System and method for assisted real-time control of vehicle headlight

This disclosure relates generally to controlling headlights and more particularly to a system and method for automatically controlling vehicle headlights using image processing techniques.In one embodiment, a Headlight Controlling Device for automatically controlling vehicle headlights is disclosed. The Headlight Controlling Device comprises a processor and a memory communicatively coupled to the processor. The memory stores processor instructions, which, on execution, causes the processor to collect at least one of vehicle information, vehicle speed, road information, area information, weather information or a multimedia object associated with a forward path of the vehicle. The processor further determines a current light intensity distribution of the vehicle headlight based on the multimedia object. The processor further compares the current light intensity distribution of the vehicle headlight with an optimal light intensity distribution, wherein the optimal light intensity distribution is retrieved from a database based on at least one of the vehicle information, the vehicle speed, the road information, the area information or the weather information. The processor further controls the vehicle headlight based on the comparison.

PRIORITY CLAIM

This U.S. patent application claims priority under 35 U.S.C. §119 to Indian Application No. 201641005527, filed Feb. 17, 2016. The aforementioned applications are incorporated herein by reference in their entirety.

TECHNICAL FIELD

This disclosure relates generally to controlling headlights of a vehicle and more particularly to a system and method for automatically controlling vehicle headlights using image processing techniques.

BACKGROUND

Vehicle headlights are typically used to improve visibility, when the visibility conditions are low due to fog, rain, smoke, darkness and the like. Nowadays, vehicles provide a large variety of headlights. Some of these headlights may include fog lights, driving lights, off-road lights, bumper lights, multiple bulb headlights, high beam lights, low beam lights, etc. Low beam lights generally provide less field of illumination, when compared to high beam lights and hence are ideal for use on urban roads with street lights or in heavy traffic conditions. On the other hand, high beam lights may typically be used in rural roads or poorly lit roads or on highways or freeways when there is no oncoming traffic.

Currently, vehicle drivers are expected to manually switch between high and low beams and various other configurations of the lights based on instinct and defined guidelines. For example, a driver may have to manually turn on the fog lamps in case the driver experiences fog conditions. In another example, a driver may have to switch the lights from a high beam to a low beam when another vehicle approaches from the opposite side. Failure to do so may cause the driver of the oncoming vehicle to be momentarily blinded which may lead to accidents. The high beam may affect the driver driving ahead as well, because the lights may get reflected through the rear view mirror and the side mirrors of the car ahead.

However, sometimes, drivers might not be aware of which type of light to be used under a particular circumstance. Also, sometimes, drivers might not be able to make a quick judgement in controlling the vehicle headlights. The failure to switch to the appropriate headlights or mode of headlights may lead to unsafe conditions for the driver of the vehicle as well as other vehicles on the road.

SUMMARY

In an embodiment the present disclosure illustrates a method for automatically controlling a vehicle headlight. The method comprises, collecting, by a Headlight Controlling Device, at least one of vehicle information, vehicle speed, road information, area information, weather information or a multimedia object associated with a forward path of a vehicle. The method further comprises, determining, by the Headlight Controlling Device, a current light intensity distribution of the vehicle headlight based on the multimedia object. The method further comprises, comparing, by the Headlight Controlling Device, the current light intensity distribution of the vehicle headlight with an optimal light intensity distribution, wherein the optimal light intensity distribution is retrieved from a database based on at least one of the vehicle information, the vehicle speed, the road information, the area information or the weather information. The method further comprises, controlling, by the Headlight Controlling Device, the vehicle headlight, based on the comparison.

In another embodiment, the present disclosure illustrates a Headlight Controlling Device. The Headlight Controlling Device comprises a processor and a memory communicatively coupled to the processor. The memory stores processor instructions, which, on execution, causes the processor to collect at least one of vehicle information, vehicle speed, road information, area information, weather information or a multimedia object associated with a forward path of the vehicle. The processor further determines a current light intensity distribution of the vehicle headlight based on the multimedia object. The processor further compares the current light intensity distribution of the vehicle headlight with an optimal light intensity distribution, wherein the optimal light intensity distribution is retrieved from a database based on at least one of the vehicle information, the vehicle speed, the road information, the area information or the weather information. The processor further controls the vehicle headlight based on the comparison.

In another embodiment, a non-transitory computer-readable storage medium for assisted real-time control of a vehicle headlight, is disclosed, which when executed by a computing device, cause the computing device to perform operations comprising collecting at least one of vehicle information, vehicle speed, road information, area information, weather information or a multimedia object associated with a forward path of the vehicle. The operations further comprise determining a current light intensity distribution of the vehicle headlight based on the multimedia object. The operations further comprise comparing the current light intensity distribution of the vehicle headlight with an optimal light intensity distribution, wherein the optimal light intensity distribution is retrieved from a database based on at least one of the vehicle information, the vehicle speed, the road information, the area information or the weather information. The operations further comprise controlling the vehicle headlight based on the comparison.

DETAILED DESCRIPTION

The present subject matter discloses a system and method for assisted real-time control of a vehicle headlight. The system and method may be implemented in a variety of computing systems. The computing systems that can implement the described method(s) include, but are not limited to a server, a desktop personal computer, a notebook or a portable computer, hand-held devices, and a mainframe computer. Although the description herein is with reference to certain computing systems, the system and method may be implemented in other computing systems, albeit with a few variations, as will be understood by a person skilled in the art.

Working of the systems and methods for assisted real-time control of the vehicle headlight is described in conjunction withFIGS. 1-4. It should be noted that the description and drawings merely illustrate the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described or shown herein, embody the principles of the present subject matter and are included within its spirit and scope. Furthermore, all examples recited herein are principally intended expressly to be only for pedagogical purposes to aid the reader in understanding the principles of the present subject matter and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the present subject matter, as well as specific examples thereof, are intended to encompass equivalents thereof. While aspects of the systems and methods can be implemented in any number of different computing systems environments, and/or configurations, the embodiments are described in the context of the following exemplary system architecture(s).

FIG. 1illustrates an exemplary network environment100comprising a Headlight Controlling Device102, in accordance with some embodiments of the present disclosure. As shown inFIG. 1, the Headlight Controlling Device102, is communicatively coupled to a database104. Although the database104is shown external to the Headlight Controlling Device102inFIG. 1, it may be noted that, in one implementation, the database104may be present within the Headlight Controlling Device102.

The Headlight Controlling Device102may be implemented on variety of computing systems.

The database104may comprise vehicle information106, vehicle speed108, road information110, area information112, weather information114, recommended light mode116and optimal light intensity distribution118. The vehicle information106may comprise at least one of vehicle type, vehicle size or vehicle position. The road information110may comprise at least one of road type, route number, driving side or road conditions.

The Headlight Controlling Device102may be communicatively coupled to the database104through a network. The network may be a wireless network, wired network or a combination thereof. The network can be implemented as one of the different types of networks, such as intranet, local area network (LAN), wide area network (WAN), the internet, and such. The network may either be a dedicated network or a shared network, which represents an association of the different types of networks that use a variety of protocols, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol/Internet Protocol (TCP/IP), Wireless Application Protocol (WAP), etc., to communicate with each other. Further, the network may include a variety of network devices, Including routers, bridges, servers, computing devices, storage devices, etc.

As shown inFIG. 1, the Headlight Controlling Device102comprises a processor120, a memory122coupled to the processor120, and interface(s)124. The processor120may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor120is configured to fetch and execute computer-readable instructions stored in the memory122. The memory122can include any non-transitory computer-readable medium known in the art including, for example, volatile memory122(e.g., RAM), and/or non-volatile memory122(e.g., EPROM, flash memory, etc.).

The interface(s)124may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, etc., allowing the Headlight Controlling Device102to interact with user devices. Further, the interface(s)124may enable the Headlight Controlling Device102respectively to communicate with other computing devices. The interface(s)124can facilitate multiple communications within a wide variety of networks and protocol types, Including wired networks, for example LAN, cable, etc., and wireless networks such as WLAN, cellular, or satellite. The interface(s)124may include one or more ports for connecting a number of devices to each other or to another server.

In order to assist in real-time control of the vehicle headlight, a Light intensity analyzer126may receive at least one of the vehicle information106, the vehicle speed108, the road information110, the area information112, the weather information114or a multimedia object202associated with a forward path of a vehicle, wherein the multimedia object202may comprise at least one of a video or an Image.

After receiving the vehicle information106, the vehicle speed108, the road information110, the area information112, the weather information114and the multimedia object202, the Light intensity analyzer126may determine a current light intensity distribution204of the vehicle headlight128based on the multimedia object202. This is shown inFIG. 2. In one embodiment, the current light intensity distribution204may be determined based on an intensity Histogram of a Red-Green-Blue (RGB) image, which may be derived from the multimedia object202. An alternative embodiment may be to derive an RGB image from the multimedia object202and to convert it into a Grayscale image. Then the current light intensity distribution204may be determined based on the Intensity Histogram of the Grayscale image.

After determining the current light intensity distribution204, the Light Intensity Analyzer126, compares the current light intensity distribution204with an optimal light intensity distribution118, wherein the optimal light intensity distribution118is retrieved by looking-up the database104using current vehicle parameters. The current vehicle parameters may include the vehicle information106, the vehicle speed108, the road information110, the area information112and the weather information114.

After comparing the current light intensity distribution204with the optimal light intensity distribution118, the vehicle headlight128may be controlled based on the comparison. In one implementation, the vehicle headlight128may be switched between low beam and high beam or between higher light intensity and lower light intensity. The vehicle headlight128may be switched between various other configurations of the vehicle headlight128to bring the vehicle to the optimal light intensity distribution118.

FIG. 3is a flow diagram Illustrating a method for assisted real-time control of a vehicle headlight. With reference toFIG. 3, at step302, parameters including but not limited to, the vehicle information106, the vehicle speed108, the road information110, the area information112and the weather information114may be collected. Further, the multimedia object202, which may include an image or a video, may also be captured. The image or the video may capture the field of view of a driver of the vehicle as the vehicle moves in a forward path. The multimedia object202may be captured using one or more image capturing devices.

In some embodiments, one or more of the vehicle information106, the vehicle speed108, the road information110, the area information112and the weather information114may be collected in real time. For example, the driver may be uniquely associated with the registration number of the vehicle and the vehicle registration number may be looked up in a database104to determine the type of the vehicle. The vehicle speed108, the road information,110the area information112and the weather information114may be collected in real time due to the dynamic nature of the information. In some other embodiments, the vehicle information106may be predefined. For example, the vehicle information106may be provided by the driver during a registration process. The driver may also provide a driving side i.e. whether the vehicle is being driven in a left-driving country or a right-driving country.

Here, the vehicle information106may comprise vehicle type, vehicle size and vehicle position. The Vehicle type may indicate, for example, if the vehicle is a Sports Utility Vehicle (SUV), a sedan, a truck, a van etc., and the vehicle size may indicate if the vehicle is a minicompact, a subcompact, a compact, a midsize, a large vehicle etc. The vehicle position, the vehicle speed108and the area information112may be collected through a Global Positioning System (GPS) associated with the vehicle. In some embodiments, the vehicle position may be obtained by a satellite ranging method, which involves measuring the distance between a GPS receiver and GPS satellites. In some embodiments, the vehicle speed108may be calculated using the Doppler Effect. GPS may implement receivers to continuously track carder frequencies generated by satellites. The Doppler shift, which is the difference between the known satellite carrier frequency and the frequency determined at the receiver, is directly proportional to the velocity of the receiver. This may be used to calculate the speed of the vehicle. Further, in some embodiments, the area information112may be determined using Geographic information Systems (GIS). The GPS data is compared with geographic map data and road data in order to determine the area information. Examples for the area information112may be urban, suburban, rural etc. Examples for the weather information114may be windy, sunny, cloudy etc. Further, in some embodiments, the weather information114might be obtained by using weather sensors130.

In addition to the vehicle information106, the vehicle speed108, the area information112and the weather information114, the road information110may also be collected at step302. Here, the road information110may include road type, route number, driving side or road conditions. The road type, the route number and the road conditions may be determined using GIS. The road type may indicate, for example, whether the road is a highway, a rural road, an interstate road, a motorway, an arterial road, a mountain road, a pedestrian zone, a trunk road, an expressway, etc. The driving side may be left or right, depending on whether the vehicle is being driven in a left-driving country or a right-driving country. The “road conditions” parameter may include information on whether the road is accident prone, is of degraded quality, under construction, under illuminated, etc.

In addition to the vehicle information106, the vehicle speed108, the road information110, the area information112and the weather information114, the multimedia object202may also be collected at step302. The multimedia objects202are captured using the image capturing devices. The multimedia object202may be an image or a video of the area in front of the vehicle. This may typically include the view of the driver as the vehicle moves in a forward path.

Once the multimedia object202is captured, a current light intensity distribution204of the vehicle headlight128may be determined based on the multimedia object202at step304. The current light intensity distribution204may represent the distribution of light as seen by the driver of the vehicle. The light intensity distribution as determined from the image or video of the forward path of the vehicle may represent light distribution from various sources as the vehicle moves in a forward path. For example, the light sources may include the headlight of the vehicle, light from street lights, headlights from oncoming vehicles, tail lights from other vehicles travelling in the same direction as the vehicle, lights from billboards, etc. Image capturing techniques may be used on the image or the video captured by the image capturing device to determine the light intensity distribution. In some embodiments, the light intensity distribution may be determined from a histogram of the image.

In some embodiments, the current light intensity distribution204may be determined by first deriving the RGB image from the multimedia object202and then converting the derived RGB image into a Grayscale image and finally determining the Intensity Histogram of the Grayscale image. In an alternative embodiment, the current light intensity distribution may be determined by determining the Intensity Histogram of the RGB image. Noise may be eliminated from the RGB image by using Filtering Techniques like an averaging filter or a median filter etc. Skew error may be eliminated by providing skew correction like top line, scan line, etc.

On determining the current light intensity distribution204, the current light intensity distribution204may be compared with an optimal light intensity distribution118at step306. The optimal light intensity distribution118may represent the ideal or optimal light distribution for a particular set of parameter values. In other words, the optimal light intensity distribution118may suggest the optimal headlight configuration by taking into consideration parameters such as the vehicle information106, the vehicle speed108, the road information110, the area information112and the weather information114, herein after referred to as current vehicle parameters. To determine the optimal light intensity distribution118for a set of current vehicle parameters or for a given set of conditions, a database104may be looked-up using the set of current vehicle parameters or the set of conditions. The database104may include a predefined mapping between the current vehicle parameters or conditions and the optimal light intensity distribution118for those current vehicle parameters. Further, the database104may include a recommended headlight mode116to achieve the optimal light distribution.

At step308, the vehicle headlight128may be controlled based on the comparison between the current light intensity distribution204and the optimal light intensity distribution118. The vehicle headlight128may be controlled either by altering the headlight mode or by altering the light intensities. The current light intensity distribution204may be altered to match the optimal light intensity distribution118. If the current light intensity distribution204is lesser than the optimal light intensity distribution118, then the vehicle headlight128may be switched from low beam to high beam or from lower light intensity to higher light intensity. If the current light intensity distribution204is greater than the optimal light intensity distribution118, then the vehicle headlight128may be switched from high beam to low beam or from higher light intensity to lower light intensity. Optimal light intensity distributions118corresponding to various permutations and combinations of possible values of the parameters may be stored in the database104. These optimal light intensity distributions118may be looked up using the current vehicle parameter values. For example, if the weather information114as collected in step302indicates foggy conditions and the optimal light intensity distribution118indicates that a wider spread of light is required when compared to the current light intensity distribution204of the headlights, then the recommended mode116may suggest to the driver of the vehicle to turn on the fog lamps of the vehicle. In some other embodiments, headlight controlling device102may automatically change the configuration of the headlights to achieve the recommended mode, in this case, automatically switching the fog lights on. Consider another illustration where the vehicle is being driven on a road that is accident prone. The road information110may be collected in step302and the optimal light intensity distribution118may indicate that a higher intensity of light is required when compared with the current light intensity distribution204of the headlights. Then the headlight mode may suggest to switch or automatically switch from low beam mode to high beam mode or from lower light intensity to higher light intensity and not to switch if it is already in the high beam mode. Consider another illustration where the vehicle is being driven in a rural area. The area information112may be collected in step302and the optimal light intensity distribution118may indicate that a higher intensity of light is required when compared with the current light intensity distribution204of the headlights. This may be due to the fact that there are less traffic in the rural areas and hence a lesser chance of blinding an oncoming vehicle driver with high beam. Hence, the headlight mode may suggest to switch from low beam mode to high beam mode or from lower light intensity to higher light intensity and not to switch, if the vehicle is already in the high beam mode Headlight controlling device102alters the mode of the headlight to match the recommended light mode116, i.e. it switches from low beam to high beam, if the current mode is in low beam, or makes no change if the current mode is in high beam.

Computer System

FIG. 4is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. Variations of computer system401may be used for implementing the Light Intensity Analyzer126. Computer system401may comprise a central processing unit (“CPU” or “processor”)402. Processor402may comprise at least one data processor for executing program components for executing user- or system-generated requests. A user may include a person, a person using a device such as such as those included in this disclosure, or such a device itself. The processor may include specialized processing units such as integrated system (bus) controllers, memory management control units, floating point units, graphics processing units, digital signal processing units, etc. The processor may include a microprocessor, such as AMD Athlon, Duron or Opteron, ARM's application, embedded or secure processors, IBM PowerPC, Intel's Core, Itanium, Xeon, Celeron or other line of processors, etc. The processor402may be implemented using mainframe, distributed processor, multi-core, parallel, grid, or other architectures. Some embodiments may utilize embedded technologies like application-specific integrated circuits (ASICs), digital signal processors (DSPs), Field Programmable Gate Arrays (FPGAs), etc.

Using the I/O interface403, the computer system401may communicate with one or more I/O devices. For example, the input device404may be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touchpad, trackball, sensor (e.g., accelerometer, light sensor, GPS, gyroscope, proximity sensor, or the like), stylus, scanner, storage device, transceiver, video device/source, visors, etc. Output device405may be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light-emitting diode (LED), plasma, or the like), audio speaker, etc. In some embodiments, a transceiver406may be disposed in connection with the processor402. The transceiver may facilitate various types of wireless transmission or reception. For example, the transceiver may include an antenna operatively connected to a transceiver chip (e.g., Texas Instruments WiLink WL1283, Broadcom BCM4750IUB8, Infineon Technologies X-Gold 618-PMB9800, or the like), providing IEEE 802.11a/b/g/n, Bluetooth, FM, global positioning system (GPS), 2G/3G HSDPA/HSUPA communications, etc.

In some embodiments, the processor402may be disposed in communication with a communication network408via a network interface407. The network interface407may communicate with the communication network408. The network interface may employ connection protocols including, without limitation, direct connect, Ethemet (e.g., twisted pair 10/100/1000 Base T), transmission control protocol/internet protocol (TCP/IP), token ring, IEEE 802.11a/b/g/n/x, etc. The communication network408may include, without limitation, a direct interconnection, local area network (LAN), wide area network (WAN), wireless network (e.g., using Wireless Application Protocol), the Internet, etc. Using the network interface407and the communication network408, the computer system401may communicate with devices410,411, and412. These devices may include, without limitation, personal computer(s), server(s), fax machines, printers, scanners, various mobile devices such as cellular telephones, smartphones (e.g., Apple iPhone, Blackberry, Android-based phones, etc.), tablet computers, eBook readers (Amazon Kindle, Nook, etc.), laptop computers, notebooks, gaming consoles (Microsoft Xbox, Nintendo DS, Sony PlayStation, etc.), or the like. In some embodiments, the computer system401may itself embody one or more of these devices.