System and method for detecting vehicles at roadway intersections using curved mirrors

Abstract

The present disclosure relates to a system and method for detecting one or more first vehicles at a road intersection using a curved mirror. To detect one or more first vehicles, a forward looking image of a second vehicle is received. The image is received when the second vehicle reaches a predetermined position in a predetermined direction at night. Furthermore, one or more ROIs are identified from the received image based on pre-stored data about the second vehicle. The one or more ROIs indicate the location of one or more curved mirrors located at the road intersection in the image. The present disclosure further identifies the presence of light in the one or more ROIs. If the light is identified, one or more first vehicles arriving at the road intersection are detected. Thus, the present disclosure provides a warning / stop to the second vehicle to avoid a collision / accident at the road intersection.

Description

[Technical Field]

[0001] The present disclosure relates generally to traffic safety, and more particularly, but not exclusively, to a system and method for detecting one or more first vehicles at a road intersection using curved mirrors. [Background technology]

[0002] Detecting approaching vehicles near road intersections is essential for the safety of vehicle drivers. Many accidents at road intersections occur due to drivers being unable to see approaching vehicles. To prevent such traffic accidents, curved mirrors are installed at road intersections. Curved mirrors are also called convex mirrors or reflecting mirrors. During the day, vehicle drivers can see the reflection of approaching vehicles in the curved mirror due to the presence of light. As a result, drivers on the opposite side of the curved mirror can see whether a vehicle is approaching the intersection and avoid a collision. Thus, curved mirrors are extremely useful for safety reasons. Curved mirrors allow drivers to see approaching vehicles around curves and corners in the road. Therefore, curved mirrors are particularly useful in blind spots and sharp corners on the road. By installing curved mirrors at an appropriate height at road intersections, vehicle drivers can see approaching vehicles and avoid collisions / accidents. Summary of the Invention [Problem to be solved by the invention]

[0003] Existing systems are equipped with automated systems that detect curved mirrors and issue a warning to the driver when a vehicle approaching the mirror is identified. In this way, automated systems help avoid accidents at road intersections by detecting vehicles on the curved mirror. Initially, curved mirrors were detected using technologies such as automotive radar to capture images of the curved mirror. Furthermore, existing systems detect moving objects from the images of the curved mirror. However, the detection of curved mirrors and moving objects may only be possible during the day. Existing systems cannot detect curved mirrors at night to avoid collisions due to low visibility. Since curved mirrors cannot be detected at night and vehicles approaching the intersection cannot be identified, accidents may occur at road intersections. Therefore, there is a need for a system that can accurately detect approaching vehicles at night to avoid collisions and accidents.

[0004] The information disclosed in the background section of this disclosure is intended only to enhance understanding of the general background art of the present invention and should not be considered as an admission or in any way suggestion that such information constitutes prior art already known to those skilled in the art. [Means for solving the problem]

[0005] In some embodiments, the present disclosure relates to a method for detecting one or more first vehicles at a road intersection using a curved mirror. To detect the one or more first vehicles, a forward-looking image of a second vehicle is received. The image is received at night when the second vehicle reaches a predetermined location in a predetermined direction. The method further includes identifying one or more regions of interest (ROIs) from the received image. The one or more ROIs are identified based on pre-stored data related to the second vehicle. The one or more ROIs indicate the location of one or more curved mirrors located at the road intersection in the received image. The method further includes identifying the presence of light within the one or more ROIs identified from the received image. If the light is identified, one or more first vehicles arriving at the road intersection are detected.

[0006] In some embodiments, the present disclosure relates to a detection system implemented in a second vehicle that detects one or more first vehicles using a curved mirror at a road intersection. The detection system includes a processor and a memory communicatively coupled to the processor. The memory stores processor-executable instructions that, when executed, cause the processor to detect one or more first vehicles using the curved mirror at the road intersection. To detect the one or more first vehicles, a forward-looking image of the second vehicle is received. The image is received at night when the second vehicle reaches a predetermined location in a predetermined direction. The detection system further identifies one or more regions of interest (ROIs) from the received image. The one or more ROIs are identified based on pre-stored data about the second vehicle. The one or more ROIs indicate the locations of one or more curved mirrors located at the road intersection within the received image. The detection system further identifies the presence of light within the one or more ROIs identified from the received image. If the light is identified, one or more first vehicles arriving at the road intersection are detected.

[0007] As used in this summary, the following description, the appended claims, and the accompanying drawings, the term "curved mirror" refers to a mirror having a curved reflective surface. Curved mirrors may also be referred to as, but are not limited to, convex mirrors, reflectors, road reflectors, etc.

[0008] As used in this Summary, the following description, the claims, and the accompanying drawings, the term "road intersection" means an area where two or more roads meet, diverge, join, or intersect.

[0009] The term "image" as used in this Summary, the following description, the claims, and the accompanying drawings means an image of a curved mirror that may be placed at a road intersection to prevent collisions or accidents. The image may be captured by one or more image capture devices. The one or more image capture devices may include, but are not limited to, a camera, a video recorder, a digital camera, etc.

[0010] The term "one or more regions of interest (ROI)" used in the above summary, the following description, the claims, and the accompanying drawings refers to the location of one or more curved mirrors that may be located at a road intersection within an image.

[0011] As used in the summary above, the following description, the claims, and the accompanying drawings, the term "one or more first vehicles" refers to vehicles that may be approaching a road intersection. The one or more first vehicles may include, but are not limited to, cars, trucks, taxis, cabs, motorcycles, etc.

[0012] As used in the summary above, the following description, claims, and drawings, the term "second vehicle" refers to a vehicle in which a detection system is implemented. The second vehicle may include, but is not limited to, a car, a truck, a taxi, a cab, etc.

[0013] As used in the summary above, the description below, the claims, and the accompanying drawings, the term "at least" followed by a number is used to indicate the beginning of a range beginning with that number (which may be an upper or lower bound, depending on the variable being defined). For example, "at least one" means one or more than one.

[0014] The foregoing summary is illustrative and not intended to be in any way limiting. In addition to the exemplary aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description.

[0015] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate several exemplary embodiments and, together with the following description, serve to explain the disclosed principles. In the drawings, the leftmost digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to refer to like features and elements. Several embodiments of systems and / or methods according to embodiments of the present subject matter are described below, by way of example only, with reference to the accompanying drawings. [Brief explanation of the drawings]

[0016] [Figure 1] 1 illustrates an example environment of a detection system that uses a curved mirror to detect one or more first vehicles at a road intersection, according to some embodiments of the present disclosure. [Figure 2] 1 illustrates a detailed block diagram of a detection system that uses curved mirrors to detect one or more first vehicles at a road intersection, according to some embodiments of the present disclosure. [Figure 3a] 1 illustrates several exemplary embodiments of detecting one or more first vehicles using a curved mirror at a road intersection, according to some embodiments of the present disclosure. [Figure 3b] 1 illustrates several exemplary embodiments of detecting one or more first vehicles using a curved mirror at a road intersection, according to some embodiments of the present disclosure. [Figure 3c] 1 illustrates several exemplary embodiments of detecting one or more first vehicles using a curved mirror at a road intersection, according to some embodiments of the present disclosure. [Figure 3d] 1 illustrates several exemplary embodiments of detecting one or more first vehicles using a curved mirror at a road intersection, according to some embodiments of the present disclosure. [Figure 4] 1 shows a flow diagram illustrating an example method for detecting one or more first vehicles using a curved mirror at a road intersection, according to some embodiments of the present disclosure. [Figure 5] FIG. 1 is a block diagram of an exemplary computer system for implementing embodiments consistent with the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0017] Those skilled in the art will appreciate that any block diagrams herein represent conceptual views of illustrative systems embodying principles of the present subject matter. Similarly, any flowcharts, flow diagrams, state transition diagrams, pseudocode, etc., may be substantially written on a computer-readable medium and represent various processes that may be executed by an expressly illustrated computer or processor.

[0018] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

[0019] While the present disclosure is susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawings and are described in detail below. However, it is not intended to limit the disclosure to the precise form disclosed, but rather it is to be understood that the disclosure is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure.

[0020] The terms "comprises," "comprising," or any other variation thereof, are intended to mean a non-exclusive inclusion, and a device, apparatus, or method that includes a list of elements or steps does not include only those elements or steps, but may include other elements or steps not expressly listed or inherent in such device, apparatus, or method. In other words, the use of "comprises" followed by one or more elements of a system or apparatus does not exclude the presence of other or additional elements in the system or method, unless further constraints exist.

[0021] The terms "includes," "including," or any other variation thereof, are intended to mean a non-exclusive inclusion, and a device, apparatus, or method that includes a list of elements or steps does not include only those elements or steps, but may include other elements or steps not expressly listed or inherent in such device, apparatus, or method. In other words, the use of "comprises" followed by one or more elements of a system or apparatus does not exclude the presence of other or additional elements in the system or method, unless further constraints exist.

[0022] In the following detailed description of several embodiments of the present disclosure, reference is made to the accompanying drawings which form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the present disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, it being understood that other embodiments may be utilized and changes may be made without departing from the scope of the present disclosure. Accordingly, the following description is not to be construed in a limiting sense.

[0023] The proposed system relates to a method and system for detecting one or more first vehicles at a road intersection using a curved mirror. The proposed system is implemented in a second vehicle to detect one or more first vehicles to avoid collisions or accidents between the vehicles. The proposed system captures one or more images of the area ahead of the second vehicle during the day and generates pre-stored data for the second vehicle. At night, when the second vehicle reaches a predetermined location in a predetermined direction, the proposed system includes receiving a forward-looking image of the second vehicle including the curved mirror. Once the image is received, the proposed system identifies one or more regions of interest (ROIs) from the image based on the pre-stored data. Furthermore, the proposed system identifies the presence of light within the one or more ROIs. Once the presence of light is identified, the proposed system accurately detects one or more first vehicles approaching the road intersection. In this way, the proposed system avoids collisions / accidents between the second vehicle and one or more first vehicles at night.

[0024] FIG. 1 illustrates an exemplary environment 100 for a detection system 101 that uses curved mirrors to detect one or more first vehicles at a road intersection, according to some embodiments of the present disclosure. The exemplary environment 100 may include the detection system 101, an image capture unit 102, a second vehicle 103, and a communication network 104. The environment 100 may be around the second vehicle 103 that implements the detection system 101. In some embodiments, the detection system 101 may be implemented inside the second vehicle 103, which may be autonomous or driven by a human driver. The second vehicle 103 may be a car, taxi, cab, truck, etc. In an alternative embodiment, the detection system 101 may be implemented in any type of vehicle capable of acquiring its own forward-looking image. For example, the second vehicle 103 may be a car used by an individual to drive from a start point to a destination. The driver of the second vehicle 103 may be navigating lanes with sharp curves and blind spots. A blind spot is an area of the road that cannot be seen by looking forward through the windshield of the second vehicle 103, nor can it be seen in the rearview and side mirrors. A sharp curve is an area where the road curves either to the left or to the right, making it difficult for the driver of the second vehicle 103 to identify an approaching vehicle. In such a scenario, the driver of the second vehicle 103 may find it difficult or problematic to identify whether a vehicle is approaching a sharp curve or blind spot at night. The detection system 101 is used in such a scenario at a road intersection using curved mirrors to detect approaching vehicles.

[0025] The detection system 101 may be in communication with the image capture unit 102 and the second vehicle 103 to perform detection of one or more first vehicles using curved mirrors at a road intersection. In some embodiments, the detection system 101 may communicate with the image capture unit 102 and the second vehicle 103 via a communication network 104. The communication network 104 may include, but is not limited to, a direct interconnect, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using a wireless application protocol), a control area network (CAN), a local interconnect network (LIN), the Internet, etc. In an alternative embodiment, a dedicated communication network may be implemented to establish communication between the detection system 101, the image capture unit 102, and the second vehicle 103 to perform detection of one or more first vehicles.

[0026] Further, the detection system 101 may include a processor 105, an input / output (I / O) interface 106, and a memory 107. In an alternative embodiment, the processor 105 may include one or more processors. In some embodiments, the memory 107 may be communicatively coupled to the processor 105. The memory 107 stores instructions executable by the processor 105 that, when executed, cause the detection system 101 to detect one or more first vehicles using a curved mirror at a road intersection as proposed in this disclosure. In some embodiments, the memory 107 may include one or more modules 108 and data 109. The one or more modules 108 may be configured to perform steps of the present disclosure using the data 109 to perform the detection of one or more first vehicles using a curved mirror at a road intersection. In some embodiments, each of the one or more modules 108 may be a hardware unit external to the memory 107 that may be coupled to the detection system 101. In some embodiments, the detection system 101 may be implemented on various computing systems, such as a laptop computer, a desktop computer, a personal computer (PC), a notebook, a smartphone, a tablet, an e-reader, a server, a network server, a cloud server, an artificial intelligence (AI) accelerator, a graphics processing unit (GPU)-enabled device, etc. In an alternative embodiment, the detection system 101 may be a dedicated server associated with a single system to perform detection of one or more first vehicles using curved mirrors at road intersections. In an alternative embodiment, the detection system 101 may be a cloud-based server associated with multiple vehicles. Such a detection system 101 may be configured to perform detection of one or more first vehicles using curved mirrors at road intersections for each of the multiple vehicles.

[0027] In some embodiments, the image capture unit 102 may be configured to capture one or more images or videos of the second vehicle 103's forward view during the day and at night. The image capture unit 102 may be configured to function differently during the day and at night. In an alternative embodiment, the image capture unit 102 may be configured to continuously capture one or more images of the second vehicle 103's forward view to identify one or more curved mirrors in front of the second vehicle 103. In an alternative embodiment, once one or more images or videos have been captured, the detection system 101 may be configured to monitor the presence of one or more curved mirrors near the road intersection using one or more frames of the one or more images or videos. In an alternative embodiment, the image capture unit 102 may be integrated into the second vehicle 103 to monitor the presence of one or more curved mirrors. In an alternative embodiment, the image capture unit 102 may be external to the second vehicle 103 to monitor for the presence of one or more curved mirrors. In some embodiments, the image capture unit 102 may be, but is not limited to, a camera, video recorder, digital camera, or the like. One or more images or videos of the forward view of the second vehicle 103 may be received as input to the detection system 101. One or more other modes known to those skilled in the art may be associated with the detection system 101 to receive the forward view images or videos of the second vehicle 103. The detection system 101 may be configured to identify one or more curved mirrors using one or more images or one or more frames of the forward view images of the second vehicle 103.

[0028] The detection system 101 may be configured to generate pre-stored data of the second vehicle 103 if identified during the day. The pre-stored data may include, but is not limited to, the location of the second vehicle 103 when one or more images of the curved mirror are acquired, the location of the one or more curved mirrors within the one or more images, and the orientation of the second vehicle 103 at the location. In some embodiments, the location of the one or more curved mirrors within the one or more images may be referred to as one or more ROIs. In some embodiments, the location of the second vehicle 103 may be referred to as a predetermined location. In some embodiments, the orientation of the second vehicle 103 may be referred to as a predetermined direction. In an alternative embodiment, the location of the second vehicle 103 may be a location where the second vehicle 103 may be located when one or more images of the one or more curved mirrors are acquired. In an alternative embodiment, the location of the second vehicle 103 may be in the form of a latitude and longitude. The latitude and longitude of the second vehicle 103 can indicate the precise location of the second vehicle 103 while acquiring one or more images. In some embodiments, the direction of the second vehicle 103 can be, but is not limited to, east, west, north, south, etc. while acquiring one or more images of the one or more curved mirrors. In some embodiments, the position and direction of the second vehicle 103 can be provided by a Global Positioning System (GPS). The GPS can be part of the second vehicle 103 configured to monitor the position and direction of the second vehicle 103 during the day and at night. In an alternative embodiment, pre-stored data about the second vehicle 103 can be generated each time a curved mirror is detected along the path of the second vehicle 103. For example, as the second vehicle 103 travels from one location to another, the second vehicle 103 may encounter multiple curved mirrors located at road intersections along its route. Each time the second vehicle 103 identifies a curved mirror, pre-stored data is generated for that curved mirror and stored in memory 107. As a result, there are multiple pre-stored data with multiple predetermined positions and corresponding predetermined orientations.

[0029] Further, consider the case where the driver of the second vehicle 103 drives at night at one of the predetermined locations stored in the pre-stored data. The predetermined location may be a location where the driver drove during the day. In some embodiments, the detection system 101 may be activated to receive forward-looking images of the second vehicle 103 when the driver of the second vehicle 103 reaches one of the predetermined locations stored in the pre-stored data at night. The detection system 101 receives one or more images when the second vehicle 103 reaches the predetermined location while traveling in a corresponding predetermined direction. In an alternative embodiment, the detection system 101 may not be activated to receive one or more images if the second vehicle 103 does not reach the predetermined location in the predetermined direction. For example, the pre-stored data may include a predetermined location and a predetermined direction for the second vehicle 103 during the day. However, one or more curved mirrors may not be discernible at night when the second vehicle 103 is traveling due to poor visibility. Therefore, if the second vehicle 103 does not reach a predetermined position in a predetermined direction that contains information about one or more curved mirrors near a road intersection, the detection system 101 may not be activated to receive one or more images.

[0030] Once the detection system 101 receives an image, it may be configured to identify one or more regions of interest (ROIs) from the image. An ROI is a portion of an image that needs to be filtered or manipulated for further processing. In some embodiments, the detection system 101 identifies the one or more ROIs based on one or more ROIs that correspond to predetermined locations in pre-stored data for the second vehicle 103. In some embodiments, the one or more ROIs indicate the location of one or more curved mirrors in the image. Furthermore, once the detection system 101 has identified the one or more ROIs, it may be configured to identify the presence of light within the one or more ROIs. In some embodiments, the presence of light can be identified by using one or more image classification algorithms. The image classification algorithm may be trained to identify the presence of light within one or more ROIs in the received image. The one or more techniques for the image classification algorithm may include, but are not limited to, a support vector machine (SVM), an artificial neural network (ANN), a convolutional neural network (CNN), etc. In some embodiments, the detection system 101 may be configured to detect that one or more first vehicles are arriving at a road intersection if the presence of light is identified. The one or more first vehicles may emit light from one or more first vehicle headlights. The light from the one or more first vehicle headlights may strike one or more curved mirrors and be reflected from the one or more curved mirrors and captured in one or more images. Thus, the reflection of the light in the one or more images may be identified to detect the approach of the one or more first vehicles.

[0031] In some embodiments, the detection system 101 may be configured to initiate one or more actions upon detecting one or more first vehicles at the road intersection. The detection system 101 may be configured to monitor one or more characteristics of light upon identifying one or more first vehicles. In some embodiments, the one or more characteristics of light include, but are not limited to, light intensity. The light intensity may be the strength or amount of light generated from a light source, such as headlights, of the one or more first vehicles. In some embodiments, the light intensity may be high when the one or more first vehicles are very close to the road intersection. In an alternative embodiment, the light intensity may be low when the one or more first vehicles are far away from the road intersection.

[0032] In an alternative embodiment, the one or more characteristics of light may be light coverage within one or more ROIs. For example, the light coverage may be an area covered by light within one or more ROIs in one or more images. Consider a case where one or more first vehicles are very far away from a road intersection where one or more curved mirrors are located for collision avoidance. In such a scenario, the area covered by light within one or more ROIs in one or more images is very small. Therefore, since the light coverage within the one or more ROIs may be very small, the detection system 101 may be configured to identify that the one or more first vehicles are far away from the road intersection. Similarly, consider a case where one or more first vehicles are very close to the road intersection. In such a scenario, the area covered by light within one or more ROIs in one or more images is larger. Therefore, since the one or more ROIs show more light coverage, the detection system 101 may be configured to identify that the one or more first vehicles are very close to the road intersection. One or more techniques known to those skilled in the art may be used to determine the approach of one or more first vehicles based on characteristics of light within one or more ROIs.

[0033] Based on monitoring one or more characteristics of the light, the detection system 101 may be configured to alert the driver of the second vehicle 103 via a human-machine interface (HMI). In some embodiments, the detection system 101 may be in communication with the HMI to alert the driver of the second vehicle 103. The detection system 101 may alert the driver of the second vehicle 103 when high light intensity indicates that one or more first vehicles may be approaching the road intersection. In an alternative embodiment, the detection system 101 may be configured to alert the driver of the second vehicle 103 when high light coverage within one or more ROIs indicates that one or more first vehicles may be approaching the road intersection.

[0034] In some embodiments, the HMI may be a user interface or dashboard that connects a person to machines, systems, or devices within the second vehicle 103. In some embodiments, the HMI may be integrated into the detection system 101. In an alternative embodiment, the HMI may be integrated into the second vehicle 103. In some embodiments, the HMI may include a display, a speaker, a microphone, etc. In some embodiments, the display may be used to display warnings in text format. In an alternative embodiment, the speaker may be used to provide audio alerts to the driver of the second vehicle 103. In an alternative embodiment, the microphone may be used by the driver of the second vehicle 103 to provide audio commands to slow or stop the second vehicle 103.

[0035] In an alternative embodiment, the detection system 101 may be configured to activate a braking system of the second vehicle 103 to automatically stop the second vehicle 103. The detection system 101 may be configured to stop the second vehicle 103 when the light intensity is extremely high, indicating that one or more first vehicles may be in a near-collision state at the road intersection. In an alternative embodiment, the detection system 101 may be configured to activate a braking system of the second vehicle 103 to automatically stop the second vehicle 103 when the light coverage within one or more ROIs is high, indicating that one or more first vehicles may be in a near-collision state with the second vehicle 103 at the road intersection.

[0036] FIG. 2 illustrates a detailed block diagram of a detection system 101 that uses curved mirrors to detect one or more first vehicles at a road intersection, according to some embodiments of the present disclosure.

[0037] The data 109 in memory 107 and one or more modules 108 of the detection system 101 are described in more detail below.

[0038] In one implementation, the one or more modules 108 may include, but are not limited to, an information receiving module 201, an ROI identification module 202, a light identification module 203, a pre-stored data collection module 204, a vehicle detection module 205, an action initiation module 206, and one or more other modules 207 associated with the detection system 101.

[0039] In some embodiments, the data 109 in the memory 107 may include image data 208, ROI data 209, light data 210, pre-stored data 211, vehicle detection data 212, action data 213, and other data 214 associated with the detection system 101.

[0040] In some embodiments, the data 109 in memory 107 may be processed by one or more modules 108 of the sensing system 101. In some embodiments, one or more modules 108 may be implemented as dedicated devices, and if so implemented, the modules may be configured with functionality as defined in this disclosure to create new hardware. As used herein, the term module may refer to an application specific integrated circuit (ASIC), an electronic circuit, a field programmable gate array (FPGA), a programmable system on a chip (PSoC), a combinational logic circuit, and / or other suitable elements that provide the functionality described above.

[0041] The one or more modules 108 of the present disclosure function to perform detection of one or more first vehicles using curved mirrors at a road intersection. The one or more modules 108, along with data 109, may be implemented in any system to perform detection of one or more first vehicles.

[0042] The pre-stored data collection module 204 of the detection system 101 may be configured to collect pre-stored data 211 about the second vehicle 103. The pre-stored data collection module 204 collects the pre-stored data 211 during daylight hours. In some embodiments, to collect the pre-stored data 211, the image capture unit 102 may first capture one or more images of a forward-looking view of the second vehicle 103 during daylight hours while the second vehicle 103 is traveling. The one or more images may be used to monitor the presence of one or more curved mirrors near a road intersection. In some embodiments, one or more object detection techniques may be used to identify the one or more curved mirrors from the one or more images captured by the image capture unit 102. The one or more object detection techniques may be based on, but are not limited to, template matching, color, shape, etc. Template matching techniques find a small portion of an image that matches a template image. Color-based techniques match images based on color histograms. Shape-based techniques match images based on the shape and texture of the object.

[0043] In some embodiments, upon identifying one or more curved mirrors in the captured images from the one or more images, the pre-stored data collection module 204 generates pre-stored data 211 for the second vehicle 103. The pre-stored data 211 may include a location of the second vehicle 103 and a direction of the second vehicle 103 during the capture of the captured images. Additionally, the pre-stored data 211 may include a location of the one or more curved mirrors within the captured images. In an alternative embodiment, the location of the second vehicle 103 indicates the coordinates of the second vehicle 103 during daytime while capturing one or more images of the one or more curved mirrors near the road intersection. The location of the second vehicle 103 during daytime may be referred to as a predetermined location. In an alternative embodiment, the direction of the second vehicle 103 indicates the path of the second vehicle 103 during daytime while capturing the one or more images. In some embodiments, the direction of the second vehicle 103 during daytime while capturing the one or more images may be referred to as a predetermined direction. The positions of one or more curved mirrors in one or more images may be stored as one or more ROIs in the pre-stored data 211 .

[0044] For example, consider the environment shown in Figure 3a. Figure 3a illustrates an environment including a second vehicle 301, a first vehicle 302, a curved mirror 303, and a reflection of the first vehicle on the curved mirror 303, referred to as the reflection of the first vehicle 304. The image capture unit 102 integrated into the second vehicle 301 may be configured to capture one or more images of a forward view of the second vehicle 301 as the second vehicle 301 is moving. The vehicle detection module 205 present in the second vehicle 301 may identify the reflection of the first vehicle 304 on the curved mirror 303 because the first vehicle 302 may be reflected in the curved mirror 303 due to the presence of daylight. Once the second vehicle 301 identifies the reflection of the first vehicle 304, it may issue a warning to avoid a collision with the first vehicle 302. At the same time, the pre-stored data collection module 204 may be configured to identify the curved mirror 303 from the one or more captured images. Once the curved mirror 303 is identified, the position of the curved mirror 303 within the one or more images is identified and stored as an ROI. The pre-stored data collection module 204 may store the position of the second vehicle 301 and the direction of the second vehicle 301, which is east, as pre-stored data 211.

[0045] For example, consider the case where the second vehicle 301 in FIG. 3a is traveling and reaches a predetermined location in a predetermined direction that was generated by the pre-stored data collection module 204 during the daytime in FIG. 3a. One of the one or more other modules 207 may be configured to monitor the predetermined location and the corresponding predetermined direction of the second vehicle 301. Once the one or more other modules 207 identify the predetermined location and the corresponding predetermined direction, the one of the one or more other modules 207 may be configured to activate the image capture unit 102 to capture a forward-looking image of the second vehicle 301. The image capture unit 102 captures the image once the second vehicle 301 reaches the predetermined location while traveling in the predetermined direction. The information receiving module 201 of the detection system 101 may be configured to receive the forward-looking image of the second vehicle 301 once the image is captured. In some embodiments, the information receiving module 201 may be configured to dynamically receive the forward-looking image of the second vehicle 301. The information receiving module 201 may be configured to receive images at night from the image capture unit 102. For example, consider Fig. 3B, which illustrates a scenario in which a second vehicle 301 arrives at a predetermined location while traveling in a predetermined direction at night. The image capture unit 102 is activated to capture a forward looking image of the second vehicle 301 for processing by the ROI identification module 202.

[0046] Once the image is received, the ROI identification module 202 may be configured to identify one or more regions of interest (ROIs) from the received image. The one or more ROIs are portions of the image acquired by the image acquisition unit 102. The ROI identification module 202 identifies one or more ROIs based on pre-stored data 211 related to the second vehicle 103. For example, consider the pre-stored data 211 generated during the day by the pre-stored data collection module 204 in FIG. 3a. The image received by the information receiving module 201 is compared to the pre-stored data 211. The pre-stored data 211 includes information regarding the position of the curved mirror 303 in one or more images acquired during the day. In some embodiments, the ROI identification module 202 may be configured to compare whether the position of the curved mirror in the received image acquired during the night is similar to the position of the curved mirror 303 stored in the pre-stored data 211. If the comparison reveals that the positions are similar, the ROI identification module 202 may identify one or more ROIs. In some embodiments, one or more ROIs indicate the location of one or more curved mirrors within the received image.

[0047] Furthermore, once the light identification module 203 has identified one or more ROIs, it may be configured to identify the presence of light within the one or more ROIs identified based on the pre-stored data 211. In an alternative embodiment, the presence of light may be identified using one or more image classification algorithms. In some embodiments, the image classification algorithm may be implemented using a CNN that can be trained to identify the presence or absence of light within one or more ROIs of one or more images. In some embodiments, information regarding the presence or absence of light is referred to as light data 210 and is stored in memory 107.

[0048] The vehicle detection module 205 may be configured to detect one or more first vehicles that may arrive at the road intersection once it identifies the presence of light. In some embodiments, the one or more first vehicles may be detected using one or more object detection techniques, including, but not limited to, Histogram of Oriented Gradients (HOG), Single Shot Detector (SSD), etc. HOG is a feature descriptor used in image processing and computer vision techniques to detect one or more first vehicles. SSD is a method of detecting one or more first vehicles in a received image using a single deep learning neural network. For example, consider the environment shown in FIG. 3b. In this environment, a second vehicle 301 arrives at a predetermined location while traveling in a predetermined direction at night. In some embodiments, the predetermined direction of the second vehicle 301 may be eastward. In some embodiments, the predetermined location may be the position of the second vehicle 301 while acquiring one or more images of a curved mirror 303 at the road intersection, as shown in FIG. 3a.

[0049] The information receiving module 201 may be configured to receive a forward looking image of the second vehicle 301 once the second vehicle 301 reaches a predetermined position in a predetermined direction at night. The information receiving module 201 receives the forward looking image of the second vehicle 301 from an image capture unit 102 incorporated in the second vehicle 301. The image capture unit 102 may be activated to capture an image when the second vehicle 301 reaches a predetermined position in a predetermined direction at night.

[0050] Once the ROI identification module 202 receives the images, it identifies one or more ROIs based on the pre-stored data 211 by comparing the images captured at night with the pre-stored data 211. In some embodiments, the pre-stored data 211 may be collected during the day, as described in FIG. 3a. In some embodiments, when the first vehicle 302 of FIG. 3b approaches the road intersection at night, the curved mirror 303 located at the road intersection reflects light from the headlights of the first vehicle 302. The images captured at night include the reflection of light from the headlights of the first vehicle 302. In some embodiments, the ROI identification module 202 identifies one or more ROIs in the captured images. Furthermore, once one or more ROIs are identified in the captured images, the presence or absence of light is identified within the one or more ROIs.

[0051] The vehicle detection module 205 may be configured to detect a first vehicle 302 approaching a road intersection if it identifies the presence of light within one or more ROIs. In some embodiments, the vehicle detection module 205 detects the first vehicle 302 at night based on light reflections 305. In some embodiments, the light reflections 305 may be high or low intensity depending on the distance of the first vehicle 302 from the road intersection. In some embodiments, the detection of the first vehicle 301 may be referred to as vehicle detection data 212 and stored in the memory 107. For example, the presence of light within one or more ROIs may be a reflection of the light 305. The reflection of the light 305 may indicate the approach of the first vehicle 302 from the road intersection. A low reflection of the light 305 within one or more ROIs may indicate that the first vehicle 302 is far away from the road intersection. In an alternative embodiment, a high reflection of light 305 within one or more ROIs may indicate that the first vehicle 302 is very close to the road intersection. In an alternative embodiment, the reflection of light 305 may indicate a coverage of light within one or more ROIs. In an alternative embodiment, a low reflection of light 305 may indicate that the first vehicle 302 is far from the road intersection due to a low coverage of light within one or more ROIs. In an alternative embodiment, a high reflection of light 305 may indicate that the first vehicle 302 is close to the road intersection due to a high coverage of light within one or more ROIs.

[0052] The action initiation module 206 may be configured to initiate one or more actions depending on one or more characteristics of the light upon detecting the first vehicle 302. In some embodiments, the one or more actions may include alerting the driver of the second vehicle 301, activating the braking system of the second vehicle 301, etc. In some embodiments, the one or more actions may be referred to as action data 213 and stored in the memory 107. For example, consider the environment shown in FIG. 3c. A first vehicle 302 may be detected by the vehicle detection module 205 using one or more object detection techniques. The action initiation module 206 may be configured to monitor one or more characteristics of the light upon detecting the first vehicle 302. In some embodiments, the vehicle detection module 205 and the action initiation module 206 may be integrated to detect the first vehicle 302, initiate one or more actions upon detecting the first vehicle 302, and monitor one or more characteristics of the light. In some embodiments, one or more characteristics that may be monitored may be the intensity of light reflected from the curved mirror 303. For example, consider a case where the first vehicle 302 is moving away from a road intersection. In such a case, the intensity of the light reflected from the curved mirror 303 may be reduced. FIG. 3c illustrates a low intensity of light reflected from the curved mirror 303. In some embodiments, the intensity of the reflected light may be referred to as a low intensity of light 306. If the action initiation module 206 detects a low intensity of light 306, it may be configured to alert the driver of the second vehicle 301 upon the arrival of the first vehicle 302. The action initiation module 206 may alert the driver of the second vehicle 301 by providing either an audio message, a beep, or a visual message that causes the second vehicle 301 to stop.

[0053] In an alternative embodiment, the one or more actions may include activating a braking system of the second vehicle 301 to stop the second vehicle 301. For example, consider the environment shown in FIG. 3d. Consider that a first vehicle 302 may be detected by the vehicle detection module 205 using one or more object detection techniques. The action initiation module 206 may be configured to monitor the intensity of light reflected from the curved mirror 303 upon detecting the first vehicle 302. In some embodiments, consider a case where the first vehicle 302 is very close to a road intersection. In such a case, the intensity of the light reflected from the curved mirror 303 may be very high. FIG. 3d illustrates that the intensity of the light reflected from the curved mirror 303 is very high. In some embodiments, the intensity of the reflected light may be referred to as a high intensity of light 307. Upon detecting the high intensity of light 307, the action initiation module 206 may be configured to activate the braking system of the second vehicle 301 to automatically stop the second vehicle 301. The action initiation module 206 stops the second vehicle 301 to avoid an accident with the first vehicle 302 .

[0054] Other data 214 may store data including temporary data and temporary files generated by modules that perform various functions in detection system 101. One or more modules 108 may include other modules 207 that perform various miscellaneous functions in detection system 101. It will be appreciated that such modules may be represented as a single module or as a combination of different modules.

[0055] FIG. 4 shows a flow diagram illustrating an exemplary method for detecting one or more first vehicles using curved mirrors at a road intersection, according to some embodiments of the present disclosure.

[0056] In block 401, the information receiving module 201 may be configured to receive a forward looking image of the second vehicle 103 at night. In some embodiments, the forward looking image of the second vehicle 103 may be received when the second vehicle 103 reaches a predetermined location while traveling in a predetermined direction. In some embodiments, the predetermined location and predetermined orientation of the second vehicle 103 may be generated during the day from one or more images of a forward view of the second vehicle 103. In some embodiments, the one or more images may be acquired to identify the presence of one or more curved mirrors near a road intersection. If the presence of one or more curved mirrors is identified, the predetermined location and predetermined orientation of the second vehicle 103 may be stored as pre-stored data 211. The pre-stored data 211 also indicates the location of the one or more curved mirrors in the one or more images, which may be stored as a region of interest for the one or more images.

[0057] At block 402, the ROI identification module 202 may be configured to identify one or more ROIs from one or more images received during the night. In some embodiments, the one or more ROIs may be identified based on pre-stored data 211 regarding the second vehicle 103. The one or more ROIs indicate the location of one or more curved mirrors within the one or more images.

[0058] In block 403, the light identification module 203 may be configured to identify the presence of light within one or more ROIs. In some embodiments, the presence of light can be identified by one or more image classification algorithms. The one or more image classification algorithms may use one or more images to identify whether light is present within one or more ROIs in the one or more images. In an alternative embodiment, one or more other algorithms or techniques known to those skilled in the art may be implemented to identify the presence of light within one or more ROIs in the one or more images.

[0059] In block 404, the vehicle detection module 205 may be configured to detect one or more first vehicles approaching the road intersection. In some embodiments, the one or more first vehicles may be detected based on the presence of light within one or more ROIs. Upon detecting the one or more first vehicles, the action initiation module 206 may be configured to monitor one or more characteristics of the light within the one or more ROIs. In some embodiments, the action initiation module 206 monitors the intensity of the light and performs at least one action. In some embodiments, the action initiation module 206 monitors one or more characteristics of the light to identify the approach of one or more first vehicles from the road intersection. For example, the action initiation module 206 may be configured to alert the driver of the second vehicle 103 upon the arrival of one or more first vehicles if the intensity of the light is low. In another example, the action initiation module 206 may be configured to activate a braking system of the second vehicle 103 when the light intensity is high to automatically stop the second vehicle 103 and avoid a collision or accident with one or more first vehicles.

[0060] 4, the method 400 may include one or more blocks that perform operations within the detection system 101. The method 400 may be described in the general context of computer-executable instructions. Generally, computer-executable instructions may include routines, programs, objects, components, data structures, procedures, modules, and functions that perform particular functions or implement particular abstract data types.

[0061] The order in which method 400 is described is not intended to be limiting, and any number of the above-described method blocks may be combined in any order to perform the method. Also, individual blocks may be deleted from the method without departing from the scope of the subject matter described herein. Furthermore, the method may be performed by any suitable hardware, software, firmware, or combination thereof.

[0062] One embodiment of the present disclosure avoids collisions / accidents with a second vehicle near a road intersection by detecting one or more first vehicles using one or more ROIs in one or more images.

[0063] One embodiment of the present disclosure provides a strategy for detecting one or more curved mirrors that are poorly visible at night using one or more ROIs in one or more images.

[0064] One embodiment of the present disclosure avoids a collision between a second vehicle and one or more first vehicles near a road intersection by alerting the driver of the second vehicle via an HMI.

[0065] One embodiment of the present disclosure avoids an accident between a second vehicle and one or more first vehicles by automatically activating a braking system of the second vehicle to stop the second vehicle.

[0066] Computing Systems 5 illustrates a block diagram of an exemplary computer system 500 for implementing embodiments consistent with the present disclosure. In some embodiments, the computer system 500 is used to implement the detection system 101, which performs detection of one or more first vehicles at a road intersection using curved mirrors. The computer system 500 may include a central processing unit ("CPU" or "processor") 502. The processor 502 may include at least one data processor that performs processing in a virtual memory area network. The processor 502 may include a special-purpose processing unit such as an integrated system (bus) controller, a memory management controller, a floating-point unit, a graphics processing unit, a digital signal processing unit, or the like.

[0067] The processor 502 may be placed in communication with one or more input / output (I / O) devices 509, 510 via an I / O interface 501. The I / O interface 501 may employ communication protocols / methods including, but not limited to, audio, analog, digital, mono, RCA, stereo, IEEE-1394, serial bus, universal serial bus (USB), infrared, PS / 2, BNC, coaxial, component, composite, digital visual interface (DVI), high-definition multimedia interface (HDMI), radio frequency (RF) antenna, S-video, VGA, IEEE 802.n / b / g / n / x, Bluetooth, cellular (e.g., code division multiple access (CDMA), high-speed packet access (HSPA+), global system for mobile communications (GSM), long-term evolution (LTE), WiMax, etc.).

[0068] Computer system 500 can communicate with one or more I / O devices 509, 510 using I / O interface 501. For example, input device 509 can be an antenna, keyboard, mouse, joystick, (infrared) remote control, camera, card reader, fax machine, dongle, biometric reader, microphone, touch screen, touch pad, trackball, stylus, scanner, storage device, transceiver, video device / source, etc. Output device 510 can be a printer, fax machine, video display (e.g., cathode ray tube (CRT), liquid crystal display (LCD), light emitting diode (LED), plasma, plasma display panel (PDP), organic light emitting diode display (OLED), etc.), audio speaker, etc.

[0069] In some embodiments, computer system 500 may include detection system 101. Processor 502 may be in communication with communication network 511 via network interface 503. Network interface 503 may be capable of communicating with communication network 511. Network interface 503 may employ a connection protocol including, but not limited to, a direct connection, Ethernet (e.g., twisted pair 10 / 100 / 1000BaseT), Transmission Control Protocol / Internet Protocol (TCP / IP), Token Ring, IEEE 802.11a / b / g / n / x, etc. Communication network 511 may include, but is not limited to, a direct interconnect, a local area network (LAN), a wide area network (WAN), a wireless network (e.g., using a wireless application protocol), the Internet, etc. Computer system 500 may communicate with image capture unit 512 and second vehicle 513 using network interface 503 and communication network 511 to perform detection of one or more first vehicles using a curved mirror at a road intersection. The network interface 503 may employ connection protocols including, but not limited to, direct connect, Ethernet (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.

[0070] The communications network 511 may include, but is not limited to, direct interconnections, e-commerce networks, peer-to-peer (P2P) networks, local area networks (LANs), wide area networks (WANs), wireless networks (e.g., using wireless application protocols), the Internet, Wi-Fi, etc. The communications network 511 may be a dedicated network or a shared network and represents an association of different types of networks that communicate with each other using various protocols, such as, for example, Hypertext Transfer Protocol (HTTP), Transmission Control Protocol / Internet Protocol (TCP / IP), Wireless Application Protocol (WAP), etc. Additionally, the communications network 511 may include various network devices, including routers, bridges, servers, computing devices, storage devices, etc.

[0071] In some embodiments, the processor 502 may be placed in communication with memory 505 (e.g., RAM, ROM, etc., not shown in FIG. 5 ) via a storage interface 504. The storage interface 504 may be connected to memory 505, including, but not limited to, memory drives, removable disk drives, etc., employing connection protocols such as Serial Advanced Technology Attachment (SATA), Integrated Drive Electronics (IDE), IEEE-1394, Universal Serial Bus (USB), Fibre Channel, Small Computer System Interface (SCSI), etc. The memory drives may further include drum, magnetic disk drives, magneto-optical drives, optical drives, redundant array of independent disks (RAID), solid state memory devices, solid state drives, etc.

[0072] Memory 505 may store a collection of program or database components, including, but not limited to, a user interface 506, an operating system 507, a web browser 508, etc. In some embodiments, computer system 500 may store user / application data, such as data, variables, records, etc., as described in this disclosure. Such databases may be implemented as fault-tolerant, relational, scalable, secure databases, such as Oracle® or Sybase®.

[0073] The operating system 507 may enable resource management and operation of the computer system 500. Examples of operating systems include, but are not limited to, APPLE MACINTOSH® OS X, UNIX®, UNIX-like system distributions (e.g., BERKELEY SOFTWARE DISTRIBUTION® (BSD), FREEBSD®, NETBSD®, OPENBSD®, etc.), LINUX distributions (e.g., RED HAT®, UBUNTU®, KUBUNTU®, etc.), IBM® OS / 2, MICROSOFT® WINDOWS® (XP®, VISTA® / 7 / 8, 10, etc.), APPLE®, IOS®, GOOGLE®, ANDROID®, BLACKBERRY®, OS, etc.

[0074] In some embodiments, computer system 500 may implement program elements stored on a web browser 508. Web browser 508 may be a hypertext browsing application such as Microsoft Internet Explorer, Google Chrome, Mozilla Firefox, or Apple Safari. Secure web browsing may be provided using Hypertext Transport Protocol Secure (HTTPS), Secure Sockets Layer (SSL), Transport Layer Security (TLS), or the like. Web browser 508 may utilize functionality such as AJAX, DHTML, Adobe Flash, JavaScript, Java, and application programming interfaces (APIs). In some embodiments, computer system 500 may implement program elements stored on a mail server. The mail server may be an Internet mail server such as Microsoft Exchange. The mail server may utilize functionality such as ASP, ActiveX, ANSI C++ / C#, Microsoft.NET, Common Gateway Interface (CGI) scripting, Java, JavaScript, PERL, PHP, Python, WebObjects, or the like. The mail server may utilize communication protocols such as Internet Message Access Protocol (IMAP), Messaging Application Programming Interface (MAPI), Microsoft Exchange, Post Office Protocol (POP), Simple Mail Transfer Protocol (SMTP), etc. In some embodiments, computer system 500 may implement program elements stored in a mail client. The mail client may be a mail viewing application such as Apple Mail, Microsoft Entourage, Microsoft Outlook, Mozilla Thunderbird, etc.

[0075] Additionally, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory capable of storing processor-readable information or data. Thus, a computer-readable storage medium may store instructions executed by one or more processors, including instructions that cause the processor to perform steps or stages consistent with embodiments described herein. It should be understood that the term "computer-readable medium" includes tangible objects and excludes carrier waves and transient signals, i.e., non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, non-volatile memory, hard drives, compact disc (CD) ROMs, DVDs, flash drives, disks, and any other known physical storage medium.

[0076] The operations described above may be implemented as a method, system, or article of manufacture using standard programming and / or engineering techniques to generate software, firmware, hardware, or any combination thereof. The operations described above may also be implemented as code stored on a "non-transitory computer-readable medium," from which a processor can read and execute the code. The processor may be a microprocessor and / or processor capable of processing and executing queries. Non-transitory computer-readable media may include media such as magnetic storage media (e.g., hard disk drives, floppy disks, tape, etc.), optical storage (e.g., CD-ROMs, DVDs, optical disks, etc.), volatile and non-volatile memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, DRAMs, SRAMs, flash memory, firmware, programmable logic, etc.). Furthermore, non-transitory computer-readable media may include any computer-readable media that is not transitory. Code implementing the operations described above may also be implemented in hardware logic (e.g., an integrated circuit chip, a programmable gate array (PGA), an application-specific integrated circuit (ASIC), etc.).

[0077] An "article of manufacture" includes non-transitory computer-readable media and / or hardware logic on which code may be embodied. An apparatus encoded with code implementing embodiments of the operations described above may include computer-readable media or hardware logic. Of course, those skilled in the art will recognize that many variations on the configuration may be made without departing from the scope of the present invention, and that the article of manufacture may include any suitable information-bearing medium known in the art.

[0078] The terms "one embodiment," "embodiment," "embodiments," "the embodiment," "the embodiments," "one or more embodiments," "some embodiments," and "one embodiment" mean "one or more, but not all, embodiments of the invention," unless expressly specified otherwise.

[0079] The terms "including," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.

[0080] The listing of items does not imply that any or all items are mutually exclusive, unless expressly specified otherwise.

[0081] The terms "a," "an," and "the" mean "one or more," unless expressly specified otherwise.

[0082] A description of an embodiment having multiple elements in communication with each other does not imply that all such elements are required, but rather describes a variety of optional elements to illustrate a wide range of possible embodiments of the present invention.

[0083] Where a single device or article is described herein, it will be readily apparent that multiple devices / articles (whether or not cooperating) may be used rather than the single device / article. Similarly, where more than one device or article is described herein (whether or not cooperating), it will be readily apparent that a single device / article may be used rather than the more than one device or article, or that a different number of devices / articles may be used rather than the number of devices or programs listed. The functionality and / or features of a device may alternatively be implemented by one or more other devices not explicitly described as having such functionality / features. Thus, other embodiments of the present invention may not include the device itself.

[0084] The operations depicted in Figure 4 indicate that certain events occur in a particular order. In alternative embodiments, certain operations may be performed in a different order, modified, or removed. Furthermore, steps may be added to the logic described above and still be consistent with the embodiments described above. Furthermore, operations described herein may be performed sequentially, or certain operations may be processed in parallel. Furthermore, operations may be performed by a single processing unit or by distributed processing units.

[0085] Finally, the language used in this specification has been selected primarily for readability and descriptive purposes, and not necessarily to define or encompass inventive subject matter. Accordingly, the scope of the invention is intended to be limited not by this detailed description, but by the claims issued in an application based thereon. Accordingly, the disclosure of multiple embodiments of the invention is intended to present, but not limit, the scope of the invention, which is set forth in the following claims.

[0086] While various aspects and embodiments have been disclosed herein, other aspects and embodiments will become apparent to those skilled in the art. The various aspects and embodiments disclosed herein are illustrative and not intended to be limiting, with the true scope and spirit being indicated by the following claims. The present application relates to the invention described in the claims, but also includes the following as other aspects. 1. A method for detecting one or more first vehicles at a road intersection using a curved mirror, said method being performed by a detection system (101) mounted on a second vehicle (103); A) receiving, at night, a forward-looking image of a second vehicle (103) when the second vehicle (103) reaches a predetermined position in a predetermined direction; B) identifying one or more regions of interest (ROIs) from the images received in step A) based on pre-stored data (211) relating to the second vehicle (103), such that the one or more ROIs indicate the location of one or more curved mirrors located at a road intersection within the acquired images; C) identifying the presence of light within the one or more ROIs identified in step B); D) detecting that one or more first vehicles are arriving at the road intersection if the light is identified within the one or more ROIs in step C). 2. In step D), when the one or more first vehicles are detected at the road intersection, monitoring one or more characteristics of the light within the one or more ROIs; Based on one or more of the above characteristics, alerting a driver of the second vehicle (103) to the arrival of the one or more first vehicles; activating a braking system of the second vehicle (103) to automatically stop the second vehicle (103). 3. 3. The method of claim 1 or 2, further comprising collecting the pre-stored data (211) for the second vehicle (103) during the daytime. 4. The step of collecting the pre-stored data (211) during the daytime further comprises: acquiring one or more images of the forward looking view of the second vehicle (103) during daylight hours to monitor the presence of one or more curved mirrors at a road intersection; and if the one or more curved mirrors are identified in one of the one or more images, generating the pre-stored data (211) for the second vehicle (103) using the position of the second vehicle (103) when the image was acquired as the predetermined position, the positions of the one or more curved mirrors in the image as the one or more ROIs, and the direction of the second vehicle (103) at the positions as the predetermined direction. 5. A detection system (101) for detecting one or more first vehicles at a road intersection using a curved mirror, the detection system (101) being mounted on a second vehicle (103), comprising: a processor (105); A system comprising: a memory (107) communicatively coupled to the processor (105), the memory (107) storing processor-executable instructions that, when executed, cause the processor (105) to perform the method described in any one of 1 to 4 above. 6. 6. The detection system (101) of claim 5, further comprising an image capture unit (102) for capturing the forward looking image of the second vehicle (103) for use in step A). 7. 7. The detection system (101) according to any one of claims 5 or 6, further comprising a plurality of sensors for identifying the presence of light within said one or more ROIs for use in step D). 8. a warning unit for warning the driver of the second vehicle (103) upon the arrival of the one or more first vehicles; and / or The detection system (101) described in any one of 5 to 7 above, further including an activation unit that activates the brake system of the second vehicle (103) to automatically stop the second vehicle (103). 9. receiving the forward looking image of the second vehicle (103) for use in step A); and / or providing warning and / or activation data for the second vehicle (103) based on the one or more characteristics of the light; The detection system (101) according to any one of the above items 5 to 8, further comprising an interface for: 10. A computer program product comprising instructions that, when executed by a computer, cause the computer to perform steps 1 to 4 above. 11. A computer program product comprising instructions for causing the detection system (101) described in any of the above items 5 to 9 to perform the steps of the method described in any of the above items 1 to 4. 12. A computer-readable storage medium containing instructions that, when executed by a computer, cause the computer to perform the steps of the methods described in 1 to 4 above. [Explanation of symbols]

[0087] 100 Example Environment 101 Detection System 102 Image acquisition unit 103 Second vehicle 104 Communication Network 105 processors 106 I / O interfaces 107 memory 108 modules 109 Data 201 Information Receiving Module 202 ROI Identification Module 203 Optical Identification Module 204 Pre-stored Data Collection Module 205 Vehicle Detection Module 206 Action Initiation Module 207 other modules 208 Image Data 209 ROI Data 210 Optical Data 211 Pre-saved data 212 Vehicle Detection Data 213 Action Data 214 Other Data 301 Second vehicle 302 First car 303 Curved mirror 304 First vehicle reflection 305 Reflection of Light 306 Low Light Intensity 307 High Light Intensity 500 Computer Systems 501 I / O interface 502 processor 503 Network Interface 504 Storage Interface 505 memory 506 User Interface 507 Operating Systems 508 Web Browser 509 Input Devices 510 Output Devices 511 Communication Network 512 Image acquisition unit 513 Second vehicle

Claims

1. 1. A method for detecting one or more first vehicles at a road intersection using a curved mirror, said method being performed by a detection system (101) mounted on a second vehicle (103); A) receiving, at night, a forward-looking image of a second vehicle (103) when said second vehicle (103) reaches a predetermined position in a predetermined direction; B) identifying one or more regions of interest (ROIs) from the images received in step A) based on pre-stored data (211) relating to the second vehicle (103), such that the one or more ROIs indicate the location of one or more curved mirrors located at the road intersection within the acquired images; C) identifying the presence of light within the one or more ROIs identified in step B); D) detecting the arrival of one or more first vehicles at the road intersection if the light is identified within the one or more ROIs in step C).

2. Upon detecting the one or more first vehicles at the road intersection in step D), monitoring one or more characteristics of the light within the one or more ROIs; Based on one or more of the above characteristics, alerting a driver of said second vehicle (103) to the arrival of said one or more first vehicles; activating a braking system of the second vehicle (103) to automatically stop the second vehicle (103).

3. The method of claim 1, further comprising collecting the pre-stored data (211) for the second vehicle (103) during daytime.

4. The step of collecting the pre-stored data (211) during the daytime further comprises: acquiring one or more images of the forward looking view of the second vehicle (103) during daylight hours to monitor the presence of one or more curved mirrors at a road intersection; and if the one or more curved mirrors are identified in one of the one or more images, generating the pre-stored data (211) for the second vehicle (103) using the position of the second vehicle (103) when the image was acquired as the predetermined position, the positions of the one or more curved mirrors in the image as the one or more ROIs, and the direction of the second vehicle (103) at the position as the predetermined direction.

5. A detection system (101) for detecting one or more first vehicles at a road intersection using a curved mirror, the detection system (101) being mounted on a second vehicle (103), comprising: a processor (105); 10. A system comprising: a memory communicatively coupled to the processor, the memory storing processor-executable instructions that, when executed, cause the processor to perform the method of claim 1.

6. 6. The detection system (101) of claim 5, further comprising an image capture unit (102) for capturing the forward looking image of the second vehicle (103) for use in step A).

7. 7. The detection system (101) of claim 5 or 6, further comprising a plurality of sensors for identifying the presence of light within said one or more ROIs for use in step D).

8. a warning unit for warning the driver of the second vehicle (103) upon the arrival of the one or more first vehicles; and / or 7. The detection system (101) of claim 5 or 6, further comprising an activation unit for activating a braking system of the second vehicle (103) to automatically stop the second vehicle (103).

9. receiving the forward looking image of the second vehicle (103) for use in step A); and / or providing warning and / or activation data for the second vehicle (103) based on the one or more characteristics of the light; The detection system (101) according to claim 5 or 6, further comprising an interface for

10. A computer program comprising instructions for causing a computer to carry out the steps of claims 1 to 4.

11. The detection system (101) according to claim 5 A computer program comprising instructions for carrying out the steps of the method of claim 1.

12. A computer-readable storage medium containing instructions that, when executed by a computer, cause the computer to perform the steps of the method according to claims 1-4.

Images