Flood risk assessment system for vehicle

Abstract

A flood risk assessment system for a vehicle includes: one or more cameras oriented to collect image data of a flood located along a road on which the vehicle travels; a time-of-flight sensor system that directs the laser beam to a plurality of target points distributed along the flood; and one or more controllers in electronic communication with the one or more cameras and the time-of-flight sensor system. The one or more controllers execute instructions to determine a risk associated with crossing the flood at each of a plurality of target points located along the flood based on a flow rate of the flood and a depth of the flood. The one or more controllers generate notifications indicative of risks associated with crossing the flood at a plurality of target points located along the flood.

Description

Technical Field

[0001] The present disclosure relates to a flood risk assessment system for a vehicle that determines flood depth along a roadway and creates a notification indicating the risk associated with the vehicle traveling through the flood based on the flood depth and flow velocity. Background Art

[0002] Sometimes, roads may be flooded due to severe weather conditions, such as severe storms. It will be appreciated that even relatively shallow flooding may create complications when vehicles attempt to cross a flooded road. Furthermore, flood depth is not always clear to drivers. For example, approximately fifteen centimeters (approximately six inches) of flooding along a roadway may reach the bottom of many passenger vehicles, which may result in loss of control and stalling. Additionally, approximately thirty centimeters (approximately one foot) of flooding may cause many vehicles to float away. However, there are currently no systems that can notify drivers when flooding is deep enough to cause problems such as loss of control or stalling.

[0003] Therefore, while current vehicles achieve their intended purpose, there is a need in the art for a method of indicating flood depth located along a roadway. Summary of the invention

[0004] According to several aspects, a flood risk assessment system for a vehicle is disclosed and includes: one or more cameras oriented to collect image data of a flood located along a road on which the vehicle is traveling; a time-of-flight sensor system that directs a laser beam to a plurality of target points distributed along the flood; and one or more controllers in electronic communication with the one or more cameras and the time-of-flight sensor system. The time-of-flight sensor system receives polarized backscattered laser light when the laser beam is reflected from an upper surface of the flood, and the time-of-flight sensor system receives depolarized backscattered laser light when the laser beam is reflected from a lower surface of the flood. The one or more controllers execute instructions to estimate the flow velocity of the flood at the plurality of target points by analyzing the image data collected by the one or more cameras based on one or more video-based motion estimation algorithms. The one or more controllers calculate the depth of the flood at the plurality of target points based on the difference in flight time between a first time point at which the time-of-flight sensor system receives the polarized backscattered laser light and a second time point at which the time-of-flight sensor system receives the depolarized backscattered laser light. The one or more controllers determine the associated risk of crossing the flood at each of the plurality of target points along the flood based on the flow velocity of the flood and the depth of the flood. The one or more controllers generate a notification indicating the risk associated with crossing the flood at the plurality of target points located along the flood.

[0005] In another aspect, the flood risk assessment system further includes an augmented reality heads-up display system in electronic communication with the one or more controllers, wherein the augmented reality heads-up display includes a graphics projection device that generates an image on a windshield of the vehicle.

[0006] In yet another aspect, one or more controllers execute instructions to instruct a graphic projection device of an augmented reality head-up display system to generate a graphic on a windshield of a vehicle, wherein the graphic represents a notification indicating a risk associated with traversing flood water.

[0007] In one aspect, the graphic is a color-coded bar overlaid on the flood.

[0008] In another aspect, the color-coded strip includes a plurality of individual portions, each of the plurality of individual portions corresponding to one of the plurality of target points.

[0009] In yet another aspect, individual portions of the color-coded bar are designated red to provide a warning indicating that the crossing risk at the corresponding target point is unacceptable.

[0010] In one aspect, a time-of-flight sensor system includes a pulsed illumination source and a fiber optic cable.

[0011] In another aspect, a pulsed illumination source generates a laser beam that is received by a fiber optic cable, wherein the laser beam exits a tip of the fiber optic cable.

[0012] In yet another aspect, a time-of-flight sensor system includes an actuation element that directs a laser beam emitted from a tip of a fiber optic cable toward one of a plurality of target points disposed along a floodwater.

[0013] In one aspect, the time-of-flight sensor system includes a first detector, a second detector, and a polarization beam splitter, wherein the polarization beam splitter separates polarized backscattered laser light and depolarized backscattered laser light, and the polarized backscattered laser light is received by the first detector and the depolarized backscattered laser light is received by the second detector.

[0014] In another aspect, one or more controllers store one or more lookup tables that provide depth and velocity combination values ​​representing the product of a flow velocity of a flood and a depth of the flood.

[0015] In yet another aspect, the one or more controllers execute instructions to compare a depth and velocity combination value corresponding to a particular target point among the plurality of target points along the floodwater to a threshold vehicle instability value, and in response to determining that the depth and velocity combination value is less than the threshold vehicle instability value, determine that the risk of crossing the floodwater at the particular target point is acceptable. The threshold vehicle instability value is a function of one or more vehicle parameters.

[0016] In one aspect, the threshold vehicle instability value is determined based on the following equation:

[0017]

[0018] Where v represents the flow velocity of the flood at the threshold vehicle instability value, F r represents the restoring force at the vehicle axle, ρ represents the density of water, C D The drag coefficient of the vehicle, A tyre represents the area of ​​the tires which are the part of the vehicle in contact with the ground, and D represents the flood depth.

[0019] In another aspect, the flood risk assessment system further includes a lighting device in electronic communication with the one or more controllers, wherein the lighting device projects a light beam onto a surface of floodwater and the light beam is oriented parallel to a direction of travel of the vehicle.

[0020] In yet another aspect, one or more controllers determine the presence of road damage located beneath floodwater based on a plurality of images captured by one or more cameras, wherein the plurality of images represent light beams projected by lighting devices along the floodwater.

[0021] In one aspect, one or more controllers determine that a risk of crossing flood water at a particular destination point is unacceptable in response to determining that road damage exists at the particular destination point.

[0022] In another aspect, a method for generating a notification by a flood risk assessment system of a vehicle is provided. The method includes receiving, by one or more controllers, image data of a flood located along a road on which the vehicle is traveling, collected by one or more cameras. The method includes estimating, by the one or more controllers, a flow rate of the flood at a plurality of target points located along the flood by analyzing the image data collected by the one or more cameras based on one or more video-based motion estimation algorithms. The method also includes calculating the depth of the flood at the plurality of target points based on a time-of-flight difference between a first time point when a time-of-flight sensor system receives polarized backscattered laser light and a second time point when a time-of-flight sensor system receives depolarized backscattered laser light, wherein the time-of-flight sensor system directs a laser beam to the plurality of target points disposed along the flood, and receives polarized backscattered laser light when the laser beam is reflected from an upper surface of the flood, and receives depolarized backscattered laser light when the laser beam is reflected from a lower surface of the flood. The method also includes determining a risk associated with crossing the flood at each of the plurality of target points located along the flood based on the flow rate of the flood and the depth of the flood. The method also includes generating a notification indicating the risk associated with crossing the flood at the plurality of target points located along the flood.

[0023] On the other hand, a flood risk assessment system for a vehicle is disclosed, the system comprising: one or more cameras oriented to collect image data of floods located along a road traveled by the vehicle; a time-of-flight sensor system that directs a laser beam to a plurality of target points set along the flood; an augmented reality head-up display system including a graphic projection device that generates an image on a windshield of the vehicle; and one or more controllers in electronic communication with the one or more cameras, the time-of-flight sensor system, and the augmented reality head-up display. When the laser beam is reflected from the upper surface of the flood, the time-of-flight sensor system receives polarized backscattered laser light, and when the laser beam is reflected from the lower surface of the flood, the time-of-flight sensor system receives depolarized backscattered laser light. The one or more controllers execute instructions to estimate the flow rate of the flood at the plurality of target points by analyzing the image data collected by the one or more cameras based on one or more video-based motion estimation algorithms. The one or more controllers calculate the depth of the flood at the plurality of target points based on the difference in flight time between a first time point at which the time-of-flight sensor system receives the polarized backscattered laser light and a second time point at which the time-of-flight sensor system receives the depolarized backscattered laser light. The one or more controllers determine a risk associated with crossing the floodwater at each of a plurality of target points located along the floodwater based on a flow rate of the floodwater and a depth of the floodwater. The one or more controllers instruct a graphic projection device of the augmented reality head-up display system to generate a graphic on the windshield of the vehicle, wherein the graphic represents a notification indicating the risk associated with crossing the floodwater at the plurality of target points located along the floodwater.

[0024] In another aspect, the graphic is a color-coded bar overlaid on the flood.

[0025] In yet another aspect, the color-coded strip includes a plurality of individual portions, each of the plurality of individual portions corresponding to one of the plurality of target points.

[0026] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.

[0028] Figure 1 is a schematic diagram of a vehicle including a disclosed flood risk assessment system including one or more controllers in electronic communication with a time-of-flight sensor system and an augmented reality head-up display system according to an exemplary embodiment;

[0029] Figure 2Ashows a driver observing floodwater disposed along a road through a windshield of a vehicle according to an exemplary embodiment;

[0030] Figure 2B According to an exemplary embodiment, Figure 1 Notification projected by an augmented reality head-up display system as shown;

[0031] Figure 3 FIG. 1 is a diagram showing a method according to an exemplary embodiment. Figure 1 A diagram of the software architecture of one or more controllers shown;

[0032] Figure 4 According to an exemplary embodiment Figure 1 A schematic diagram of a time-of-flight sensor system is shown; and

[0033] Figure 5 is a process flow diagram illustrating a method for generating, by a flood risk assessment system, a notification indicating a risk of crossing a flood, according to an exemplary embodiment. DETAILED DESCRIPTION

[0034] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.

[0035] Reference Figure 1 , an exemplary flood risk assessment system 10 for a vehicle 12 is shown. It should be understood that the vehicle 12 can be any type of vehicle, such as, but not limited to, a car, a truck, a sport utility vehicle, a van, or an RV. The flood risk assessment system 10 includes one or more controllers 20 that electronically communicate with one or more cameras 22, one or more time-of-flight sensor systems 24, an augmented reality head-up display system 26, and lighting devices 28. As explained below, the flood risk assessment system 10 determines the depth ( Figure 2A ), and creates a notification 44 indicating the risk of crossing the flood 40 based on the flood depth ( Figure 2B ).

[0036] One or more cameras 22 are oriented to collect image data of the environment located in front of the vehicle 12. It should be understood that image data refers to both images and videos representing the environment surrounding the vehicle 12. The time-of-flight sensor system 24 is oriented to face the front of the vehicle 12. Some examples of the time-of-flight sensor system 24 include, but are not limited to, LiDAR and single-photon avalanche diode (SPAD) sensors. The augmented reality head-up display system 26 includes a graphic projection device 34, which is configured to generate an image on a windshield 36 of the vehicle 12. The graphic projection device 34 includes a projection device with an excitation light for projecting an image onto the windshield 36 of the vehicle 12. Some examples of projection devices include, but are not limited to, optical collimators, laser projectors, and digital light processing projectors (DLP). The lighting device 28 is a flood 40 ( Figure 2A ) on a surface of the vehicle, wherein the light beam is oriented parallel to the direction of travel of the vehicle. For example, in one non-limiting embodiment, the lighting device 28 is a laser line projector including a laser diode, a collimating lens, and a line generating optical device.

[0037] Reference Figure 1 , Figure 2A and Figure 2B , the flood risk assessment system 10 determines that a flood 40 ( Figure 2A The flood risk assessment system 10 also creates a notification 44 indicating the risk of crossing the flood 40 based on the flood depth ( Figure 2B ). Figure 2B In the example shown, the graphic 38 generated by the graphic projection device 34 of the augmented reality head-up display system 26 and displayed on the windshield 36 of the vehicle 12 represents the notification 44. Figure 2B In the example shown, the graphic 38 is a color-coded bar 48 overlaid on floodwater 40 located along a road 42. As explained below, the color-coded bar 48 indicates which areas of the floodwater 40 are acceptable or unacceptable for the vehicle 12 to cross, wherein a warning is provided to indicate which areas of the floodwater 40 are unacceptable to cross. Specifically, as explained below, individual portions 90 of the color-coded bar 48 are colored red to provide a warning indicating that the risk of crossing the floodwater 40 is unacceptable. Although Figure 2B The notification 44 is shown as a graphic 38 displayed on the windshield 36, but it should be understood that the notification 44 is not limited to graphics generated by an augmented reality head-up display. For example, in another embodiment, the notification 44 can be a voice instruction notifying the occupants of the vehicle 12 not to cross flood water. In fact, it should be understood that although the augmented reality head-up display system 26 is shown in the figures, the notification 44 can be generated by any type of driver information system.

[0038] Figure 3 It is shown Figure 1 FIG. 1 is a diagram of the software architecture of one or more controllers 20 shown. Figure 1 , Figure 2A and Figure 3 , the one or more controllers 20 include a flow rate module 50 that estimates the flow rate of flood water 40 located along the road 42, a depth assessment module 52 that calculates the depth of the flood water, a road damage module 54 for detecting road damage located below the flood water 40, a risk assessment module 56 that determines which areas of the flood water 40 are acceptable or unacceptable for the vehicle 12 to traverse, and a notification module 58 that instructs the graphic projection device 34 of the augmented reality head-up display system 26 to generate a graphic 38 on the windshield 36 of the vehicle 12.

[0039] Continue to refer to Figure 1 , Figure 2A and Figure 3 , one or more cameras 22 are oriented to collect image data of flood water 40 located along a road 42, wherein the image data is received by one or more controllers 20. A flow rate module 50 of the one or more controllers 20 estimates the flow rate of the flood water 40 at a plurality of target points P by analyzing the image data collected by the one or more cameras 22 based on one or more video-based motion estimation algorithms. An example of a video-based motion estimation technique is a dense optical flow (DOF) algorithm, however, it should be understood that other methods may also be used. In a specific embodiment, the Farneback optical flow method (FOFM), which is a DOF algorithm, calculates the velocity of the flood water 40 at one of the target points P ( Figure 2A ), wherein the two consecutive frames are part of the image data collected by one or more cameras 22.

[0040] Specific reference Figure 2A and Figure 3 , the flow velocity module 50 of the one or more controllers 20 estimates the flow velocity of the flood water 40 at a plurality of target points P located along the width W of the flood water 40, where the width W extends between the opposing lane edges 46 of the road 42. It should be understood that the flow velocity of the flood water 40 may vary at different locations along the flood water 40, and therefore the flow velocity of the flood water 40 is determined at a plurality of points along the flood water 40 to obtain the flow velocity.

[0041] Figure 4is a schematic diagram of an exemplary time-of-flight sensor system 24. As described above, the time-of-flight sensor system 24 can be, for example, a LiDAR, a photon multiplier tube (PMT) in photon counting mode, or a single photon avalanche diode (SPAD) sensor. The time-of-flight sensor system 24 includes a pulsed illumination source 64, a first detector 66, a second detector 68, a polarization beam splitter 70, an actuating element 72, an optical cable 74, and an imaging lens 76. It should be understood that in an embodiment, the first detector 66 and the second detector 68 can be time-sensitive photon counters, and the polarization beam splitter 70 can be a polarization-sensitive fiber combiner / splitter. The pulsed illumination source 64 of the time-of-flight sensor system 24 generates a laser beam received by the optical cable 74, wherein the laser beam is horizontally polarized. The laser beam leaves the tip 80 of the optical cable 74 and is directed to the flood 40 located along the road 42. Specifically, the actuating element 72 guides the laser beam emitted by the tip 80 of the optical cable 74 to one of a plurality of target points P disposed along the width W of the flood 40. The actuating element 72 is any type of actuator that moves the tip 80 of the optical cable 74 to scan the flood water 40 at the target point P. For example, in one embodiment, the actuating element 72 is a piezoelectric actuator that moves in response to an applied voltage. The polarized backscattered laser light is reflected from the upper surface of the flood water 40, and the depolarized backscattered laser light is reflected from the lower surface of the flood water 40 (i.e., the surface of the road 42). It should be understood that the depolarized backscattered laser light also includes randomly polarized light.

[0042] Light reflected from the upper surface of the flood water 40 includes a different polarization state than light reflected from the lower surface of the flood water 40. Specifically, both the polarized backscattered laser light and the depolarized backscattered laser light are directed to the imaging lens 76 of the time-of-flight sensor system 24. The imaging lens 76 directs the polarized backscattered laser light and the depolarized backscattered laser light to the end 82 of the optical cable 74 and is received by the polarizing beam splitter 70. The polarizing beam splitter 70 separates the polarized backscattered laser light and the depolarized backscattered laser light, wherein the polarized backscattered laser light is received by the first detector 66 and the depolarized backscattered laser light is received by the second detector 68. It should be understood that the return photons associated with the polarized backscattered laser light and the depolarized backscattered laser light are time-stamped by the detectors 66, 68 and used to calculate the time-of-flight difference, as described below.

[0043] Reference Figure 2A , Figure 3 and Figure 4, the depth assessment module 52 of the one or more controllers 20 calculates the depth of the flood 40 at each target point P located along the road 42 based on the flight time difference between the first time point when the first detector 66 receives the polarized backscattered laser light and the second time point when the second detector 68 receives the depolarized backscattered laser light. It should be understood that the depth of the flood 40 measured by the time-of-flight sensor system 24 is oriented at a certain angle, and the depth of the flood 40 calculated by the depth assessment module 52 is adjusted to reflect the vertical depth.

[0044] Reference Figure 1 and Figure 2A , the road damage module 54 of the one or more controllers 20 determines the presence of road damage located below the floodwater 40 based on multiple images captured by the one or more cameras 22, wherein the multiple images represent beams of light projected by the lighting device 28 along the floodwater 40. A method for determining the presence of road damage is described in U.S. Patent Application No. 18 / 183,403 filed on March 14, 2023, the entire contents of which are incorporated herein by reference.

[0045] Reference Figure 1 , Figure 2A and Figure 3 As shown, the road damage module 54 of the one or more controllers 20 determines the presence of road damage located below the floodwater 40 by instructing the lighting device 28 to project a light beam onto the floodwater 40 in front of the vehicle 12. The light beam is a linear beam projected onto the floodwater 40 in front of the vehicle 12. It should be understood that when the light beam is projected onto a flat road surface or floodwater, the light beam appears to be approximately linear (i.e., straight). However, when projected onto an irregular road surface or floodwater (e.g., a road surface with deformations, such as potholes), the light beam is distorted and does not appear to be a straight line.

[0046] The one or more cameras 22 capture a plurality of images representing light beams projected by the lighting device 28 along the floodwater 40. The road damage module 54 of the one or more controllers 20 binarizes the plurality of images representing light beams captured by the one or more cameras 22 to create binary image data including the light beam being measured. The binary image data of the measured light beam is compared to a reference beam to determine a plurality of deformation values ​​quantifying how much the measured light beam deviates from the reference beam. The road damage module 54 of the one or more controllers 20 determines a plurality of deformation values ​​representing deviations between the measured light beam and the reference beam, wherein a severity of deformation in the road surface is determined based on the plurality of deformation values.

[0047] Road damage module 54 then compares the severity of the deformation to a threshold deformation value, where the threshold deformation value indicates road damage that will substantially affect the depth of floodwater 40. In response to determining that the severity of the deformation is greater than the threshold deformation value, road damage module 54 determines that road damage exists beneath floodwater 40.

[0048] Reference Figure 1 , Figure 2A and Figure 3 , the risk assessment module 56 of the one or more controllers 20 determines a risk of crossing the floodwater 40 at each of a plurality of target points P located along the floodwater 40, wherein the crossing risk is based on the flow rate of the floodwater determined by the flow rate module 50, the depth of the floodwater determined by the depth assessment module 52, and the presence of road damage beneath the floodwater 40 determined by the road damage module 54. The crossing risk indicates which areas of the floodwater 40 are acceptable or unacceptable for the vehicle 12 to cross.

[0049] The risk assessment module 56 stores one or more lookup tables 86 in the memory of one or more controllers 20. The one or more lookup tables 86 provide depth and velocity combination values ​​that represent the product of the flow velocity of the flood 40 measured at a specific one of the target points P and the depth of the flood. The risk assessment module 56 stores the depth and velocity combination value ( Figure 2A ), which is compared to a threshold vehicle instability value. In response to determining that the depth and speed combination value is less than the threshold vehicle instability value, the risk assessment module 56 of the one or more controllers 20 determines that the risk of crossing the flood water 40 at the particular target point P is acceptable. In one embodiment, the risk assessment module 56 may determine an acceptable risk level, wherein shallower areas of the flood water 40 are assigned a lower risk level. In response to determining that the depth and speed combination value is greater than the threshold vehicle instability value, the risk assessment module 56 of the one or more controllers 20 determines that the risk of crossing the flood water 40 at the particular target point P is unacceptable. The risk assessment module 56 also determines that the risk of crossing the flood water 40 at any area determined by the road damage module 54 to have road damage located below the flood water 40 is unacceptable.

[0050] The threshold vehicle instability value indicates that the vehicle 12 has lost overall stability. It should be understood that the threshold vehicle instability value is a function of one or more vehicle parameters. The vehicle parameters refer to the size and weight of the vehicle 12, and include, for example, measurements such as the height and wheelbase of the vehicle 12. It should be understood that overall stability refers to the floating instability, sliding instability, and tipping instability of the vehicle. The threshold vehicle instability value varies depending on the type of vehicle, with larger vehicles (e.g., vans or trucks) having higher threshold vehicle instability values ​​than smaller vehicles (e.g., sedans). In one embodiment, the threshold vehicle instability value is determined based on the following equation:

[0051]

[0052] Where v represents the flow velocity of flood 40 at the threshold vehicle instability value, F r represents the restoring force at the axle of the vehicle 12, ρ represents the density of water, C D represents the drag coefficient of the vehicle 12 (1.1 when the flood level is below the vehicle chassis and 1.15 when the flood level is above the vehicle chassis), A tyre represents the area where the tires of the vehicle 12 are in contact with the ground, and D represents the flood depth.

[0053] Reference Figure 1 , Figure 2A , Figure 2B and Figure 3 As shown, the notification module 58 of one or more controllers 20 generates a notification 44 indicating the risk of crossing the flood 40 at a plurality of target points P located along the flood 40. As described above, although Figure 2B The notification 44 is shown as a graphic 38 generated by the augmented reality head-up display system 26, and it should be understood that Figure 2B are merely exemplary in nature. Figure 2B In the example shown, the graphic 38 is a color-coded bar 48 overlaid on the floodwater 40. The color-coded bar 48 includes a plurality of individual portions 90, each corresponding to one of a plurality of target points P. Each individual portion 90 of the color-coded bar 48 is assigned a color indicating the risk of crossing the floodwater 40 at the corresponding target point P. It should be understood that the notification 44 may also provide a warning to the occupants of the vehicle 12 in the event that the risk associated with crossing the floodwater 40 is unacceptable. For example, an individual portion 90 of the color-coded bar 48 assigned as red provides a warning indicating that the risk of crossing is unacceptable, while an individual portion 90 of the color-coded bar 48 assigned as green indicates that the risk of crossing is acceptable. In an embodiment, these individual portions 90 of the color-coded bar 48 are assigned different shades of green to indicate different acceptable risk levels.

[0054] Figure 5is a process flow diagram illustrating a method 500 for generating a notification 44 by the flood risk assessment system 10. Figure 1-Figure 5 , the method 500 begins at box 502. In box 502, one or more controllers 20 receive images collected by one or more cameras 22 along the road 42 ( Figure 2A ) image data of the located flood 40. The method 500 may then proceed to block 504.

[0055] In block 504, the flow rate module 50 of the one or more controllers 20 estimates the plurality of target points P ( Figure 2A ) The method 500 may then proceed to block 506.

[0056] In block 506, the depth assessment module 52 of the one or more controllers 20 determines the depth of the image based on the depth of the image acquired by the time-of-flight sensor system 24 ( Figure 4 ) receives the first time point of the polarized backscattered laser light by the first detector 66 of the time-of-flight sensor system 24 ( Figure 4 ) receives the depolarized backscattered laser light at the second time point, and calculates the flight time difference along the road 42 ( Figure 2A ) The depth of the flood 40 at each target point P located. The method 500 may then proceed to block 508.

[0057] In block 508, the road damage module 54 of the one or more controllers 20 determines the presence of road damage located below the floodwater 40 based on the plurality of images captured by the one or more cameras 22, wherein the plurality of images represent the beams of light projected by the lighting devices 28 along the floodwater 40. The method 500 may then proceed to block 510.

[0058] In box 510, the risk assessment module 56 of one or more controllers 20 determines the risk of crossing the flood 40 at each of a plurality of target points P located along the flood 40, wherein the risk of crossing is based on the flow rate of the flood determined by the flow rate module 50, the depth of the flood determined by the depth assessment module 52, and the presence of road damage below the flood 40 determined by the road damage module 54.

[0059] Specifically, in decision block 510A, the risk assessment module 56 of one or more controllers 20 will communicate with the risk assessment module 56 of the flood 40 ( Figure 2A), and is compared to a threshold vehicle instability value. In response to determining that the depth and velocity combination value is less than the threshold vehicle instability value, the method proceeds to box 510B, and the risk assessment module 56 of the one or more controllers 20 determines that the risk of crossing the flood water 40 at the particular target point P is acceptable. In response to determining that the depth and velocity combination value is greater than the threshold vehicle instability value, the method 500 proceeds to box 510C, and the risk assessment module 56 of the one or more controllers 20 determines that the risk of crossing the flood water 40 at the particular target point P is unacceptable. In box 510B, in the event that the risk is determined to be acceptable, the method 500 may then proceed to box 510D. In box 510D, the risk assessment module 56 determines that the risk of crossing the flood water 40 at the particular target point P is unacceptable in response to the road damage module 54 determining that there is road damage at the particular target point P. The method 500 may then proceed to box 512.

[0060] In block 512, the notification module 58 of the one or more controllers 20 generates a notification 44 indicating a risk of crossing the floodwater 40 at a plurality of target points P located along the floodwater 40. As described above, in one non-limiting embodiment, the notification 44 is a graphic 38 generated by the augmented reality heads-up display system 26. The method 500 may then terminate.

[0061] Reference Figure 1-Figure 5 The disclosed flood risk assessment system provides various technical effects and benefits. It should be understood that the depth of flood water along a road is not always known, and even traversing relatively shallow flood water may present complications for a vehicle. The disclosed flood risk assessment system provides a method for determining the depth of flood water at multiple points along a flood water and for informing a vehicle occupant of the risk associated with traversing the flood water. In an embodiment, the flood risk assessment system includes an augmented reality head-up display system that generates a graphic on a windshield of a vehicle that informs the vehicle occupant of the risk associated with traversing flood water at multiple locations along the width of a road.

[0062] A controller may refer to an electronic circuit, a combinational logic circuit, a field programmable gate array (FPGA), a processor (shared, dedicated, or group) that executes code, or a combination of some or all of the above, or as part of them, such as in a system on a chip. In addition, the controller may be microprocessor-based, such as a computer having at least one processor, memory (RAM and / or ROM), and associated input and output buses. The processor may operate under the control of an operating system residing in the memory. The operating system may manage computer resources so that computer program code embodied as one or more computer software applications (such as applications residing in the memory) may have instructions executed by the processor. In an alternative embodiment, the processor may directly execute the application, in which case the operating system may be omitted.

[0063] The description of the present disclosure is merely exemplary in nature, and variations that do not depart from the gist of the present disclosure are intended to fall within the scope of the present disclosure. These variations should not be regarded as departing from the spirit and scope of the present disclosure.

Claims

1. A flood risk assessment system for a vehicle, the flood risk assessment system comprising: one or more cameras oriented to collect image data of flood water located along a road on which the vehicle is traveling; a time-of-flight sensor system that directs a laser beam to a plurality of target points distributed along a flood, wherein the time-of-flight sensor system receives polarized backscattered laser light when the laser beam reflects from an upper surface of the flood, and receives depolarized backscattered laser light when the laser beam reflects from a lower surface of the flood; and one or more controllers in electronic communication with the one or more cameras and the time-of-flight sensor system, wherein the one or more controllers execute instructions to: estimating flow velocities of the floodwater at the plurality of target points by analyzing the image data collected by the one or more cameras based on one or more video-based motion estimation algorithms; calculating flood depths at the plurality of target points based on a time-of-flight difference between a first time point when the time-of-flight sensor system receives the polarized backscattered laser light and a second time point when the time-of-flight sensor system receives the depolarized backscattered laser light; determining a risk associated with crossing the flood at each of the plurality of target points located along the flood based on a flow rate of the flood and a depth of the flood; and A notification is generated indicating a risk associated with traversing the flood at the plurality of target points located along the flood.

2. The flood risk assessment system of claim 1, further comprising an augmented reality head-up display system in electronic communication with the one or more controllers, wherein: The augmented reality head-up display system includes a graphics projection device that generates an image on a windshield of the vehicle.

3. The flood risk assessment system according to claim 2, wherein: The one or more controllers execute instructions to: A graphic projection device instructs the augmented reality head-up display system to generate a graphic on a windshield of the vehicle, wherein the graphic represents the notification indicating a risk associated with traversing the flood water.

4. The flood risk assessment system according to claim 3, wherein: The graphic is a color coded bar overlaid on the flood.

5. The flood risk assessment system according to claim 4, wherein: The color-coded strip includes a plurality of individual sections, each of the plurality of individual sections corresponding to one of the plurality of target points.

6. The flood risk assessment system according to claim 5, wherein: Individual portions of the color-coded strip are designated red to provide a warning indicating that the crossing risk at the corresponding target point is unacceptable.

7. The flood risk assessment system according to claim 1, wherein: The time-of-flight sensor system includes a pulsed illumination source and a fiber optic cable.

8. The flood risk assessment system according to claim 7, wherein: The pulsed illumination source generates a laser beam that is received by the fiber optic cable, wherein the laser beam exits a tip of the fiber optic cable.

9. The flood risk assessment system according to claim 8, wherein: The time-of-flight sensor system includes an actuating element that directs the laser beam emitted from the tip of the optical cable toward one of a plurality of target points distributed along the floodwater.

10. The flood risk assessment system according to claim 9, wherein: The time-of-flight sensor system includes a first detector, a second detector, and a polarization beam splitter, wherein the polarization beam splitter separates the polarized backscattered laser light and the depolarized backscattered laser light, and the polarized backscattered laser light is received by the first detector, and the depolarized backscattered laser light is received by the second detector.

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