System and method for controlling operation of vehicle exterior lights

Abstract

The present disclosure provides "systems and methods for controlling operation of vehicle exterior lights". A vehicle is disclosed that includes a sensor unit, an exterior light, and a processor. The sensor unit can capture inputs associated with a surrounding environment of the vehicle. The processor can determine, based on the inputs obtained from the sensor unit, that a user can be performing an activity in a vicinity of the exterior light. The processor can also determine, based on the inputs, an activity type in response to determining that the user is performing the activity. The processor can also determine, based on the activity type, an optimal lighting intensity for the exterior light. The processor can then illuminate the exterior light at the optimal lighting intensity.

Description

Technical Field

[0001] This disclosure relates to systems and methods for controlling the operation of vehicle exterior lights to optimize vehicle energy consumption. Background Technology

[0002] Modern vehicles feature numerous advanced features and components that enhance the experience of operating or using the vehicle. For example, most modern vehicles have infotainment systems, cameras, proximity sensors, interior and exterior lights, etc., which significantly enhance the vehicle's user experience. Furthermore, many of these vehicle components allow users to use their vehicles for additional activities beyond simply driving / driving. For instance, users can use some of these vehicle components for entertainment or leisure purposes, surveillance, illuminating the surroundings in dark conditions, etc.

[0003] While the aforementioned vehicle components significantly enhance the user experience, they also consume vehicle energy during operation. Continuous efforts are being made to optimize energy consumption, particularly when these components are used while the vehicle is in the ignition-off state. Summary of the Invention

[0004] This disclosure describes a vehicle that can control the operation of its exterior lights to optimize vehicle energy consumption. Specifically, the vehicle can illuminate the exterior lights at an optimal intensity, which allows the user to easily perform activities that the user might perform near the vehicle, while ensuring that the vehicle's energy is not unnecessarily used to illuminate the exterior lights beyond what is needed.

[0005] In some respects, the vehicle can first determine that a user may be performing an activity near the vehicle. In response to this determination, the vehicle can determine whether the user is an authorized or unauthorized user based on input obtained from the vehicle's sensor units. When the vehicle determines that the user is an authorized user, it can determine the type of activity the user may be performing (“activity type”) based on the obtained input. In response to determining the activity type, the vehicle can determine the external lights of the vehicle most likely closest to the user and the ambient lighting intensity near the user based on the obtained input. The vehicle can then determine the optimal lighting intensity of the external lights based on the activity type and the determined ambient lighting intensity.

[0006] In some respects, a vehicle can determine the optimal lighting intensity for its exterior lights by subtracting the ambient lighting intensity from the desired lighting intensity required for the activity type. In other respects, the desired lighting intensity associated with the activity type can be stored in the vehicle's memory as a "user preference" for lighting. In still other respects, the vehicle itself can determine the desired lighting intensity based on a lookup table that can be pre-stored in the vehicle's memory or a mapping between multiple desired lighting intensities and multiple activity types.

[0007] In response to determining the optimal illumination intensity of the exterior lights as described above, the vehicle can illuminate the exterior lights at the optimal intensity. In some aspects, the vehicle can also obtain user feedback on the illumination intensity and adjust the illumination intensity of the exterior lights based on the user feedback.

[0008] In another aspect, the vehicle can monitor user movement near the vehicle, the type of activity the user is performing, ambient light intensity, user behavior, etc., based on input obtained from the sensor unit. When one or more of these parameters change, the vehicle can adjust the illumination intensity and / or the light projection angle of the external lights. The vehicle can further optimize the vehicle's energy consumption by adjusting the sampling rate or polling rate of one or more sensors in the sensor unit that monitor the aforementioned parameters based on the time of day, ambient weather conditions, the type of activity the user is performing, and the amount of user movement near the vehicle.

[0009] The vehicle can further “balance” the energy consumption of various vehicle features / components (including exterior lights) to further optimize the vehicle's energy consumption. In this case, the vehicle can determine the preferred proportion of vehicle energy that can be used to illuminate the vehicle's exterior lights based on one or more parameters, including but not limited to the vehicle's exterior light usage patterns, vehicle geographic location, expected vehicle route, vehicle battery state of charge (SoC), vehicle fuel level, profiles of one or more occupants in the vehicle, time of day, user preferences, expected duration of the activity, and weather conditions in the geographic area where the vehicle is located.

[0010] The vehicle can also determine the actual proportion of vehicle energy used to illuminate the exterior lights and compare it to a determined preferred proportion. When the actual proportion is greater than the preferred proportion, the vehicle can output an alarm notification to the user. The user can perform one or more remedial actions in response to seeing / hearing the alarm notification, thereby promoting optimized energy use of the vehicle. In some aspects, the vehicle can additionally adjust the lighting intensity associated with the exterior lights based on the determined preferred proportion.

[0011] This disclosure discloses a vehicle that controls the operation of its exterior lights to optimize vehicle energy consumption. Specifically, the vehicle illuminates the exterior lights at optimal intensity, allowing users to comfortably perform activities near the vehicle while ensuring that excessive vehicle energy is not unnecessarily consumed. The vehicle also enables users to "balance" the vehicle's energy consumption among different vehicle features / components, ensuring that the exterior lights do not consume a large proportion of the vehicle's energy during illumination. Furthermore, as users perform activities near the vehicle, the vehicle can dynamically adjust the illumination intensity of the exterior lights, their angles, the sampling rate of one or more vehicle sensors, etc., further optimizing the vehicle's energy consumption.

[0012] These and other advantages of this disclosure are provided in detail herein. Attached Figure Description

[0013] Specific embodiments are illustrated with reference to the accompanying drawings. The same reference numerals may be used to indicate similar or identical items. Various embodiments may utilize elements and / or components other than those shown in the drawings, and some elements and / or components may not be present in various embodiments. Elements and / or components in the drawings are not necessarily drawn to scale. Throughout this disclosure, singular and plural terms may be used interchangeably, depending on the context.

[0014] Figure 1 The environment in which the techniques and structures for providing the systems and methods disclosed herein can be implemented is described.

[0015] Figure 2 A block diagram of a system for controlling the operation of vehicle exterior lights according to the present disclosure is shown.

[0016] Figure 3 An exemplary view depicting a user using a user device to illuminate a book near a vehicle, according to this disclosure, is shown.

[0017] Figure 4 An exemplary view depicting a user moving an item from a first location near a vehicle to a second location, according to this disclosure, is provided.

[0018] Figure 5 A flowchart depicts an exemplary method for controlling the operation of vehicle exterior lights according to the present disclosure. Detailed Implementation

[0019] The present disclosure will be described more fully below with reference to the accompanying drawings, which illustrate exemplary embodiments of the present disclosure and are not intended to be limiting.

[0020] Figure 1 An environment 100 is depicted in which the techniques and structures for providing the systems and methods disclosed herein can be implemented. Environment 100 may include a vehicle 102, which may take the form of any passenger or commercial vehicle, such as a car, work vehicle, crossover, truck, van, minivan, taxi, bus, etc. Vehicle 102 may be a manually driven vehicle or may be configured to operate in a partially / fully autonomous mode. Furthermore, in some aspects, vehicle 102 may be an electric vehicle (EV) or a plug-in hybrid electric vehicle (PHEV). In other aspects, vehicle 102 may be an internal combustion engine (ICE) vehicle.

[0021] In some aspects, vehicle 102 may include multiple exterior lights 104a, 104b, 104c, 104n (or “zone lights,” collectively referred to as exterior lights 104) that may be located at different vehicle positions / parts. For example, a first exterior light 104a may be located at the top right vehicle portion, a second exterior light 104b may be located at the top rear vehicle portion, a third exterior light 104c may be located at the top left vehicle portion, a fourth exterior light 104n may be located near the right rearview mirror, etc. (Described above and...) Figure 1 The exemplary locations of the exterior lights 104 depicted herein should not be construed as limiting. Without departing from the scope of this disclosure, the exterior lights 104 may be located at other exterior vehicle portions. Furthermore, without departing from the scope of this disclosure, the vehicle 102 may include more or fewer than the four exterior lights described above.

[0022] External light 104 can illuminate portions / areas / zones near the corresponding external light, and can enable one or more users (e.g., user 106) to perform one or more activities near vehicle 102 that may require lighting or illumination (e.g., when ambient light may be dim). For example, user 106 can read a book (such as...). Figure 1 As shown), the user 106 moves items (e.g., tools, plants, shrubs, etc.) from one location to another near vehicle 102, assembles or disassembles equipment / toys, plays games, cuts wood, performs gardening activities, etc., near vehicle 102. External light 104 can illuminate the area / zone where the user 106 may be performing the above activities, making it convenient for the user 106 to perform the activities even if the ambient light may be dim.

[0023] When vehicle 102 may be in a key-on or key-off state, exterior lights 104 can illuminate the corresponding area. In other words, user 106 can use exterior lights 104 for illumination when vehicle 102 may be turned on (i.e., when the vehicle engine may be turned on) or off (i.e., when the vehicle engine may be turned off). It is understood that exterior lights 104 can consume energy from the vehicle battery when they can be activated. When exterior lights 104 may be operating, vehicle 102 can optimize energy consumption so that exterior lights 104 do not consume more energy than needed (i.e., exterior lights 104 do not unnecessarily consume a large amount of energy), while ensuring that user 106 can conveniently perform activities near vehicle 102 with sufficient / required lighting levels. By optimizing energy consumption, especially when exterior lights 104 are illuminated during the vehicle's key-off state, vehicle 102 can ensure that battery energy is optimally used for all key-off loads (KOLs), and that exterior lights 104 do not unnecessarily consume a large proportion of battery energy. Furthermore, by optimizing energy consumption, vehicle 102 can ensure that the vehicle battery has sufficient remaining state of charge (SoC) to effectively start the vehicle engine, for example, when user 106 expects to start and drive vehicle 102 (after the key is off). Exemplary steps / processes performed by vehicle 102 to optimize energy consumption for external light operation are briefly described below, and will be discussed later in conjunction with… Figure 2 Detailed description.

[0024] In some respects, vehicle 102 can first be based on sensor units from the vehicle (such as...) Figure 2 The vehicle sensing system 232 (as shown in the diagram) obtains input to determine that user 106 may be near vehicle 102. The sensor unit may include one or more external vehicle cameras, radar sensors, lidar sensors, Bluetooth Low Energy (BLE) transceivers, mobile phone-as-a-key transceivers, etc. In response to determining the presence of a user near vehicle 102, vehicle 102 may attempt to “identify” user 106 to determine whether user 106 is an authorized / authenticated user or an unauthorized user. In some aspects, an authorized user may be the vehicle owner or any other user (e.g., a family member, friend, etc.) whose details (e.g., facial features, fingerprints, etc.) may be pre-registered with vehicle 102 or whose user device may be pre-synchronized with or pre-registered with vehicle 102. Vehicle 102 may determine that user 106 may be an authorized user based on facial recognition technology (e.g., by using images captured by the vehicle's external cameras) and / or based on input obtained from the vehicle's BLE transceiver, mobile phone-as-a-key transceiver, and / or other similar transceivers. In the latter case, when a user device (e.g., a wireless tag, keychain, mobile phone, etc.) is associated with or carried by user 106, such as... Figure 2When the user device 204 (shown in the transceiver) is communicatively coupled to the transceiver described above, vehicle 102 can determine that user 106 may be an authorized user. On the other hand, when the transceiver is not coupled to the user device associated with user 106, vehicle 102 can determine that user 106 may be an unauthorized user.

[0025] In response to determining that user 106 may be an unauthorized user, vehicle 102 may not activate external lights 104, thereby saving vehicle energy consumption. On the other hand, in response to determining that user 106 may be an authorized user, vehicle 102 may initiate a process for determining the optimal lighting intensity of external lights (from external lights 104) that user 106 may need, which can ensure that vehicle energy is not unnecessarily consumed, while user 106 can comfortably perform activities near vehicle 102.

[0026] In this scenario, vehicle 102 can first identify external lights (e.g., external light 104a) where user 106 may be nearby and performing activities (e.g., reading a book). Figure 1 As shown. Then, vehicle 102 can determine the type of activity (“activity type”) that user 106 may be performing based on input obtained from the sensor unit. In some aspects, vehicle 102 may include an artificial intelligence / machine learning (AI / ML) based processor (in... Figure 2 The processor (shown as processor 242) can analyze user images captured by the vehicle's external cameras to determine the type of activity.

[0027] Vehicle 102 can also access the vehicle memory (in Figure 2 The image shows a memory (244) or a server (in...). Figure 2 The diagram shows server 202 obtaining / retrieving a user profile associated with user 106. This user profile may include user preferences related to user-preferred lighting intensities for different types of activities user 106 may perform near vehicle 102. Specifically, the user profile may include a mapping between user-preferred lighting intensities and different activity types. For example, the user profile may indicate that user 106 prefers an illuminance of 500 lux when reading a book near vehicle 102.

[0028] In response to obtaining a user profile, vehicle 102 can determine the ambient lighting level or ambient light intensity near user 106 (i.e., lighting naturally present near user 106 due to the sun, lampposts, or any other lighting fixtures). Vehicle 102 can then correlate the ambient light intensity with the user-preferred lighting intensity for the type of activity user 106 is likely performing (e.g., reading a book) to determine the optimal lighting intensity for turning on external light 104a (i.e., the external light closest to user 106). Vehicle 102 can then turn on external light 104a at the optimal lighting intensity. In this way, vehicle 102 can make external light 104a illuminate at an intensity that can be based on the type of activity user 106 is likely performing.

[0029] Vehicle 102 can determine the optimal illumination intensity of external light 104a such that the total luminous intensity at the area / zone where user 106 is located (i.e., the sum of the optimal illumination intensity and the ambient light intensity) equals the user's preferred illumination intensity. In this way, vehicle 102 can ensure that user 106 receives the optimal illumination level preferred by user 106 when reading a book. Furthermore, by illuminating external light 104a at the optimal illumination intensity (e.g., a minimum amount of additional light exceeding the ambient light, but not more), vehicle 102 can ensure that external light 104a does not consume unnecessary energy. For example, when the ambient light may be relatively bright (or not too dim), vehicle 102 can illuminate external light 104a at a relatively low illumination intensity, thereby promoting optimization of energy consumption.

[0030] In another aspect, vehicle 102 can seek user feedback (via the vehicle's microphone, user audio and / or gesture commands, etc.) to confirm whether the lighting intensity near user 106 is comfortable or needs adjustment. Vehicle 102 can adjust the optimal lighting intensity of the exterior lights 104a based on user feedback.

[0031] Vehicle 102 can additionally monitor (based on input from sensor units) user behavior, activities being performed by user 106 near vehicle 102, distance of user 106 from external light 104a (and external lights of other vehicles), ambient light intensity, total light intensity in the area / zone where user 106 is located, etc., and can adjust the optimal illumination intensity of external light 104a based on said monitoring. For example, if vehicle 102 determines that user 106 may be using an external light source (e.g., the flashlight or lamp of the user's mobile phone) to project additional light onto a book, vehicle 102 can determine that the light projected by external light 104a may be insufficient for user 106. In response to this determination, vehicle 102 can increase the optimal illumination intensity of external light 104a.

[0032] As another example, if vehicle 102 determines that user 106 is moving away from external light 104a (while performing an activity, such as reading a book) and moving towards external light 104b, vehicle 102 may reduce the illumination associated with external light 104a and may turn on external light 104b with the optimal illumination intensity associated with the distance between user 106 and external light 104b. As yet another example, if vehicle 102 determines that user 106 has changed the activity previously performed by user 106 (e.g., user 106 starts playing a board game or assembling a toy instead of reading a book), vehicle 102 may automatically adjust the optimal illumination intensity of external light 104a based on the new activity type and the corresponding user preference for illumination intensity. As yet another example, if the ambient light intensity changes, vehicle 102 may adjust the optimal illumination intensity of external light 104a.

[0033] In another aspect, vehicle 102 can adjust the sampling rate of the sensor units recording or polling the aforementioned parameters based on several factors, including but not limited to time of day, ambient weather conditions, activity type, and the amount or extent of user movement near vehicle 102 during the activity. For example, vehicle 102 can reduce the sampling rate associated with the ambient light intensity sensor during the daytime (e.g., near midday), since the ambient light intensity is not expected to change drastically in a short period of time at this time. As another example, if user 106 is repairing a fence or performing any other activity near vehicle 102 that may take longer to complete, and therefore it is not expected that user 106 may change activities soon or move quickly and / or substantially in a short period of time, vehicle 102 can reduce the sampling rate or image capture rate associated with the vehicle's external cameras.

[0034] By adjusting (e.g., reducing) the sampling rate associated with one or more sensors as described above, vehicle 102 can further save energy that would otherwise be used to unnecessarily monitor user 106, activities, environmental conditions, and / or the like at a higher sampling rate.

[0035] In addition, to further optimize vehicle energy consumption and enhance user convenience, vehicle 102 can balance power consumption between external light operation features and other vehicle loads, or allow user 106 to balance power consumption between different vehicle loads (including external light 104). In this case, vehicle 102 can first determine a preferred proportion of vehicle battery energy that can be used to illuminate external light 104a (and / or external lights of other vehicles), and then output an alarm notification to user 106 if the actual utilization rate of battery energy used for said external light operation exceeds the preferred proportion. For example, if illuminating one or more external lights 104 for the type of activity being performed by user 106 consumes 40% of the vehicle's battery energy and the preferred proportion of external light activation features is less than 30%, vehicle 102 can output an alarm notification. In this case, in response to seeing / hearing the alarm notification, user 106 can perform one or more remedial actions (e.g., turning off external light 104, changing activities, starting the vehicle engine to charge the battery, etc. if vehicle 102 is an ICE vehicle), or can allow vehicle 102 to continue using a higher proportion of battery energy for external light illumination.

[0036] In some respects, vehicle 102 can determine a preferred proportion of vehicle battery energy that can be used to illuminate exterior lights 104a based on user preferences / inputs. In other words, in this case, vehicle 102 can enable user 106 to limit the proportion of battery energy that user 106 expects to be used for exterior light activation / operation features (and / or other vehicle KOLs), or enable user 106 to "balance" the vehicle's battery energy among different vehicle features (including exterior light activation features).

[0037] In other respects, vehicle 102 itself can determine a preferred proportion of vehicle battery energy that can be used to illuminate exterior lights 104a based on one or more parameters. Examples of such parameters include, but are not limited to, historical usage patterns of exterior lights 104, vehicle geographic location, expected vehicle route or navigation path for future trips, current vehicle battery SoC level, current vehicle fuel level, profiles of one or more occupants in vehicle 102, time of day, expected duration of completing an activity that user 106 may be performing, weather conditions in the geographic area where vehicle 102 is located, etc. For example, when the battery SoC level may be low, or when the expected vehicle route for future trips indicates that vehicle 102 may need to travel a long distance, vehicle 102 may determine that a preferred proportion of vehicle battery energy available for illuminating exterior lights 104a should be lower.

[0038] In some respects, in response to determining the preferred proportion of vehicle battery energy as described above, vehicle 102 can adjust the optimal illumination intensity of external lights 104a according to the preferred proportion to optimize vehicle energy consumption.

[0039] The following is combined with Figure 2 Describe the details of another vehicle, 102.

[0040] Vehicle 102 shall implement and / or perform the operations described herein in accordance with the owner's manual and safety guidelines. Furthermore, any actions taken by user 106 based on notifications provided by vehicle 102 shall comply with all rules specific to the location and operation of vehicle 102 (e.g., federal, state, national, city, etc.). Notifications provided by vehicle 102 shall be considered advice and shall be followed only in accordance with any rules specific to the location and operation of vehicle 102.

[0041] Figure 2 A block diagram of a system 200 for controlling the operation of an external light 104, according to this disclosure, is depicted. In the description... Figure 2 At that time, will refer to Figure 3 and Figure 4 .

[0042] System 200 may include vehicles 102, one or more servers 202 (or server 204), and user devices 204 that can be communicatively coupled to each other via one or more networks 206. User devices 204 may be associated with user 106 and may include, for example, mobile phones, computers, laptops, tablets, smartwatches, wireless tags, or any other device with communication capabilities. Servers 202 may be part of a cloud-based computing infrastructure and may be associated with and / or include a Telematics Service Delivery Network (SDN), which delivers services to vehicles 102 and other vehicles that may be part of a vehicle fleet. Figure 2 (Not shown in the image) provides digital data services.

[0043] In another aspect, server 202 can store facial details, fingerprint details, and / or other biometric authentication details of multiple authorized users (including user 106) associated with vehicle 102. Server 202 can also store user profiles associated with multiple authorized users. (As described above...) Figure 1 As described, the user profile may include user preferences associated with user-preferred lighting intensities for different types of activities that the corresponding user may perform near vehicle 102. Specifically, the user profile may include a mapping between user-preferred lighting intensities and different types of activities that the corresponding user may perform near vehicle 102.

[0044] Server 202 may also store information associated with the historical usage patterns of external lights 104, expected vehicle routes for future trips (determined based on user input or historical vehicle driving patterns), etc.

[0045] Server 202 may transmit the aforementioned details, information, user profiles, etc. to vehicle 102 at a predefined frequency or when vehicle 102 sends a request to server 202 for such information. In other aspects, server 202 may be associated with a weather monitoring company and may transmit real-time and expected future weather conditions (e.g., ambient temperature, expected sunset or sunrise time, probability of rain, snow, cloudy weather, etc.) to vehicle 102 at a predefined frequency.

[0046] Network 206 illustrates an example communication infrastructure in which connected devices discussed in various embodiments of this disclosure may communicate. Network 206 may be and / or include the Internet, a private network, a public network, or other configurations operating using any one or more known communication protocols such as Transmission Control Protocol / Internet Protocol (TCP / IP), Bluetooth, etc. ® Bluetooth Low Energy (BLE), Wi-Fi based on the IEEE standard 802.11, Ultra Wideband (UWB), and cellular technologies such as Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), High-Speed ​​Packet Access (HSPDA), Long Term Evolution (LTE), Global System for Mobile Communications (GSM), and 5G, to name just a few.

[0047] Vehicle 102 may include multiple units, including but not limited to vehicle computer 208, vehicle control unit (VCU) 210, and lighting control unit 212 (or unit 212). VCU 210 may include multiple electronic control units (ECUs) 214 that communicate with vehicle computer 208.

[0048] In some respects, according to this disclosure, the vehicle computer 208 and / or unit 212 can be installed anywhere within the vehicle 102. Additionally, the vehicle computer 208 can operate as a functional part of unit 212. The vehicle computer 208 can be or include an electronic vehicle controller having one or more processors 216 and memory 218. Furthermore, unit 212 can be separate from the vehicle computer 208 (e.g., Figure 2 (as shown), or it can be integrated as part of the automotive computer 208.

[0049] Processor 216 can communicate with one or more memory devices (e.g., memory 218 and / or memory) of a corresponding computing system. Figure 2The processor 216 may communicate with one or more external databases (not shown). The processor 216 may utilize the memory 218 to store programs and / or data in the form of code to execute aspects of this disclosure. The memory 218 may be a non-transitory computer-readable medium or memory that stores lamp control program code. The memory 218 may include any or a combination of volatile memory elements (e.g., dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), etc.) and may include any one or more non-volatile memory elements (e.g., erasable programmable read-only memory (EPROM), flash memory, electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), etc.).

[0050] According to some aspects, VCU 210 may share a power bus with vehicle computer 208 and may be configured and / or programmed to coordinate data between the systems of vehicle 102, a connected server (e.g., server 202), and other vehicles operating as part of a vehicle fleet. VCU 210 may include or communicate with any combination of ECUs 214, such as Body Control Module (BCM) 220, Engine Control Module (ECM) 222, Transmission Control Module (TCM) 224, Telematics Control Unit (TCU) 226, Driver Assistance Technology (DAT) Controller 228, etc.

[0051] VCU 210 may also include and / or communicate with a vehicle perception system (VPS) 230, which has connectivity with and / or controls one or more vehicle sensing systems 232 (or “sensor units”). The vehicle sensing system 232 may include one or more vehicle sensors, including but not limited to radio detection and ranging (radar) sensors, seating area latch sensors, seating area sensors, light detection and ranging (LiDAR) sensors, door sensors, proximity sensors, temperature sensors, tilt and motion sensors, wheel sensors, ambient weather sensors, ambient light sensors, vehicle interior and exterior cameras, one or more rain sensors, humidity sensors, tire pressure sensors, ultrasonic sensors, etc., configured to detect and locate objects inside and outside the vehicle 102 using radio waves. In some aspects, the vehicle sensing system 232 may capture input (e.g., images) associated with the vehicle's surrounding environment. For example, an exterior vehicle camera may capture an image of the user when the user 106 may be near the vehicle 102 and / or performing an activity near the vehicle 102.

[0052] In some respects, VCU 210 can control vehicle operation aspects and implement one or more instruction sets received from user equipment 204, one or more instruction sets stored in memory 218, including instructions that operate as part of unit 212.

[0053] TCU 226 can be configured and / or programmed to provide vehicle connectivity to wireless computing systems on and outside the vehicle 102, and may include a navigation (NAV) receiver 234 for receiving and processing GPS signals, a BLE module (BLEM) 236, a Wi-Fi transceiver, a UWB transceiver, and / or other wireless transceivers that can be configured for wireless communication (including cellular communication) between the vehicle 102 and other systems (e.g., user device 204, key fob, NFC device, etc.), computers, and modules. Figure 2 (Not shown in the image). NAV receiver 234 can determine the real-time vehicle location. TCU 226 can communicate with ECU 214 via bus.

[0054] In some aspects, vehicle 102 may also include one or more BLE transceivers, mobile phone-as-a-key transceivers, and / or other similar transceivers, which may be part of the vehicle's sensor unit and may facilitate vehicle 102 in determining whether a user (e.g., user 106) near vehicle 102 is an authorized or unauthorized user. Specifically, the aforementioned transceivers may enable vehicle 102 to determine whether a user device (e.g., user device 204) carried by user 106 is pre-synchronized with or pre-registered with vehicle 102. Vehicle 102 may determine that user 106 is an authorized user when input from the transceiver instructs user device 204 to pre-register with vehicle 102, and may determine that user 106 is an unauthorized user when input from the transceiver instructs user device 204 not to pre-register with vehicle 102.

[0055] In some aspects, when pre-registered user devices may be within a predefined range of vehicle 102, thereby indicating to vehicle 102 that these user devices are approaching vehicle 102, the aforementioned transceiver can automatically connect to these user devices via BLE, UWB, NFC, etc. Therefore, when user 106 carrying user device 204 is present near vehicle 102, vehicle 102 can check the input from the transceiver to determine whether the transceiver is communicatively coupled to user device 204. In some aspects, when the input from the transceiver indicates that the transceiver is not communicatively coupled to user device 204, vehicle 102 can determine that user 106 may be an unauthorized user. On the other hand, when the input from the transceiver indicates that the transceiver is communicatively coupled to user device 204, vehicle 102 can determine that user 106 may be an authorized user.

[0056] ECU 214 can control various aspects of vehicle operation and communication using inputs from the human driver, inputs from the autonomous vehicle controller, unit 212, and / or wireless signal inputs received from other connected devices (such as user device 204, server 202, etc.) via wireless connection.

[0057] The BCM 220 typically integrates sensors, vehicle performance indicators, and variable reactors associated with vehicle systems. It may also include processor-based power distribution circuitry that controls functions associated with the vehicle body, such as lights (including exterior lights 104), windows, safety devices, cameras, fans, headlights, audio systems, speakers, wipers, door locks and entry controls, mirrors, various comfort controls, housings, etc. The BCM 220 can also operate as a gateway for bus and network interfaces to communicate with remote ECUs ( Figure 2 Interact with (not shown in the image).

[0058] The DAT controller 228 provides Level 1 to Level 3 automated driving and driver assistance functionality, which may include features such as active parking assist, vehicle reversing assist, and adaptive cruise control. The DAT controller 228 also provides various aspects of user and environmental inputs that can be used for user authentication.

[0059] In some respects, the vehicle computer 208 may connect to the infotainment system 238 (or the vehicle human-machine interface (HMI) 238). The infotainment system 238 may include a touchscreen interface portion and may include voice recognition features, and the ability to identify users based on facial recognition, voice recognition, fingerprint recognition, or other biometric methods. In other respects, the infotainment system 238 may also receive user commands / inputs via the touchscreen interface portion, and / or display notifications / recommendations, navigation maps, etc., on the touchscreen interface portion.

[0060] The computing system architecture of the automotive computer 208, VCU 210, and / or unit 212 may omit certain computing modules. This should be easily understood. Figure 2 The computing environment depicted herein is an example of possible implementations according to this disclosure and should therefore not be considered limiting or exclusive.

[0061] Depending on some aspects, unit 212 may be integrated with and / or performed as part of ECU 214. Whether integrated with vehicle computer 208 or ECU 214, or operating as a stand-alone computing system in vehicle 102, unit 212 may include transceiver 240, processor 242, and computer-readable storage 244.

[0062] Transceiver 240 can receive information / input from one or more external devices or systems (e.g., user device 204, server 202, etc.) via network 206. For example, transceiver 240 can receive user biometric identification / authentication details, user profiles, and / or the aforementioned information from server 202 (and / or user device 204) via network 206. Furthermore, transceiver 240 can transmit notifications to external devices or systems. Additionally, transceiver 240 can receive information / input from components of vehicle 102 (such as infotainment system 238, VCU 210, etc.). Furthermore, transceiver 240 can transmit notification / command signals to components of vehicle 102 (such as VCU 210, infotainment system 238, BCM 220, etc.).

[0063] Processor 242 and memory 244 may be the same as or similar to processor 216 and memory 218, respectively. In some aspects, processor 242 may utilize memory 244 to store programs in code form and / or store data for execution of aspects according to this disclosure. Memory 244 may be a non-transitory computer-readable medium or memory storing lighting control program code. In some aspects, memory 244 may store details, information, user profiles, etc., obtained by vehicle 102 from server 202 (and / or user device 204).

[0064] In some respects, processor 242 may be an AI / ML-based processor that can determine the types of activities that user 106 may be performing near vehicle 102 based on user images captured by external cameras of the vehicle (from multiple different activity types).

[0065] In operation, the processor 242 may obtain input from the vehicle sensing system 232 and / or the aforementioned transceiver, and based on the obtained input, determine that the user 106 may be near the vehicle 102 and performing an activity (e.g., reading a book, etc.). Figure 1(As shown). In response to determining the presence of a user near vehicle 102 and determining that user 106 is performing an activity, processor 242 can determine whether user 106 is an authorized user or an unauthorized user based on the obtained input. In some aspects, processor 242 can correlate facial and / or other biometric details of the user determined from user images captured by external cameras of the vehicle with biometric details of authorized users of the vehicle (obtained by vehicle 102 from server 202) to determine whether user 106 is an authorized user or an unauthorized user. For example, when the facial and / or other biometric details of the user determined from user images captured by external cameras of the vehicle match the biometric details of authorized users of the vehicle, processor 242 can determine that user 106 is likely an authorized user. On the other hand, when the facial and / or other biometric details of the user determined from user images captured by external cameras of the vehicle do not match the biometric details of any authorized user of the vehicle, processor 242 can determine that user 106 is likely an unauthorized user.

[0066] In another aspect, as described above, when an input indication received from a BLE transceiver, mobile phone / key transceiver, etc., is communicatively coupled between the user device 204 carried by user 106 and the transceiver (indicating that the user device 204 pre-registers with vehicle 102), the processor 242 can determine that user 106 may be an authorized user. On the other hand, when an input indication received from the transceiver is not communicatively coupled between the user device 204 carried by user 106 and the transceiver (indicating that the user device 204 has not pre-registered with vehicle 102), the processor 242 can determine that user 106 may be an unauthorized user.

[0067] In response to determining that user 106 may be an unauthorized user, processor 242 may not illuminate any external lights 104 and may not perform any of the steps described below. On the other hand, in response to determining that user 106 may be an authorized user, processor 242 may determine the external light (e.g., external light 104a) that may be closest to user 106 based on input obtained from vehicle sensing system 232 and / or transceiver.

[0068] In response to determining that user 106 may be performing an activity near exterior light 104a and that user 106 is an authorized user as described above, processor 242 may execute one or more AI / ML-based image processing algorithms that may be pre-stored in memory 244 to determine the type of activity associated with the activity being performed by user 106 based on user images captured by the vehicle's exterior camera (or input obtained from vehicle sensing system 232). For example, processor 242 may determine that user 106 is reading a book (as the activity type) based on user images captured by the vehicle's exterior camera (which may be a low-power camera).

[0069] In response to determining the type of activity, processor 242 can determine the ambient light intensity near user 106 based on input obtained from vehicle sensing system 232 (e.g., based on input obtained from ambient light sensors, cameras, etc.). Ambient light can be attributed to other light sources, such as infrastructure light, sunlight, moonlight, etc. Processor 242 can then determine the optimal illumination intensity of external light 104a based on the determined activity type and ambient light intensity. As an example, when the ambient light intensity may be low (indicating a dark surrounding environment), processor 242 may determine the optimal illumination intensity of external light 104a to be high. As another example, when the ambient light intensity is relatively high, processor 242 may determine the optimal illumination intensity of external light 104a to be low. As yet another example, when user 106 may be reading a book, performing fine assembly, or performing any task that may require higher illumination, processor 242 may determine the optimal illumination intensity of external light 104a to be high. As another example, when user 106 might be performing some rough parts sorting, moving items from one location to another near vehicle 102, or performing any task that might require relatively low lighting, processor 242 can determine that the optimal lighting intensity of external light 104a is low. It is understood that when external light 104a is illuminated at a lower light intensity, the vehicle's energy consumption can be reduced. Therefore, by determining the lighting intensity of external light 104a based on the activity type and ambient lighting intensity, processor 242 can optimize the vehicle's energy consumption required to operate external light 104a.

[0070] In some aspects, processor 242 may use a lookup table (which may be pre-stored in memory 244) that may include a mapping of multiple activity types and required lighting intensities to determine the optimal lighting intensity of external light 104a based on the determined activity type and ambient light intensity. In some aspects, the required lighting intensity for the determined activity type may be the sum of the ambient light intensity and the optimal lighting intensity of external light 104a. Therefore, processor 242 may subtract the ambient light intensity from the required lighting intensity for the determined activity type (as identified from the lookup table) to determine the optimal lighting intensity of external light 104a. In response to determining the optimal lighting intensity as described above, processor 242 may illuminate external light 104a at the optimal lighting intensity via BCM 220.

[0071] Alternatively, in response to determining the activity type, processor 242 can retrieve / obtain a user profile associated with user 106 from memory 244. Processor 242 can also determine, based on the user profile, a user preference for the desired lighting intensity associated with the activity type. User preferences can indicate how bright / dim the external light 104 might be expected by user 106, based on the activity / action user 106 might be performing. For example, when user 106 is reading a book near vehicle 102, processor 242 can determine the user's preference for the desired lighting intensity as 500 lux (or any other lighting intensity value) based on the user profile.

[0072] In response to determining a user's preference for desired lighting intensity associated with an activity type (e.g., reading a book), processor 242 can determine the optimal lighting intensity of external light 104a based on the user's preference / desired lighting intensity and ambient light intensity. For example, processor 242 can subtract the ambient light intensity from the desired lighting intensity to determine the optimal lighting intensity of external light 104a. Processor 242 can then illuminate external light 104a at the determined optimal lighting intensity via BCM 220.

[0073] In another aspect, in response to illuminating the external light 104a at an optimal intensity, the processor 242 can obtain user feedback, audio commands, gesture commands, etc., from the user via the user device 204 regarding the intensity of illumination that the external light 104a can provide. The user feedback may indicate whether the user 106 is satisfied with the illumination level of the external light 104a, or whether they desire more or less illumination. The processor 242 can adjust the optimal illumination intensity based on the user feedback. For example, when user feedback indicates that the user 106 desires a higher (or lower) illumination intensity, the processor 242 can increase (or decrease) the optimal illumination intensity. The processor 242 can then illuminate the external light 104a at the adjusted intensity. In some aspects, the processor 242 can also turn off the external light 104a when user feedback indicates that the user 106 does not require illumination from the external light 104a.

[0074] In some respects, processor 242 may output a request (via the vehicle's speakers, user device 204, etc.) to seek user feedback regarding the illumination intensity of exterior lights 104a, and may obtain such user feedback from user 106 in response to outputting the request. In other respects, processor 242 may obtain user feedback without outputting a request.

[0075] In an exemplary aspect, processor 242 may store user feedback in a user profile associated with user 106, and may use the feedback to determine the optimal illumination intensity of exterior light 104 when user 106 performs the same or similar activity again near vehicle 102 in the future. In this way, processor 242 may determine the optimal illumination intensity of exterior light 104a (and / or other vehicle exterior lights) based on historical user feedback regarding the desired illumination intensity associated with the type of activity that user 106 may be performing.

[0076] The processor 242 can also continuously monitor, at a predefined sampling rate, the types of activities that user 106 may perform near vehicle 102, the ambient light intensity near user 106 when user 106 performs an activity, user behavior, user movement, and the total light intensity in the area around user 106 when user 106 performs an activity (which may be the sum of ambient light intensity and the light intensity that external light 104a can illuminate), based on the monitoring of the above parameters. The processor 242 can adjust the optimal illumination intensity and / or the angle of external light 104a (or the illumination angle of external light 104a) based on the monitoring of the above parameters.

[0077] In one exemplary aspect, processor 242 can adjust the optimal illumination intensity that external light 104a can provide when the activity type and / or ambient light intensity changes. For example, when ambient light intensity decreases (e.g., due to cloud cover), processor 242 can adjust (e.g., increase) the optimal illumination intensity of external light 104a. As another example, when a user moves to another location where ambient light intensity may be lower (while performing the same or different activities), processor 242 can adjust (e.g., increase) the optimal illumination intensity of external light 104a. In some aspects, as ambient light decreases (e.g., during sunset or when the intensity of ambient light decreases or is turned off, etc.), processor 242 can intelligently reduce the light intensity of external light 104a as the user's eye adjusts to adapt to the change in light, still allowing visibility, but adjusting downwards because higher intensity is not needed over time based on the light source angle and the distance of external light 104a relative to the work position / user 106. In this case, processor 242 can calculate the duration sensitivity associated with the decrease in ambient light to determine the required additional light amount (i.e., the light intensity of external light 104a).

[0078] As another example, when user 106 begins to perform a different activity (e.g., something other than reading a book), processor 242 can adjust the illumination intensity of external light 104a. In this case, the adjusted illumination intensity of external light 104a can be based on the different (new) activity.

[0079] In another exemplary aspect, processor 242 may adjust the optimal illumination intensity and / or angle of external light 104a based on detected user movement, user behavior, and / or the total light intensity in the area surrounding user 106. For example, when processor 242 determines that user 106 may be moving away from vehicle 102, processor 242 may adjust (e.g., reduce) the optimal illumination intensity of external light 104a. As another example, when processor 242 determines that user 106 may be walking around vehicle 102 and talking to a friend, processor 242 may adjust (e.g., slightly reduce) the optimal illumination intensity of external light 104a and / or adjust (e.g., change) the angle of external light 104a. In this way, processor 242 may adjust the optimal illumination intensity and / or angle of external light 104a based on the “background” of the situation associated with user 106 and vehicle 102.

[0080] As another example, when processor 242 determines, based on detected user behavior, that user 106 may be performing an activity with difficulty under the illumination intensity of external light 104a, processor 242 may adjust (e.g., increase) the optimal illumination intensity of external light 104a and / or adjust (e.g., change) the angle of external light 104a. For example, when processor 242 determines (e.g., based on user images captured by a vehicle exterior camera) that user 106 may be using an external light source (e.g., a flashlight or lamp associated with user device 204, such as...) while performing an activity (e.g., reading a book). Figure 3 When enhancing lighting (as shown), processor 242 can adjust (e.g., increase) the optimal lighting intensity of external light 104a. In this case, by automatically increasing the lighting intensity of external light 104a, processor 242 can enhance the lighting around user 106, thereby enhancing user convenience.

[0081] As yet another example, when processor 242 determines (e.g., based on user images captured by an external camera of the vehicle) that user 106 may be trying to focus on something or read fine letters (e.g., on tools / paint / accessories / equipment), processor 242 may adjust (e.g., increase) the optimal illumination intensity of external light 104a. In this case, processor 242 may increase the illumination intensity of external light 104a when user 106 may be focusing to read fine letters, and may decrease the illumination intensity again when user 106 looks away and stops reading, thereby ensuring that external light 104a does not unnecessarily operate at a higher illumination intensity when it may not be needed (thus optimizing energy consumption).

[0082] As yet another example, when processor 242 determines (e.g., based on user images captured by vehicle exterior cameras) that user 106 may be moving near vehicle 102 while performing an activity, processor 242 may adjust the angle of exterior lights 104a, actuate / illuminate different exterior lights 104 and / or recommend optimal work location to user 106 near vehicle 102. Figure 4 An exemplary scenario of this situation is depicted. In this scenario, when the activity involves user 106 moving item 402 (e.g., tools, plants, etc.) from a first location 404 near vehicle 102 to a second location 406, processor 242 can determine, based on images obtained from an external camera, that user 106 may be moving away from external light 104a and towards external light 104b while performing the activity. In response to this determination, processor 242 can adjust (e.g., reduce) the illumination intensity of external light 104a based on the distance between user 106 and external light 104a. Furthermore, when user 106 moves towards external light 104b, processor 242 can determine a secondary optimal illumination intensity of external light 104b based on the activity type (i.e., moving an item) and the distance between user 106 and external light 104b. Processor 242 can then illuminate external light 104b at the determined secondary optimal illumination intensity. In this way, the processor 242 can ensure that the user 106 always receives sufficient lighting when the user 106 moves from the first position 404 to the second position 406, while gradually reducing the illumination of the external lights 104a, thereby saving vehicle energy.

[0083] The processor 242 can additionally identify shadow effects or shadows near the user 106 based on images captured by the vehicle's external cameras, and only illuminate those external lights 104 that eliminate shadow effects, thereby illuminating the workspace used by the user 106 for their activities, while keeping all other external lights off. In this case, the processor 242 can illuminate two external lights 104 at a lower energy level (e.g., with lower illumination intensity) than one external light at a high level of illumination. With reduced shadow effects, visibility can be improved for more localized and finer tasks, thus enhancing user convenience.

[0084] Processor 242 can further induce autonomous vehicle movement based on user behavior, lighting intensity in the area surrounding user 106, ambient light intensity, etc., to obtain a better lighting perspective. For example, processor 242 can induce such vehicle movement when it determines, based on the type of activity and the possible position of user 106 relative to external headlights 104, that moving vehicle 102 a few inches (e.g., to the left, right, forward, or backward) would enable external headlights 104 to provide better illumination to user 106.

[0085] In some respects, processor 242 can perform the steps described above (e.g., adjusting the illumination intensity and / or angle of external lights 104a (or other external lights), causing vehicle movement, etc.) to ensure that the external lights project / provide a minimum amount of additional light on top of the ambient light, enabling user 106 to easily complete activities while optimizing vehicle energy consumption. Processor 242 also monitors user movement near each side / section of vehicle 102 and activates or deactivates external lights 104 accordingly based on user movement near each side / section of vehicle.

[0086] Furthermore, as described above, the processor 242 can continuously monitor parameters associated with user 106 (e.g., user movement), activities, ambient lighting conditions, etc., at a predefined sampling rate based on input obtained from the vehicle sensing system 232 and / or the aforementioned transceiver. In some aspects, to further optimize vehicle energy consumption, the processor 242 can adjust the sampling or polling rate (i.e., the rate at which data is acquired / captured) of one or more sensors associated with the vehicle sensing system 232 based on the time of day, ambient weather conditions, the type of activity being performed by user 106, the amount of user movement within a predefined duration, etc. For example, when the current time may be closer to noon, the processor 242 can reduce the sampling rate associated with the ambient light sensor (thus saving vehicle energy) because ambient light is not expected to change drastically at noon. As another example, when user 106 may be performing fence maintenance or may spend a significant amount of time completing it, and therefore the task / activity type may not change rapidly (therefore, the processor 242 may not need to track changes in activity type too frequently), the processor 242 can reduce the sampling rate associated with external cameras (thus saving vehicle energy).

[0087] As yet another example, when detected user movement may be low, processor 242 can reduce the sampling rate associated with the external camera (thus saving vehicle energy). As yet another example, if the activity requires handling work, such as moving large objects, processor 242 can reduce the intensity of any "task-specific" lighting and compensate with higher sensor tracking to allow lighting to follow the work that user 106 may be performing.

[0088] In addition, to further optimize vehicle energy consumption, processor 242 can enable user 106 to balance vehicle energy consumption for different vehicle characteristics (including the illumination of external lights 104), or can itself balance vehicle energy consumption for different vehicle characteristics, so that external lights 104 do not unnecessarily consume a large proportion of vehicle battery energy. In this case, processor 242 can first determine a preferred proportion or percentage of vehicle battery energy available for illuminating external lights 104a (and / or other external lights 104) based on one or more parameters, including but not limited to the historical usage patterns of external lights 104, vehicle geographic location, expected vehicle travel routes for future trips (which may be provided by user 106, obtained from server 202, or determined based on the vehicle's historical driving patterns), vehicle battery SoC level, vehicle fuel level, profiles of one or more occupants in vehicle 102, time of day, user preference for proportion / percentage, expected duration of completing activities that user 106 may be performing (which may be communicated by user 106 to vehicle 102 via user device 204 / HMI), weather conditions in the geographic area where vehicle 102 may be located, etc.

[0089] As an example, when vehicle 102 may have sufficient fuel or the SoC level may be high (e.g., above a threshold level), processor 242 can identify a high proportion (e.g., 40% or more) of the vehicle battery energy used for external light 104 illumination. As another example, when the SoC level may be low, processor 242 can identify a low proportion (e.g., 20% or less) of the vehicle battery energy used for external light 104 illumination. As yet another example, when vehicle 102 is expected to travel a long distance in the future and therefore may require a sufficient SoC level in the vehicle battery, processor 242 can identify a low proportion (e.g., 20% or less) of the vehicle battery energy used for external light 104 illumination. As yet another example, when user 106 is expected to perform an activity for an extended period (e.g., above a predefined duration threshold), processor 242 can identify a low proportion (e.g., 20% or less) of the vehicle battery energy used for external light 104 illumination.

[0090] In response to determining a preferred proportion or percentage of vehicle battery energy that can be used to illuminate the exterior lights 104, the processor 242 can determine, based on input obtained from the VCU 210, the actual proportion of vehicle energy used to illuminate the exterior lights 104 at its corresponding optimal lighting intensity. The processor 242 can also compare the actual proportion with the preferred proportion and output an alarm notification (via user device 204, infotainment system 238, vehicle speakers, etc.) when the actual proportion may be greater than the preferred proportion. In this case, in response to seeing / hearing the alarm notification, the user 106 can perform the actions described above. Figure 1 One or more remedial actions as described.

[0091] In some respects, the processor 242 may further determine and / or adjust (e.g., increase or decrease) the optimal illumination intensity of the external lights 104a (and / or other external lights 104) based on a determined preferred ratio / percentage to further optimize the vehicle’s energy consumption.

[0092] In an additional aspect, if vehicle 102 is part of a fleet of vehicles that can be parked adjacent to each other, vehicle 102 can monitor the lighting conditions of all vehicles within a predefined distance of vehicle 102, such that only a single vehicle (e.g., vehicle 102) performs a lighting assessment in response to the user's requirements. In this case, the vehicle 102 performing these assessments can be switched on a time-based basis to distribute energy requirements fairly among all vehicles.

[0093] Figure 5 A flowchart depicts an exemplary method 500 for controlling the operation of an external light 104 according to the present disclosure. Further description can be made with reference to the preceding figures. Figure 5 The following process is exemplary and is not limited to the steps described below. Furthermore, alternative embodiments may include more or fewer steps than shown or described herein, and may include these steps in a different order than that described in the following example embodiments.

[0094] Method 500 begins at step 502. At step 504, method 500 may include the processor 242 determining, based on input obtained from the vehicle sensing system 232 and / or the aforementioned transceiver, that user 106 may be performing an activity near exterior light 104a. At step 506, method 500 may include, in response to determining that user 106 is performing an activity, the processor 242 determining the type of activity based on the obtained input.

[0095] At step 508, method 500 may include processor 242 determining the optimal illumination intensity of external light 104a based on activity type, as described above. At step 510, method 500 may include processor 242 illuminating external light 104a at the optimal illumination intensity.

[0096] At step 512, method 500 stops.

[0097] In the foregoing disclosure, reference has been made to the accompanying drawings, which form a part of the foregoing disclosure, illustrating specific embodiments in which the present disclosure may be practiced. It should be understood that other embodiments and structural changes may be utilized without departing from the scope of the present disclosure. References to “an embodiment,” “embodiment,” “example embodiment,” etc., in this specification indicate that the described embodiment may include specific features, structures, or characteristics, but each embodiment may not necessarily include said specific features, structures, or characteristics. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when features, structures, or characteristics are described in connection with embodiments, those skilled in the art will recognize such features, structures, or characteristics in conjunction with other embodiments, whether explicitly described or not.

[0098] Furthermore, where appropriate, the functions described herein may be performed by one or more of the following: hardware, software, firmware, digital components, or analog components. For example, one or more application-specific integrated circuits (ASICs) may be programmed to perform one or more of the systems and programs described herein. Certain terms are used throughout the specification and claims to refer to specific system components. As those skilled in the art will appreciate, components may be referred to by different names. This document is not intended to distinguish between components with different names but identical functions.

[0099] It should also be understood that the term "example" as used herein is intended to be non-exclusive and non-restrictive in nature. More specifically, the term "example" as used herein refers to one of several examples, and it should be understood that there is no undue emphasis or preference on the particular example described.

[0100] Computer-readable media (also known as processor-readable media) include any non-transitory (e.g., tangible) medium that contributes to providing data (e.g., instructions) that can be read by a computer (e.g., by the computer's processor). Such media can take many forms, including but not limited to non-volatile and volatile media. Computing devices may include computer-executable instructions, wherein the instructions can be executed by one or more computing devices (such as those listed above) and stored on a computer-readable medium.

[0101] Regarding the processes, systems, methods, heuristics, etc., described herein, it should be understood that although the steps of such processes, etc., are described as occurring in a certain ordered order, such processes can be practiced by performing the described steps in a different order than that described herein. It should also be understood that some steps may be performed simultaneously, other steps may be added, or some steps described herein may be omitted. In other words, the description of processes herein is provided for the purpose of illustrating various embodiments and should in no way be construed as limiting the claims.

[0102] Therefore, it should be understood that the above description is intended to be illustrative rather than restrictive. Many embodiments and applications beyond the examples provided will become apparent upon reading the above description. The scope should not be determined by reference to the above description, but rather by reference to the appended claims and the full scope of their equivalents. It is anticipated and expected that the techniques discussed herein will evolve in the future, and the disclosed systems and methods will be incorporated into such future embodiments. In conclusion, it should be understood that modifications and changes are possible with this application.

[0103] Unless explicitly indicated otherwise herein, all terms used in the claims are intended to be given their ordinary meaning as understood by one skilled in the art as described herein. Specifically, unless the claims explicitly limit the recitation to the contrary, the use of singular articles such as “a,” “the,” or “the” should be interpreted as one or more of the elements indicated by the recitation. Unless otherwise specifically stated or otherwise understood in the context of use, conditional language such as, in particular, “can,” “may,” “may,” or “may” is generally intended to express that some embodiments may include certain features, elements, and / or steps, while other embodiments may not include certain features, elements, and / or steps. Therefore, such conditional language is generally not intended to imply that one or more embodiments require each feature, element, and / or step in any way.

[0104] According to one embodiment, the processor is further configured to: determine an actual proportion of vehicle energy used to illuminate the first external light at the optimal lighting intensity; compare the actual proportion with the preferred proportion; and output an alarm notification when the actual proportion is greater than the preferred proportion.

[0105] According to one embodiment, the processor is further configured to: monitor user movement based on the input obtained from the sensor unit when the user performs the activity; and adjust the sampling rate associated with the sensor unit based on at least one of: the amount of user movement over a predefined duration and the type of activity.

[0106] According to one embodiment, the sensor unit includes one or more of the following: a proximity sensor or an external camera.

[0107] According to the present invention, a method includes: determining, by a processor, that a user is performing an activity near the exterior lights of a vehicle based on input obtained from a sensor unit; determining, by the processor, an activity type based on the input in response to determining that the user is performing the activity; determining, by the processor, an optimal illumination intensity of the exterior lights based on the activity type; and illuminating the exterior lights by the processor at the optimal illumination intensity.

[0108] According to the present invention, a non-transitory computer-readable storage medium having instructions stored thereon is provided, the instructions causing the processor, when executed by a processor, to: determine, based on input obtained from a sensor unit, that a user is performing an activity near the exterior lights of a vehicle; determine, based on the input, an activity type in response to determining that the user is performing the activity; determine, based on the activity type, an optimal illumination intensity of the exterior lights; and illuminate the exterior lights at the optimal illumination intensity.

Claims

1. A vehicle comprising: A sensor unit configured to capture inputs associated with the vehicle's surrounding environment; First external light; as well as Processor, the processor being configured to: Based on the input obtained from the sensor unit, it is determined that the user is performing an activity near the first external light; In response to determining that the user is performing the activity, the activity type is determined based on the input; The optimal lighting intensity of the first external light is determined based on the activity type. as well as The first external light is illuminated at the optimal lighting intensity.

2. The vehicle of claim 1, wherein the processor is further configured to: In response to determining that the user is performing the activity, the user is determined to be an authorized user based on the input obtained from the sensor unit; and The activity type is determined in response to determining that the user is the authorized user.

3. The vehicle of claim 2, wherein the processor is further configured to: The ambient light intensity near the user is determined based on the input obtained from the sensor unit; and The optimal lighting intensity is determined based on the ambient light intensity.

4. The vehicle of claim 3, further comprising a memory configured to store user profiles associated with a plurality of authorized users, and wherein the processor is further configured to: In response to determining that the user is the authorized user, a user profile associated with the user is obtained from the memory; The user profile is used to determine the user's preference for the desired lighting intensity associated with the activity type; as well as The optimal lighting intensity is determined based on the user preference and the ambient light intensity.

5. The vehicle of claim 1, wherein the processor is further configured to: Obtain user feedback from the user regarding the optimal lighting intensity; and The optimal lighting intensity is adjusted based on the user feedback.

6. The vehicle of claim 5, wherein the processor is further configured to: Output a request to obtain the user's feedback; and The user feedback is obtained in response to the output of the request.

7. The vehicle of claim 5, wherein the processor obtains the user feedback via at least one of: a user device, an audio command, or a gesture command.

8. The vehicle of claim 1, wherein the processor is further configured to determine the optimal lighting intensity based on historical user feedback on the desired lighting intensity associated with the activity type.

9. The vehicle of claim 1, wherein the processor is further configured to: When the user performs the activity, at least one of the activity type or the ambient light intensity near the user is monitored at a predefined sampling rate based on the input obtained from the sensor unit; and When at least one of the activity type or the ambient light intensity changes, the optimal lighting intensity is adjusted.

10. The vehicle of claim 9, wherein the predefined sampling rate is based on at least one of the following: time of day, ambient weather conditions, or the type of activity.

11. The vehicle of claim 1, wherein the processor is further configured to: When the user performs the activity, at least one of the user's behavior or the lighting intensity in the area surrounding the user is monitored based on the input obtained from the sensor unit; and The angle of the first external light or the optimal lighting intensity is adjusted based on the user's behavior or the lighting intensity in the area surrounding the user.

12. The vehicle of claim 11, wherein the processor is further configured to induce autonomous vehicle movement based on the user's behavior or the lighting intensity in the area surrounding the user.

13. The vehicle of claim 1, further comprising a second external light, wherein the processor is further configured to: Based on the input obtained from the sensor unit, it is determined that the user is moving away from the first external light and towards the second external light; The optimal lighting intensity is adjusted based on the distance between the user and the first external light; The secondary optimal lighting intensity of the second external light is determined based on the activity type and the distance between the user and the second external light; as well as The second external light is illuminated at the secondary optimal lighting intensity.

14. The vehicle of claim 1, wherein the processor is further configured to determine a preferred proportion of vehicle energy for illuminating the first external light based on one or more parameters, wherein the one or more parameters include at least one of: historical usage patterns of the vehicle's external lights, vehicle geographic location, expected vehicle route, vehicle battery state of charge (SoC), vehicle fuel level, profiles of one or more occupants in the vehicle, time of day, user preferences, expected duration of the activity, or weather conditions in the geographic area where the vehicle is located.

15. The vehicle of claim 14, wherein the processor is further configured to determine the optimal lighting intensity based on the preferred ratio.

Images