FLOOD RISK ASSESSMENT SYSTEM FOR A VEHICLE

Abstract

Flood risk assessment system (10) for a vehicle (12), wherein the flood risk assessment system (10) comprises the following: one or more cameras (22) oriented to collect image data of floodwater (40) located on a roadway on which the vehicle (12) is traveling; a time-of-flight sensor system (24) that directs a laser beam to several target points (P) arranged along the flood (40); and one or more controllers (20) in electronic communication with the one or more cameras (22) and the time-of-flight sensor system (24), wherein the one or more controllers (20) execute commands to: Estimating the flow velocity of the floodwater (40) at the multiple 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; Calculating a flood depth at the multiple target points (P) based on a travel time difference; Determining a risk associated with crossing the flood (40) at each of the multiple target points (P) arranged along the flood (40), based on the flow velocity of the flood (40) and the flood depth; and Generating a message indicating the risk associated with crossing the flood (40) at the multiple target points (P) arranged along the flood (40); wherein the one or more controllers (20) store one or more lookup tables that provide a combined depth and velocity value representing a product of the flow velocity of the flood (40) and the flood depth; characterized by the fact that the time-of-flight sensor system (24) receives polarized backscattered laser light when the laser beam is reflected from an upper surface of the flood (40), and receives depolarized backscattered laser light when the laser beam is reflected from a bottom of the flood (40); the time-of-flight difference between a first time at which the polarized backscattered laser light is received by the time-of-flight sensor system (24) and a second time at which the depolarized backscattered laser light is received by a time-of-flight sensor system (24); and The one or more controllers (20) execute commands to: Comparing a combined depth and speed value corresponding to one of several specific target points (P) along the flood (40) with a vehicle instability threshold and Determining in response to a determination that the combined depth and speed value is less than the vehicle instability threshold, that the risk of crossing the flood (40) at a specific target point (P) is acceptable, wherein the vehicle instability threshold is a function of one or more vehicle parameters.

Description

INTRODUCTION

[0001] The present invention relates to a flood risk assessment system for a vehicle which determines a flood depth along a roadway and generates a notification indicating a risk associated with the vehicle crossing the flood, based on the flood depth and the flow velocity.

[0002] A flood risk assessment system according to the preamble of claim 1 is essentially known from DE 10 2018 112 269 A1. Further prior art is also known from US 2022 / 0 171 064 A1, US 2019 / 0 005 727 A1, US 2016 / 0 196 656 A1 and US 2020 / 0 189 463 A1.

[0003] Sometimes, a roadway can become flooded due to severe weather conditions, such as a strong storm. It must be acknowledged that even relatively shallow floodwater can create difficulties when a vehicle attempts to cross a flooded roadway. Furthermore, the flood depth is not always apparent to the driver. For example, approximately 15 centimeters (about six inches) of floodwater on a roadway can reach the underside of many passenger cars, potentially causing loss of control and a stall. Similarly, approximately 30 centimeters (about one foot) of floodwater can cause many vehicles to float away. However, no systems are currently available to inform a driver when the floodwater is deep enough to cause problems such as loss of control or a stall.

[0004] Thus, while current vehicles achieve their intended purpose, there is a need in the state of the art for a solution that indicates the depth of floodwater located on a roadway. SUMMARY

[0005] According to the invention, a flood risk assessment system is presented which is characterized by the features of claim 1. The flood risk assessment system comprises one or more cameras oriented to collect image data of floodwater on a roadway along which the vehicle is traveling; a time-of-flight sensor system that directs a laser beam to multiple target points positioned along the floodwater; and one or more controllers in electronic communication with the camera(s) 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 floodwater and depolarized backscattered laser light when the laser beam is reflected from the bottom of the floodwater.The one or more controllers execute commands to estimate the flow velocity of the floodwater at the multiple 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 flood depth at the multiple target points based on the time-of-flight difference between a first time at which the polarized backscattered laser light is received by the time-of-flight sensor system and a second time at which the depolarized backscattered laser light is received by a time-of-flight sensor system.The one or more controllers determine a risk associated with crossing the flood at each of the multiple target points arranged along the flood, based on the flood flow velocity and flood depth. The one or more controllers generate a message indicating the risk associated with crossing the flood at the multiple target points arranged along the flood.

[0006] The one or more controllers store one or more lookup tables that provide a combined depth and velocity value representing the product of the flood flow velocity and the flood depth. The one or more controllers execute commands to compare a combined depth and velocity value corresponding to one of several specific target points along the flood with a vehicle instability threshold. In response to a determination that the combined depth and velocity value is less than the vehicle instability threshold, the controllers determine that the risk of crossing the flood at a specific target point is acceptable. The vehicle instability threshold is a function of one or more vehicle parameters.

[0007] According to another aspect, the flood risk assessment system further includes a windshield display system with augmented reality in electronic communication with the one or more controllers, wherein the windshield display with augmented reality includes a graphic projection device that generates images across a windshield of the vehicle.

[0008] According to yet another aspect, one or more controllers execute commands to instruct a graphic projection device of the windshield display system with augmented reality to generate a graphic across the windshield of the vehicle, the graphic representing the message indicating the risk associated with crossing the floodwater.

[0009] According to one aspect, the graphic is a color-coded bar superimposed on the floodwater.

[0010] According to another aspect, the color-coded bar contains several individual sections, each corresponding to one of the multiple target points.

[0011] According to yet another aspect, individual sections of the color-coded bar are assigned red to provide a warning indicating that the risk of crossing at the corresponding target point is unacceptable.

[0012] According to one aspect, the time-of-flight sensor system includes a pulsed light source and a fiber optic cable.

[0013] According to another aspect, the pulsed illumination source generates a laser beam that is received through the fiber optic cable, with the laser beam exiting at one tip of the fiber optic cable.

[0014] According to yet another aspect, the time-of-flight sensor system includes an actuating element that directs the laser beam, which is emitted through the tip of the fiber optic cable, to one of the several target points arranged along the floodwater.

[0015] According to 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 the polarized backscattered laser light and the depolarized backscattered laser light, the polarized backscattered laser light is received by the first detector and the depolarized backscattered laser light is received by the second detector.

[0016] According to one aspect, the vehicle instability threshold is determined based on the following equation: v=2FrρCDAtyreD, where v represents the flow velocity of the floodwater at the vehicle instability threshold, F r a restoring force on an axle of the vehicle, ρ represents the density of water, C D represents a resistance coefficient of the vehicle, A tyre a surface of tires that are part of the vehicle and in contact with the ground represents, and D represents the flood depth.

[0017] According to another aspect, the flood risk assessment system also 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 the flood and the light beam is oriented parallel to a direction of movement of the vehicle.

[0018] According to yet another aspect, the one or more controllers determine the existence of road damage located under the floodwater based on multiple images taken by the one or more cameras, the multiple images representing the beam of light projected along the floodwater by the lighting device.

[0019] According to one aspect, one or more controllers determine that the risk of crossing the floodwater at a specific target point is unacceptable, in response to a determination that road damage exists at that specific target point.

[0020] Furthermore, a method for generating a notification by a flood risk assessment system for a vehicle is described. The method includes receiving image data of flooding located on a roadway along which the vehicle is traveling, collected by one or more cameras, by one or more controllers. The method includes estimating the flow velocity of the flooding at several target points arranged along the flooding 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 a flood depth at the multiple target points based on a time-of-flight difference between a first time at which polarized backscattered laser light is received by a time-of-flight sensor system and a second time at which depolarized backscattered laser light is received by a time-of-flight sensor system, wherein the time-of-flight sensor system directs a laser beam to the multiple target points arranged along the flood and receives the polarized backscattered laser light when the laser beam is reflected from an upper surface of the flood, and receives the depolarized backscattered laser light when the laser beam is reflected from a bottom of the flood.The procedure also includes determining a risk associated with crossing the flood at each of the multiple target points arranged along the flood, based on the flood flow velocity and flood depth. The procedure further includes generating a message indicating the risk associated with crossing the flood at each of the multiple target points arranged along the flood.

[0021] Furthermore, another flood risk assessment system for a vehicle is disclosed. This system includes one or more cameras oriented to collect image data of floodwater located on a roadway along which the vehicle is traveling; a time-of-flight sensor system that directs a laser beam to multiple target points arranged along the floodwater; an augmented reality windscreen display system that includes a graphics projection device that generates images across the vehicle's windscreen; and one or more controllers in electronic communication with the one or more cameras, the time-of-flight sensor system, and the augmented reality windscreen display.The time-of-flight sensor system receives polarized backscattered laser light when the laser beam is reflected from an upper surface of the floodwater, and depolarized backscattered laser light when the laser beam is reflected from the bottom of the floodwater. The one or more controllers execute commands to estimate the flow velocity of the floodwater at the multiple 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 flood depth at the multiple target points based on the time-of-flight difference between a first time at which the polarized backscattered laser light is received by the time-of-flight sensor system and a second time at which the depolarized backscattered laser light is received by the time-of-flight sensor system.The one or more controllers determine a risk associated with crossing the flood at each of the multiple target points arranged along the flood, based on the flood flow velocity and flood depth. The one or more controllers instruct the augmented reality windscreen display system's graphic projection device to generate a graphic across the vehicle's windscreen, the graphic representing a message indicating the risk associated with crossing the flood at the multiple target points arranged along the flood.

[0022] According to another aspect, the graphic is a color-coded bar superimposed on the floodwater.

[0023] According to yet another aspect, the color-coded bar contains several individual sections, each corresponding to one of the multiple target points.

[0024] Further areas of application will become apparent from the description provided here. It should be understood that the description and specific examples are intended for illustrative purposes only. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described here are for illustrative purposes only; they show: Fig. 1 a schematic diagram of a vehicle incorporating the disclosed flood risk assessment system, which includes one or more controllers in electronic communication with a time-of-flight sensor system and an augmented reality windscreen display system, according to an exemplary embodiment; Fig. 2A a driver who views the floodwater on the roadway through a windshield of the vehicle, according to an exemplary embodiment; Fig. 2B a message projected through the augmented reality windscreen display system, which is in Fig. 1 is shown according to an exemplary embodiment; Fig. 3. A diagram showing the software architecture of the one or more controllers that are in Fig. 1 are shown, illustrating an exemplary embodiment; Fig. 4 a schematic diagram of the time-of-flight sensor system, which is in Fig. 1 is shown according to an exemplary embodiment; and Fig. 5 A process flow diagram illustrating a method for generating a notification by the flood risk assessment system indicating the risk of crossing the flood, according to an exemplary embodiment. DETAILED DESCRIPTION

[0026] The following description is merely exemplary.

[0027] With reference to Fig. Figure 1 illustrates an exemplary flood risk assessment system 10 for a vehicle 12. It should be acknowledged that the vehicle 12 can be, but is not limited to, any type of vehicle, such as a sedan, truck, SUV, van, or motorhome. The flood risk assessment system 10 includes one or more controllers 20 in electronic communication with one or more cameras 22, one or more time-of-flight sensor systems 24, a windshield display system with augmented reality 26, and a lighting device 28. As explained below, the flood risk assessment system 10 determines a flood depth 40 (which is in Fig. 2A), which is located on lane 42 along which vehicle 12 is traveling, and generates a message 44 (which is shown in Fig. 2B is shown), which indicates a risk of crossing the flood 40 based on the flood depth.

[0028] The one or more cameras 22 are oriented to collect image data of an environment located in front of the vehicle 12. It should be noted that the image data refers to both still 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 windshield augmented reality display system 26 includes a graphics projection device 34 configured to generate images across a windshield 36 of the vehicle 12. The graphics projection device 34 includes a projection device that has an excitation light for projecting images across the windshield 36 of the vehicle 12.Some examples of the projection device include, but are not limited to, optical collimators, laser projectors, and digital light processing (DLP) projectors. The illumination device 28 is any type of illumination device that projects a beam of light onto a surface of the floodwater 40 (which is in . Fig. (as shown in Figure 2A) is projected in front of the vehicle 12, the light beam being oriented parallel to a direction of movement of the vehicle 12. For example, in a non-restrictive embodiment, the lighting device 28 is a laser line projector comprising a laser diode, a collimator lens, and line-generating optics.

[0029] With reference to Fig. 1, Fig. 2A and Fig. 2B determines the flood risk assessment system 10 a flood depth of flood 40 (which in Fig. 2A), which is located on carriageway 42, along which vehicle 12 is traveling. The flood risk assessment system 10 also generates message 44 (which is shown in Fig. 2B), which indicates a risk of crossing floodwater 40, based on the flood depth. In the example shown in Fig. As shown in Figure 2B, a graphic 38, generated by the graphic projection device 34 of the augmented reality windscreen display system 26, which is displayed over the windscreen 36 of the vehicle 12, represents the message 44. Specifically, in the example shown in Figure 2B, the graphic 38 represents the message 44. Fig. Figure 2B shows a color-coded bar 48 superimposed on the flood 40 located on the carriageway 42. As explained below, the color-coded bar 48 indicates which areas of the flood 40 are acceptable or unacceptable for the vehicle 12 to cross, with a warning provided to indicate the areas of the flood 40 that are unacceptable to cross. Specifically, as explained below, individual sections 90 of the color-coded bar 48 are colored red to provide a warning indicating that the risk of crossing the flood 40 is unacceptable. Fig. 2B While the message 44 is illustrated as a graphic 38 displayed on the windshield 36, it must be acknowledged that the message 44 is not limited to a graphic generated by an augmented reality windshield display. For example, in another embodiment, the message 44 could be voice commands informing the occupants of the vehicle 12 not to cross the floodwater. Indeed, it must be acknowledged that, although an augmented reality windshield display system 26 is illustrated in the figures, the message 44 could be generated by any type of driver information system.

[0030] Fig. Figure 3 is a diagram illustrating the software architecture of the one or more controllers 20 that are in Fig. 1 are shown. With reference to Fig. 1, Fig. 2A and Fig. 3 The one or more controllers 20 include a flow velocity module 50, which estimates the flow velocity of the flood 40 located on the roadway 42; a depth assessment module 52, which calculates the flood depth; a road damage module 54, which detects road damage located under the flood 40; a risk assessment module 56, which determines which areas of the flood 40 are acceptable or unacceptable for passage by the vehicle 12; and a communication module 58, which instructs the graphic projection device 34 of the windshield display system with augmented reality 26 to generate the graphic 38 over the windshield 36 of the vehicle 12.

[0031] With continued reference to Fig. 1, Fig. 2A and Fig. 3. The one or more cameras 22 are oriented to collect image data of the flood 40 located on the roadway 42, with the image data being received by the one or more controllers 20. The flow velocity module 50 of the one or more controllers 20 estimates the flow velocity of the flood 40 at the multiple 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 the dense optical flow (DOF) algorithm; however, it should be acknowledged that other solutions can also be used.In a specific embodiment, the Farneback optical flow (FOFM) method, which is a DOF algorithm, calculates a surface velocity (SVWF) of a water flow of flood 40 at one of the target points P (. Fig. 2A) between two successive frames that are part of the image data collected by the one or more cameras 22.

[0032] Specifically with reference to Fig. 2A and Fig. 3 The flow velocity module 50 of one or more controllers 20 estimates the flow velocity of the flood 40 at the multiple target points P arranged along a width W of the flood 40, where the width W lies between the opposite lane edges 46 of the roadway 42. It must be acknowledged that the flow velocity of the flood 40 can vary at different locations along the flood 40, and therefore the flow velocity of the flood 40 is determined at multiple points along the flood 40 in order to record the flow velocity.

[0033] Fig. Figure 4 is a schematic diagram of an exemplary time-of-flight sensor system 24. As mentioned above, the time-of-flight sensor system 24 can be, for example, LiDAR, a photon multiplier tube (PMT) in photon counting mode, or a single-photon avalanche diode sensor (SPAD sensor). The time-of-flight sensor system 24 includes a pulsed illumination source 64, a first detector 66, a second detector 68, a polarizing beam splitter 70, an actuating element 72, a fiber optic cable 74, and an imaging lens 76. It should be noted that in embodiments, the first detector 66 and the second detector 68 can be time-critical photon counters, and the polarizing 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 which is received through the fiber optic cable 74, the laser beam being horizontally polarized.The laser beam exits a tip 80 of the fiber optic cable 74 and is directed towards the flood 40 located on the roadway 42. Specifically, the actuator 72 directs the laser beam emitted through the tip 80 of the fiber optic cable 74 to one of several target points P arranged along the width W of the flood 40. The actuator 72 is any type of actuator that moves the tip 80 of the fiber optic cable 74 to scan the flood 40 at the target points P. For example, in one embodiment, the actuator 72 is a piezoelectric actuator that moves in response to an applied voltage. Polarized backscattered laser light is reflected from an upper surface of the flood 40, and depolarized backscattered laser light is reflected from a bottom (i.e., the surface of the roadway 42) of the flood 40.It must be acknowledged that the depolarized backscattered laser light also contains randomly polarized light.

[0034] The light reflected from the upper surface of the flood 40 has a different polarization state than the light reflected from the bottom of the flood 40. Specifically, the polarized backscattered laser light and the depolarized backscattered laser light are both 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 one end 82 of the fiber optic cable 74, where it is received by the polarization beam splitter 70. The polarization beam splitter 70 separates the polarized backscattered laser light and the depolarized backscattered laser light, with the polarized backscattered laser light being received by the first detector 66 and the depolarized backscattered laser light being received by the second detector 68.It should be acknowledged that the returning photons, which are associated with the polarized backscattered laser light and the depolarized backscattered laser light, are time-labeled by the detectors 66, 68 and are used to calculate a time-of-flight difference, as explained below.

[0035] With reference to Fig. 2A, Fig. 3 and Fig. 4 The depth assessment module 52 of one or more controllers 20 calculates the depth of the flood 40 at each target point P arranged along the roadway 42, based on the time-of-flight difference between a first time at which the polarized backscattered laser light is received by the first detector 66 and a second time at which the depolarized backscattered laser light is received by the second detector 68. It should be noted that the depth of the flood 40 measured by an airborne sensor system 24 is oriented at an angle, and the depth of the flood 40 calculated by the depth assessment module 52 is adjusted to reflect the vertical depth.

[0036] With reference to Fig. 1 and Fig. 2A The road damage module 54 of the one or more controllers 20 determines the presence of road damage located beneath the flood 40 based on multiple images captured by the one or more cameras 22, the multiple images representing the light beam projected by the lighting device 28 along the flood 40. A method for determining the presence of road damage is described in U.S. Application No. 18 / 183,403, filed on March 14, 2023, which is incorporated herein by reference in its entirety.

[0037] With reference to Fig. 1, Fig. 2A and Fig. 3. The road damage module 54 of one or more controllers 20 determines the presence of road damage located beneath the flood 40 by instructing the lighting device 28 to project the light beam onto the flood 40 in front of the vehicle 12. The light beam is a linear ray of light projected onto the flood 40 in front of the vehicle 12. It should be noted that when the light beam is projected onto a flat road surface or flood, the light beam appears approximately straight (i.e., as a straight line). However, when it is projected onto an irregular road surface or flood (e.g., a road surface with a deformation such as a pothole), the light beam is distorted and does not appear as a straight line.

[0038] The one or more cameras 22 capture the multiple images representing the light beam projected by the lighting device 28 along the flood 40. The road damage module 54 of the one or more controllers 20 binarizes the multiple images representing the light beam captured by the one or more cameras 22 to generate binary image data containing a measured light beam. The measured light beam of the binary image data is compared to a reference light beam to determine several distortion values ​​that quantify how much the measured light beam deviates from the reference light beam.The road damage module 54 of the one or more controllers 20 determines several deformation values ​​representing the deviation between the measured light beam and the reference light beam, whereby the severity of a deformation in the road surface is determined on the basis of the several deformation values.

[0039] The road damage module 54 then compares the severity of the deformation with a deformation threshold, where the deformation threshold represents road damage that would significantly affect the depth of the flood 40. In response to a determination that the severity of the deformation is greater than the deformation threshold, the road damage module 54 determines the presence of road damage below the flood 40.

[0040] With reference to Fig. 1, Fig. 2A and Fig. 3. The risk assessment module 56 of one or more controllers 20 determines the risk of crossing the flood 40 at each of the multiple target points P arranged along the flood 40, using as a basis the flow velocity of the flood, determined by the flow velocity module 50, the flood depth, determined by the depth assessment module 52, and the presence of road damage beneath the flood 40, determined by the road damage module 54. The risk of crossing indicates which areas of the flood 40 are acceptable or unacceptable for crossing by the vehicle 12.

[0041] The risk assessment module 56 stores one or more lookup tables 86 in a memory of the one or more controllers 20. The one or more lookup tables 86 provide a combined depth and velocity value that represents a product of the flow velocity of the flood 40 and the flood depth measured at one of the specific target points P. The risk assessment module 56 compares the combined depth and velocity value measured at one of the several specific target points P along the flood 40 ( Fig. 2A) corresponds to a vehicle instability threshold. In response to a determination that the combined depth and velocity value is less than the vehicle instability threshold, the risk assessment module 56 of one or more controllers 20 determines that the risk of crossing the flood 40 at the specific target point P is acceptable. In one embodiment, the risk assessment module 56 can determine a degree of acceptable risk, assigning a lower degree of risk to shallower areas of the flood 40. In response to a determination that the combined depth and velocity value is less than the vehicle instability threshold, the risk assessment module 56 of one or more controllers 20 determines that the risk of crossing the flood 40 at the specific target point P is unacceptable.The risk assessment module 56 also determines that the risk of crossing the flood 40 is unacceptable in any areas where the presence of road damage located under the flood 40 has been determined by the road damage module 54.

[0042] The vehicle instability threshold indicates that the vehicle 12 loses overall stability. It is acknowledged that the vehicle instability threshold is a function of one or more vehicle parameters. The vehicle parameters relate to the size and weight of the vehicle 12 and include measurements such as the vehicle 12's height and wheelbase. It is acknowledged that overall stability refers to a vehicle's floating instability, sliding instability, and rollover instability. The vehicle instability threshold varies based on the type of vehicle, with larger vehicles, such as a van or truck, having a higher vehicle instability threshold compared to smaller vehicles, such as a sedan. In one embodiment, the vehicle instability threshold is determined based on the following equation: v=2FrρCDAtyreD, where v represents the flow velocity of the floodwater 40 at the vehicle instability threshold, F r a restoring force at the axle of the vehicle 12 represents, ρ represents the density of water, C D the drag coefficient of the vehicle 12 (which is 1.1 when the flood level is below the vehicle body, and 1.15 when the flood level is above the vehicle body) represents, A tyre a surface area of ​​the tires of vehicle 12 that is in contact with the ground, and D represents the flood depth.

[0043] With reference to Fig. 1, Fig. 2A, Fig. 2B and Fig. 3. The message module 58 of one or more controllers 20 generates the message 44, which indicates the risk of crossing the flood 40 at the multiple target points P arranged along the flood 40. As mentioned above, it must be acknowledged that, although Fig. 2B the message 44 illustrates as a graphic 38 generated by the windshield display system with augmented reality 26, Fig. 2B is merely exemplary. In the example that is in Fig. As shown in Figure 2B, Figure 38 is a color-coded bar 48 superimposed on the flood 40. The color-coded bar 48 contains several individual sections 90, each corresponding to one of the several target points P. Each individual section 90 of the color-coded bar 48 is assigned a color indicating the risk of crossing the flood 40 at the corresponding target point P. It should be acknowledged that the communication 44 can also provide a warning to the occupants of the vehicle 12 if the risk associated with crossing the flood 40 is unacceptable. For example, individual sections 90 of the color-coded bar 48 assigned red provide a warning indicating that the risk of crossing is unacceptable, while individual sections 90 of the color-coded bar 48 that are green indicate that the risk of crossing is acceptable.In one embodiment, 48 different shades of green are assigned to the individual sections 90 of the color-coded bar to indicate varying degrees of acceptable risk.

[0044] Fig. Figure 5 is a process flow diagram illustrating a procedure 500 for generating communication 44 by the flood risk assessment system 10. With reference to Fig. 1-5 begins procedure 500 in block 502. In block 502, the one or more controllers receive 20 image data of the flood 40, which is located along the roadway 42 ( Fig. 2A), which were collected by the one or more cameras 22. Procedure 500 can then proceed to block 504.

[0045] In block 504, the flow velocity module 50 of one or more controllers 20 estimates the flow velocity of the floodwater 40 at the multiple target points P ( Fig. 2A) by analyzing the image data collected by the one or more cameras 22, based on one or more video-based motion estimation algorithms. Procedure 500 can then proceed to block 506.

[0046] In block 506, the depth assessment module 52 of one or more controllers 20 calculates the depth of the floodwater 40 at each target point P located along the roadway 42 ( Fig. 2A), based on a time-of-flight difference between a first time at which the polarized backscattered laser light is received by the first detector 66 and a second time at which the depolarized backscattered laser light is received by the second detector 68 of the time-of-flight sensor system 24 ( Fig. 4) Procedure 500 can then proceed to block 508.

[0047] In block 508, the road damage module 54 of the one or more controllers 20 determines the presence of road damage located beneath the flood 40 based on multiple images captured by the one or more cameras 22, the multiple images representing the light beam projected along the flood 40 by the lighting device 28. The procedure 500 can then proceed to block 510.

[0048] In Block 510, the risk assessment module 56 of one or more controllers 20 determines the risk of crossing the flood 40 at each of the multiple target points P arranged along the flood 40, using as a basis the flow velocity of the flood determined by the flow velocity module 50, the flood depth determined by the depth assessment module 52, and the presence of road damage under the flood 40 determined by the road damage module 54.

[0049] Specifically, in decision block 510A, the risk assessment module 56 of one or more controllers 20 compares the combined depth and velocity value corresponding to one of the several specific target points P along the flood 40 ( Fig. 2A), with the vehicle instability threshold. In response to a determination that the combined depth and velocity value is less than the vehicle instability threshold, the procedure proceeds to Block 510B and the risk assessment module 56 of one or more controllers 20 determines that the risk of crossing the flood 40 at the specific target point P is acceptable. In response to a determination that the combined depth and velocity value is less than the vehicle instability threshold, the procedure 500 proceeds to Block 510C and the risk assessment module 56 of one or more controllers 20 determines that the risk of crossing the flood 40 at the specific target point P is unacceptable. If the risk is determined to be acceptable in Block 510B, the procedure 500 may then proceed to Block 510D.In Block 510D, the risk assessment module 56 determines that the risk of crossing the floodwater 40 at a specific target point P is unacceptable, in response to the determination by the road damage module 54 that road damage exists at the specific target point P. The procedure 500 can then proceed to Block 512.

[0050] In block 512, the message module 58 of one or more controllers 20 generates the message 44, which indicates the risk of crossing the flood 40 at the multiple target points P arranged along the flood 40. As mentioned above, in a non-restrictive embodiment, the message 44 is displayed as a graphic 38 generated by the augmented reality windscreen display system 26. The method 500 can then terminate.

[0051] With reference to Fig. 1- Fig.5. The disclosed flood risk assessment system creates various technical effects and benefits. It is acknowledged that the depth of floodwater on a roadway is not always apparent, and crossing even a relatively shallow flood can pose difficulties for a vehicle. The disclosed flood risk assessment system offers a solution for determining the flood depth at multiple points along the floodwater and for informing vehicle occupants about the risk associated with crossing the floodwater. In embodiments, the flood risk assessment system includes an augmented reality windshield display system that generates a graphic on the vehicle's windshield informing the vehicle occupants about the risk associated with crossing the floodwater at multiple locations along the width of the roadway.

[0052] Controllers can refer to or be part of an electronic circuit, a combinational logic circuit, a field-programmable gate array (FPGA), a processor (shared, dedicated, or a group) that executes code, or a combination of some or all of the above, such as in a system on a chip. Additionally, controllers can be microprocessor-based, such as a computer, which has at least one processor, memory (RAM and / or ROM), and dedicated input and output buses. The processor can operate under the control of an operating system residing in memory. The operating system can manage computer resources such that computer program code, embodied as one or more computer software applications, such as an application residing in main memory, can direct instructions to be executed by the processor.In an alternative embodiment, the processor can execute the application directly, in which case the operating system can be omitted.

Claims

[1] Flood risk assessment system (10) for a vehicle (12), wherein the flood risk assessment system (10) comprises the following: one or more cameras (22) oriented to collect image data of floodwater (40) located on a roadway on which the vehicle (12) is traveling; a time-of-flight sensor system (24) that directs a laser beam to several target points (P) arranged along the flood (40); and one or more controllers (20) in electronic communication with the one or more cameras (22) and the time-of-flight sensor system (24), wherein the one or more controllers (20) execute commands to: Estimating the flow velocity of the floodwater (40) at the multiple 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; Calculating a flood depth at the multiple target points (P) based on a travel time difference; Determining a risk associated with crossing the flood (40) at each of the multiple target points (P) arranged along the flood (40), based on the flow velocity of the flood (40) and the flood depth; and Generating a message indicating the risk associated with crossing the flood (40) at the multiple target points (P) arranged along the flood (40); wherein the one or more controllers (20) store one or more lookup tables that provide a combined depth and velocity value representing a product of the flow velocity of the flood (40) and the flood depth; characterized by , that the time-of-flight sensor system (24) receives polarized backscattered laser light when the laser beam is reflected from an upper surface of the flood (40), and receives depolarized backscattered laser light when the laser beam is reflected from a bottom of the flood (40); the time-of-flight difference between a first time at which the polarized backscattered laser light is received by the time-of-flight sensor system (24) and a second time at which the depolarized backscattered laser light is received by a time-of-flight sensor system (24); and The one or more controllers (20) execute commands to: Comparing a combined depth and speed value corresponding to one of several specific target points (P) along the flood (40) with a vehicle instability threshold and Determining in response to a determination that the combined depth and speed value is less than the vehicle instability threshold, that the risk of crossing the flood (40) at a specific target point (P) is acceptable, wherein the vehicle instability threshold is a function of one or more vehicle parameters. [2] Flood risk assessment system (10) according to claim 1, further comprising a windshield display system with augmented reality (26) in electronic communication with the one or more controllers (20), wherein the windshield display with augmented reality (26) includes a graphics projection device that generates images via a windshield (36) of the vehicle (12). [3] Flood risk assessment system (10) according to claim 2, wherein the one or more controllers (20) execute commands to: Instructing the graphic projection device of the windscreen display system with augmented reality (26) to generate a graphic across the windscreen (36) of the vehicle (12), wherein the graphic represents the message indicating the risk associated with crossing the floodwater (40). [4] Flood risk assessment system (10) according to claim 3, wherein the graphic is a color-coded bar (48) superimposed on the flood (40). [5] Flood risk assessment system (10) according to claim 4, wherein the color-coded bar (48) contains several individual sections (90) which each correspond to one of the several target points (P). [6] Flood risk assessment system (10) according to claim 5, wherein individual sections (90) of the color-coded bar (48) are assigned red to provide a warning indicating that the risk of crossing at the corresponding target point (P) is unacceptable. [7] Flood risk assessment system (10) according to claim 1, wherein the time-of-flight sensor system (24) includes a pulsed light source (64) and a fiber optic cable (74). [8] Flood risk assessment system (10) according to claim 7, wherein the pulsed illumination source (64) generates a laser beam which is received through the fiber optic cable (74), wherein the laser beam exits a tip (80) of the fiber optic cable (74). [9] Flood risk assessment system (10) according to claim 8, wherein the time-of-flight sensor system (24) includes an actuating element (72) that directs the laser beam emitted through the tip (80) of the fiber optic cable (74) to one of the multiple target points (P) arranged along the flood (40). [10] Flood risk assessment system (10) according to claim 9, wherein the time-of-flight sensor system (24) comprises a first detector (66), a second detector (68) and a polarization beam splitter (70), the polarization beam splitter (70) separating the polarized backscattered laser light and the depolarized backscattered laser light, the polarized backscattered laser light being received by the first detector (66) and the depolarized backscattered laser light being received by the second detector (68). [11] Flood risk assessment system (10) according to claim 1, wherein the vehicle instability threshold is determined on the basis of the following equation: v=2FrρCDAtyreD, where v represents the flow velocity of the floodwater (40) at the vehicle instability threshold, F r a restoring force at an axle of the vehicle (12) is represented, ρ is represented as a density of water, C Da resistance coefficient of the vehicle (12) represents, A tyre an area of ​​tires that are part of the vehicle (12) and are in contact with the ground, and D represents the flood depth. [12] Flood risk assessment system (10) according to claim 1, further comprising a lighting device (28) in electronic communication with the one or more controllers (20), wherein the lighting device (28) projects a light beam onto a surface of the flood (40) and the light beam is oriented parallel to a direction of movement of the vehicle (12). [13] Flood risk assessment system (10) according to claim 12, wherein the one or more controllers (20) determine the presence of road damage located under the floodwater (40) on the basis of multiple images taken by the one or more cameras (22), wherein the multiple images represent the light beam projected along the floodwater (40) by the lighting device (28).

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