational activities in the context of other efficiency-indicative data.

As discussed in greater detail below, the components and general system architecture of the efficiency management system1illustrated inFIG. 1may be adapted for use in specific environments. For example, in certain embodiments, the efficiency management system may be configured as a “fleet management system” adapted for evaluating and managing a fleet of vehicles (e.g., a fleet of vehicles operated by a carrier entity, a fleet of taxis or buses operated by a private or public transportation entity, and/or the like). In such embodiments, the data sources may comprise telematics devices positioned on various vehicles in the fleet, as well as mobile service devices operated at least in part by operators of the fleet vehicles. Likewise, the central server may be configured for evaluating telematics data received from the telematics devices in order to assess vehicle efficiency and other logistical efficiencies. In addition, the central server may be configured for providing graphical presentations of telematics data in efficiency-indicative formats, as well as for updating GPS-based maps based on vehicle telematics data.

The following description provides a detailed explanation of certain embodiments of the efficiency management system, including the aforementioned fleet management system. As will be appreciated from the detailed description herein, the various components and features of these systems may be modified and adapted to assess efficiencies in a variety of operational contexts.

Fleet Management System

According to various embodiments, a fleet management system is provided for capturing and storing operational data for a fleet of vehicles, and for evaluating the operational data in order to assess various fleet efficiencies and improve the overall operational efficiency of the fleet. The fleet management system may be used, for example, by a carrier entity to evaluate the efficiency of a fleet of vehicles used to deliver freight or packages. A carrier may be a traditional carrier, such as United Parcel Service (UPS), FedEx, DHL, courier services, the United States Postal Service (USPS), Canadian Post, freight companies (e.g. truck-load, less-than-truckload, rail carriers, air carriers, ocean carriers, etc.), and/or the like. However, a carrier may also be a nontraditional carrier, such as Amazon, Google, Uber, ride-sharing services, crowd-sourcing services, retailers, and/or the like.

As described in detail below, various embodiments of the fleet management system are configured to capture operational data from the fleet—including telematics data from fleet vehicles—and evaluate the captured operational data in order to identify inefficient operations. As a particular example, the efficiency management system may be configured to evaluate telematics data captured from one or more vehicles to evaluate the accuracy of map data based on vehicle travel during a particular time period, along a particular travel route, and/or within a particular geographic area. As will be appreciated from the description herein, this and other system attributes allow the fleet management system to assist vehicle fleet managers (e.g., carrier entities) in improving the operating efficiency of their fleet.

Fleet Management System Architecture

FIG. 2shows the system architecture of a fleet management system5according to various embodiments. In the illustrated embodiment, the fleet management system5comprises a vehicle telematics device102positioned on a vehicle100and a central server120. A vehicle100may be a manned or an unmanned tractor, a truck, a car, a motorcycle, a moped, a Segway, a bicycle, a golf cart, a hand truck, a cart, a trailer, a tractor and trailer combination, a van, a flatbed truck, a vehicle, a drone, an airplane, a helicopter, a barge, a boat, and/or any other form of object for moving or transporting people and/or items (e.g., one or more packages, parcels, bags, containers, loads, crates, items banded together, vehicle parts, pallets, drums, the like, and/or similar words used herein interchangeably). The telematics device102and the central server120are configured to communicate with each other via a communications network130(e.g., the Internet, an Intranet, a cellular network, or other suitable network). In addition, the telematics device102and central server120are configured for storing data to an accessible central server database (not shown) located on, or remotely from, the central server120.

In the description provided herein, the fleet management system5may be configured for managing and evaluating the operation of a large fleet of vehicles. As such, in various embodiments, the fleet management system5may further comprise a plurality of telematics devices102, each being associated with one of a plurality of vehicles100. While the detailed description of the fleet management system's components is provided below with reference to individual components or devices, it will be understood from the description herein that various embodiments of the fleet management system5may include a plurality of the components each configured as described below. For example, large-scale embodiments of the fleet management system may include thousands of telematics devices102each capturing data from a unique vehicle100and transmitting the captured data to multiple servers120. In addition, as will be appreciated from the description herein, the fleet management system5may be adapted for managing and evaluating a fleet of vehicles in a variety of contexts, such as a fleet of taxis, buses, and other service vehicles. Accordingly, the telematics device102represents one embodiment of a telematics device that may be adapted for providing telematics data for a fleet of vehicles.

In the illustrated embodiment ofFIG. 2, the vehicle100includes a plurality of vehicle sensors configured for generating telematics data indicative of various vehicle dynamics, such as engine ignition, engine speed, vehicle speed, vehicle location, vehicle heading, and the status of various vehicle components. The vehicle sensors may be controlled by the telematics device102, which may be positioned on or within the vehicle100. In controlling the various vehicle sensors, the telematics device102is able to capture and store telematics data from the various vehicle sensors according to a programmed logic and associate the captured telematics data with contextual data (e.g., date, time, location). The captured telematics data and contextual data may then be transmitted by the telematics device102directly to the central server120via the network130, or to another computing device (which may later transmit the data to the central server120itself).

According to various embodiments, the central server120is generally configured for evaluating operational data (e.g., telematics data) for a fleet of vehicles in order to assess various fleet efficiencies and aid fleet management system5users in managing the fleet. As shown inFIG. 2, the central server120may be configured for receiving and storing telematics data from the telematics device102over the network130. By collecting such operational data over a period of time from various telematics devices102—which may be associated with a fleet of vehicles100—the central server120is able to amass operational data reflecting the overall operations of the fleet. As will be described in greater detail below, the central server120may be configured for evaluating telematics data, presenting the data to a user, and evaluating the data in a variety of ways in order to improve the operating efficiency of the fleet of vehicles100.

The various components of the fleet management system5are now described in detail below according to various embodiments.

Network

Vehicle Sensors

As noted above, in various embodiments the vehicle100is equipped with a variety of vehicle sensors capable of generating vehicle telematics data. For example, in one embodiment, the vehicle100includes sensors configured to make measurements and capture data pertaining to the following vehicle dynamics: engine ignition (e.g., on or off), engine speed (e.g., RPM and idle time events), vehicle speed (e.g., miles per hour), seat belt status (e.g., engaged or disengaged), vehicle heading (e.g., degrees from center), vehicle backing (e.g., moving in reverse or not moving in reverse), vehicle door status (e.g., open or closed), vehicle handle status (e.g., grasped or not grasped by a driver), vehicle location (e.g., GPS coordinates; latitude and longitude), distance traveled (e.g., miles between two points), throttle position, brake pedal position, parking brake position, distance or time since last maintenance, and various engine measurements (e.g., engine oil pressure, engine temperature, and engine faults). In various other embodiments, the vehicle100may include any combination of the above-referenced sensors (and additional sensors known in the art) depending on the operational data desired by a fleet management system5user.

According to various embodiments, the vehicles sensors disposed within the vehicle100comprise on/off sensors, which register a voltage amount that corresponds with an on/off condition. For example, in one embodiment, a seat belt sensor may register 0V when the seat belt is disengaged and 12V when the seat belt is engaged. Such on/off sensors are sufficient for measuring vehicle dynamics in which operational data is needed to indicate two conditions, such as a seat belt, which is either engaged or disengaged at all times. As another example, one or more door position sensors may be connected, for example, to the driver side, passenger side, and bulkhead doors, and may register 0V when the door with which the sensor is associated is in an open position, and 12V when the door is closed. As another example, an ignition sensor may register 0V when the vehicle100is turned off and 12V when the vehicle100is turned on. As yet another example, a backing light sensor may register 0V when the vehicles' backing lights are off and 12V when the vehicle's backing lights are on. As yet another example, the engine idle sensor may be configured to generate 0V when the engine speed is above idle and 12V when the engine is idling.

In addition, according to various embodiments, the vehicle sensors disposed within the vehicles100also comprise variable voltage sensors, which may be used to register variations in voltage reflecting a certain vehicle dynamic. For example, the engine speed sensor may detect the speed of the engine in revolutions per minute (RPM) by registering a particular voltage that corresponds to a particular RPM reading. The voltage of the sensor may increase or decrease proportionately with increases or decreases in the engine RPM. As another example, oil pressure sensors may detect the vehicle's oil pressure by registering a particular voltage that corresponds to a particular oil pressure. Other examples of variable voltage sensors may include temperature sensors, vehicle speed sensors, vehicle heading sensors, and vehicle location sensors.

In addition, according to various embodiments, the vehicle sensors disposed within the vehicles100also comprise environmental sensors, such as air quality sensors, temperature sensors, and/or the like. Thus, the captured data may also include carbon monoxide (CO), nitrogen oxides (NOx), sulfur oxides (SOx), Ethylene Oxide (EtO), ozone (O3), hydrogen sulfide (H2S) and/or ammonium (NH4) data, and/or meteorological data (e.g., referred to herein as telematics data).

The exemplary vehicle sensors described above may be configured, for example, to operate in any fashion suitable to generate computer-readable data that may be captured, stored, and transmitted by the telematics device102. In addition, while certain sensors are preferably disposed at particular locations on or within the vehicles100(e.g., handle sensors at the vehicle handles), other sensors may be disposed anywhere within the vehicle, such as within the telematics device102itself (e.g., a location sensor).

Data Source: Telematics Device

As noted above, according to various embodiments, the telematics device102(or data source) may be configured to control various vehicle sensors positioned on an associated vehicle100, capture vehicle telematics data generated by those sensors, and transmit the captured telematics data to the central server120via one of several communication methods. According to various embodiments, the various functions of the telematics device102described herein may be generally understood as being performed by one or more of the telematics device102components described below.

FIG. 3illustrates a detailed schematic block diagram of an exemplary telematics device102according to one embodiment. In the illustrated embodiment, the telematics device102includes the following components: a processor or processing element201(e.g., one or more complex programmable logic devices (CPLDs), microprocessors, multi-core processors, coprocessing entities, application-specific instruction-set processors (ASIPs), integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), hardware accelerators, other circuitry, and/or the like), a location-determining device or sensor202(e.g., GPS sensor), a real-time clock203, J-Bus protocol architecture204, an electronic control module (ECM)205, a port206for receiving data from vehicle sensors410located in one of the vehicles100(shown inFIG. 2), a communication port207for receiving instruction data, a radio frequency identification (RFID) tag212, a power source208, a data radio209for communication using various wired or wireless protocols and/or various memory210, and a programmable logic controller (PLC)211. In an alternative embodiment, the RFID tag212, the location sensor202, and the PLC211may be located in the vehicle100, external from the telematics device102. In other embodiments, the processes described herein as being carried out by a single processor201may be accomplished by multiple processors. In various embodiments, the telematics device102may not include certain of the components described above, and may include any other suitable components in addition to, or in place of, those described above. For example, the telematics device102may include various types of communications components other than those described above (e.g., to support new or improved communications techniques).

In one embodiment, the location sensor202may be one of several components available in the telematics device102. The location sensor202may be, for example, a GPS-based sensor compatible with GPS satellites115, such as Low Earth Orbit (LEO) satellite systems, Department of Defense (DOD) satellite systems, the European Union Galileo positioning systems, the Chinese Compass navigation systems, Indian Regional Navigational satellite systems, and/or the like. This data can be collected using a variety of coordinate systems, such as the Decimal Degrees (DD); Degrees, Minutes, Seconds (DMS); Universal Transverse Mercator (UTM); Universal Polar Stereographic (UPS) coordinate systems; and/or the like. Alternatively, triangulation may be used in connection with a device associated with a particular vehicle and/or the vehicle's operator and with various communication points (e.g., cellular towers or Wi-Fi access points) positioned at various locations throughout a geographic area to monitor the location of the vehicle100and/or its operator. The location sensor202may be used to receive position, time, and speed data. In addition, the location sensor202may be configured to detect when its vehicle100has entered or exited a GPS-defined geographic area (e.g., a geo-fenced area). As will be appreciated from the description herein, more than one location sensor202may be utilized, and other similar techniques may likewise be used to collect geo-location information associated with the vehicle100and/or its driver.

In one embodiment, the ECM205with J-Bus protocol204may be one of several components available in the telematics device102. The ECM205, which may be a scalable and subservient device to the telematics device102, may have data processor capability to decode and store analog and digital inputs and ECM data streams from vehicle systems and sensors410,420. The ECM205may further have data processing capability to collect and present vehicle data to the J-Bus204(which may allow transmittal to the telematics device102), and output standard vehicle diagnostic codes when received from a vehicle's J-Bus-compatible on-board controllers420or vehicle sensors410.

In one embodiment, the instruction data receiving port207may be one of several components available in the telematics device102. Embodiments of the instruction data receiving port207may include an Infrared Data Association (IrDA) communication port, a data radio, and/or a serial port. The instruction receiving data port207may receive instructions for the telematics device102. These instructions may be specific to the vehicle100in which the telematics device102is installed, specific to the geographical area in which the vehicle100will be traveling, or specific to the function the vehicle100serves within the fleet.

In one embodiment, an RFID tag212may be one of several components available for use with the telematics device102. One embodiment of the RFID tag212may include an active RFID tag, which comprises at least one of the following: (1) an internal clock; (2) a memory; (3) a microprocessor; and (4) at least one input interface for connecting with sensors located in the vehicle100or the telematics device102. Another embodiment of the RFID tag212may be a passive RFID tag. One or more RFID tags212may be internal to the telematics device102, wired to the telematics device102, and/or proximate to the telematics device102. Each RFID tag212may communicate wirelessly with RFID interrogators within a certain geographical range of each other. RFID interrogators may be located external to the vehicle100.

In one embodiment, the data radio209may be one of several components available in the telematics device102. The data radio209may be configured to communicate using various wired or wireless protocols, or any combination thereof. In one embodiment, a WPAN data radio provides connectivity between the telematics device102and peripheral devices used in close proximity to the vehicle100, a local computer, a cellular telephone, and/or the like. As mentioned above, in one embodiment of the invention, a WPAN, such as, for example, a Bluetooth™ network (IEEE 802.15.1 standard compatible) may be used to transfer information between the telematics device102and a portable data acquisition device or a peripheral device. In other embodiments, WPANs compatible with the IEEE 802 family of standards may be used. In one embodiment, the data radio209may be a Bluetooth™ serial port adapter that communicates wirelessly via WPAN to a Bluetooth™ chipset located in a peripheral device. In addition, a Media Access Control (MAC) address, which is a code unique to each Bluetooth™-enabled device that identifies the device, similar to an Internet protocol address identifying a computer in communication with the Internet, can be communicated to other devices in communication with the WPAN, which may assist in identifying and allowing communication among vehicles, cargo, and portable data acquisition devices equipped with Bluetooth™ devices. As discussed above with regard toFIG. 2, and as one of ordinary skill in the art will readily recognize, other wireless protocols exist (e.g., cellular technology) and can likewise be used in association with embodiments of the present invention.

As described in greater detail below, in various embodiments, the telematics device102may be configured to capture and store telematics data from the vehicle sensors410at predefined time intervals and in response to detecting the occurrence of one or more of a plurality of predefined vehicle events. Generally, a vehicle event may be defined as a condition relating to any parameter or combination of parameters measurable by the one or more vehicle sensors410(e.g., the engine idling, vehicle direction, vehicle turns, vehicle speed exceeding a certain threshold, etc.). As such, the telematics device102may be configured to continuously monitor the various vehicle sensors410and detect when the data being generated by one or more the vehicle sensors410indicates one or more of the plurality of predefined vehicle events. In response to detecting a vehicle event, the telematics device102can capture data from all of the vehicle sensors410or a particular subset of the vehicle sensors410associated with the detected vehicle event.

As an example, the telematics device102may be configured to recognize the occurrence of a first vehicle event (e.g., the vehicle's100engine being turned on or off), a second vehicle event (e.g., the vehicle's100speed exceeding a certain threshold), a third vehicle event (e.g., a seat belt in the vehicle100being engaged or disengaged), and/or a fourth vehicle event (e.g., vehicle's100heading reaching a threshold away from center). In one embodiment, the telematics device102may be configured to capture and store telematics data from all of the vehicle sensors410in response to detecting any of the first vehicle event, the second vehicle event, the third vehicle event, and/or the fourth event. In another embodiment, the telematics device102is further configured such that the first vehicle event is associated with a first subset of vehicle sensors (e.g., the seat belt sensor and location sensor), the second vehicle event is associated with a second subset of vehicle sensors (e.g., a vehicle speed sensor and location sensor), the third vehicle event is associated with a third subset of vehicle sensors (e.g., a seat belt sensor, engine speed sensor, and vehicle speed sensor), and the fourth vehicle event is associated with a fourth subset of vehicle sensors (e.g., a heading sensor and a location sensor). Accordingly, in this embodiment, the telematics device102will capture and store telematics data from the first set of vehicle sensors after detecting the first vehicle event, the second set of vehicle sensors after detecting the second vehicle event, the third set of vehicle sensors after detecting the third vehicle event, and the fourth set of vehicle sensors after detecting the fourth vehicle event.

The vehicle events programmed for recognition by the telematics device102can be defined in a variety of ways. As will be appreciated from the description herein, the telematics device102may be configured to capture telematics data in response to vehicle events defined by any combination of conditions sensed by the vehicle sensors410. These predefined vehicle events may be stored, for example, on the telematics device's memory210, or on another data storage medium accessible by the telematics device's processor201.

For example, in various embodiments, the telematics device102may be configured to recognize vehicle events characterized by data generated by on/off vehicle sensors. These vehicle events may include: (a) a vehicle's engine being turned on, (b) a vehicle's engine being turned off, (c) a vehicle door opening, (d) a vehicle door closing, (e) a vehicle door being locked, (f) a vehicle door being unlocked, (g) a vehicle's reverse gear being selected, (h) a vehicle's one or more forward drive gears being selected, (i) a vehicle's neutral or park gear being selected, (j) a vehicle's parking break being engaged, (k) a vehicle's seat belt being engaged, (l) a vehicle's seat belt being disengaged, (m) a vehicle's heading changing or continuing, (l) a vehicle turning, and any other event definable by a parameter measured by an on/off sensor.

In addition, various embodiments of the telematics device102are also configured to recognize vehicle events characterized by data generated by variable voltage vehicles sensors or other types of dynamic vehicle sensors. These vehicle events may include (a) a vehicle's speed increasing from standstill to a non-zero value, (b) a vehicle's speed decreasing from a non-zero value to standstill, (c) a vehicle's engine speed exceeding a certain threshold, (d) a vehicle's engine speed dropping below a certain threshold, (e) a vehicle beginning to move in a reverse direction, (f) a vehicle ceasing to move in a reverse direction, (g) a vehicle's heading reaching a threshold away from center, (h) a vehicle's engine temperature exceeding a certain threshold, (i) a vehicle's gas level falling below a certain level, (j) a vehicle's speed exceeding a certain threshold, and any other event definable by a parameter measured by a variable voltage or other dynamic sensor.

In addition, various embodiments of the telematics device102are also configured to recognize vehicle events characterized by data generated by GPS-sensors or other location sensing devices. These vehicle events may include (a) a vehicle moving into a geo-fenced area (e.g., a geo-fenced area defining a shipping hub, delivery area, or other work area), (b) a vehicle moving out of a geo-fenced area (e.g., a geo-fenced area defining a shipping hub, delivery area, or other work area), (c) a vehicle traveling onto a predefined route (e.g., a GPS-based road route), (d) a vehicle traveling off of a predefined route, (e) a vehicle traveling onto a known road (e.g., a road recognized by a GPS device), (f) a vehicle traveling off of a known road (e.g., exceeding a certain predefined distance from a known road), and any other event definable by a parameter measured by a location sensing device.

According to various embodiments, the telematics device102may be also configured to recognize multiple unique vehicle events based on a single varying parameter measured by one of the vehicle sensors410. As one example, the telematics device102may be configured such that a first vehicle event is detected anytime the vehicle's speed begins to exceed 50 miles-per-hour, while a second vehicle event is detected anytime the vehicle's speed begins to exceed 70 miles-per-hour. As such, the telematics device102may capture telematics data from vehicle sensors410in response to the vehicle100accelerating past 50 miles-per-hour, and again as the vehicle100accelerates past 70 miles-per-hour. In addition, as noted earlier, the telematics device102may capture telematics data from unique subsets of vehicle sensors based on the varying measurements of vehicle speed (e.g., a first subset of vehicles sensors associated with the 50-mph vehicle event and a second subset of vehicle sensors associated with the 70-mph vehicle event). This concept may also be applied to other variable parameters sensed by vehicle sensors, such as vehicle heading (e.g., various threshold degrees from center), engine speed (e.g., various threshold RPM measurements), and vehicle distance from a predefined path (e.g., threshold value for feet from a known road, vehicle route, or other GPS-based geographic location).

In addition, vehicle events may be defined by a combination of conditions indicated by various vehicle sensors410. For example, in certain embodiments, the telematics device102may be configured to detect instances of stationary vehicle engine idling (e.g., where the engine is on and the vehicle is not moving) based on a combination of data from a vehicle engine sensor and a vehicle speed sensor. In such embodiments, a first vehicle event is defined as the vehicle100being turned on and beginning to idle (e.g., instances in which the vehicle sensors410indicate the vehicle's engine is turned on and the vehicle speed is zero), a second vehicle event is defined as the vehicle100beginning to move and thereby ceasing to idle (e.g., instances in which the vehicle sensors410indicate the vehicle's engine is on and the vehicle's speed has increased from zero to a non-zero value), a third vehicle event is defined as the vehicle100slowing to a stop and beginning to idle again (e.g., any instance in which the vehicle sensors410indicate the vehicle's engine is on and the vehicle's speed has decreased from a non-zero value to zero), and a fourth vehicle event is defined as the vehicle100being turned off and again ceasing to idle (e.g., any instance in which the vehicle sensors410indicate the vehicle's engine is turned off and the vehicle speed is zero). As a result, in this embodiment, vehicle events are detected and telematics data is captured at the beginning and end of every period during which the vehicle's engine is idling. In various embodiments, the telematics device102can capture every period of engine idling for each vehicle. Other examples of vehicle events defined by a combination of conditions include (a) where a vehicle seat belt is engaged or disengaged while the vehicle is idling, (b) where a vehicle exceeds a certain speed while located within a certain geographic area associated with the certain speed, and (c) a vehicle door opening or closing while the engine is on.

In addition to—or as an alternative to—capturing telematics data in response to detected vehicle events, the telematics device102may be further configured to automatically capture telematics data from the vehicle sensors410at predefined time intervals. For example, in one embodiment, the telematics device102is programmed with a threshold data capture time (e.g., one second, 10 seconds, one minute) and may be configured to automatically capture telematics data from the vehicle sensors410where no vehicle events are detected for a period exceeding the defined time. This configuration ensures that the threshold data capture time is the longest possible duration between telematics data being collected and ensures that the vehicle100is continuously monitored even through periods where none of the predefined vehicle events are detected. As will be appreciated from the description herein, the threshold data capture time may be defined as any period of time according to the preference of a fleet management system5user. Where no vehicle events are defined, the telematics device102would then capture telematics data from the vehicle sensors according to the threshold data capture time interval as a default setting.

Although the telematics device102is described above as capturing telematics data in response to detected vehicle events, or in response to a certain elapsed time, the telematics device102may also be configured to capture telematics data in response to other occurrences. For example, the telematics device102may be triggered remotely from the central server to capture telematics data from all, or particular, vehicle sensors at any time.

As noted above, in response to a triggering event—such as a defined vehicle event or elapsed threshold data capture time—the telematics device102can capture telematics data from the vehicle sensors410. In one embodiment, the telematics device102may be configured to store the captured telematics data in fields of one or more data records, each field representing a unique measurement or other data from a unique vehicle sensor. As the telematics device102continues to capture telematics data in response to triggering events, multiple records of data comprising multiples sets of concurrently captured telematics data are amassed. The captured telematics data may be initially stored, for example, in the telematics devices memory modules201, in another data storage component of the telematics device102, or in a remote location (e.g., a cloud database).

In various embodiments, after capturing data from any of the vehicle sensors410, the telematics device102may be further configured to concurrently capture and store contextual data. The contextual data may include, for example, the date (e.g., 12/30/10) and time (e.g., 13:24) the data was captured, the vehicle from which the data was captured (e.g., a vehicle identification number such as 16234), the driver of the vehicle from which the data was captured at the time it was captured (e.g., John Q. Doe), and/or a logged reason for the data capture (e.g., a code indicating a detected vehicle event or indicating that the predefined time interval had elapsed). The contextual data may be captured, for example, from various telematics device components (e.g., an internal clock) and from data stored on the telematics device102(e.g., current driver name, current vehicle id, or various vehicle event codes). Further, the telematics device102may be configured to associate the captured telematics data with the captured contextual data in order to ensure concurrently captured telematics data and contextual data are linked. For example, in one embodiment, the telematics device102stores concurrently captured telematics data and contextual data in the same data record or records.

In various embodiments, a driver may be required to enter his or her driver ID number (or name) and vehicle id number at the beginning of each day (e.g., using a portable data acquisition device in communication with the telematics device102) in order to enable the telematics device102to associate telematics data captured that day with accurate contextual data. In other embodiments, the telematics device102may be programmed remotely (e.g., from the central server120over the network130) such that it is associated with the appropriate driver and vehicle information. According to various embodiments, the contextual data may be formatted in any computer-readable and transmittable data format. For example, in one embodiment, the contextual data is metadata. As the telematics data captured from the various vehicle sensors410is associated with the captured contextual data, the central server120will later be able to search and identify stored telematics data based on—for example—a particular date, time, vehicle, driver, and/or vehicle event.

As noted above, the telematics device102is also configured to transmit captured telematics data and contextual data to the central server120. According to various embodiments, the captured data may be transmitted using any of the communication methods or protocols described herein, as well as various other methods and protocols known in the art. For example, the telematics device102may be configured to first attempt to establish a connection with the central server120(e.g., via a wireless signal). If a successful connection is made, the telematics device102will transfer captured data to the central server120. However, if a successful connection cannot be made, the telematics device may be configured to alternatively transfer data to a portable data acquisition device (e.g., via a wireless signal or USB connection).

According to various embodiments, the defined vehicle events that trigger the telematics device102to capture and store telematics data, the sensors410from which telematics data are captured, and the intervals defined for capturing and storing data when no vehicle events are detected each may impact the effectiveness with which the fleet management system5is able to evaluate the captured telematics data. For example, capturing data from a large number of vehicle sensors at a high frequency may allow the fleet management system5to analyze the telematics data with greater accuracy. This could be accomplished, for example, by a fleet management system with many defined vehicle events and relatively short intervals for automatically capturing telematics data. Although the preceding is described in the context of a telematics device102capturing telematics data. The same can occur through various other devices (e.g., mobile phones) and other data (e.g., GPS and heading data captured from a mobile phone).

Data Source: User Computing Entity

In one embodiment, a data source2may be a user computing entity. A user may be an individual, a family, a company, an organization, an entity, a department within an organization, a representative of an organization and/or person, and/or the like. As indicated, the terms device, system, computing entity, entity, and/or similar words used herein interchangeably may refer to, for example, one or more computers, computing entities, desktop computers, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, gaming consoles (e.g., Xbox, Play Station, Wii), watches, glasses, iBeacons, proximity beacons, key fobs, RFID tags, ear pieces, scanners, televisions, dongles, cameras, wristbands, wearable items/devices, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein. Although not shown, the user computing entity can include an antenna, a transmitter (e.g., radio), a receiver (e.g., radio), and a processing element (e.g., CPLDs, microprocessors, multi-core processors, cloud processors, coprocessing entities, ASIPs, microcontrollers, and/or controllers) that provides signals to and receives signals from the transmitter and receiver, respectively.

The signals provided to and received from the transmitter and the receiver, respectively, may include signaling information in accordance with air interface standards of applicable wireless systems. In this regard, the user computing entity may be capable of operating with one or more air interface standards, communication protocols, modulation types, and access types. More particularly, the user computing entity may operate in accordance with any of a number of wireless communication standards and protocols, such as those described above with regard to the central server120. In a particular embodiment, the user computing entity may operate in accordance with multiple wireless communication standards and protocols, such as UMTS, CDMA2000, 1×RTT, WCDMA, GSM, EDGE, TD-SCDMA, LTE, E-UTRAN, EVDO, HSPA, HSDPA, Wi-Fi, Wi-Fi Direct, WiMAX, UWB, IR, NFC, Bluetooth, USB, and/or the like. Similarly, the user computing entity may operate in accordance with multiple wired communication standards and protocols, such as those described above with regard to the central server120via a network interface.

Via these communication standards and protocols, the user computing entity can communicate with various other entities using concepts such as Unstructured Supplementary Service Data (USSD), Short Message Service (SMS), Multimedia Messaging Service (MMS), Dual-Tone Multi-Frequency Signaling (DTMF), and/or Subscriber Identity Module Dialer (SIM dialer). The user computing entity can also download changes, add-ons, and updates, for instance, to its firmware, software (e.g., including executable instructions, applications, program modules), and operating system.

According to one embodiment, the user computing entity may include location determining aspects, devices, modules, functionalities, and/or similar words used herein interchangeably. For example, the user computing entity may include outdoor positioning aspects, such as a location module adapted to acquire, for example, latitude, longitude, altitude, geocode, course, direction, heading, speed, UTC, date, and/or various other information/data. In one embodiment, the location module can acquire data, sometimes known as ephemeris data, by identifying the number of satellites in view and the relative positions of those satellites (e.g., using GPS). The satellites may be a variety of different satellites, including Low Earth Orbit (LEO) satellite systems, DOD satellite systems, the European Union Galileo positioning systems, the Chinese Compass navigation systems, Indian Regional Navigational satellite systems, and/or the like. This data can be collected using a variety of coordinate systems, such as the DD, DMS, UTM, UPS coordinate systems, and/or the like. Alternatively, the location information can be determined by triangulating the user computing entity's position in connection with a variety of other systems, including cellular towers, Wi-Fi access points, and/or the like. Similarly, the user computing entity may include indoor positioning aspects, such as a location module adapted to acquire, for example, latitude, longitude, altitude, geocode, course, direction, heading, speed, time, date, and/or various other information/data. Some of the indoor systems may use various position or location technologies including RFID tags, indoor beacons or transmitters, Wi-Fi access points, cellular towers, nearby computing devices (e.g., smartphones, laptops) and/or the like. For instance, such technologies may include the iBeacons, Gimbal proximity beacons, Bluetooth Low Energy (BLE) transmitters, Bluetooth Smart, NFC transmitters, and/or the like. These indoor positioning aspects can be used in a variety of settings to determine the location of someone or something to within inches or centimeters. The position data, location data, heading data, and/or the like may be referred to as location data, GPS data, user computing entity data, and/or the like.

The user computing entity may also comprise a user interface (that can include a display coupled to a processing element) and/or a user input interface (coupled to a processing element). For example, the user interface may be a user application, browser, user interface, interface, and/or similar words used herein interchangeably executing on and/or accessible via the user computing entity to interact with and/or cause display of information from the central server120or telematics device102, as described herein. The user input interface can comprise any of a number of devices or interfaces allowing the user computing entity to receive data, such as a keypad (hard or soft), a touch display, voice/speech or motion interfaces, or other input device. In embodiments including a keypad, the keypad can include (or cause display of) the conventional numeric (0-9) and related keys (#, *), and other keys used for operating the user computing entity and may include a full set of alphabetic keys or set of keys that may be activated to provide a full set of alphanumeric keys. In addition to providing input, the user input interface can be used, for example, to activate or deactivate certain functions, such as screen savers and/or sleep modes.

The user computing entity can also include volatile storage or memory and/or non-volatile storage or memory, which can be embedded and/or may be removable. For example, the non-volatile memory may be ROM, PROM, EPROM, EEPROM, flash memory, MMCs, SD memory cards, Memory Sticks, CBRAM, PRAM, FeRAM, NVRAM, MRAM, RRAM, SONOS, FJG RAM, Millipede memory, racetrack memory, and/or the like. The volatile memory may be RAM, DRAM, SRAM, FPM DRAM, EDO DRAM, SDRAM, DDR SDRAM, DDR2 SDRAM, DDR3 SDRAM, RDRAM, TTRAM, T-RAM, Z-RAM, RIMM, DIMM, SIMM, VRAM, cache memory, register memory, and/or the like. The volatile and non-volatile storage or memory can store databases, database instances, database management systems, data, applications, programs, program modules, scripts, source code, object code, byte code, compiled code, interpreted code, machine code, executable instructions, and/or the like to implement the functions of the user computing entity. As indicated, this may include a user application that is resident on the entity or accessible through a browser or other user interface for communicating with the telematics device102, the central server120, and/or various other computing entities.

In another embodiment, the user computing entity may include one or more components or functionality that are the same or similar to those of the central server120, as described in greater detail above. As will be recognized, these architectures and descriptions are provided for exemplary purposes only and are not limiting to the various embodiments.

Central Server

As noted above, various embodiments of the central server120are generally configured for receiving and storing operational data (e.g., telematics data received from the telematics device102) and evaluating the operational data for a fleet of vehicles in order to assess various fleet efficiencies and aid fleet management system5users in improving the operational efficiency of the fleet. According to various embodiments, the central server120includes various means for performing one or more functions in accordance with embodiments of the present invention, including those more particularly shown and described herein. As will be appreciated from the description herein, however, the central server120may include alternative devices for performing one or more like functions without departing from the spirit and scope of the present invention.

FIG. 4illustrates a schematic diagram of the central server120according to various embodiments. The central server120includes a processor60that communicates with other elements within the central server120via a system interface or bus61. In the illustrated embodiment, the central server120includes a display device/input device64for receiving and displaying data. This display device/input device64may be, for example, a keyboard or pointing device that is used in combination with a monitor. In certain embodiments, the central server120may not include a display device/input device and may be alternatively accessed by a separate computing device (e.g., a networked device/entity) having a display device and input device. The central server120further includes memory66, which preferably includes both ROM65and RAM67. The server's ROM65is used to store a basic input/output system26(BIOS), containing the basic routines that help to transfer information between elements within the central server120.

In addition, the central server120includes at least one storage device63for storing information on various computer-readable media. As will be appreciated by one of ordinary skill in the art, each of these storage devices63is connected to the system bus61by an appropriate interface. The storage devices63and their associated computer-readable media provide nonvolatile storage for a personal computer. It is important to note that the computer-readable media described above could be replaced by any other type of computer-readable media known in the art.

A number of program modules may be stored by the various storage devices and within RAM65. In the illustrated embodiment, such program modules include an operating system80, a segment identification module2000, an individual segment analysis module3000, a one-way segment module4000, a regional analysis module5000, and a summary report module6000. According to various embodiments, the modules2000-6000control certain aspects of the operation of the central server120with the assistance of the processor60and operating system80. Embodiments of these modules are described in more detail below in relation toFIGS. 6-23. In a particular embodiment, these program modules2000-6000, are executed by the central server120and are configured to generate user interfaces accessible to users of the system. In one embodiment, the user interfaces may be accessible via the Internet or other communications network. In other embodiments, one or more of the modules2000-6000may be stored locally on one or more computers and executed by one or more processors of the computers.

According to various embodiments, the central server120may be configured to send data to, receive data from, and utilize data contained in a central server database, which may be comprised of one or more separate, linked databases. For example, in executing the various modules2000-6000, the central server120may retrieve data necessary for performing various analyses from the central server database, and may store data resulting from various analyses in the central server database. According to various embodiments, the central server database may be a component of the central server120, or a separate component located remotely from the central server120. In addition, the central server database may be configured for storing data in various data sets. In various embodiments, each data set may comprise a plurality of stored data records, each record (or set of associated records) comprising one or more data fields of unique data entries. For example, telematics data and contextual data concurrently captured by the telematics device102may be stored in a data record, where each data field in the data record represents a unique data entry (e.g., a measurement of vehicle speed, GPS coordinates, the time and date the data was captured, and an ID number of the vehicle from which the data was captured).

Also located within the central server120is a network interface74, for interfacing and communicating (e.g., using wired and/or wireless protocols) with other elements of a computer network. It will be appreciated by one of ordinary skill in the art that one or more of the central server120components may be located geographically remotely from other central server120components. Furthermore, one or more of the components may be combined, and additional components performing functions described herein may be included in the central server120.

While the foregoing describes a single processor/processing element60, as one of ordinary skill in the art will recognize, the central server120may comprise multiple processors operating in conjunction with one another to perform the functionality described herein. In addition to the memory66, the processor60can also be connected to at least one interface or other means for displaying, transmitting and/or receiving data, content or the like. In this regard, the interface(s) can include at least one communication interface or other means for transmitting and/or receiving data, content or the like, as well as at least one user interface that can include a display and/or a user input interface. The user input interface, in turn, can comprise any of a number of devices allowing the entity to receive data from a user, such as a keypad, a touch display, a joystick or other input device.

While reference is made to a central “server”120, as one of ordinary skill in the art will recognize, embodiments of the present invention are not limited to a client-server architecture and that the server need not be centralized. The system of embodiments of the present invention is further not limited to a single server, or similar network entity or mainframe computer system. Rather, the terms server, computing entity, computer, entity, device, system, and/or similar words used herein interchangeably may refer to, for example, one or more computers, computing entities, desktop computers, mobile phones, tablets, phablets, notebooks, laptops, distributed systems, gaming consoles (e.g., Xbox, Play Station, Wii), watches, glasses, iBeacons, proximity beacons, key fobs, radio frequency identification (RFID) tags, ear pieces, scanners, televisions, dongles, cameras, wristbands, wearable items/devices, kiosks, input terminals, servers or server networks, blades, gateways, switches, processing devices, processing entities, set-top boxes, relays, routers, network access points, base stations, the like, and/or any combination of devices or entities adapted to perform the functions, operations, and/or processes described herein. Other similar architectures including one or more network entities operating in conjunction with one another to provide the functionality described herein may likewise be used without departing from the spirit and scope of embodiments of the present invention. For example, a mesh network of two or more personal computers (PCs), or similar electronic devices, collaborating with one another to provide the functionality described herein in association with the central server120may likewise be used without departing from the spirit and scope of embodiments of the present invention.

EXEMPLARY OPERATION

Capturing Data for a Fleet

According to various embodiments, the fleet management system5may be configured to capture operational data from various vehicles100and/or their respective drivers over a period of time in order to amass data reflecting the overall operations of the fleet. The operational data captured by the fleet management system5may comprise telematics data, contextual data, user computing entity data, and/or the like.

As described in greater detail below, a data source entity (e.g., telematics device102, user computing entity, and/or the like) may be configured for capturing operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like) such that the data may later be evaluated. The captured operational data is then transmitted to the central server120, which receives, processes, and stores the data in order to it prepare it for evaluation in accordance with user requests received via a graphical user interface and/or for automatic analysis in accordance with pre-determined analysis protocols.

Operation of Data Source Capturing Data

As noted above, according to various embodiments, a data source entity may be configured to collect data from various sensors or determinations, store the data, and transmit the data to the central server120.FIG. 5illustrates exemplary steps executed by the telematics device102to capture and transmit telematics data according to one embodiment. In various embodiments, the components of the telematics device102described herein may be configured to execute the steps ofFIG. 5in accordance with the principles described above. As will also be recognized, various other devices/entities can capture and store various types data using a variety of techniques and approaches.

Beginning with step602, the telematics device102monitors data generated by the vehicle sensors410for parameters that match predefined vehicle events programmed in the telematics device102. In one embodiment, the telematics device102can be programmed to monitor some or all the following predefined vehicle events in step602: (a) the vehicle100being turned on and beginning to idle (e.g., where vehicle sensors410indicate the vehicle's engine is turned on and the vehicle speed is zero), (b) the vehicle100beginning to move and thereby ceasing to idle (e.g., where the vehicle sensors410indicate the vehicle's engine is on and the vehicle's speed has increased from zero to a non-zero value), (c) the vehicle100slowing to a stop and beginning to idle (e.g., where the vehicle sensors410indicate the vehicle's engine is on and the vehicle's speed has decreased from a non-zero value to zero), (d) the vehicle100being turned off and ceasing to idle (e.g., where the vehicle sensors410indicate the vehicle's engine is turned off and the vehicle speed is zero), (e) the vehicle100moving out of a geo-fenced area associated with its home shipping hub (e.g., as indicated by a GPS sensor), (f) the vehicle100moving into a geo-fenced area associated with its home shipping hub, (g) the vehicle100moving into a geo-fenced area associated with a delivery area assigned to vehicle100and its driver, (h) the vehicle100moving out of a geo-fenced area associated with a delivery area assigned to vehicle100and its driver, (i) the vehicle100beginning to move in a reverse direction, (j) the vehicle100ceasing to move in a reverse direction, (k) the vehicle's seat belt being engaged or disengaged while the vehicle's engine is on, (l) the vehicle's heading changing beyond a predefined threshold degree, (m) the vehicle's blinker or lights being activated or inactivated, and/or the like.

Next, at step604, the telematics device102determines whether any of the predefined vehicle events have occurred. If a vehicle event is detected, the telematics device102moves to step606, where it can capture and stores telematics data from the vehicle sensors410. As noted earlier, the telematics data captured from the sensors410may indicate measurements or data from each of the vehicle sensors410. This telematics data may indicate, for example, engine ignition status (e.g., on or off), engine speed (e.g., RPM), vehicle speed (e.g., miles per hour), vehicle location (e.g., latitude and longitude), current distance traveled (e.g., current odometer reading), location status (e.g., on-property, on-area), seat belt status (e.g., engaged or disengaged), heading, speed, acceleration, vehicle backing status (e.g., moving in reverse or not moving in reverse), and/or the like. In one embodiment, the telematics device102stores captured telematics data in its memory210, in another data storage component of the telematics device102, or in an associated database (e.g., a cloud database).

If a vehicle event is not detected in step604, the data source entity (e.g., telematics device102, user computing entity, and/or the like) moves to step608, where it determines whether a threshold data capture time has elapsed. For example, in one embodiment, the threshold data capture time is defined as 3 seconds. If the data source entity (e.g., telematics device102, user computing entity, and/or the like) determines that the threshold data capture time has not elapsed, it returns to step602to continue monitoring for vehicle events. However, if the data source entity (e.g., telematics device102, user computing entity, and/or the like) determines that the threshold data capture time has elapsed (e.g., more than 3 seconds have passed since the last time data was captured from the vehicle sensors), the data source entity moves to step606and can capture telematics data (and/or various other types of data) from all or some of the vehicle sensors410as described above.

Next, at step612, the data source entity (e.g., telematics device102, user computing entity, and/or the like) can capture contextual data and associates the contextual data with the telematics data captured and stored in step606. In various embodiments, step612may be executed concurrently with the step606. In one embodiment, the data source entity (e.g., telematics device102, user computing entity, and/or the like) may be configured to capture some or all of the following contextual data in step612: the date (e.g., 12/30/10) and time (e.g., 13:24) the data was captured, the vehicle from which the data was captured (e.g., a vehicle identification number such as 16234), the driver of the vehicle from which the data was captured at the time it was captured (e.g., John Q. Doe), and a logged reason for the data capture (e.g., a code indicating the detected vehicle event or indicating that the threshold data capture time interval elapsed). Further, in one embodiment, the data source entity (e.g., telematics device102, user computing entity, and/or the like) (or various other entities/devices) may be configured to associate the captured telematics data with the captured contextual data by storing fields of telematics data captured from the vehicles sensors410in the same record, or records, as concurrently captured contextual data, thereby associating concurrently captured data.

Next, at step614, the data source entity (e.g., telematics device102, user computing entity, and/or the like) (or various other entities/devices) can transmit the telematics data and associated contextual data captured and stored in steps606and612to the central server120. This may be accomplished by using any of the transmission methods and systems described herein, as well as other methods, protocols, and systems known in the art. As described earlier, in one embodiment the data source entity (e.g., telematics device102, user computing entity, and/or the like) may be configured to first attempt to transmit captured data to the central server120, and subsequently attempt to transfer data to a portable data acquisition device if a connection with the central server120is unavailable.

Operation of Central Server Processing Data

According to various embodiments, the central server120(or various other entities/devices) may be configured for receiving, processing, and storing the data (e.g., telematics data, user computing entity data, contextual data, and/or the like) received from the data source entity (e.g., telematics device102, user computing entity, and/or the like). In particular, the central server120processes and stores received operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like) in a manner that facilitates evaluation of the data.

According to various embodiments, in response to receiving operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like), the central server120may be configured to process and store the data in an operational data set stored on the central server database (which may comprise one or more databases). The central server120can populate the operational data set by storing telematics data/user computing entity data in association with concurrently captured contextual data, thereby providing a contextual relationship between all of the stored operational data. For example, in various embodiments, the operational data set comprises a plurality of data records representing concurrently captured data. Each data record (or plurality of associated data records) comprises a plurality of data fields representing a unique data entry.

In one embodiment, a data record of operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like) may comprise a plurality of data fields each representing a measurement from the vehicle sensors410(e.g., vehicle speed, vehicle location, engine speed, vehicle heading) and a plurality of data fields each representing a contextual data measurement (e.g., date, time, driver, vehicle, logged reason for data capture). The data in each data field of the record represents data captured concurrently with the data in the other data fields. By storing telematics data/user computing entity data in association with contextual data, the central server120may later access and retrieve data from the operational data set by searching the stored data according to date, time, driver, vehicle, logged reason for data capture, or any other data field or combination of data fields associated with the stored telematics data (e.g., engine speed, street segment, intersection, vehicle speed, RPM, etc.).

In addition, according to various embodiments, the central server120may be configured for maintaining a planning data set stored in the central server database (or in another database accessible by the central server120). The planning data set may include stored data indicating, for example, planned delivery routes for various drivers and vehicles (e.g., a GPS-based route plan for a particular vehicle100), the locations of planned stops along each delivery route (e.g., location name and/or GPS location), planned distances associated with planned delivery routes and stops (e.g., total planned distance for a delivery route, planned distances between planned stops), planned times associated with various routes and stops (e.g., planned times for travel between stops, planned times for executing a delivery at a particular stop), planned delivery activities at each stop (e.g., pickup, delivery, pickup & delivery), particular packages or freight to be picked-up or delivered at a given stop (e.g., one or more tracking numbers for packages or freight), bills of lading associated with packages or freight being picked up or delivered at a particular stop (e.g., a number or code associated with a bill of lading), the weight of packages or freight to be picked-up or delivered at a particular stop (e.g., total weight for a pickup or delivery, or weight associated with a particular bill of lading, package, or portion of freight), and the number of units to be picked up or delivered at each stop (e.g., total number of units for a pickup or delivery, or number of units associated with a particular bill of lading).

The data stored in the planning data set may be stored such that it is associated with, for example, a particular driver, vehicle, route, date, and/or hub location. As such, the central server120may access and retrieve data from the planning data set by searching the stored data according to driver, vehicle, route, date, hub location, or any data field associated with the above described data (e.g., time, distance, weight, bill of lading number, tracking number, etc.). Accordingly, as described in greater detail below, the central server120may retrieve planning data stored in the planning data set for use in evaluating the operational data stored in the operational data set, and/or the central server120may retrieve operational data stored in the operational data set for use in evaluating planning data stored in the planning data set.

According to various embodiments, the central server120may be further configured to evaluate data stored in the operational data set to identify segments of activity indicated by the operational data (herein referred to as “segmenting” the data). For example, each identified activity segment may represent a period of time (e.g., 11:00 to 11:42 on 12/31/10) classified according to activity (e.g., engine idle segments, turning segments, change of direction segments, vehicle stop time, vehicle travel time), many of which may overlap with one another. According to various embodiments, these activity segments may be identified by the central server120in accordance with the principles and configurations detailed in U.S. patent application Ser. No. 13/435,498 (now published as U.S. Publication No. 2012/0253888), the entirety of which is hereby incorporated by reference. In such embodiments, the resulting segmented data may be stored in a segmented data set for use in further evaluations or analyses performed by the central server120.

In various embodiments, the central server120may be configured to evaluate data stored in the operational data set to identify segment data corresponding to a defined street segment, the direction and/or heading of a vehicle as it traveled a defined street segment; to determine various attributes of each defined street segment (e.g., whether a defined street segment is a bi-directional segment, a reversible segment, or a one-way segment; the direction of travel of one-way segments; and/or the like); and/or to evaluate the accuracy of map data associated with each defined street segment. For example, the central server120may be configured to identify one or more defined street segments. The central server120may be further configured to identify incidences where a vehicle traveled along a defined street segment, resulting in a data set corresponding to the vehicle traveling along the defined street segment (referred to herein as “traveled segment data”). Additionally, the central server120may be configured to analyze one or more traveled segments for a defined street segment. In various embodiments, the resulting traveled segment data is stored in a street segment data set of the central server database (which may be unique from, or a subset of, the aforementioned segmented data set). As described in greater detail below, according to various embodiments, the central server120may be configured to execute the above-referenced segment identification module2000in order to segment the operational data stored in the operational data set and generate traveled segment data to be stored in the street segment data set. For example, in one embodiment, the central server120may be configured to execute the segment identification module2000at the end of each business day (and/or at various other time periods and/or in response to certain triggers), segment the day's data added to the operational data set, and add the resulting segmented data to the street segment data set. In various other embodiments, the central server120may be configured to run the segment identification module2000at other increments or in response to a specific user request (e.g., a user request to segment a specific subset of operational data in the operational data set).

Segment Identification

As noted above, various embodiments of the segment identification module2000are configured for identifying one or more defined street segments and evaluating operational data in order to identify traveled segment data corresponding to one or more defined street segments. Generally, each identified set of traveled segment data corresponds to operational data collected as the vehicle traveled along a defined street segment. For example, the operational data collected by a vehicle as it traversed Main Street between 9thStreet and 10thStreet may be identified as a set of traveled segment data corresponding to defined street segment defined along Main Street between 9thStreet and 10thStreet. By identifying one or more sets of traveled segment data corresponding to a defined street segment within the operational data captured by the data source entity (e.g., telematics device102, user computing entity, and/or the like), the segment identification module2000can generate an accounting of the direction of travel by one or more vehicles within the fleet during one or more time periods as the one or more vehicles traversed the defined street segment. As described in relation to the various modules3000-6000below, identifying traveled segment data in the captured operational data for a fleet enables the central server120to perform a variety of further analyses in order to assess various fleet efficiencies, evaluate the accuracy of map data, and to provide a graphical representation of vehicle and delivery activities for any period of time.

FIG. 6illustrates steps executed by the segment identification module2000to segment operational data according to one embodiment. Beginning at step2002, the segment identification module2000first defines one or more street segments. A street segment may be defined based on map data, user input, and/or the like. Each defined street segment is defined by one or more GPS coordinates, latitude and longitude coordinates, a geo-fenced area, and/or the like and corresponds to a portion of a street or roadway that a vehicle might travel. For example, the defined street segment may be defined by a pair of end points, a middle point and a length of the defined segment, or a series of points along the defined street segment, where each point may be given by GPS coordinates or latitude and longitude coordinates. In some embodiments, the segment identification module2000loads data identifying and/or defining one or more defined street segments, rather than defining the defined street segments each time the segment identification module2000is initiated.

Next, the segment identification module selects operational data from the operational data set to segment for segment data identification at step2004. As noted above, the central server120may call the segment identification module2000to segment newly captured (or previously unsegmented) operational data stored in the operational data set with a predefined frequency (e.g., at the end of every business day) or in response to a user request (e.g., a request received via the user interface to segment operational data corresponding to certain user-selected parameters). Accordingly, the segment identification module2000executes step2004according to these frequency or user request parameters (e.g., by identifying unsegmented data in the operational data set or by retrieving operational data corresponding to user-specified parameters).

Next, at step2006the segment identification module2000assesses data points in the selected operational data to identify instances in which the vehicle has traveled along a defined street segment. For example, in certain embodiments, the segment identification module2000may be configured to identify instances in which a particular vehicle's location indicates that the vehicle traveled along the defined street segment. For example, if the defined street segment is defined by a geo-fence or if the location of the vehicle indicated by an operational data point is within the geo-fence, the operational data point corresponds to when the vehicle traveled along the defined street segment. If the defined street segment is defined by one or more points (e.g., GPS coordinates, latitude and longitude coordinates, and/or the like) or if a location of the vehicle indicated by an operational data point is within a predetermined distance of one of the points, a line defined by one or more of the points, and/or the like, the operational data point corresponds to when the vehicle traveled along the defined street segment.

To illustrate this concept,FIG. 7Ashows a defined street segment310defined by street segment end points311. The dashed line312connects end points311. Data points301,302,303,304,305, and306are operational data points collected as a vehicle traveled in the vicinity of defined street segment310.FIG. 7Bis an expanded view of the circled portion ofFIG. 7A. The minimum distance between data point304and the dashed line312is calculated to be a distance d1and the minimum distance between data point305and the dashed line312is calculated to be a distance d2. A threshold distance d, which may be predetermined or provided via user input, is used to determine if an operational data point was collected while the vehicle was traveling down the street segment. For example, in the example illustrated inFIGS. 7A and 7B, d1is less than or approximately equal to the threshold value d and d2is greater than the threshold value d. Thus, as data point304is less than the threshold distance away from the dashed line312, data point304was collected as the vehicle traveled along the defined street segment310and, as data point305is greater than the threshold distance away from the dash line312, data point305was captured as the vehicle traveled in the vicinity of the street segment310, but not along the defined street segment310. Using this logic, the segment identification module2000can identify operational data that was collected as a vehicle traveled along a defined street segment. It should be understood that a variety of other methods may be used to determine which operational data points were collected as the vehicle traveled along a defined street segment. For example, in another embodiment, a defined street segment may be defined by a geo-fence. In such an embodiment, the segment identification module2000may determine that an operational data point was captured while the vehicle traveled along the defined street segment if the location of the vehicle when the data point was captured is within the geo-fence used to define the defined street segment.

Referring back toFIG. 6, the segment identification module2000next proceeds to step2008where it determines whether the current data point was captured while the vehicle traveled along a defined street segment based on the analysis performed in step2006. If the current data point does not correspond to a defined street segment, the segment identification module2000returns to step2006and analyzes the next data point in the operational data. If the current data point has been marked as corresponding to a defined street segment, the segment identification module2000continues to step2010.

As multiple data points are typically captured as a vehicle travels along a street segment, the segment identification module2000next identifies in step2010the data points associated with the vehicle entering and exiting the defined street segment. According to various embodiments, the segment identification module2000may be configured to identify these segment starting and ending points based on an analysis similar to that discussed above with respect to step2006and/or other suitable analysis. For example, using the data point marked in step2006as a base, the segment identification module2000first analyzes data points preceding the marked data point to identify the data point corresponding to the vehicle beginning to travel along the defined street segment. In various embodiments, the data point corresponding to the vehicle entering the defined street segment, referred to as the segment starting point, may be defined as a data point captured when the vehicle was traveling along and/or located on the defined street segment and for which the immediately preceding data point was not captured when the vehicle was traveling along and/or located on the defined street segment. For example, the segment identification module2000analyzes prior data points to determine which data point corresponds to the vehicle entering the defined street segment.

After identifying the segment starting point, the segment identification module2000next analyzes data points succeeding the marked data point to identify the data point corresponding to the vehicle leaving the defined street segment. In various embodiments, the data point corresponding to the vehicle leaving the defined street segment, referred to as the segment ending point, may be defined as a data point captured when the vehicle was traveling along and/or located on the defined street segment and for which the immediately seceding data point was not captured when the vehicle was traveling along and/or located on the defined street segment. In various embodiments, this may be accomplished using a methodology similar to that employed to identify the segment starting point. For example, in one embodiment, the segment identification module2000analyzes later data points to determine the data point corresponding to when the vehicle exited the defined street segment. Referring back to the illustration ofFIG. 7Aas an example, if data point302is the marked data point, the segment identification module2000would first identify data point303as the next data point after the marked data point302. In this example, data point303was captured when the vehicle was traveling along the defined street segment, so the segment identification module2000would determine that data point302is not the segment ending point. The segment identification module2000would then analyze data point303and determine the data point immediately seceding data point303, data point304, was captured while the vehicle was located along the defined street segment. Thus, data point303is not the segment ending point. The segment identification module would then analyze data point304and determine that the data appoint immediately seceding data point304, data point305, was captured while the vehicle was not located along the defined street segment. Thus, the segment identification module2000would determine that data point304is the segment ending point.

In various embodiments, the segment starting and ending points define a traveled segment. After identifying the starting and ending points of the traveled segment, the segment identification module2000completes step2010by storing the segment starting and ending points for the traveled segment, all of the points associated with the traveled segment, and/or a sub-set of the points associated with the traveled segment in a street segment data set as being associated with an incidence of a vehicle traveling along a defined street segment (e.g., in the central server database). In various embodiments, the traveled segment data may be stored in association with a defined segment identifier, wherein the defined segment identifier may be configured to identify the defined street segment to which the traveled segment corresponds. In addition, in one embodiment, the identified traveled segment is stored in the street segment data set in association with contextual data indicating the operational data from which it was derived. For context,FIG. 8shows a Gantt chart type illustration of a traveled segment for a vehicle traveling along a defined street segment identified based on the travel of the vehicle shown inFIG. 7A.

Referring back toFIG. 6, at step2012, the segment identification module2000next determines a traveled heading associated with the traveled segment, wherein the traveled heading indicates the direction the vehicle traveled as it traversed the defined street segment. For example, the segment identification module2000may determine the traveled heading as a directional heading (e.g., the vehicle traveled at 36° or 198°), a cardinal or intermediate direction (e.g., the vehicle traveled east or southwest), a relative direction (e.g., heading in to town, away from the airport), and/or the like. As noted above, the operational data may comprise a variety of operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like), such as vehicle heading, location, time the data was collected, and/or other types of data that may be used to determine the traveled heading.

In one embodiment, the vehicle heading data associated with the traveled segment data may be used to determine the traveled heading associated with the traveled segment. The traveled heading determination may be made based on the vehicle heading data associated with a single data point in the traveled segment data or an average or weighted average of the vehicle heading data associated with two or more data points in the traveled segment data. Referring toFIG. 7A, for example, the traveled heading determination may be based on the vehicle heading data associated with data point303, an average of the vehicle heading data associated with data points302and303, or an average of the vehicle heading data associated with data points301,302,303, and304. As will be recognized, a variety of other approaches and techniques can be used to determine the heading.

In another embodiment, location data associated with the traveled segment data may be used to determine the traveled heading associated with the traveled segment. As noted above, each data point may be associated with a GPS location or other location. The change in location between two or more data points may therefore be used to determine the direction in which the vehicle traveled between when the data points were captured (e.g., using component or magnitude and direction vector arithmetic and/or the like). The traveled heading may be determined based on the change of location between two consecutive data points of the traveled segment data, two non-consecutive data points of the traveled segment data, an average or weighted average of two or more change in location calculations, based on the change in location between the segment starting point and the segment ending point, and/or the like. For example, referring toFIG. 7A, the traveled heading associated with the traveled segment may be determined by calculating/determining the change in location between the segment starting point301and the segment ending point304, the change in location between points302and303, or by averaging the direction of travel based on the change in location between data points301and302,302and303, and303and304. In various embodiments, when determining the traveled heading, any data points of the traveled data segment that were captured while the vehicle was in reverse may be removed from consideration. As should be understood, a variety of methods may be used to determine the traveled heading associated with the traveled segment.

As should be understood, in various embodiments, one or two data points from the traveled segment data may be sufficient to determine the heading of the vehicle as it traveled along the defined street segment. Thus, in various embodiments, it may not be necessary to identify the segment starting and ending points, to determine all of the data points associated with a traveled segment, and/or store the segment starting and ending points or all of the traveled segment data to the street segment data. In some embodiments, only one data point associated with a traveled segment is identified and/or stored to the street segment data. In other embodiments, two or more data points associated with the traveled segment are identified and/or stored to the street segment data. In some embodiments, all of the data points associated with the traveled segment are identified and/or stored to the street segment data set. Returning toFIG. 6, at step2014, the segment identification module2000stores the traveled heading in association with the traveled segment in the street segment data set.

According to various embodiments, the segment identification module2000may also be further configured to execute additional steps to meet the preferences of a particular user. For example, as noted above, the data source entity (e.g., telematics device102, user computing entity, and/or the like) may be configured to detect when the vehicle100has entered or exited a particular geographic area, such as a geo-fenced area surrounding a shipping hub. Accordingly, in one embodiment, the segment identification module2000is further configured to review operational data and identify data indicating instances in which the vehicle100has entered or departed a predefined geographical area. As a result, the segment identification module2000may be configured to analyze street segments traveled within a geo-fenced area or outside of a geo-fenced area separately. For example, in certain embodiments a user may want to assess only traveled segments occurring within a particular geo-fenced delivery area (e.g., a residential neighborhood), which the segment identification module2000may be configured to accomplish.

As a result of the foregoing steps, the segment identification module2000is able to populate the street segment data set with data records each corresponding to an identified traveled segment. For example, in one embodiment, each traveled segment data record comprises a traveled heading, a defined segment identifier, a segment starting point, a segment ending point, a traveled segment location (e.g., GPS coordinates), a traveled segment time, a traveled segment duration, a traveled segment driver, a traveled segment vehicle ID, a traveled segment route ID, and a traveled segment hub location (e.g., the shipping hub from which the vehicle associated with the traveled segment departed).

User Interface

As described above, the central server120may be configured for evaluating operational data (e.g., telematics data and contextual data) for a fleet of vehicles in order to assess various fleet efficiencies and aid fleet management system5users in improving the operational efficiency of the fleet. According to various embodiments, the central server's120evaluation of operational data is conducted in accordance with user instructions received via the central server's user interface. In various embodiments, the user interface is a graphical user interface accessible from a remote device/entity (e.g., in communication with the central server120via the network130), or by using the central server's display device/input device64. For example, in various embodiments, a user may log in to the fleet management system5from a remote device/entity (e.g., by opening a log-in page and entering a user id and password using a device/entity display and keyboard). The central server120may be configured to recognize any such log-in request, verify that user has permission to access the system (e.g., by confirming the user id and password are valid), and present/provide the user with a user interface (e.g., displayed on the device/entity's monitor).

FIG. 9illustrates a start-up user interface800according to one embodiment. In the illustrated embodiment, the start-up user interface800includes an interactive geographical map display810, a location menu811, a date selection field812, a route selection menu813, a driver selection menu814, a vehicle selection menu815, a summary report button836, an individual segment analysis button834, a regional analysis button832, a one-way segment analysis830, and a run analysis button819.

According to various embodiments, the map and menus810-815allow a system user to specify various operational data (e.g., telematics data, user computing entity data, contextual data, and/or the like) attributes in order to select certain traveled segment data for evaluation by the central server120. In various embodiments, any combination of selections made from the map and menus810-815will dictate the traveled segment data loaded and analyzed by the central server120. For example, in one embodiment, the user may request evaluation of only traveled segment data relating to a particular vehicle route by selecting a route from the route selection menu813. Likewise, the user may request evaluation of only traveled segment data relating to a particular vehicle by selecting a vehicle ID from the vehicle selection menu815and may request evaluation of only traveled segment data relating to vehicles operated by a particular driver by selecting a driver from the driver selection menu814. As an example, where both a route and vehicle have been selected, the central server120would load only traveled segment data relating to the selected vehicle while traveling along the selected route.

Furthermore, a user may request evaluation only of operational data captured on a particular date or range of dates by selecting a desired date or date range (as well as specific time of day associated with any selected date) using the date section field812. The user also has the option of requesting evaluation of operational data for all routes stemming from a particular location (e.g., by selecting only one or more shipping hub locations from the location menu811), or for all routes at all locations on a particular date (e.g., by selecting only a date or date range using the date selection field812). Moreover, a user may request evaluation of traveled segment data relating to a particular geographical area by selecting an area on map display810(e.g., by using a mouse to select a two-dimensional geographical area on the map display810). The map display810may also include tools for zooming in on various portions of the illustrated route, selecting a specific intersection for further analysis, and/or the like. As will be appreciated from the description above, the user may request evaluation of all operational data or any subset of operational data defined by any combination of parameters provided in the map/menus810-815.

After selecting operational data to be evaluated, the user may select a particular type of segment analysis to be performed by the central server120. As described in greater detail below, in one embodiment, the central server120may be configured to analyze the user-selected traveled segment data to generate a summary report, an individual segment analysis, a regional analysis, and a one-way segment analysis. Each of these analyses may be requested by a user by selecting the corresponding one of the analysis type buttons830-836on the start-up interface800. After the user-selected data and analysis type has been defined using the map/menus810-815and analysis type buttons830-836, the user may select the run analysis button819to trigger the user-requested analysis by the central server120.

According to various embodiments, the central server120may be configured to detect a user's selection of the various parameters and options presented on the user interface800and call one or more of the software modules2000-6000to perform the appropriate data evaluation.FIG. 10illustrates exemplary steps executed by the central server120in order to respond to user evaluation requests received via the user interface800. Beginning at step902, the central server120monitors the user interface800for user input (e.g., selection of the various menus and buttons810-839). Next, at step904, the central server120determines whether the user has requested an analysis of particular traveled segment data (e.g., by selecting the run analysis button819). If the user has not requested that an analysis be performed, the central server120moves back to step902, where it continues to monitor the user interface800for user input. If the user has requested that an analysis be performed, the central server120moves to step906.

At step906, the central server120identifies the traveled segment data corresponding to the user's selections from the map/menus810-815on the user interface. For example, in one embodiment, the central server120reviews the traveled segment data in the street segment data set and identifies the appropriate data based on the contextual data in each traveled segment data record. According to various embodiments, the central server120reviews the traveled segment time field to identify segments occurring on a particular date/time, the traveled segment location field to identify segments within a particular geographic location, the traveled segment defined segment identifier to identify segments corresponding to a particular defined street segment, the traveled segment route field to identify segments relating to a particular vehicle route, the traveled segment driver field to identify segments relating to a particular driver, and the traveled segment vehicle field to identify segments relating to a particular vehicle. In certain embodiments, where the user selects the individual segment analysis button834, the central server120may be configured to prompt the user to select a defined street segment (or to define a new defined street segment) from the map display810(or by entering a textual description of the street segment) and retrieve traveled segment data corresponding to that particular location (e.g., based on the location field in the traveled segment data records). After identifying the traveled segment data corresponding to the user's request, the central server120loads the identified traveled segment database for analysis by one or more of the modules3000-6000(e.g., by retrieving the data from the street segment data set in the central server database and loading it in the central server's memory).

Next, at step908, the central server120executes the analysis module corresponding to the user's selection on the user interface800. For example, if the user selects the individual segment analysis button834, the central server120will execute the individual segment analysis module3000. If the user selects the one-way segment analysis button830, the central server120will execute the one-way segment analysis module4000. If the user selects the regional analysis button832, the central server120will execute the regional analysis module5000. And if the user selects the summary report button836, the central server120will execute the summary report module6000. A detailed description of the functionality and steps executed by each of the modules3000-6000now follows.

Individual Segment Analysis

According to various embodiments, the individual segment analysis module3000may be configured to analyze traveled segment data relating to a particular user-selected defined street segment and determine the accuracy of map data associated with the defined segment. For example,FIG. 11illustrates exemplary steps executed by the individual segment analysis module3000in order to analyze traveled segments in the loaded data corresponding to the user-selected segment3100and provide an interactive display of information for the related defined street segment to a user. Beginning at step3002, the individual segment analysis module3000displays an individual segment analysis user interface.FIG. 12shows an individual segment analysis user interface807according to one embodiment. As shown inFIG. 12, the individual segment analysis user interface807includes a map display810, a textual description of the user-selected segment844, analysis buttons830-836(e.g., the same as those provided on the start-up user interface800), a data table850, a update map data button855, and a return to data selection button865.

As discussed above in relation to step906executed by the central server120inFIG. 10, where the user selects the individual segment analysis button834, the central server120may be configured to prompt the user to select a defined street segment from the map display810(or by entering a textual description of the defined street segment) and retrieve traveled segment data corresponding to that street segment. For example, the individual segment analysis module3000may load one or more traveled segments associated with the segment identifier corresponding to the user-selected segment. Accordingly, at step3004, the individual segment analysis module3000next analyzes the loaded traveled segment data relating to the user-selected segment to determine the traveled direction. For example, the individual segment analysis module3000may determine that the defined street segment is a one-way segment or a bi-directional segment based on the loaded traveled segment data.

FIG. 13illustrates an example process used to determine the traveled direction in one embodiment. At step3502, a first traveled heading associated with a first traveled segment is identified. For example, as noted above, each traveled segment record may have a traveled heading stored in association therewith. At step3504, a second traveled heading associated with a second traveled segment is identified. Next, at step3506, the first traveled heading and the second traveled heading are compared to determine if the second traveled heading is approximately equal to the first traveled heading. For example, if the first traveled heading is north and the second traveled heading is also north, the individual segment analysis module3000will determine that the second traveled heading is approximately equal to the first traveled heading. In another example, if the first traveled heading is north and the second traveled heading is northeast, the individual segment analysis module3000will determine that the second traveled heading is approximately equal to the first traveled heading. In yet another example, if the first traveled heading is north and the second traveled heading is south or southeast, the individual analysis module3000will determine that the second traveled heading is not approximately equal to the first traveled heading. In still another example, if the first traveled heading is 0°, the individual analysis module3000will determine that the second traveled heading is approximately equal to the first traveled heading if the second traveled heading is within a predetermined range of the first traveled heading (e.g., within 10°, 30°, 60°, or 90° of the first traveled heading) and the individual analysis module3000will determine that the second traveled heading is not approximately equal to the first traveled heading if the second traveled heading is not within a predetermined range of the first traveled heading (e.g., not within 10°, 30°, 60°, or 90° of the first traveled heading).

If, at step3506, the individual segment analysis module3000determines that the second traveled heading is not approximately equal to the first traveled heading, then the individual segment analysis module3000will determine that the user-selected segment is a bi-directional segment. If at step3506, the individual segment analysis module3000determines that the second traveled heading is approximately equal to the first traveled heading, then it is determined, at step3508, if the first traveled heading has been compared to the traveled heading for each of the loaded travel segments. If the first traveled heading has been compared to the travel heading for each of the loaded travel segments, then the segment is a one-way segment. If the first traveled heading has not yet been compared to the traveled heading for each of the loaded traveled segments, then the individual segment analysis module3000returns to step3504and selects another second traveled heading associated with another second traveled segment. It should be understood that a variety of methods may be used to determine the traveled direction based on the loaded traveled segment data.

Returning toFIG. 11, at step3006, the map data associated with the user-selected segment being analyzed is loaded. The map data comprises an indication of the map direction (e.g., whether the user-selected segment is a one-way segment or a bi-directional segment). For example, the map data may indicate the direction(s) vehicles may travel along the segment, may have a one-way segment flag associated therewith, and/or the like. At step3008, the traveled direction is compared to the map direction. If the traveled direction and the map direction agree (e.g., both the traveled direction and the map direction indicate the defined segment is a one-way segment), the individual segment analysis module3000determines that the map data is accurate. If the traveled direction and the map direction disagree (e.g., the traveled direction indicates the defined segment is a bi-directional segment and the map direction indicates the defined segment is a one-way segment), the individual segment analysis module3000determines that the map data is inaccurate and may flag the map data and/or user-selected segment for further analysis and/or review.

Next, at step3010, the individual segment analysis module3000displays the results of the analysis of the user-selected segment and the corresponding traveled segments. As shown inFIG. 12, the user-selected segment3100may be shown on the map display810. The parameters used to define the user-selected segment3100may also be illustrated on the map display810. For example, geo-fence3110, used to define the user-selected segment3100, is shown on the map display810, inFIG. 12. The individual segment analysis module3000also displays the calculated segment statistics in the data table850on the segment analysis user interface807. For example, the data table850shows the traveled direction, a first heading and the number of traveled segments having a traveled heading approximately equal to the first heading, a second heading and the number of traveled segments having a traveled heading approximately equal to the second heading, the map direction and an indicator of whether the map data is accurate or not. In some embodiments, an indicator of which direction(s) a vehicle may travel the user-selected segment according to the map data may also be provided. In some embodiments, the user may request to update the map data based on the loaded traveled segment data. For example, if the map data is not accurate, a user may select the update map data button855indicating the central server120should update the map data based on the loaded traveled segment data.

As will be appreciated from the foregoing description, the individual segment user interface807generated by the individual segment analysis module3000provides a clear display of segment information/data for a user-selected segment. Once the individual segment analysis module3000has executed the steps shownFIG. 11, the user may return to the start-up interface800by selecting the return to data selection button865, or request a different analysis of the currently selected data by selecting one of the analysis type buttons830-836.

As noted above, a user may select the update map data button855. In various embodiments, upon receipt of input indicating user selection of the update map data button855, the map data may be automatically updated based on the traveled segment data. For example, if the map data indicates that a segment is a one-way segment, but the traveled segment data indicates the segment is a bi-directional segment, the central server120may automatically updated the map data associated with the segment upon receipt of input indicating user selection of the update map data button855. In another embodiment, upon selection of the update map data button855, a satellite or aerial image of the segment or a portion of the segment may be identified and displayed to the user. The user may then determine and provide input regarding whether the map data for the segment should be updated. For example, the central server120may identify and cause display of a satellite or aerial image (e.g., via the user interface). The central server120may then receive user input (e.g., via the user interface) indicating the user would like to update the map data or not update the map data. If the user input received (e.g., via the user interface) indicates the user would like to update the map data, the map data is updated accordingly. In yet another embodiment, the map data may be automatically updated based on the traveled segment data without the user selecting the update map data button855.

According to various embodiments, the one-way segment module4000may be configured to identify one-way segments in the map data for a user-selected geographical region, a user-selected time range, or other user-selected data set, and analyze traveled segment data associated with the identified one-way segments to determine if the map data is accurate. For example,FIG. 14illustrates exemplary steps executed by the one-way segment module4000in order to determine the accuracy of map data and provide a user with an analysis thereof. Beginning at step4002, the one-way segment module4000displays a one-way segment user interface.FIG. 15shows a one-way segment user interface803according to one embodiment. As shown inFIG. 15, the one-way segment user interface803includes a map display810, analysis buttons830-836(e.g., the same as those provided on the start-up user interface800), a data table850, an analysis summary852, a segment selector853, an update map data button855, a segment type filter menu862, a filter by map button863, and a return to data selection button865.

Next, at step4004, the one-way segment analysis module4000identifies one-way segments located within the user-selected geographical region. For example, the one-way segment analysis module4000accesses the map data associated with the user-selected geographical region and, based on the map data, identifies one-way segments located therein. For example, the map data associated with a defined street segment may comprise one or more directions that a vehicle may travel along the defined street segment, a flag indicating that the defined segment is a one-way segment, and/or other indicia of whether the defined street segment is a one-way segment or bi-directional segment.

In various embodiments, the user-selected geographical region is based on a hub location (e.g., the defined street segments traveled by all vehicles operating out of a particular hub), a route (e.g., the defined street segments traveled by a particular route), a selected region of a map, a predefined geographical area (e.g., a particular town/city, a zone or portion of a town/city (e.g., Northeast Atlanta), a particular neighborhood), and/or other geographical region.

At step4006, the one-way segment module4000loads traveled segment data from the street segment data set for traveled segments corresponding to the identified one-way segments and in accordance with the user-selected date and/or time range. For example, the one-way segment module4000may load traveled segment data associated with a defined segment identifier associated with one of the identified one-way segments. At step4008, the one-way segment module4000may analyze the loaded traveled segment data to determine a traveled direction for each of the identified one-way segments. For example, the one-way segment module4000may conduct an analysis of the loaded traveled segment data for each of the identified one-way segments similar to the analysis illustrated inFIG. 13and described above.

At step4010, the one-way segment module4000may compare the traveled direction to the map direction for each of the identified one-way segments to determine the accuracy of the map data. For example, if the traveled segment data indicates that a segment that was identified as a one-way segment based on the map data is a bi-directional segment, the map data may be inaccurate. In some embodiments, the one-way segment module4000may further identify a map heading for at least one of the identified one-way segments based on the map data and indicating a direction that a vehicle can travel along the identified one-way segment. The traveled heading associated with one or more of the traveled segments corresponding to the identified one-way segment may be compared to the map heading to determine the accuracy of the map data.

The analysis is displayed at step4012via the one-way segment user interface803, as illustrated inFIG. 15. For example, the one-way segment module4000displays the user-selected geographical region on the map display810and the identified one-way segments may be marked thereon. As noted above, the one-way segment user interface803may include a segment selector853configured to allow a user to select one of the identified one-way segments. As shown inFIG. 15, the data table850may display a detailed analysis of the selected one-way segment in addition to the analysis summary852. Additionally, the one-way segment module4000may cause the selected one-way segment to be highlighted on the map display810.

As will be appreciated from the foregoing description, the one-way segment user interface803generated by the one-way segment module4000provides a clear display of the identified one-way segments for the user-selected geographical region and time and/or date range and enables the user to quickly view and compare attributes of each of these one-way segments and the accuracy of the corresponding map data. Once the one-way segment analysis module4000has executed the steps shownFIG. 14, the user may review the analysis for one or more of the identified one-way segments, update map data for one or more identified one-way segments based on the corresponding traveled segment data by selecting the update map data button855, return to the start-up interface800by selecting the return to data selection button865, or request a different analysis of the currently selected data by selecting one of the analysis type buttons830-836.

Regional Analysis

According to various embodiments, the regional analysis module5000may be configured to analyze user-selected traveled segment data corresponding to defined segments located within a user-selected geographical region and determine the accuracy of map data associated with the defined segments based on the traveled segment data. For example,FIG. 16illustrates exemplary steps executed by the regional analysis module5000in order to analyze traveled segments in the loaded data and provide an interactive display of traveled segment statistics to a user. Beginning at step5002, the regional analysis module5000displays a regional analysis user interface.FIG. 17shows a regional analysis user interface805according to one embodiment. As shown inFIG. 17, the regional analysis user interface805includes a map display810, analysis buttons830-836(e.g., the same as those provided on the start-up user interface800), a data table850, current data indicators840, an analysis summary852, a segment selector853, an update map data button855, a segment type filter menu862, a filter by map button863, and a return to data selection button865.

Next, at step5004, the regional analysis module5000identifies the defined street segments located within the user-selected geographical area. In various embodiments, the user may select the geographical region based on a hub location (e.g., the defined street segments traveled by all vehicles operating out of a particular hub), a route (e.g., the defined street segments traveled by a particular route), a selected region of a map, a predefined geographical area (e.g., a particular town/city, a zone or portion of a town/city (e.g., Northeast Atlanta), a particular neighborhood), and/or other geographical region. The map data for the user-selected geographical region may be accessed and used to identify the defined street segments located within the user-selected geographical area.

At step5006, the traveled segment data corresponding to the identified segments is loaded. The regional analysis module5000analyzes the loaded traveled segment data to determine a traveled direction for each identified segment at step5008. For example, the regional analysis module5000may conduct an analysis similar to that described above and illustrated inFIG. 13. At step5010, the regional analysis module5000compares the traveled direction to a map direction indicated by the identified segment map data for each identified segment, to determine the accuracy of the map data.

The analysis is provided to the user and a map representation of the identified segments is generated and displayed to the user at step5012. For example, if the selected geographical region is a particular route, the regional analysis module5000generates a graphical representation of the travel path2100of the vehicle associated with user-selected data on the map display810. In one embodiment, the regional analysis module5000accomplishes this by plotting each individual location data point in the loaded operational data (e.g., the loaded traveled segment data) on the map display810and then connecting the plotted location points in chronological order—based on the retrieved time data—with lines displayed over the base map. In various embodiments the travel path(s) generated by the regional analysis module5000may each comprise colored line(s) having a thickness greater than that of roads shown in the base map and which include arrows disposed along the travel path(s) to indicate the direction of the vehicle's100travel. If the user-selected geographical region is a set of routes, a vehicle travel path for each route may be generated and displayed on the map display810.

The user may view information/data corresponding to a particular identified segment by selecting the particular identified segment using the segment selector853. In various embodiments, the map display810may highlight the selected identified segment on the map, may automatically zoom in on the selected identified segment, and/or the like. For example, the regional analysis module5000may highlight the selected segment2200as illustrated inFIG. 17. The data table850may be updated to display information/data associated with the identified segment selected via the segment selector853.

As will be appreciated from the foregoing description, the regional analysis user interface805generated by the regional analysis module5000provides a clear display of segment information/data for defined street segments located within a user-selected geographical area. Once the regional analysis module5000has executed the steps shownFIG. 16, the user may return to the start-up interface800by selecting the return to data selection button865, or request a different analysis of the currently selected data by selecting one of the analysis type buttons830-836.

Summary Reports

According to various embodiments, the summary report module6000may be configured to analyze the user-selected traveled segment data and provide an overall summary of the defined street segments associated with the user-selected data. For example,FIG. 18illustrates exemplary steps executed by the summary report module6000in order to provide an interactive display of segment statistics to a user. Beginning at step6002, the summary report module6000displays a summary report user interface.FIG. 19shows a summary report user interface802according to one embodiment. As shown inFIG. 19, the summary report user interface802includes a map display810, analysis buttons830-836(e.g., the same as those provided on the start-up user interface800), a data table850, a segment type filter menu862, a filter by map button863, current data indicators840, and a return to data selection button865.

Next, at step6004, the summary report module6000analyzes the traveled segment data loaded by the central server120and calculates a plurality of segment statistics based on the loaded traveled segment data. For example, in one embodiment the summary report module6000may be configured to calculate the following statistics: (i) the total number of defined segments corresponding to traveled segments in the loaded traveled segment data; (ii) the number of one-way segments traveled as indicated by the traveled segment data; (iii) the number of bi-directional segments traveled as indicated by the traveled segment data; (iv) map data accuracy for traveled one-way segments (e.g., the percentage of traveled segments that the map data indicates are one-way segments that the traveled segment data indicates are one-way segments); (v) the map data accuracy for traveled bi-directional segments (e.g., the percentage of traveled segments that the map data indicates are bi-directional segments that the traveled segment data indicates are bi-directional segments); and (vi) the combined map data accuracy for one-way and bi-direction segments traveled (e.g., the percentage of all segments traveled for which the map data and the traveled segment data agree). In various embodiments, the summary report module6000may use a process similar to that illustrated inFIG. 13and described above when calculating one or more of the summary statistics. As will be appreciated from the description herein, the summary report module6000may be configured to execute these calculations based on the relevant fields in each traveled segment data record contained in the loaded traveled segment data. Additionally, according to various other embodiments, the summary report module6000may be configured to calculate any additional relevant statistics based on the loaded traveled segment data.

Next, at step6006, the summary report module6000displays the calculated segment statistics in the data table850on the summary report user interface802. In addition, the current data indicators840show the route, driver, and/or vehicle associated with the currently analyzed user-selected data. As shown inFIG. 19, the segment statistics displayed in the data table850can be recalculated based on filtered data using the segment type filter menu862, and the filter by map button863. For example, in response to user input received via the segment type filter menu862, the summary report module6000will recalculate the segment statistics for only traveled segments having a type matching one or more types specified by the user. For example, the segment type may indicate whether the segment is a delivery segment, in which a delivery or pickup occurred, a travel segment, which was traveled to get to a delivery segment, located in particular part of the region (e.g., downtown, midtown, and/or the like), or some other segment classification. Additionally, in response to selection of the filter by map button863, the summary report module6000enables a user to select a geographical area in the map display810and will then recalculate the segment statistics based only on traveled segments occurring within the user-defined map area.

If the user-selected data is defined by one or more routes (e.g., a summary report of a particular route or set of routes), at step6008, the summary report module6000generates and displays the vehicle path(s)2100, as described above, on the map display810. Thus, the summary report module6000also plots the travel path (or paths)2100of the vehicle (or vehicles) associated with the user-selected traveled segments on the map display810.

As will be appreciated from the foregoing description, the summary report user interface802generated by the summary report module6000provides a clear display of segment statistics for the user-selected data and enables the user to quickly assess the overall map data accuracy for defined street segments based on traveled segment data for traveled segments associated with particular routes, drivers, vehicles, hubs, geographical regions, or the like associated with the analyzed data. Once the summary report module6000has executed the steps shownFIG. 18, the user may return to the start-up interface800by selecting the return to data selection button865, or request a different analysis of the currently selected data by selecting one of the analysis type buttons830-836.

Conclusion