Method for distraction driver detection and alert

Abstract

A method (400) for distraction driver detection and alert includes receiving vehicle speed data (20) from one or more wheel speed sensors (122) disposed on a vehicle (105), and receiving proximity data from one or more proximity sensors disposed on the vehicle, the proximity data indicating a distance (32) of the vehicle relative to any object in front of the vehicle. The method also includes executing a distracted driver detection algorithm (300) that uses the vehicle speed data and the proximity data to determine that the vehicle is interrupting the stop-time traffic flow and that a driver of the vehicle is distracted from operating the vehicle. The method includes instructing a system (270) of the vehicle to output an alert to reengage a driver based on determining that the vehicle is interrupting the stop-time traffic flow and the driver of the vehicle is distracted.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to a method for distracted driver detection and alerting. BACKGROUND

[0002] Distracted driving constitutes any activity that diverts a driver’s attention from the road, such as using a wireless device, interacting with an infotainment system of the vehicle, conversing with a passenger, etc. Distracted drivers disrupt traffic flow, increase travel time for fellow drivers, compromise road safety, and can lead to road rage situations. Drivers are most likely to be distracted when stopped at a red light and / or in traffic congestion. In these scenarios, a distracted driver can not react properly to the traffic flow (e.g., the driver does not start driving when the traffic signal changes from red to green), which can cause additional congestion and / or cause a collision as other drivers attempt to avoid the distracted driver. SUMMARY

[0003] One aspect of the present disclosure provides a computer-implemented method for distracted driver detection and alerting during stopped and going traffic of a vehicle, which can include a conventional internal combustion engine vehicle, a hybrid electric vehicle, a fuel cell vehicle, and / or a battery electric vehicle containing front proximity sensors. The computer-implemented method executes on data processing hardware, causing the data processing hardware to perform operations comprising receiving, during operation of the vehicle, vehicle speed data from one or more wheel speed sensors disposed on the vehicle, and proximity data from one or more proximity sensors disposed on the vehicle, the proximity data indicating a distance of the vehicle relative to any objects in front of the vehicle. The operations include executing a distracted driver detection algorithm that uses the vehicle speed data and the proximity data to determine whether the vehicle is disrupting a stop-and-go traffic flow. The operations further include executing a distracted driver detection algorithm that uses vehicle speed data and proximity data to determine whether a driver of the vehicle is distracted from operating the vehicle. The operations include, based on determining both that the vehicle is disrupting the stop-and-go traffic flow and that the driver of the vehicle is distracted, instructing a system of the vehicle to output an alert that causes the driver to refocus.

[0004] Implementations of the present disclosure can include one or more of the following optional features. In some implementations, the distracted driver detection algorithm is executed to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted without using any data obtained from a driver monitoring device and without using any data obtained from an advanced driver assistance system (ADAS) device. Further, the system output indicating the vehicle that alerts the driver to re-engage can include the vehicle’s infotainment system audibly outputting an audible alert from an acoustic speaker of the vehicle that is in communication with the data processing hardware. Alternatively, the system output indicating the vehicle that alerts the driver to re-engage can include the vehicle’s infotainment system visually outputting a graphical alert on a display screen of the vehicle that is in communication with the data processing hardware. In some implementations, the system output indicating the vehicle that alerts the driver to re-engage includes one or more interior components of the vehicle outputting a haptic alert.

[0005] In some implementations, executing the distracted driver detection algorithm includes determining that the vehicle is in a stop-and-go traffic flow based on the vehicle speed data indicating that the speed of the vehicle is less than a threshold speed. Executing the distracted driver detection algorithm in these implementations also includes determining that the driver of the vehicle is distracted from operating the vehicle based on the proximity data indicating that the distance of the vehicle relative to a second vehicle in front of the vehicle is greater than a threshold distance or that the rate of change of the distance of the vehicle relative to the second vehicle in front of the vehicle is greater than a threshold rate of change.

[0006] In some implementations, the operations further include receiving drive state data indicating that a drive gear of the vehicle is actuated. In these implementations, executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the drive state data indicating that the drive gear of the vehicle is actuated.

[0007] In other implementations, the operations include receiving a parking brake state data indicating that a parking brake of the vehicle is released. In these implementations, executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the parking brake state data indicating that the parking brake of the vehicle is released.

[0008] In still other implementations, the operations include receiving a hazard light state indication indicating that a hazard light of the vehicle is off. In these implementations, executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the hazard light state indication indicating that the hazard light of the vehicle is off.

[0009] In some embodiments, the operations include receiving a power mode indication indicating that the power mode of the vehicle includes a propulsion mode. In these embodiments, executing the distracted driver detection algorithm to determine that the vehicle is both interrupting a stop-and-go traffic flow and the driver of the vehicle is distracted is further based on the power mode indication indicating that the power mode of the vehicle includes a propulsion mode.

[0010] The vehicle can include any of a battery electric vehicle, a hybrid electric vehicle, or an internal combustion engine. In some embodiments, the data processing hardware is onboard the vehicle.

[0011] Another aspect of the present disclosure provides a system for distracted driver detection and alerting during stop-and-go traffic in a vehicle, which can include a conventional internal combustion engine vehicle, a hybrid electric vehicle, a fuel cell vehicle, and / or a battery electric vehicle that includes a front proximity sensor. The system includes data processing hardware and memory hardware in communication with the data processing hardware. The memory hardware stores instructions that, when executed on the data processing hardware, cause the data processing hardware to perform operations. The operations include receiving, during operation of the vehicle, vehicle speed data from one or more wheel speed sensors disposed on the vehicle, and proximity data from one or more proximity sensors disposed on the vehicle, the proximity data indicating a distance of the vehicle relative to any objects in front of the vehicle. The operations include executing a distracted driver detection algorithm that uses the vehicle speed data and the proximity data to determine whether the vehicle is interrupting a stop-and-go traffic flow. The operations further include executing a distracted driver detection algorithm that uses the vehicle speed data and the proximity data to determine whether a driver of the vehicle is distracted from operating the vehicle. The operations include indicating, based on determining both that the vehicle is interrupting the stop-and-go traffic flow and that the driver of the vehicle is distracted, a system of the vehicle to output an alert to re-engage the driver.

[0012] This aspect can include one or more of the following optional features. Implementations of the disclosure can include one or more of the following optional features. In some implementations, the executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is performed without using any data obtained from a driver monitoring device and without using any data obtained from an advanced driver assistance system (ADAS) device. Further, the system output indicating the vehicle that alerts the driver to re-engage can include the infotainment system of the vehicle audibly outputting an audible alert from an acoustic speaker of the vehicle that is in communication with the data processing hardware. Alternatively, the system output indicating the vehicle that alerts the driver to re-engage can include the infotainment system of the vehicle visually outputting a graphical alert on a display screen of the vehicle that is in communication with the data processing hardware. In some implementations, the system output indicating the vehicle that alerts the driver to re-engage includes one or more interior components of the vehicle outputting a haptic alert.

[0013] In some implementations, the executing the distracted driver detection algorithm includes determining that the vehicle is in a stop-and-go traffic flow based on the vehicle speed data indicating that a speed of the vehicle is less than a threshold speed. In these implementations, the executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted further includes determining that the driver of the vehicle is distracted from operating the vehicle based on the proximity data indicating that a distance of the vehicle relative to a second vehicle in front of the vehicle is greater than a threshold distance or a rate of change of the distance of the vehicle relative to the second vehicle in front of the vehicle is greater than a threshold rate of change.

[0014] In some implementations, the operations further include receiving drive state data indicating that a drive gear of the vehicle is actuated. In these implementations, the executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the drive state data indicating that the drive gear of the vehicle is actuated.

[0015] In other implementations, the operations include receiving a parking brake state data indicating that a parking brake of the vehicle is released. In these implementations, the executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the parking brake state data indicating that the parking brake of the vehicle is released.

[0016] In still other implementations, the operations include receiving a hazard light state indication indicating that a hazard light of the vehicle is off. In these implementations, the executing the distracted driver detection algorithm to determine both that the vehicle is in a stop-and-go traffic flow and that the driver of the vehicle is distracted is further based on the hazard light state indication indicating that the hazard light of the vehicle is off.

[0017] In some embodiments, the operations include receiving a power mode indication indicating that the power mode of the vehicle includes a propulsion mode. In these embodiments, executing the distracted driver detection algorithm to determine that the vehicle is both interrupting a stopped-while-going traffic flow and that the driver of the vehicle is distracted is further based on the power mode indication indicating that the power mode of the vehicle includes a propulsion mode.

[0018] The vehicle can include any of a battery electric vehicle, a hybrid electric vehicle, or an internal combustion engine. In some embodiments, the data processing hardware is onboard the vehicle.

[0019] The details of one or more implementations of the disclosure are set forth in the accompanying drawings and the description below. Other aspects, features, and advantages will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 is a schematic diagram of an example system for distracted driver detection and alerting deployed within a vehicle.

[0021] Figure 2 is a schematic diagram of a distracted driver detection and alerting system.

[0022] Figure 3 is a schematic diagram of an example distracted driver detection algorithm.

[0023] Figure 4 is a flowchart of an example arrangement of operations for a method for distracted driver detection and alerting.

[0024] Figure 5 is a schematic diagram of an example computing device that can be used to implement the systems and methods described herein.

[0025] Like reference numbers in different drawings represent the same element. DETAILED DESCRIPTION

[0026] With the rise of smartphones and sophisticated infotainment systems, drivers are becoming more and more distracted. Distracted driving is problematic because it leads to longer traffic times, impairs road safety, and is a leading cause of collisions. One way to prevent distracted driving is to detect and alert a distracted driver through visual, audible, or tactile feedback. Current distracted driver detection systems incorporate sophisticated advanced driver assistance systems (ADAS) devices (e.g., camera modules, radar, lidar) integrated with object detection, traffic sign detection, and driver monitoring algorithms. Such devices are often expensive and require sophisticated software to operate accurately, making them less suitable for aftermarket integration into existing vehicles. The complexity and cost of the components used by current distracted driver detection systems make these systems less accessible.

[0027] Embodiments herein relate to a distracted driver detection system and method for detecting a distracted driver and providing an alert during stop-and-go traffic. In particular, the distracted driver detection system of the present disclosure monitors the state of a vehicle during operation to detect a distracted driver that is disrupting the flow of traffic based on arbitration of vehicle data. The vehicle data of the vehicle includes any data collected by sensors of the vehicle that can be used to determine whether a driver is distracted, such as proximity data, speed data, gear data, power data, control data, etc. The distracted driver detection system of the present disclosure relies on conventional sensors available in most vehicles (e.g., wheel speed sensors and / or proximity sensors) without the need to implement complex and expensive ADAS equipment. By utilizing components and equipment already included in most vehicles, the distracted driver detection system of the present disclosure is more accessible than known systems and easier to integrate into most vehicles (i.e., no additional hardware is needed).

[0028] Reference Figure 1 The vehicle 105 (e.g., a battery-powered electric vehicle, a plug-in hybrid vehicle, a hybrid electric vehicle, or an internal combustion engine vehicle) includes a distracted driver detection and alert system 110. The distracted driver detection and alert system 100 includes a distracted driver detection module 250 coupled to one or more vehicle sensors 122 and a driving mode 124 of the vehicle 105 to collect vehicle data of the vehicle 105 that can be used to detect a distracted driver. In some embodiments, the distracted driver detection module 250 implements one or more algorithms (see Figure 3 ) to determine whether a driver of the vehicle 105 is distracted based on the vehicle data. In particular, the distracted driver detection module 250 can determine whether the vehicle 105 is disrupting the flow of stop-and-go traffic and / or whether the driver of the vehicle 105 is distracted from operating the vehicle 105. In some embodiments, the distracted driver detection module 250 determines that the driver is distracted when the vehicle 105 is disrupting the flow of stop-and-go traffic and the driver of the vehicle 105 is distracted from operating the vehicle 105. Upon detecting a distracted driver, the distracted driver detection module 250 is configured to output one or more alerts to the driver of the vehicle 105 via an alert module 260 through a driver interface system 270. The driver interface system 270 can include any components of the vehicle 105 that can be used to alert the driver through audio, visual, and / or tactile signals. For example, the driver interface system 270 includes a speaker, an infotainment system (i.e., a graphical user interface), a screen, and tactile interior components (seat, steering wheel, armrest, etc.).

[0029] The battery or energy storage device (ESD) 180 of vehicle 105 supplies power for operating the distracted driver detection and warning system 100. In some examples, vehicle 105 includes an electric or battery-powered vehicle, and ESD 180 powers multiple systems of vehicle 105, such as the driving system of vehicle 105 and the distracted driver detection and warning system 100. Optionally, ESD 180 includes an auxiliary battery or a dedicated battery for powering the distracted driver detection and warning system 100 solely.

[0030] The distracted driver detection module 250 is based on memory hardware 520 that communicates with data processing hardware 510. Figure 5 The instructions in the data processing hardware 510 ( Figure 5 The data processing hardware 510 executes the instructions, which, when executed on the data processing hardware 510, cause the data processing hardware 510 to execute the distracted driver detection module 250 to perform operations. For example, the distracted driver detection module 250 stores instructions for operating the distracted driver detection and alarm system 100 based on vehicle data collected from vehicle sensors 122 and driving mode selector 124. As described below, the distracted driver detection module 250 continuously receives input from one or more sensors 122 and driving mode selector 124 throughout the operation of the vehicle 105 to detect whether the driver of the vehicle 105 is distracted and generate an alarm at the driver interface system 270 via the alarm module 260.

[0031] One or more vehicle sensors 122 may be deployed throughout the vehicle 105. For example, one or more proximity sensors 122, 122B may be deployed at the front of the vehicle 105, and one or more wheel speed sensors 122, 122A may be deployed at the wheels of the vehicle 105. Additionally, the distracted driver detection module 250 may use any other sensors 122 that can be deployed in the vehicle 105 to collect vehicle data indicative of the operation of the vehicle 105. Other example sensors 122 include GPS, body control, powertrain domain controller, electronic parking brake, odometer, accelerometer, light sensor, power mode sensor, hazard light status, etc. Driving mode 124 may include any data related to the vehicle's actuation gear (e.g., park, reverse, neutral, drive). The distracted driver detection and warning system 100 may be configured to detect a distracted driver without using any data obtained from driver monitoring devices and without using any data obtained from advanced driver assistance system (ADAS) devices.

[0032] The alert module 260 is electrically coupled to the ESD 180 and the driver interface system 270 to control one or more alerts at the driver interface system 270 based on a signal from the distracted driver detection module 250. The distracted driver detection module 250 and the alert module 260 are configured to cause one or more alerts at the driver interface system 270 of the distracted driver detection and alert system 100. For example, the distracted driver detection module 250 determines that the driver of the vehicle is distracted based on vehicle data from one or more vehicle sensors 122. In this example, the distracted driver detection module 250 sends a signal (e.g., the distracted driver status 251) to the alert module 260 that the driver is distracted. Here, the alert module 260 activates one or more components of the driver interface system 270 to alert the driver of the vehicle 105 that they are exhibiting unsafe driving behavior, as discussed in more detail below in Figure 2 Figure 2

[0033] Figure 2 A schematic diagram 200 of a distracted driver detection and alert system is shown. In particular, Figure 2 The schematic diagram 200 shows that vehicle data is obtained at various sensors 122, 122A-122E, a distracted driver status 251 is determined via the distracted driver detection module 250, and an alert is output to the driver with one or more components of the driver interface system 270, including a visual component 270, 270A, an audible component 270, 270B, or a haptic component 270, 270C, via the alert module 260. The distracted driver detection and alert system can be configured to work in a “stop-and-go” scenario where the vehicle 105 is constantly accelerating and / or decelerating.

[0034] The wheel speed sensor 122, 122A can include any sensor that can measure the speed of the vehicle 105. For example, the wheel speed sensor 122A can be a speedometer, an odometer, an accelerometer, etc. In some implementations, the wheel speed sensor 122A is disposed at or near a wheel of the vehicle 105 and measures the speed of the vehicle 105 based on the rotation of the wheel. In some implementations, the vehicle 105 can be in a vehicle stationary state 203 when the vehicle 105 is not moving. In other words, the vehicle 105 can be determined to have a speed of zero or near zero.

[0035] The drive mode 124 of the vehicle can refer to an actuated gear state and / or drive state data that indicates which drive gear of the vehicle 105 is actuated. For example, the drive mode 124 can indicate that the vehicle 105 is in park, reverse, neutral, drive, or low.

[0036] ​​The front proximity sensors 122, 122B can be used to determine proximity data indicative of the distance between the vehicle 105 and any objects (e.g., other vehicles) in front of the vehicle 105. Further, the front proximity sensors 122B can be used to determine the change in distance between the vehicle 105 and any objects in front of the vehicle 105 over time. For example, when the distance between the vehicle 105 and objects in front of the vehicle 105 is continually increasing and decreasing as measured, the distracted driver detection module 250 is more likely to determine that the driver is distracted (i.e., the distracted driver state 251 is true). Alternatively, when the distance between the vehicle 105 and objects in front of the vehicle 105 is relatively constant as measured, the distracted driver detection module 250 is more likely to determine that the driver is not distracted (i.e., the distracted driver state 251 is false). The front proximity sensors 122B can include any known sensors for measuring distance.

[0037] The electronic parking brake 122, 122C provides parking brake state data indicative of the position of the parking brake of the vehicle 105. When the parking brake of the vehicle 105 is activated and the distance between the vehicle 105 and objects in front of the vehicle 105 increases, the distracted driver detection module 250 can determine that the driver is distracted. Alternatively, when the parking brake of the vehicle 105 is released, the distracted driver detection module 250 can determine that the driver is less likely to be distracted.

[0038] The powertrain domain controller 122, 122D can indicate the power mode of the vehicle. In particular, the powertrain domain controller 122D can indicate whether the vehicle 105 is in a propulsion mode. Further, the powertrain domain controller 122D can indicate any other known or applicable power mode of the vehicle 105.

[0039] The body controller 122, 122E of the vehicle 105 can provide a hazard light state indication indicative of the state of the hazard lights of the vehicle 105. In some embodiments, the body controller 122E provides an indication of any other lights of the vehicle, such as brake lights, high beams, fog lights, interior lights, headlamps, etc.

[0040] The distracted driver detection module 250 can obtain and / or receive data from the sensors 122A-122E and 124. In some embodiments, the distracted driver detection module 250 continually obtains vehicle data from the sensors 122A-122E and 124 throughout the operation of the vehicle 105 to determine whether the driver of the vehicle is distracted. In other embodiments, the distracted driver detection module 250 is only activated when the vehicle 105 accelerates and / or decelerates a threshold number of times over a period of time (i.e., indicative of the vehicle 105 being in stop-and-go traffic). In some embodiments, the distracted driver detection module 250 implements an algorithm that determines whether the driver of the vehicle is distracted based on the data obtained from the sensors 122A-122E and 124. Figure 3distracted driver state 251. The distracted driver state 251 can be a Boolean variable, a probability distribution function, a fraction, or some other representation that can be used to represent the driver state. The distracted driver detection module 250 can transmit the distracted driver state 251 to the alert module 260.

[0041] Based on the distracted driver state 251, the alert module 260 can cause one or more components 270A-270C of the driver interface system 270 to issue an alert to the driver of the vehicle 105. For example, the alert module 260 causes the visual component 270A to display a graphical alert on a display screen of the vehicle 105 indicating that the driver is distracted. In another example, the alert module 260 causes the audible component 270B to audibly output an audible alert from an acoustic speaker of the vehicle 105 indicating that the driver is distracted. In yet another example, the alert module 260 causes the haptic component 270C to output a haptic alert from an interior component of the vehicle 105 indicating that the driver is distracted.

[0042] The above-described examples regarding the Figure 2 The examples described above are not intended to be limiting. The vehicle 105 can be equipped with any applicable vehicle sensors 122 and driving patterns 124 to obtain vehicle data during operation of the vehicle 105 that the distracted driver detection module 250 can use to determine whether the driver is distracted. In some implementations, the distracted driver detection module 250 is configured to obtain any vehicle data other than vehicle data obtained from the driver monitoring device without using any data obtained from an advanced driver assistance system (ADAS) device. Further, the distracted driver detection module 250 via the alert module 260 can cause an acceptable alert through the driver interface system 270. The alert can include any visual, audio, or haptic alert that can be communicated through any applicable interface component of the vehicle 105.

[0043] Figure 3 An example algorithm 300 that can be executed by the distracted driver detection and alert system 100 is shown. In particular, the example algorithm 300 can be deployed by the distracted driver detection module 250 using vehicle data obtained by the sensors 122 and the driving patterns 124 of the vehicle 105. The distracted driver state 19 (i.e., Figure 2The distracted driver state 251 is determined based on arbitration of the following conditions. One condition can be based on a comparison of the vehicle speed 20 to a threshold 22 (stationary state) based on the operation 21. Another condition can depend on whether the Boolean condition 25 of the vehicle stationary state 24 meets a time threshold 26. Another condition can be based on a comparison 28 of the actuated gear 27 of the vehicle 105 to a "driving state" 29. The condition can be based on a transition from the "park" gear to the "drive" gear 30, indicating that the vehicle has transitioned out of stationary 31. Another condition can be based on a Boolean operation 34 that compares whether the distance 32 to an object in front of the vehicle 105 meets a threshold 33 or the rate of change of the distance 35 meets a different threshold 36. Another condition can be based on a comparison 38 between the parking brake state 37 and the state "released" 39. Yet another condition can be based on a comparison 41 of the vehicle power mode 40 to the state "propulsion" 42. Further, a condition can be based on a comparison 44 between the hazard light state 43 and the state "off" 45. In some embodiments, each of the above conditions are combined in a Boolean "and" operation 23 to determine the output. When the output of the Boolean "and" operation 23 is met within a time threshold 46, 47, the distracted driver state 19 can transition to "true."

[0044] Figure 3 The example algorithm 300 is not intended to be limiting. The distracted driver detection module 250 can implement any applicable algorithm to determine whether the driver is distracted. In particular, the distracted driver detection module 250 can execute any distracted driver algorithm that uses any applicable vehicle data (e.g., any of the vehicle data described above with respect to the sensors 122A-122E and the driving mode 124) to determine whether the vehicle 105 is interrupting the flow of traffic when stopped and whether the driver of the vehicle 105 is distracted from operating the vehicle 105.

[0045] Figure 4 is a flowchart of an example operational arrangement of a method 400 of distracted driver detection and alerting. The method 400 can be performed, for example, by a computing device (such as the computing device 110) deployed in a vehicle (such as the vehicle 105) Figure 1 Figure 5 ​on one or more processors of the data processing hardware 500. At operation 402, the method 400 includes receiving vehicle speed data from one or more wheel speed sensors 122A disposed on the vehicle 105. At operation 404, the method 400 includes receiving proximity data from one or more proximity sensors 122B disposed on the vehicle 105, the proximity data indicating a distance of the vehicle 105 relative to any objects in front of the vehicle 105. At operation 406, the method 400 includes executing the distracted driver detection algorithm 300, which uses the vehicle speed data and the proximity data to determine that the vehicle 105 is stop-and-go traffic interrupting and that the driver of the vehicle is distracted from operating the vehicle 105. At operation 408, the method 400 includes instructing a system 270 of the vehicle 105 to output an alert to refocus the driver based on determining both that the vehicle 105 is stop-and-go traffic interrupting and that the driver of the vehicle 105 is distracted.

[0046] Figure 5 is a schematic diagram of an example computing device 500 that can be used to implement the systems and methods described in this document. The computing device 500 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The components shown here, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and / or claimed in this document.

[0047] The computing device 500 includes a processor 510, memory 520, a storage device 530, a high-speed interface / controller 540 connecting the memory 520 and the high-speed expansion ports 550 to the processor 510, and a low-speed interface / controller 560 connecting the low-speed bus 570 and the storage device 530 to the processor 510. Each of the components 510, 520, 530, 540, 550, and 560 are interconnected using various busses, and can be mounted on a common motherboard or in other ways as appropriate. The processor 510 can process instructions for execution within the computing device 500, including instructions stored in the memory 520 or on the storage device 530 to

[0048] Memory 520 non-transitorily stores information within computing device 500. Memory 520 can be a computer-readable medium, a volatile memory unit or units, or a non-volatile memory unit or units. Non-transitory memory 520 can be physical devices that temporarily or permanently store programs (e.g., sequences of instructions) or data (e.g., program state information) for use by computing device 500. Examples of non-volatile memory include, but are not limited to, flash memory and read-only memory (ROM) / programmable read-only memory (PROM) / erasable programmable read-only memory (EPROM) / electrically erasable programmable read-only memory (EEPROM) (e.g., typically used for firmware such as BIOS). Examples of volatile memory include, but are not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), phase change memory (PCM), and disk or tape.

[0049] Storage device 530 can provide mass storage for computing device 500. In some implementations, storage device 530 is a computer-readable medium. In various different implementations, storage device 530 can be a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. In additional implementations, a computer program product is tangibly embodied in an information carrier. The computer program product contains instructions that, when executed, perform one or more methods, such as those described above. The information carrier is a computer- or machine- readable medium, such as the memory 520, the storage device 530, or memory on processor 510.

[0050] High-speed controller 540 manages bandwidth-intensive operations for computing device 500, while low-speed controller 560 manages lower bandwidth-intensive operations. Such allocation of functions is exemplary only. In some implementations, high-speed controller 540 is coupled to memory 520, display 580 (e.g., through a graphics processor or accelerator), and to high-speed expansion ports 550, which can accept various expansion cards (not shown). In some implementations, low-speed controller 560 is coupled to storage device 530 and low-speed expansion port 590. The low-speed expansion port 590, which can include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), can be coupled to one or more input / output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.

[0051] The computing device 500 can be implemented in a number of different forms, as shown in the figure. For example, it can be implemented as a standard server 500a or multiple times in a group of such servers 500a, as a laptop computer 500b, or as part of a rack server system 500c.

[0052] Various implementations of the systems and techniques described herein can be realized in digital electronic and / or optical circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0053] A software application (i.e., a software source) can refer to computer software that causes a computing device to perform a task. In some examples, a software application can be referred to as an “application,” “app,” or “program.” Example applications include, but are not limited to, system diagnostic applications, system management applications, system maintenance applications, word processing applications, spreadsheet applications, messaging applications, media streaming applications, social networking applications, and gaming applications.

[0054] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and / or object-oriented programming language, and / or in assembly / machine language. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, non-transitory computer readable medium, apparatus and / or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0055] The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit). Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical, or optical disks, or

[0056] To provide for interaction with a user, one or more aspects of the disclosure can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube), LCD (liquid crystal display), or touch screen, for displaying information to the user and optionally a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device of the user; for example, by sending web pages to a web browser on a user’s client device in response to requests received from the web browser.

[0057] A number of implementations have been described. Nevertheless, it will be understood that various modifications can be made without departing from the spirit and scope of the disclosure. Accordingly, other implementations are within the scope of the following claims.

Claims

1. A computer-implemented method (400) executed on data processing hardware (510), the method causing the data processing hardware (510) to perform operations comprising: receiving vehicle speed data (20) from one or more wheel speed sensors (122) disposed on a vehicle (105); receiving proximity data from one or more proximity sensors (122) disposed on the vehicle (105), the proximity data indicating a distance (32) of the vehicle (105) from any object in front of the vehicle (105); executing a distracted driver detection algorithm (300) that uses the vehicle speed data (20) and the proximity data to determine: that the vehicle (105) is interrupting a stop-and-go traffic flow; and that a driver of the vehicle (105) is distracted from operating the vehicle (105); and based on determining both that the vehicle (105) is interrupting the stop-and-go traffic flow and that the driver of the vehicle (105) is distracted, instructing a system (270) of the vehicle (105) to output an alert to refocus the driver.

2. The computer-implemented method (400) of claim 1, wherein executing the distracted driver detection algorithm (300) determines both that the vehicle (105) is interrupting the stop-and-go traffic flow and that the driver of the vehicle (105) is distracted without using any data obtained from a driver monitoring device and without using any data obtained from an advanced driver assistance system (ADAS) device.

3. The computer-implemented method (400) of claim 1 or 2, wherein instructing the system (270) of the vehicle (105) to output the alert to refocus the driver includes instructing an infotainment system (270) of the vehicle (105) to audibly output an audible alert from an acoustic speaker of the vehicle (105) that is in communication with the data processing hardware (510).

4. The computer-implemented method (400) of any of claims 1-3, wherein instructing the system (270) of the vehicle (105) to output the alert to refocus the driver includes instructing an infotainment system (270) of the vehicle (105) to visually output a graphical alert on a display screen of the vehicle (105) that is in communication with the data processing hardware (510).

5. The computer-implemented method (400) according to any one of claims 1 to 4, wherein, instructing the system (270) of the vehicle (105) to output the alert to refocus the driver includes instructing one or more interior components of the vehicle (105) to output a haptic alert.

6. The computer-implemented method (400) of any of claims 1-5, wherein executing the distracted driver detection algorithm (300) includes: determining that the vehicle (105) is interrupting the stop-and-go traffic flow based on the vehicle speed data (20) indicating a speed of the vehicle (105) is less than a threshold speed; and determine that a driver of the vehicle (105) is distracted from operating the vehicle (105) based on the proximity data indicating that: a distance (32) of the vehicle (105) relative to a second vehicle ahead of the vehicle (105) is greater than a threshold distance; or a rate of change of the distance (32) of the vehicle (105) relative to the second vehicle ahead of the vehicle (105) is greater than a threshold rate of change.

7. The computer-implemented method (400) of any one of claims 1 to 6, wherein, the operations further include: receiving drive state data indicating that a drive gear (27) of the vehicle (105) is actuated, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the drive state data indicating that the drive gear (27) of the vehicle (105) is actuated.

8. The computer-implemented method (400) of any one of claims 1 to 7, wherein, the operations further include: receiving park brake state data indicating that a park brake of the vehicle (105) is released, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the park brake state data indicating that the park brake of the vehicle (105) is released.

9. The computer-implemented method (400) according to any one of claims 1 to 8, wherein, the operations further include: receiving hazard light state (43) data indicating that a hazard light of the vehicle (105) is off, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the hazard light state (43) data indicating that the hazard light of the vehicle (105) is off.

10. The computer-implemented method (400) according to any one of claims 1 to 9, wherein, the operations further include: receiving power mode data indicating that a power mode of the vehicle (105) includes a propulsion mode, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the power mode data indicating that the power mode of the vehicle (105) includes the propulsion mode.

11. The computer-implemented method (400) of any one of claims 1-10, wherein the vehicle (105) comprises a battery electric vehicle.

12. The computer-implemented method (400) of any one of claims 1-10, wherein the vehicle (105) comprises a hybrid electric vehicle.

13. The computer-implemented method (400) of any one of claims 1-10, wherein the vehicle (105) comprises an internal combustion engine.

14. The computer-implemented method (400) of any one of claims 1-13, wherein the data processing hardware (510) is onboard the vehicle (105).

15. A vehicle (105), comprising: data processing hardware (510); and wherein the data processing hardware (510) is configured to: receive proximity data indicating a distance (32) of the vehicle (105) relative to a second vehicle ahead of the vehicle (105), determine that a driver of the vehicle (105) is distracted from operating the vehicle (105) based on the proximity data indicating that: a distance (32) of the vehicle (105) relative to a second vehicle ahead of the vehicle (105) is greater than a threshold distance; or a rate of change of the distance (32) of the vehicle (105) relative to the second vehicle ahead of the vehicle (105) is greater than a threshold rate of change. memory hardware (520) in communication with the data processing hardware (510) and storing instructions that, when executed on the data processing hardware (510), cause the data processing hardware (510) to perform operations comprising: receiving vehicle speed data (20) from one or more wheel speed sensors (122) disposed on the vehicle (105); receiving proximity data from one or more proximity sensors (122) disposed on the vehicle (105), the proximity data indicating a distance (32) of the vehicle (105) relative to any objects in front of the vehicle (105); executing a distracted driver detection algorithm (300) that uses the vehicle speed data (20) and the proximity data to determine: the vehicle (105) is interrupting a stop-and-go traffic flow; and a driver of the vehicle (105) is distracted from operating the vehicle (105); and based on determining both that the vehicle (105) is interrupting the stop-and-go traffic flow and that the driver of the vehicle (105) is distracted, instructing a system (270) of the vehicle (105) to output an alert to refocus the driver.

16. The vehicle (105) of claim 15, wherein executing the distracted driver detection algorithm (300) determines both that the vehicle (105) is interrupting the stop-and-go traffic flow and that the driver of the vehicle (105) is distracted without using any data obtained from a driver monitoring device and without using any data obtained from an advanced driver assistance system (ADAS) device.

17. The vehicle (105) of claim 15 or 16, wherein instructing a system (270) of the vehicle (105) to output an alert to refocus the driver includes instructing an infotainment system (270) of the vehicle (105) to audibly output an audible alert from an acoustic speaker of the vehicle (105) in communication with the data processing hardware (510).

18. The vehicle (105) of any one of claims 15 to 17, wherein instructing a system (270) of the vehicle (105) to output an alert to refocus the driver includes instructing an infotainment system (270) of the vehicle (105) to visually output a graphical alert on a display screen of the vehicle (105) in communication with the data processing hardware (510).

19. The vehicle (105) according to any one of claims 15 to 18, wherein Instructing a system (270) of the vehicle (105) to output an alert to refocus the driver includes instructing one or more interior components of the vehicle (105) to output a haptic alert.

20. The vehicle (105) of any one of claims 15 to 19, wherein executing the distracted driver detection algorithm (300) includes: determining that the vehicle (105) is interrupting the stop-and-go traffic flow based on the vehicle speed data (20) indicating a speed of the vehicle (105) is less than a threshold speed; and determine that a driver of the vehicle (105) is distracted from operating the vehicle (105) based on the proximity data indicating: a distance (32) of the vehicle (105) relative to a second vehicle ahead of the vehicle (105) is greater than a threshold distance; or a rate of change of the distance (32) of the vehicle (105) relative to the second vehicle ahead of the vehicle (105) is greater than a threshold rate of change.

21. The vehicle (105) according to any one of claims 15 to 20, wherein the operations further include: receiving drive state data indicating that a drive gear (27) of the vehicle (105) is actuated, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the drive state data indicating that the drive gear (27) of the vehicle (105) is actuated.

22. The vehicle (105) according to any one of claims 15 to 21, wherein the operations further include: receiving park brake state data indicating that a park brake of the vehicle (105) is released, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the park brake state data indicating that the park brake of the vehicle (105) is released.

23. The vehicle (105) according to any one of claims 15 to 22, wherein the operations further include: receiving hazard light state (43) data indicating that a hazard light of the vehicle (105) is off, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the hazard light state (43) data indicating that the hazard light of the vehicle (105) is off.

24. The vehicle (105) according to any one of claims 15 to 23, wherein, the operations further include: receiving power mode data indicating that a power mode of the vehicle (105) includes a propulsion mode, wherein executing the distracted driver detection algorithm (300) to determine that both the vehicle (105) is disrupting the stop-and-go traffic flow and the driver of the vehicle (105) is distracted is further based on the power mode data indicating that the power mode of the vehicle (105) includes the propulsion mode.

25. The vehicle (105) of any one of claims 15 to 24, wherein the vehicle (105) includes an electric battery electric vehicle.

26. The vehicle (105) of any one of claims 15 to 24, wherein the vehicle (105) includes a hybrid electric vehicle.

27. The vehicle (105) of any one of claims 15 to 24, wherein the vehicle (105) includes an internal combustion engine.

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