Driving behavior analysis and correction

Abstract

Driving characteristics are monitored by a first sensor and environmental characteristics are monitored by a second sensor, and anomalous driving characteristics and associated environmental characteristics are determined based on the data of the first sensor and the data of the second sensor. Anomalous driving behavior is determined further based on the anomalous driving characteristics and associated environmental characteristics, e.g., based on repeated instances of anomalous driving characteristics and associated environmental characteristics. A driver of the vehicle is indicated of a corrective action for correcting the anomalous driving characteristics, where the indication can be via a user interface of the vehicle or a mobile device. In some implementations, the driver can view the determined anomalous driving behavior via an application and provide driving goals to the application for centrally correcting certain anomalous driving behavior.

Description

Technical Field

[0001] This disclosure generally relates to driving behavior analysis and correction, and more particularly to detecting abnormal driving behavior and instructing corrective actions. Background Technology

[0002] Many factors must be considered when driving a vehicle, such as safety, efficiency, and wear and tear. However, these factors may be overlooked, for example, if the driver is in a hurry, if the driver is distracted, or if the driver has simply developed poor driving habits. Many modern vehicles include safety features to help prevent accidents, for example, by providing warnings to the driver (such as flashing blind spot warning lights) or by providing immediate and / or temporary control of the vehicle (such as applying emergency braking). However, these safety features are often spontaneous and reactive, and therefore they typically do not provide the driver with repetitive feedback to help them develop safer driving habits. Furthermore, these safety features are generally focused on accident avoidance, and therefore do not provide the driver with feedback related to vehicle wear and tear or driving efficiency. Summary of the Invention

[0003] This document discloses aspects, features, elements, implementations, and embodiments of methods, systems, and non-transitory computer-readable media for detecting abnormal driving behavior (i.e., undesirable driving behavior) (e.g., driving behavior that may lead to unsafe driving, inefficient driving, or premature wear of a vehicle) and further providing timely and / or repetitive feedback to the driver so that the driver can identify and correct the abnormal driving behavior.

[0004] Many modern vehicles include sensors that monitor driving characteristics, such as rate sensors, acceleration sensors, braking sensors, motor revolutions per minute (RPM) sensors, and wheel traction / slip sensors. In addition, many modern vehicles include sensors that monitor environmental conditions or characteristics, such as external cameras, light detection and ranging (LiDAR), radio detection and ranging (Radar), sonar, infrared (IR) sensors, ultrasonic sensors, internal cameras, and Global Navigation Satellite Systems (GNSS) (e.g., Global Positioning System (GPS)). Data collected by these sensors can be synthesized and analyzed to detect abnormal driving characteristics and corresponding associated environmental characteristics, and further, based on these abnormal driving characteristics and corresponding associated environmental characteristics, to detect abnormal driving behavior. User interface devices (such as in-vehicle infotainment (IVI) displays and / or mobile phone displays) can be used to communicate the detection of abnormal driving behavior and / or corrective actions for such behavior. Furthermore, user interface devices within the vehicle (such as IVI displays, speakers, seat vibrators, and / or cabin lights) and user interface devices not integrated into the vehicle (such as mobile phone displays and / or mobile phone speakers) can be used to provide targeted feedback and / or alerts to the driver when abnormal driving behavior and corresponding associated environmental characteristics are detected. Abnormal driving behavior can be determined in several ways; for example, the vehicle (or component) manufacturer can define abnormal driving behavior, or systems (both inside and outside the vehicle) can learn abnormal driving behavior, for example, via machine learning and / or artificial intelligence models executed on processors inside or outside the vehicle.

[0005] These and other aspects, features, elements, implementations, and variations of the methods, apparatuses, processes, and algorithms disclosed herein are described in further detail below. Attached Figure Description

[0006] The various aspects of the methods and systems disclosed herein will become more apparent by referring to the examples provided in the following description and accompanying drawings, in which the same reference numerals refer to the same elements unless otherwise stated.

[0007] Figure 1 This is a diagram illustrating an example of a vehicle that can realize a portion of the aspects, features, and elements disclosed herein.

[0008] Figure 2 The diagram is an example of a vehicle transportation and communication system that can realize the aspects, features and elements disclosed herein.

[0009] Figure 3 This is a block diagram of an example internal configuration of a computing device capable of implementing the aspects, features, and elements disclosed herein for electronic computing and communication systems.

[0010] Figure 4 This is a block diagram of an example system for driving behavior analysis and correction.

[0011] Figure 5 This is a flowchart of an example of a process used to detect abnormal driving behavior and instruct corrective actions. Detailed Implementation

[0012] For a more detailed description of some implementations, please refer to the following figures.

[0013] Figure 1 This is a diagram illustrating an example of a vehicle 1050 that can implement the aspects, features, and elements disclosed herein. The vehicle 1050 may include a chassis 1100, a powertrain 1200, a controller 1300, wheels 1400 / 1410 / 1420 / 1430, or any other element or combination of elements of the vehicle. Although for simplicity, the vehicle 1050 is shown as including four wheels 1400 / 1410 / 1420 / 1430, but one or more other propulsion devices (such as pushers or step plates) may be used. Figure 1 In this configuration, the lines that interconnect components such as powertrain 1200, controller 1300, and wheels 1400 / 1410 / 1420 / 1430 indicate information such as data or control signals, power such as electricity or torque, or both information and power that can communicate between the components. For example, controller 1300 may receive power from powertrain 1200 and communicate with powertrain 1200, wheels 1400 / 1410 / 1420 / 1430, or both, to control vehicle 1050. This may include accelerating, decelerating, steering, or otherwise controlling vehicle 1050.

[0014] The powertrain 1200 includes a power source 1210, a transmission 1220, a steering unit 1230, a vehicle actuator 1240, or any other element or combination of elements of the powertrain, such as suspension, drive shaft, axle, or exhaust system. Although shown separately, wheels 1400 / 1410 / 1420 / 1430 may be included in the powertrain 1200. A braking system may be included in the vehicle actuator 1240.

[0015] Power source 1210 can be any device or combination of devices operable to provide energy (such as electrical, chemical, or thermal energy). For example, power source 1210 includes an engine (such as an internal combustion engine, an electric motor, or a combination of an internal combustion engine and an electric motor) and is operable to provide energy as a prime mover to one or more of the wheels 1400 / 1410 / 1420 / 1430. In some embodiments, power source 1210 includes a potential energy unit, such as one or more dry cell batteries (such as nickel-cadmium (NiCd) batteries, nickel-zinc (NiZn) batteries, nickel-metal hydride (NiMH) batteries, lithium-ion (Li-ion) batteries, etc.), solar cells, fuel cells, or any other device capable of providing energy.

[0016] The transmission 1220 receives energy from the power source 1210 and transmits it to the wheels 1400 / 1410 / 1420 / 1430 to provide prime mover power. The transmission 1220 can be controlled by the controller 1300, the vehicle actuator 1240, or both. The steering unit 1230 can be controlled by the controller 1300, the vehicle actuator 1240, or both, and controls the wheels 1400 / 1410 / 1420 / 1430 to steer the vehicle. The vehicle actuator 1240 can receive signals from the controller 1300 and can actuate or control the power source 1210, the transmission 1220, the steering unit 1230, or any combination thereof to operate the vehicle 1050.

[0017] In some embodiments, the controller 1300 includes a positioning unit 1310, an electronic communication unit 1320, a processor 1330, a memory 1340, a user interface 1350, a sensor 1360, an electronic communication interface 1370, or any combination thereof. Although shown as a single unit, any one or more elements of the controller 1300 can be integrated into any number of individual physical units. For example, the user interface 1350 and the processor 1330 can be integrated into a first physical unit, and the memory 1340 can be integrated into a second physical unit. Although in Figure 1 Although not shown, controller 1300 may include a power source such as a battery. Although shown as separate elements, positioning unit 1310, electronic communication unit 1320, processor 1330, memory 1340, user interface 1350, sensor 1360, electronic communication interface 1370, or any combination thereof may be integrated into one or more electronic units, circuits, or chips.

[0018] In some embodiments, processor 1330 includes any means or combination of means capable of manipulating or processing signals or other information that are present or will develop in the future, including optical processors, quantum processors, molecular processors, or combinations thereof. For example, processor 1330 may include one or more dedicated processors, one or more digital signal processors, one or more microprocessors, one or more controllers, one or more microcontrollers, one or more integrated circuits, one or more application-specific integrated circuits (ASICs), one or more field-programmable gate arrays (FPGAs), one or more programmable logic arrays (PLAs), one or more programmable logic controllers (PLCs), one or more state machines, or any combination thereof. Processor 1330 may be operatively coupled to positioning unit 1310, memory 1340, electronic communication interface 1370, electronic communication unit 1320, user interface 1350, sensor 1360, powertrain 1200, and any combination thereof. For example, the processor may be operatively coupled to memory 1340 via communication bus 1380.

[0019] In some embodiments, processor 1330 may be configured to execute instructions, including instructions for remote operation, which may be used to operate vehicle 1050 from a remote location, including a data processing center. The instructions for remote operation may be stored in vehicle 1050 or received from an external source (such as a traffic management center) or a server computing device (which may include a cloud-based server computing device). As described herein, processor 1330 may be configured to execute instructions for following a projection path.

[0020] Memory 1340 may include any tangible, non-transitory computer-usable or computer-readable medium capable of, for example, containing, storing, communicating, or transmitting machine-readable instructions or any information associated therewith, for use by or in connection with processor 1330. Memory 1340 may be, for example, one or more solid-state drives, one or more memory cards, one or more removable media, one or more read-only memories, one or more random access memories, one or more solid-state drives, one or more disks (including hard disks, floppy disks, optical disks, magnetic cards, or optical cards), or any type of non-transitory medium suitable for storing electronic information, or any combination thereof.

[0021] The electronic communication interface 1370 may be a wireless antenna, a wired communication port, an optical communication port, or any other wired or wireless unit that can be coupled to the wired or wireless electronic communication medium 1500, as shown in the figure.

[0022] The electronic communication unit 1320 can be configured to transmit or receive signals via a wired or wireless electronic communication medium 1500 (such as via an electronic communication interface 1370). Although in Figure 1 Although not explicitly stated, the electronic communication unit 1320 is configured to transmit, receive, or both via any wired or wireless communication medium (such as radio frequency (RF), ultraviolet (UV), visible light, optical fiber, wired lines, or combinations thereof). Figure 1 A single electronic communication unit 1320 and a single electronic communication interface 1370 are shown, but any number of communication units and any number of communication interfaces can be used. In some embodiments, the electronic communication unit 1320 may include a dedicated short-range communication (DSRC) unit, a wireless security unit (WSU), IEEE 802.11p (Wifi-P), a cellular communication unit such as a Long Term Evolution (LTE) or 5G transceiver, or a combination thereof.

[0023] Positioning unit 1310 can determine geographic location information, including but not limited to the longitude, latitude, altitude, direction of travel, or speed of vehicle 1050. For example, positioning units include Global Positioning System (GPS) units, such as National Marine Electronics Association (NMEA) units with Wide Area Augmentation System (WAAS) enabled, radio triangulation units, or combinations thereof. Positioning unit 1310 can be used to obtain information, for example, indicating the current heading of vehicle 1050, the current position of vehicle 1050 in two or three dimensions, the current angular orientation of vehicle 1050, or combinations thereof.

[0024] User interface 1350 may include any unit capable of serving as a human interface, including any of a virtual keyboard, physical keyboard, touchpad, display, touchscreen, speaker, microphone, camera, sensor, and printer. User interface 1350 may be operatively coupled to processor 1330 as shown, or operatively coupled to any other element of controller 1300. Although shown as a single unit, user interface 1350 may include one or more physical units. For example, user interface 1350 includes an audio interface for audio communication with a person and a touchscreen display for vision- and touch-based communication with a person.

[0025] Sensor 1360 may include one or more sensors (such as a sensor array) operable to provide information that can be used to control the vehicle. Sensor 1360 may provide information relating to the current operating characteristics of the vehicle or its surrounding environment. Sensor 1360 may include, for example, a rate sensor, an acceleration sensor, a steering angle sensor, a traction-related sensor, a braking-related sensor, or any sensor or combination of sensors operable to report information relating to some aspect of the current dynamic state of the vehicle 1050.

[0026] In some embodiments, sensor 1360 may include sensors operable to obtain information relating to the physical environment surrounding vehicle 1050. For example, one or more sensors detect road geometry and obstacles (such as stationary obstacles, vehicles, cyclists, and pedestrians). In some embodiments, sensor 1360 may be or may include one or more cameras, laser sensing systems, infrared sensing systems, acoustic sensing systems, or any other suitable type of vehicle-mounted environmental sensing device, or a combination of such devices, now known or subsequently developed. In some embodiments, sensor 1360 and positioning unit 1310 are combined.

[0027] Although not shown separately, vehicle 1050 may include a trajectory controller. For example, controller 1300 may include a trajectory controller. The trajectory controller is operable to obtain information describing the current state of vehicle 1050 and a planned route for vehicle 1050, and to determine and optimize the trajectory of vehicle 1050 based on that information. In some embodiments, the trajectory controller outputs a signal operable to control vehicle 1050 such that vehicle 1050 follows the trajectory determined by the trajectory controller. For example, the output of the trajectory controller may be an optimized trajectory that can be supplied to powertrain 1200, wheels 1400 / 1410 / 1420 / 1430, or both. In some embodiments, the optimized trajectory may control inputs such as a set of steering angles, where each steering angle corresponds to a point in time or position. In some embodiments, the optimized trajectory may be one or more paths, lines, curves, or combinations thereof.

[0028] One or more of wheels 1400 / 1410 / 1420 / 1430 may be: a steering wheel that pivots to a steering angle under the control of steering unit 1230; a drive wheel that twists under the control of transmission 1220 to propel vehicle 1050; or a steering drive wheel that steers and propels vehicle 1050.

[0029] The vehicle may include those not in Figure 1The units or components shown include housings, Bluetooth® modules, FM radio units, near field communication (NFC) modules, liquid crystal display (LCD) units, organic light-emitting diode (OLED) display units, speakers, or any combination thereof.

[0030] Figure 2 This is a diagram illustrating an example of a vehicle transportation and communication system 2000 that can implement a portion of the aspects, features, and elements disclosed herein. The vehicle transportation and communication system 2000 includes a vehicle 2100 (such as...) Figure 1 The vehicle 1050 shown (e.g.) and one or more external objects (e.g., external object 2110, etc.), the external objects may include any form of transportation vehicle (e.g., Figure 1 The vehicle 2100 can travel via one or more parts of the transportation network 2200 and can communicate with the external object 2110 via one or more parts of the electronic communication network 2300. Although in Figure 2 Not explicitly shown, but vehicles may traverse areas not explicitly or fully included in the transport network (such as off-road areas). In some embodiments, the transport network 2200 may include one or more vehicle detection sensors 2202 (such as inductive loop sensors) that can be used to detect movement of vehicles on the transport network 2200.

[0031] Electronic communication network 2300 can be a multiple access system that provides communication (such as voice communication, data communication, video communication, message transmission communication, or combinations thereof) between vehicle 2100, external object 2110, and data processing center 2400. For example, vehicle 2100 or external object 2110 can send information (such as information representing transportation network 2200) to data processing center 2400 or database server 2420 via electronic communication network 2300, or receive such information from data processing center 2400 or database server 2420. Data processing center 2400 includes computing device 2410, which includes... Figure 3 Some or all of the features of the computing device 3000 shown. In some implementations, the data processing center 2400 includes a database server 2420. The database server 2420 is configured to store data, and the database server 2420 may be implemented using a suitable computer storage medium.

[0032] Data processing center 2400 can monitor and coordinate the movement of vehicles (including autonomous vehicles). Data processing center 2400 can monitor the status or conditions of vehicles (such as vehicle 2100) and external objects (such as external object 2110). Data processing center 2400 can receive vehicle data and infrastructure data, including any of the following: vehicle speed; vehicle location; vehicle operational status; vehicle destination; vehicle route; vehicle sensor data; external object speed; external object location; external object operational status; external object destination; external object route; and external object sensor data.

[0033] Furthermore, the data processing center 2400 can establish remote control over one or more vehicles (such as vehicle 2100) or external objects (such as external object 2110). In this way, the data processing center 2400 can remotely operate the vehicles or external objects from a remote location. The computing device 2410 can exchange (send or receive) status data with the vehicles, external objects, or computing devices (such as vehicle 2100, external object 2110, or database server 2420) via a wireless communication link (such as wireless communication link 2380) or a wired communication link (such as wired communication link 2390).

[0034] In some embodiments, the vehicle 2100 or external object 2110 communicates via wired communication link 2390, wireless communication links 2310 / 2320 / 2370, or any combination of wired or wireless communication links of any number or type. For example, as shown, the vehicle 2100 or external object 2110 communicates via terrestrial wireless communication link 2310, via non-terrestrial wireless communication link 2320, or via a combination thereof. In some implementations, the terrestrial wireless communication link 2310 includes an Ethernet link, a serial link, a Bluetooth link, an infrared (IR) link, an ultraviolet (UV) link, or any link capable of providing electronic communication.

[0035] A vehicle (such as vehicle 2100) or an external object (such as external object 2110) can communicate with another vehicle, external object, or data processing center 2400. For example, the primary vehicle or main vehicle 2100 can receive one or more inter-vehicle messages, such as Basic Safety Messages (BSMs), from data processing center 2400 via direct communication link 2370 or via electronic communication network 2300. For example, data processing center 2400 can broadcast messages to the primary vehicle within a defined broadcast range (such as 300 meters) or to a defined geographical area. In some embodiments, vehicle 2100 receives messages via a third party (such as a signal repeater (not shown) or another remote vehicle (not shown)). In some embodiments, vehicle 2100 or external object 2110 periodically transmits one or more inter-vehicle messages based on defined intervals (such as 100 milliseconds).

[0036] Automated vehicle-to-vehicle (AVV) messages can include vehicle identification information, geospatial status information (such as longitude, latitude, or altitude), geospatial location accuracy information, kinematic status information (such as vehicle acceleration, yaw rate, speed, heading, braking system status data, throttle position, steering wheel angle, or route information), or vehicle operational status information (such as vehicle size, headlight status, turn signal information, wiper status data, transmission information, or any other information or combination of information related to the transmitting vehicle's status). For example, transmission status information indicates whether the transmission of the transmitting vehicle is in neutral, parked, forward, or reverse.

[0037] In some embodiments, vehicle 2100 communicates with electronic communication network 2300 via access point 2330. Access point 2330, which may include a computing device, may be configured to communicate with vehicle 2100, electronic communication network 2300, data processing center 2400, or a combination thereof via wired or wireless communication links 2310 / 2340. For example, access point 2330 is a base station, base transceiver station (BTS), node B, enhanced node B (eNode-B), home node B (HNode-B), wireless router, wired router, hub, repeater, switch, or any similar wired or wireless device. Although shown as a single unit, access point may include any number of interconnecting elements.

[0038] The vehicle 2100 can communicate with the electronic communication network 2300 via satellite 2350 or other non-terrestrial communication devices. The satellite 2350, which may include a computing device, can be configured to communicate with the vehicle 2100, the electronic communication network 2300, the data processing center 2400, or a combination thereof via one or more communication links 2320 / 2360. Although shown as a single unit, the satellite may include any number of interconnecting elements.

[0039] Electronic communication network 2300 can be any type of network configured to provide voice, data, or any other type of electronic communication. For example, electronic communication network 2300 includes a local area network (LAN), a wide area network (WAN), a virtual private network (VPN), a mobile or cellular telephone network, the Internet, or any other electronic communication system. Electronic communication network 2300 can use communication protocols such as Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Internet Protocol (IP), Real-Time Transfer Protocol (RTP), Hypertext Transfer Protocol (HTTP), or combinations thereof. Although shown as a single unit, electronic communication network can include any number of interconnecting elements.

[0040] In some embodiments, the vehicle 2100 communicates with the data processing center 2400 via an electronic communication network 2300, an access point 2330, or a satellite 2350. The data processing center 2400 may include one or more computing devices capable of exchanging (sending or receiving) data relative to vehicles such as the vehicle 2100, external objects including external objects 2110, or storage devices such as database servers 2420.

[0041] In some embodiments, the vehicle 2100 identifies a portion of the transportation network 2200 or its conditions. For example, the vehicle 2100 may include one or more on-vehicle sensors 2102 (such as...). Figure 1 The sensors shown (such as 1360) include rate sensors, wheel rate sensors, cameras, gyroscopes, optical sensors, laser sensors, radar sensors, acoustic sensors (e.g., microphones or acoustic sensors), compasses, or any other sensor or device or combination thereof capable of determining or identifying a portion of or the conditions of the transportation network 2200.

[0042] Vehicle 2100 may use information communicated via electronic communication network 2300 (such as information representing transportation network 2200, information identified by sensors 2102 on one or more vehicles, or a combination thereof) to traverse one or more portions of transportation network 2200. External object 2110 is capable of performing all or some of the communication and actions described above with respect to vehicle 2100.

[0043] For the sake of simplicity, Figure 2 The diagram shows a vehicle 2100 as the main transport vehicle, an external object 2110, a transport network 2200, an electronic communication network 2300, and a data processing center 2400. However, any number of vehicles, networks, or computing devices can be used. In some embodiments, the vehicle transport and communication system 2000 includes... Figure 2 Devices, units, or elements not shown. Although the vehicle 2100 or external object 2110 is shown as a single unit, the vehicle may include any number of interconnecting elements.

[0044] Although vehicle 2100 is shown communicating with data processing center 2400 via electronic communication network 2300, vehicle 2100 (and external object 2110) can communicate with data processing center 2400 via any number of direct or indirect communication links. For example, vehicle 2100 or external object 2110 can communicate with data processing center 2400 via a direct communication link such as a Bluetooth communication link. Although for simplicity... Figure 2 One of the transportation networks 2200 and one of the electronic communication networks 2300 are shown, but any number of networks or communication devices can be used. The vehicle 2100 (and the external object 2110) can be monitored or coordinated by the data processing center 2400, can be operated autonomously or by a human driver, and can exchange (send and receive) vehicle data related to the vehicle's status or conditions and its surrounding environment, including any of the following: vehicle speed (e.g., vehicle rate and vehicle trajectory or heading); vehicle location; vehicle operating status; vehicle destination; vehicle route; vehicle sensor data; external object speed; external object location; etc.

[0045] Figure 3 A block diagram illustrating an example of a computing device 3000 capable of performing the functions described later herein is shown. The computing device 3000 includes components or units such as a processor 3002, a memory 3004, a bus 3006, a power supply 3008, peripheral devices 3010, a user interface 3012, a network interface 3014, other suitable components, or combinations thereof. One or more of the memory 3004, power supply 3008, peripheral devices 3010, user interface 3012, and network interface 3014 can communicate with the processor 3002 via the bus 3006.

[0046] Processor 3002 is a central processing unit such as a microprocessor, and may include one or more processors having one or more processing cores. Alternatively, processor 3002 may include another type of means or means configured to manipulate or process information. For example, processor 3002 may include multiple processors interconnected in one or more ways including hard-wired or network connections. Operation of processor 3002 may be distributed across multiple means or units that may be directly coupled or coupled across a local area or other suitable type of network. Processor 3002 may include a cache or cache memory for local storage of operating data or instructions.

[0047] Memory 3004 includes one or more memory components, each of which can be volatile or non-volatile memory. For example, the volatile memory can be random access memory (RAM) (e.g., a DRAM module, such as DDR SDRAM). In another example, the non-volatile memory of memory 3004 can be a disk drive, a solid-state drive, flash memory, or phase-change memory. In some implementations, memory 3004 can be distributed across multiple devices. For example, memory 3004 can include network-based memory or memory in multiple clients or servers that perform operations on those multiple devices.

[0048] Memory 3004 may include data readily accessible to processor 3002. For example, memory 3004 may include executable instructions 3016, application data 3018, and operating system 3020. Executable instructions 3016 may include one or more application programs that may be loaded, in whole or in part, from non-volatile memory or copied to volatile memory for execution by processor 3002. For example, executable instructions 3016 may include instructions for performing the techniques of this disclosure. In some implementations, application data 3018 may include functional programs, such as computing programs, analysis programs, database programs, etc. Operating system 3020 may be, for example, Microsoft Windows®, Mac OS X®, or Linux®; an operating system for mobile devices (such as smartphones or tablets); or an operating system for non-mobile devices (such as mainframe computers).

[0049] Power supply 3008 provides power to computing device 3000. For example, power supply 3008 may be an interface to an external power distribution system. In another example, such as when computing device 3000 is a mobile device or otherwise configured to operate independently of an external power distribution system, power supply 3008 may be a battery. In some implementations, computing device 3000 may include or otherwise use multiple power supplies. In some such implementations, power supply 3008 may be a backup battery.

[0050] Peripheral device 3010 may include one or more sensors, detectors, or other devices configured to monitor computing device 3000 or the environment surrounding computing device 3000. For example, peripheral device 3010 may include geolocation components such as a Global Positioning System (GPS) positioning unit. In another example, peripheral device 3010 may include a temperature sensor for measuring the temperature of components of computing device 3000, such as processor 3002. In some implementations, peripheral device 3010 may be omitted from computing device 3000.

[0051] User interface 3012 includes one or more input interfaces and / or output interfaces. Input interfaces may be, for example, position input devices (such as mice, touchpads, or touchscreens), keyboards, or other suitable human-machine interface devices or machine interface devices. Output interfaces may be, for example, displays, such as liquid crystal displays, cathode ray tube displays, light-emitting diode displays, or other suitable displays.

[0052] Network interface 3014 provides access to the network (e.g., Figure 2 The network interface 3014 can be a wired network interface or a wireless network interface. The computing device 3000 can communicate with other devices via the network interface 3014 using one or more network protocols (such as Ethernet, Transmission Control Protocol (TCP), Internet Protocol (IP), power line communication, IEEE 802.X protocols (e.g., Wi-Fi, Bluetooth, or ZigBee), infrared, visible light, General Packet Radio Service (GPRS), Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), Z-Wave, another protocol, or a combination thereof). For example, the computing device 3000 can communicate with a database server (such as...) Figure 2 (Database server 2420, etc.) communication.

[0053] In this description, sentences describing an autonomous vehicle as taking actions (such as performing, determining, initiating, receiving, calculating, deciding, etc.) will be understood as an appropriate module of the AV taking an action. Such modules can be stored in the AV's memory (such as...). Figure 1 In memory 1340, etc., and by a processor (such as...) Figure 1 Processors such as the 1330 (e.g., processors) execute this. Such modules can be included, partially or completely, in components such as... Figure 2 In a controller device such as a computing device 2410, the execution may be performed partially or entirely by the processor of the AV, the processor of the data processing center, or a combination thereof. For example, the expression "AV determines trajectory" can be understood as meaning "AV module determines trajectory" or "AV trajectory planning module determines trajectory".

[0054] Figure 4 A block diagram illustrating an example of a system 4000 for driving behavior analysis and correction is shown. Vehicle hardware component 4002 includes one or more driving characteristic sensors 4040 that monitor driving characteristics. These sensors 4040 include or are coupled to the engine control unit (ECU) 4004, transmission control unit (TCU) 4006, powertrain control module (PCM) 4008, traction control unit 4010, GNSS / GPS / mapping unit 4014, and other vehicle-integrated circuits (ICs) 4012. Figure 4 In this diagram, the GNSS / GPS / map rendering unit 4014 is shown as a single unit; however, the GNSS / GPS sensing component of the GNSS / GPS / map rendering unit 4014 can be separated from the map rendering component of the GNSS / GPS / map rendering unit 4014. Furthermore, the GNSS / GPS / map rendering unit 4014 is shown as both a driving characteristic sensor 4040 and an environmental characteristic sensor 4042, because the GNSS / GPS / map rendering unit 4014 can provide driving data (e.g., vehicle speed) or environmental data (e.g., vehicle location, map rendering data, etc.). One or more driving characteristic sensors 4040 can be, for example... Figure 1 One or more sensors 1360 and / or positioning unit 1310. Driving characteristics are characteristics of the vehicle and / or its components, such as vehicle speed; vehicle acceleration; vehicle braking; vehicle yaw, pitch, or roll; tire pressure; wheel traction; gear selection; engine speed per minute; engine temperature; brake temperature; tire temperature; battery temperature; battery state of charge; undercarriage clearance; suspension position; etc. One or more of the driving characteristic sensors 4040 may be coupled to the vehicle local area network (CAN) 4016.

[0055] The vehicle hardware component 4002 also includes one or more environmental characteristic sensors 4042 that monitor environmental characteristics inside the vehicle (e.g., inside the vehicle's cabin) and / or outside the vehicle (e.g., outside the cabin). These environmental characteristic sensors 4042 include one or more internal cameras 4018, one or more external cameras 4020, and a LiDAR or Radar 4022. As described above, the GNSS / GPS / map rendering unit 4014 may be included as the environmental characteristic sensor 4042. Other sensors monitoring environmental conditions ( Figure 4 (Not shown) may include sonar, infrared, and ultrasound. One or more of the environmental characteristic sensors 4042 may be, for example... Figure 1 Sensor 1360 and / or positioning unit 1310. Environmental characteristics are the characteristics of the environment inside and / or outside the vehicle's cabin, as well as the characteristics of inanimate and / or animate objects within that environment, such as the driver's gaze direction; the duration of the driver's gaze; the state of traffic signals; the location of traffic signs or signals; the location of lane markings; the location of the vehicle, the location of one or more other vehicles; the curvature of the road; and so on. Some environmental characteristics can be determined with varying degrees of accuracy from driving characteristic sensor 4040 or environmental characteristic sensor 4042. For example, the curvature of the road (e.g., radius of curvature) can be determined from mapping data included with GNSS / GPS / mapping unit 4014, or the curvature of the road (e.g., radius of curvature) can be determined from one or more of external cameras 4020 or LiDAR or Radar 4022.

[0056] Driving data collected by driving characteristic sensor 4040 and environmental data collected by environmental characteristic sensor 4042 are provided to behavior analyzer 4024 via one or more communication channels (such as wired or wireless communication channels). Behavior analyzer 4024 can be provided via components integrated within the vehicle (such as... Figure 1 Processor 1330, etc.) and / or via components outside the vehicle (such as Figure 2 This is achieved through a data processing center 2400 and computing devices 2410, etc. The behavior analyzer 4024 synthesizes driving data and environmental data to determine or detect abnormal driving characteristics and corresponding associated environmental characteristics. Abnormal driving characteristics are driving characteristics that deviate from baseline driving characteristics, such as sudden braking, excessive g-force during cornering, repeated cycles of rapid acceleration and deceleration, excessive deflection of suspension springs, reduced chassis clearance, etc. Abnormal driving characteristics can be referred to as "features," allowing the behavior analyzer 4024 to detect features based on driving data and environmental data.

[0057] Driving characteristics themselves may not deviate from the baseline, but they may when considered in conjunction with (one or more) related environmental characteristics. For example, driving at 60 miles per hour (MPH) may not be an anomalous driving characteristic in itself, but driving at 60 MPH in a 25 MPH school zone (environmental characteristic) could be an anomalous driving characteristic manifested as unsafe driving. In this example, environmental characteristic sensors 4042, such as (one or more) external cameras 4020, could capture and process images of the school zone or speed limit signs and provide such environmental data to a behavior analyzer 4024. As another example, sudden braking itself may not be an anomalous driving characteristic, but sudden braking when approaching a red traffic light could be an anomalous driving characteristic, potentially leading to excessive and / or unnecessary wear and / or inefficient driving of the vehicle (e.g., reduced miles per gallon (MPG)).

[0058] Baseline driving characteristics can be predefined, for example, by the manufacturer of the vehicle or its components, or they can be learned over time by training a machine learning model (e.g., a neural network). Methods for training machine learning models and associated computing hardware are known in the art and will not be discussed further here.

[0059] As indicated by the preceding examples, abnormal driving characteristics alone may not indicate abnormal driving behaviors that require correction. For example, sudden braking when approaching a red traffic light may be a better alternative than driving through the red traffic light. However, repeated instances of sudden braking when approaching a red traffic light may indicate that the driver was not paying attention to the traffic light, or that the driver was unaware that unnecessary wear on the vehicle could be reduced by coasting and / or lightening the brakes when approaching a red traffic light. Therefore, the behavior analyzer 4024 utilizes memory (such as...) Figure 1 The behavior analyzer 4024 uses memory (such as memory 1340, etc.) to store previous driving data, previous environmental data, and / or previous abnormal driving characteristics and their corresponding associated environmental characteristics. Furthermore, the behavior analyzer 4024 analyzes current (i.e., recent) driving data and / or environmental data in the context of previous (i.e., earlier) driving data and / or environmental data, and utilizes the history of abnormal driving characteristics and their corresponding associated environmental characteristics to determine patterns of abnormal driving behavior, i.e., abnormal driving behavior. The behavior analyzer 4024 can utilize memory (such as memory 1340, etc.) to store previous driving data, previous environmental data, and / or previous abnormal driving characteristics and their corresponding associated environmental characteristics. Figure 1 The abnormal driver behavior can be stored in a memory such as 1340. The abnormal driving behavior and / or abnormal driving characteristics and the corresponding environmental characteristics can be indexed for later retrieval by appropriate parameters (such as by time, by location, or by one or more behavior types or categories (e.g., safety category, wear category, severity category, frequency category, age category, etc.)).

[0060] As previously stated, the example of abnormal driving behavior that behavior analyzer 4024 can identify is sudden braking when approaching a red traffic light, which is indicated by numerous instances of abnormal driving characteristics of sudden braking associated with the environmental characteristics of approaching a red traffic light.

[0061] Another example of abnormal driving behavior that behavior analyzer 4024 can identify is a vehicle entering a turn at an excessively high rate for a given road curvature radius. In this example, behavior analyzer 4024 can receive driving data, such as vehicle speed from a speedometer, lateral acceleration from an accelerometer, and data from (e.g., in...) Figure 4 The vehicle tilt is detected by a gyroscope located within or coupled to the engine control unit 4004. The behavior analyzer 4024 can detect vehicle tilt from a GPS unit (e.g.,...). Figure 4 The GNSS / GPS unit 4014 receives environmental data, such as the radius of curvature of the road the vehicle is driving. The behavior analyzer 4024 can record instances of the vehicle entering a turn at an excessively high rate for a given turning radius in memory (e.g., ...). Figure 1 The abnormal driving behavior is determined or detected after a predefined number of instances are recorded in the memory 1340 within a predefined duration.

[0062] Another example of abnormal driving behavior that behavior analyzer 4024 can identify is a driver failing to check blind spots when changing lanes. In this example, behavior analyzer 4024 can detect this from a GPS unit (e.g., Figure 4 The GNSS / GPS unit 4014 receives driving data (e.g., vehicle location and road lanes) and receives lateral acceleration of the vehicle (indicating changes in the vehicle's direction of travel) from an accelerometer. The behavior analyzer 4024 can receive data from an internal camera (e.g., Figure 4 An internal camera 4018 (one or more) receives environmental data (e.g., driver gaze data). A behavior analyzer 4024 can record instances of a vehicle entering a turn at an excessively high rate for a given turning radius in memory (e.g., Figure 1 The abnormal driving behavior is determined or detected after a predefined number of instances are recorded in the memory 1340 within a predefined duration.

[0063] Other examples of abnormal driving behavior include, for instance, slowing down to a stop at a stop sign, (e.g., for an automatic transmission vehicle) failing to shift into the appropriate gear, driving too fast on a bumpy road, failing to use turn signals when changing lanes or turning, following too closely to the vehicle in front at a given speed, and insufficient or excessive use of the car horn. Specific abnormal driving behaviors and corresponding thresholds can be established in several ways; for example, the vehicle (or component) manufacturer can define the abnormal driving behaviors and corresponding thresholds, or the system (internal and / or external to the vehicle) can learn the abnormal driving behaviors and / or their thresholds using, for example, machine learning and / or artificial intelligence models executed on processors internal or external to the vehicle. Methods for training machine learning models and associated computing hardware are known in the art and will not be discussed further here.

[0064] In some implementations, the behavior analyzer 4024 can be stored in cloud storage or a database (e.g., a remote non-transitory computer-readable medium) (such as by...). Figure 2 The computing device 2410, implemented as a storage server, etc., stores and / or retrieves driving data, environmental data, abnormal driving characteristics, and corresponding associated environmental characteristics and / or abnormal driving behaviors. In some implementations, the behavior analyzer 4024 can store and / or retrieve driving data, environmental data, abnormal driving characteristics, and corresponding associated environmental characteristics and / or abnormal driving behaviors based on the driver's profile of the vehicle, wherein the profile can be determined by the driver performing an active authentication step (such as issuing a voice command processed by a voice recognition unit) or by passive authentication (such as detecting a driver-specific key used to start the vehicle).

[0065] The behavior analyzer 4024 is also configured to communicate with the driver or instruct the driver to detect and / or correct abnormal driving behavior using user interface 4050 and / or user interface 4052. User interface 4052 is a user interface integrated within the vehicle, such as a graphic display of an IVI system, vehicle audio speakers, vehicle lights (e.g., dome lights or side mirror lights), vibration actuators within the vehicle (e.g., seat vibrators or steering wheel vibrators), etc. User interface 4052 may be, for example... Figure 1 User interface 1350 is one or more instances of a user interface. User interface 4050 is a user interface not integrated into a vehicle, such as a graphics display or audio speaker of a mobile device, tablet, laptop, personal computer, smartwatch, etc.

[0066] Examples of communication or instructions regarding the detection of abnormal driving behavior and / or corrective actions for such behavior are found in the graphic display of a mobile device or IVI system (e.g., Figure 1The message is displayed on the user interface (1350). A specific example of an indication of abnormal driving behavior of following too closely behind a vehicle ahead could be a message displayed on a graphical display stating, "You are following too closely behind a vehicle ahead." A specific example of an indication of corrective action for abnormal driving behavior of following too closely behind a vehicle ahead could be a message displayed on a graphical display stating, "You are following too closely behind a vehicle ahead; a good distance is equal to a 3-second interval, plus 1 second for every 10 mph increase after exceeding 30 mph." The corrective action for a given abnormal driving behavior can be, for example, predefined by the manufacturer of the vehicle or its components, or can be learned over time by training a machine learning model (e.g., a neural network). Methods for training machine learning models and associated computing hardware are known in the art and will not be discussed further here.

[0067] Once the behavior analyzer 4024 has identified abnormal driving behavior for a given driver and has communicated or indicated this behavior to the driver, it can provide a targeted alert for the abnormal driving behavior. As described above, the instruction for corrective action can be a visual message displayed on the IVI system's graphic display stating, "You are following too closely behind the vehicle in front; a good distance is a 3-second interval, plus 1 second for every 10 mph increase after 30 mph." This alert can also be a shortened visual message displayed on the head-up display (HUD) or a shortened audio message played on the vehicle's speakers stating, "Too close, maintain at least a 3-second distance." This alert can be communicated to the user each time the behavior analyzer 4024 detects one or more abnormal driving characteristics and corresponding one or more associated environmental characteristics leading to the abnormal driving behavior, or in some of these cases. The targeted alert can be a shortened, truncated, or alternative version of the instruction for corrective action. For example, the instruction to correct the action could be an audio message saying "Check your blind spot," and the corresponding targeted reminder could be the vibration of the left-side seat vibrator. The instruction to correct the action and / or the targeted reminder can be communicated to the driver before (a priori) the corresponding abnormal driving characteristic may occur or after (a posteriori) the corresponding abnormal driving characteristic occurs. An example of an a priori instruction to check the blind spot when changing lanes could be the vibration of the left-side seat vibrator if the vehicle immediately begins to turn left after the driver checks the left-side rearview mirror but does not turn their head to check the left-side blind spot. An example of a posteriori a priori instruction to check the blind spot when changing lanes could be an audio message asking "Have you checked your blind spot?"

[0068] like Figure 4As shown, the behavior analyzer 4024 can communicate with the behavior modification logic 4028 via a communication channel 4046 through a cloud network 4032. The behavior modification logic 4028 may include hardware and software components, such as a mobile / web application 4030 or an in-vehicle application 4034 that can be communicatively coupled to one or more user interface devices (such as user interfaces 4050 and 4052). The cloud network may be, for example... Figure 2 Network 2300. Mobile / web application 4030 may be running on a mobile device such as a smartphone or tablet, and in-vehicle application 4034 may be running by an IVI system. Additionally or alternatively, behavior analyzer 4024 may communicate with mobile / web application 4030 via direct communication channel 4048, and behavior analyzer 4024 may communicate with in-vehicle application 4034 via direct communication channel 4044. Examples of direct communication channels may include Wi-Fi, Bluetooth, ZigBee, etc.

[0069] In some implementations, drivers can utilize mobile / web applications 4030 and / or in-vehicle applications 4034 to view abnormal behaviors or abnormal driving characteristics and corresponding associated environmental characteristics. These abnormal behaviors or abnormal driving characteristics and corresponding associated environmental characteristics can be indexed and searched using appropriate parameters, such as by time, by location, or by one or more behavior types or categories (e.g., safety category, wear category, severity category, frequency category, age category, etc.). Drivers can provide driver feedback 4036 to mobile / web applications 4030 or driver feedback 4038 to in-vehicle applications 4034 via the user interface of those devices. This can include establishing driving goals that can be based on abnormal driving characteristics and / or abnormal driving behaviors. Examples of driving goals can be specific, such as reducing a given abnormal driving behavior by 50% within one month, or general, such as reducing vehicle wear. The objective is provided to the behavior analyzer 4024 by the mobile / web application 4030 and / or the in-vehicle application 4038, allowing the behavior analyzer 4024 to modify its data collection processing, data analysis processing, and / or abnormal driving behavior indication processing according to the objective. For example, given the objective of reducing vehicle wear, the behavior analyzer 4024 may emphasize the collection, analysis, and storage of driving data (such as tire pressure, gear selection, and brake temperature) that may lead to abnormal driving characteristics, which in turn cause excessive wear such as worn tires, worn gears, and worn brakes.

[0070] For the sake of simplicity, each technique or process is depicted and described herein as a series of steps or operations. However, the steps or operations of the techniques according to this disclosure may occur in various orders and / or simultaneously. Additionally, other steps or operations not presented and described herein may be used. Furthermore, not all illustrated steps or operations may be necessary to implement the techniques according to the disclosed subject matter.

[0071] The technology 5000 described below is for detecting abnormal driving behavior and instructing corrective actions. These technologies can be comprised of hardware and software components integrated into or associated with the vehicle (such as…). Figure 4 This is achieved through hardware components such as the vehicle hardware 4002 and behavior change logic 4028.

[0072] Figure 5 This is a flowchart illustrating an example of technology 5000 used to detect abnormal driving behavior and instruct corrective actions.

[0073] Step 5010 includes monitoring one or more driving characteristics by at least one first sensor of the vehicle. The monitoring of the driving characteristics can be performed by... Figure 4 The vehicle hardware component 4002 (such as driving characteristic sensor 4040) may include one or more of the following: the driving characteristic sensor 4040 may include or be coupled to the engine control unit (ECU) 4004, transmission control unit (TCU) 4006, powertrain control module (PCM) 4008, traction control unit 4010, GNSS / GPS / mapping unit 4014 and (one or more) other vehicle-in-vehicle integrated circuit (IC) 4012.

[0074] Step 5020 includes monitoring one or more environmental characteristics by at least one second sensor of the vehicle. The monitoring of the environmental characteristics can be performed by... Figure 4 One or more of the vehicle hardware components 4002 (such as environmental characteristic sensor 4042) may be included, which may include one or more internal cameras 4018, one or more external cameras 4020, and LiDAR or Radar 4022. As previously mentioned, GNSS / GPS / map rendering unit 4014 may be included as environmental characteristic sensor 4042. In some implementations, the second sensor may include a sonar sensor, an ultrasonic sensor, and / or an infrared sensor.

[0075] Step 5030 includes determining at least one abnormal driving characteristic and associated environmental characteristic based on first data from a first sensor and second data from a second sensor. The determination of the abnormal driving characteristic and associated environmental characteristic can be achieved by... Figure 4 The behavior analyzer 4024 performs the analysis. The first data may include at least one of the following: vehicle speed; vehicle acceleration; vehicle braking; vehicle yaw, pitch, or roll; tire pressure; wheel traction; gear selection; engine speed per minute; engine temperature; brake temperature; tire temperature; battery temperature; battery state of charge; chassis clearance; suspension position; etc.

[0076] Step 5040 includes determining abnormal driving behavior based on abnormal driving characteristics and associated environmental characteristics. In some implementations, abnormal driving behavior is stored in non-transitory computer-readable storage for retrieval by the driver. In some implementations, the driver can retrieve the abnormal driving behavior via an application (such as...). Figure 4 (e.g., mobile / web applications 4030 and / or in-vehicle applications 4034) retrieve abnormal driving behavior.

[0077] Step 5050 includes instructing the driver of the vehicle to perform corrective actions to correct abnormal driving behavior. In some implementations, the instruction of corrective actions may utilize at least one of the following: the user interface of the vehicle, such as... Figure 4 User interface 4052; and user interface of mobile device, such as Figure 4 The user interface is 4050. In some implementations, the indication of the correction action may utilize at least one of the following: a graphic display; an audio speaker; visible light; and a vibration actuator.

[0078] In some implementations, further steps include: receiving an instruction for a driving objective based on at least one abnormal driving behavior; and increasing the frequency of instructing the driver to take corrective actions. The driving objective can be received via an application such as a mobile / web application 4030 and / or an in-vehicle application 4034. The baseline frequency of instructing corrective actions may be to instruct the driver to take corrective actions whenever the behavior analyzer detects an instance of a given abnormal driving behavior, and the frequency of instructing corrective actions may be increased by additionally instructing corrective actions whenever the driver starts the vehicle. The frequency of instructing corrective actions does not need to be periodic.

[0079] In some implementations, a further step includes prompting the driver to indicate a corrective action consisting of a shortened, truncated, or alternative version of the indicated corrective action.

[0080] The above techniques can be implemented as methods, systems, and non-transitory computer-readable media.

[0081] In an example implementation of the method, the method includes: monitoring one or more driving characteristics by at least one first sensor of the vehicle; monitoring one or more environmental characteristics by at least one second sensor of the vehicle; determining at least one abnormal driving characteristic and an associated environmental characteristic based on first data from the first sensor and second data from the second sensor; determining abnormal driving behavior based on the abnormal driving characteristic and the associated environmental characteristic; and instructing the driver of the vehicle to perform corrective actions to correct the abnormal driving behavior.

[0082] In some implementations, the method further includes instructing the correction action by at least one of the following: the user interface of the vehicle; and the user interface of the mobile device.

[0083] In some implementations, the method further includes instructing the correction action by at least one of the following: a graphic display; an audio speaker; visible light; and a vibration actuator.

[0084] In some implementations, the method further includes storing at least one abnormal driving behavior in a non-transitory computer-readable storage medium for retrieval by the driver.

[0085] In some implementations, the method further includes: receiving an instruction based on a driving target based on at least one abnormal driving behavior; and increasing the frequency of instructing the driver to perform the corrective action.

[0086] In some implementations, the method further includes: providing the driver with a reminder of the corrective action, which consists of a shortened, truncated, or alternative version of the indicated corrective action.

[0087] In some implementations, the first data includes at least one of the following: vehicle speed; vehicle acceleration; vehicle braking; vehicle yaw, pitch, or roll; tire pressure; wheel traction; gear selection; engine speed per minute; engine temperature; brake temperature; tire temperature; battery temperature; battery state of charge; chassis clearance; and suspension position.

[0088] In some implementations, the method further includes: an internal camera; an external camera; LiDAR; Radar; sonar; an ultrasonic sensor; an infrared sensor; and a global navigation satellite system.

[0089] In another example implementation as a non-transitory computer-readable medium, the non-transitory computer-readable medium stores instructions operable to cause one or more processors to operate, the operations including: monitoring one or more driving characteristics by at least one first sensor of the vehicle; monitoring one or more environmental characteristics by at least one second sensor of the vehicle; determining at least one abnormal driving characteristic and an associated environmental characteristic based on first data from the first sensor and second data from the second sensor; determining abnormal driving behavior based on the abnormal driving characteristic and the associated environmental characteristic; and instructing the driver of the vehicle to perform corrective actions to correct the abnormal driving behavior.

[0090] In some implementations, the operation further includes instructing the correction action via at least one of the following: the user interface of the vehicle; and the user interface of the mobile device.

[0091] In some implementations, the operation further includes instructing the correction action by at least one of the following: a graphic display; an audio speaker; visible light; and a vibration actuator.

[0092] In some implementations, the operation further includes storing at least one abnormal driving behavior in a second non-transitory computer-readable storage device for retrieval by the driver.

[0093] In some implementations, the operation further includes: receiving an instruction based on a driving objective of at least one abnormal driving behavior; and increasing the frequency of instructing the driver to perform the corrective action.

[0094] In some implementations, the operation further includes: instructing the driver to provide a reminder of the corrective action, which consists of a shortened, truncated, or alternative version of the indicated corrective action.

[0095] In another example implementation of the system, the system includes: one or more memories; and one or more processors configured to execute instructions stored in the one or more memories to: monitor one or more driving characteristics by at least one first sensor of the vehicle; monitor one or more environmental characteristics by at least one second sensor of the vehicle; determine at least one abnormal driving characteristic and an associated environmental characteristic based on first data from the first sensor and second data from the second sensor; determine abnormal driving behavior based on the abnormal driving characteristic and the associated environmental characteristic; and instruct the driver of the vehicle to perform corrective actions to correct the abnormal driving behavior.

[0096] In some implementations, the instructions include instructions for performing the correction action by at least one of the following: the user interface of the vehicle; and the user interface of the mobile device.

[0097] In some implementations, the instructions include instructions to perform the correction action by at least one of the following: a graphic display; an audio speaker; visible light; and a vibration actuator.

[0098] In some implementations, the instructions include instructions to perform the following operation: store at least one abnormal driving behavior in a non-transitory computer-readable storage medium for retrieval by the driver.

[0099] In some implementations, the instructions include instructions to perform the following operations: receiving an instruction based on a driving objective based on at least one abnormal driving behavior; and increasing the frequency of instructing the driver to perform the corrective action.

[0100] In some implementations, the instructions include instructions to perform the following: to remind the driver of a correction action consisting of a shortened, truncated, or alternative version of the indicated correction action.

[0101] As used herein, the terms “example,” “implementation,” “aspect,” “feature,” or “element” indicate that they are used as examples, instances, or illustrations. Unless expressly indicated, any example, embodiment, implementation, aspect, feature, or element is independent of various other examples, embodiments, implementations, aspects, features, or elements, and may be used in combination with any other example, embodiment, implementation, aspect, feature, or element.

[0102] As used herein, the terms “determine” and “identify” or any variation thereof include using one or more of the devices shown and described herein to select, identify, calculate, locate, receive, determine, establish, obtain or otherwise identify or determine in any way.

[0103] As used herein, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise stated or clearly indicated from the context, “X includes A or B” is intended to indicate any natural inclusion arrangement. That is, “X includes A or B” is satisfied in any of the foregoing instances if X includes A; X includes B; or X includes both A and B. Furthermore, unless otherwise specified or clearly indicated from the context, the articles “a” and “an” as used in this application and the appended claims should generally be understood to mean “one or more.”

[0104] Furthermore, for the sake of simplicity, although the accompanying drawings and descriptions may include a sequence or series of steps or stages, the elements of the methods disclosed herein may occur in various orders or in parallel. Additionally, the elements of the methods disclosed herein may occur together with other elements not explicitly presented and described herein. Moreover, it is not necessary to require all elements of the methods described herein to implement the method according to this disclosure. Although aspects, features, and elements are described herein in specific combinations, each aspect, feature, or element may be used independently, or in various combinations with other aspects, features, and elements, or in various combinations without other aspects, features, and elements.

[0105] The foregoing aspects, examples, and implementations have been described to allow for easy understanding that this disclosure is not restrictive. In contrast, this disclosure covers various modifications and equivalent arrangements included within the scope of the appended claims, which should be interpreted in the broadest possible sense to encompass all such modifications and equivalent structures permitted by law.

Claims

1. A method comprising: One or more driving characteristics are monitored by at least one first sensor of the vehicle; One or more environmental characteristics are monitored by at least one second sensor of the vehicle. Based on the first data from the first sensor and the second data from the second sensor, at least one abnormal driving characteristic and associated environmental characteristic are determined. Abnormal driving behavior is determined based on the abnormal driving characteristics and the associated environmental characteristics; as well as Instruct the driver of the vehicle to take corrective actions to correct the abnormal driving behavior.

2. The method according to claim 1, further comprising: The correction action is indicated by at least one of the following: The user interface of the vehicle; as well as User interface for mobile devices.

3. The method according to claim 1, further comprising: The correction action is indicated by at least one of the following: Graphics display; Audio speakers; Visible light; as well as Vibration actuator.

4. The method according to claim 1, further comprising: At least one abnormal driving behavior is stored in a non-transitory computer-readable storage device for retrieval by the driver.

5. The method according to claim 1, further comprising: Receive instructions based on at least one driving objective based on abnormal driving behavior; as well as Increase the frequency of instructing the driver to perform the corrective action.

6. The method according to claim 1, further comprising: A reminder to the driver that the corrective action consists of a shortened, truncated, or alternative version of the indicated corrective action.

7. The method according to claim 1, wherein, The first data includes at least one of the following: Vehicle speed; Vehicle acceleration; Vehicle braking; The vehicle sways, pitches, or tilts; Tire pressure; Wheel traction; Gear selection; Engine revolutions per minute; Engine temperature; Brake temperature; Tire temperature; Battery temperature; Battery state of charge; Chassis clearance; as well as Suspension position.

8. The method according to claim 1, wherein, The second sensor includes at least one of the following: Internal camera; External camera; LiDAR; Radar; Sonar; Ultrasonic sensor; Infrared sensor; and Global Navigation Satellite System.

9. A non-transitory computer-readable medium storing instructions operable to cause one or more processors to perform operations, the operations comprising: One or more driving characteristics are monitored by at least one first sensor of the vehicle; One or more environmental characteristics are monitored by at least one second sensor of the vehicle. Based on the first data from the first sensor and the second data from the second sensor, at least one abnormal driving characteristic and associated environmental characteristic are determined. Abnormal driving behavior is determined based on the abnormal driving characteristics and the associated environmental characteristics; as well as Instruct the driver of the vehicle to take corrective actions to correct the abnormal driving behavior.

10. The medium according to claim 9, wherein the operation further comprises: The correction action is indicated by at least one of the following: The user interface of the vehicle; as well as User interface for mobile devices.

11. The medium according to claim 9, wherein the operation further comprises: The correction action is indicated by at least one of the following: Graphics display; Audio speakers; Visible light; as well as Vibration actuator.

12. The medium according to claim 9, wherein the operation further comprises: At least one abnormal driving behavior is stored in a second non-transitory computer-readable storage device for retrieval by the driver.

13. The medium according to claim 9, wherein the operation further comprises: Receive instructions based on at least one driving objective based on abnormal driving behavior; as well as Increase the frequency of instructing the driver to perform the corrective action.

14. The medium according to claim 9, wherein the operation further comprises: A reminder to the driver that the corrective action consists of a shortened, truncated, or alternative version of the indicated corrective action.

15. A system comprising: One or more memory devices; as well as One or more processors are configured to execute instructions stored in one or more memories to: One or more driving characteristics are monitored by at least one first sensor of the vehicle; One or more environmental characteristics are monitored by at least one second sensor of the vehicle. Based on the first data from the first sensor and the second data from the second sensor, at least one abnormal driving characteristic and associated environmental characteristic are determined. Abnormal driving behavior is determined based on the abnormal driving characteristics and the associated environmental characteristics; as well as Instruct the driver of the vehicle to take corrective actions to correct the abnormal driving behavior.

16. The system of claim 15, wherein the instructions include instructions for performing the following operations: The correction action is indicated by at least one of the following: The user interface of the vehicle; and User interface for mobile devices.

17. The system of claim 15, wherein the instructions include instructions for performing the following operations: The correction action is indicated by at least one of the following: Graphics display; Audio speakers; Visible light; and Vibration actuator.

18. The system of claim 15, wherein the instructions include instructions for performing the following operations: At least one abnormal driving behavior is stored in a non-transitory computer-readable storage device for retrieval by the driver.

19. The system of claim 15, wherein the instructions include instructions for performing the following operations: Receive instructions for a driving objective based on at least one abnormal driving behavior; and Increase the frequency of instructing the driver to perform the corrective action.

20. The system of claim 15, wherein the instructions include instructions for performing the following operations: A reminder to the driver that the corrective action consists of a shortened, truncated, or alternative version of the indicated corrective action.

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