Expressway lane level guiding method and device under agglomerate fog condition

Abstract

The invention provides an expressway lane level guiding method and device under an agglomerate fog condition, and the method comprises the steps: obtaining a visibility value and the driving information of a vehicle in real time for the vehicle which is about to drive into an agglomerate fog burst section and is passing through the agglomerate fog burst section; a vehicle operation safety speed estimation model under the low-visibility condition is adopted to estimate and obtain a vehicle suggested operation speed and a safety vehicle distance which guarantee vehicle operation safety; determining the running safety level of the vehicle by adopting a vehicle running safety judgment model under different visibility conditions; and executing a corresponding vehicle management and control strategy on the vehicle, and carrying out multi-mode cooperative lane-level driving safety active induction on the vehicle, so that the vehicle i safely and efficiently passes through the agglomerate fog burst section. Accurate intervention and active guidance of the road traffic flow operation state are achieved through the photoelectric technology, road section front early warning and lane-level active guidance under the agglomerate fog condition are achieved, and the road vehicle operation safety and the road passing efficiency are effectively improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of highway traffic safety and intelligent control, and particularly relates to a method and device for lane-level guidance on expressways under the condition of advection fog. Background Art

[0002] With the increasing mileage of expressway construction year by year, more and more expressways passing through mountain roads, and the intensification of global warming, adverse weather, especially advection fog, has a serious impact on the safety of highway operation. Effectively solving the problem of vehicle operation safety under the meteorological condition of advection fog has become an urgent problem to be solved at present.

[0003] Currently, for the problem of vehicle operation safety under the meteorological condition of advection fog, vehicles are mainly induced through road auxiliary facilities and information interaction, etc., which solves the problem of vehicle driving safety to a certain extent. However, the traditional road auxiliary induction mode is single, and the accuracy of the road auxiliary induction mode is limited, making it difficult to effectively solve the problem of vehicle operation safety under the meteorological condition of advection fog. Summary of the Invention

[0004] In view of the defects existing in the prior art, the present invention provides a method and device for lane-level guidance on expressways under the condition of advection fog, which can effectively solve the above problems.

[0005] The technical solution adopted by the present invention is as follows:

[0006] The present invention provides a method for lane-level guidance on expressways under the condition of advection fog, including the following steps:

[0007] Step S1, for vehicle i about to enter the advection fog sudden section and vehicle i passing through the advection fog sudden section, the visibility value S at the current moment t is obtained in real time n,t and the driving information of vehicle i; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t and the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,t and the distance ΔS between vehicle i and the nearest vehicle f in front of it in the same lane i,t ;

[0008] Step S2, using the vehicle running safety speed estimation model under low visibility conditions, according to the visibility value S at the current moment t n,t and the driving information of vehicle i, the vehicle recommended running speed v of vehicle i to ensure vehicle running safety at the current moment t is estimated c,i,t and the safe vehicle distance SS of vehicle i i,t ;

[0009] Step S3, using the vehicle running safety determination model under different visibility conditions, comprehensively considering the safe vehicle distance SS of vehicle i i,tand the distance ΔS between vehicle i and the nearest vehicle f in the same lane ahead i,t the relationship between the running speed v of vehicle i i,t and the recommended running speed v c,i,t of vehicle i, and the running speed v f,t of the nearest vehicle f in the same lane ahead of vehicle i, to determine the running safety level of vehicle i at the current moment t;

[0010] Step S4, according to the running safety level of vehicle i at the current moment t, execute the corresponding vehicle control strategy on vehicle i at the current moment t;

[0011] Step S5, according to the vehicle control strategy of vehicle i at the current moment t, perform multi-mode collaborative lane-level active induction for vehicle i to enable vehicle i to safely and efficiently pass through the sudden fog section.

[0012] Preferably, in step S2, the low visibility condition vehicle running safety speed estimation model includes a low visibility condition vehicle recommended running speed estimation sub-model and a low visibility condition safe vehicle distance estimation sub-model.

[0013] Preferably, the low visibility condition vehicle recommended running speed estimation sub-model is:

[0014]

[0015] where: v o is the recommended speed value for vehicle running under ultra-low visibility; m1, m2, and m3 are respectively the vehicle running speed control coefficients in different visibility intervals; m1 < m2 < m3.

[0016] Preferably, the low visibility condition safe vehicle distance estimation sub-model is:

[0017]

[0018] where:

[0019] S 1,i,t represents the driver's reaction distance when vehicle i travels at the vehicle running speed v i,t at time t; t0 is the driver's reaction time in a normal driving environment; α and b are respectively the first relationship coefficient and the second relationship coefficient;

[0020] S 2,i,t represents the braking distance required for vehicle i when traveling at the vehicle running speed v i,t at time t;

[0021] b i,m is the maximum allowable deceleration of vehicle i, which is a configuration parameter of vehicle i.

[0022] Preferably, the vehicle operation safety determination model under different visibility conditions is as follows:

[0023]

[0024] Where: B c,i,t represents the operation safety level of vehicle i at the current moment t;

[0025] B c,i,t The operation safety level is divided into four levels, namely level 0, level 1, level 2, and level 3.

[0026] Preferably, the vehicle control strategy for each operation safety level B c,i,t is as follows:

[0027] When the operation safety level B c,i,t is level 0, it means that vehicle i is operating absolutely safely, and its vehicle control strategy is: vehicle i moves forward at a constant speed according to the vehicle operation speed v i,t at the current moment t through the sudden fog section, or accelerates from the current moment t to pass through the sudden fog section; the recommended value of its vehicle operation speed is max{v f,t , v c,i,t};

[0028] When the operation safety level B c,i,t is level 1, it means that vehicle i is operating relatively safely, and its vehicle control strategy is: vehicle i starts to decelerate from the current moment t until the recommended value of the vehicle operation speed v c,i,t ;

[0029] When the operation safety level B c,i,t is level 2, it means that vehicle i is operating unsafely, and its vehicle control strategy is: vehicle i starts to decelerate emergently from the current moment t until the vehicle operation speed v f,t of the nearest vehicle f in the same lane ahead;

[0030] When the operation safety level B c,i,t is level 3, it means that vehicle i is operating seriously unsafely, and its vehicle control strategy is: comprehensively determine to execute the lane change induction decision or emergency stop.

[0031] Preferably, the comprehensive determination to execute the lane change induction decision or emergency stop is specifically as follows:

[0032] Obtain the state of the adjacent lane of vehicle i at moment t, that is: determine whether there is a vehicle passing through in the set area before and after the position of vehicle i in the adjacent lane; if not, it means that the adjacent lane of vehicle i has abnormal traffic, and execute the emergency stop operation; if so, it means that the adjacent lane of vehicle i has normal traffic, and execute the lane change induction decision.

[0033] Preferably, the lane-changing induction decision is as follows:

[0034] Obtain the vehicle position x of the nearest vehicle yi+1 in the adjacent lane in front of vehicle i yi+1 , the vehicle running speed v yi+1 and the vehicle running acceleration a yi+1 ;

[0035] Obtain the vehicle position x of the nearest vehicle yi-1 in the adjacent lane behind vehicle i yi-1 , the vehicle running speed v yi-1 and the vehicle running acceleration a yi-1 ;

[0036] Obtain the vehicle position x of vehicle i in its lane i ;

[0037] Judge whether to execute the lane-changing operation through the lane-changing induction decision model of formula (4):

[0038]

[0039] Where:

[0040] H i is the lane-changing induction decision variable; 1 means can change lanes, 0 means cannot change lanes;

[0041] x1(v i , v yi+1 ) is the constraint condition function of vehicle i's decision to change lanes and the vehicle in front in the adjacent lane at the current moment t; x2(v i , v yi-1 ) is the constraint condition function of vehicle i's decision to change lanes and the vehicle behind in the adjacent lane at the current moment t; The expressions are as follows:

[0042]

[0043] Where: L i represents the distance traveled by vehicle i during the lane-changing process along the lane line direction; D represents the lateral movement distance of lane-changing; a H represents the maximum acceleration allowed for lane-changing, and its value is related to the vehicle running speed; t H represents the shortest duration required for lane-changing; d safe is the minimum safe stopping distance.

[0044] Preferably, step S5 is specifically as follows:

[0045] When the operation safety level is B c,i,tWhen the level is 0, the projection imaging module emits blue prompt imaging information into the air and magnifies and displays it in the air. The displayed information is "recommended vehicle speed and dynamic vehicle distance before and after"; at the same time, the light induction module executes a green flashing mode to prompt the driver of the current running safety status;

[0046] When the running safety level is B c,i,t When the level is 1, the projection imaging module emits yellow prompt imaging information into the air and magnifies and displays it in the air. The displayed information is "recommended vehicle speed and dynamic vehicle distance before and after"; at the same time, the light induction module executes a yellow flashing mode to prompt the driver of the current running safety status;

[0047] When the running safety level is B c,i,t When the level is 2, the projection imaging module emits red warning imaging information into the air and magnifies and displays it in the air. The displayed information is "speed limit and dynamic vehicle distance before and after"; at the same time, the light induction module warns the driver that the vehicle distance before and after is too close through the red light flashing mode;

[0048] When the running safety level is B c,i,t When the level is 3, if an emergency stop operation is performed, the projection imaging module emits red warning imaging information into the air and magnifies and displays it in the air. The displayed information is "accident ahead, please slow down"; at the same time, the light induction module executes a red light always-on mode to prompt the driver of the current running safety status;

[0049] If a lane change induction decision is executed; when H i = 1, the projection imaging module emits green warning imaging information into the air and magnifies and displays it in the air. The displayed information is "accident ahead, please change lanes to the right"; at the same time, the beam module emits a right-turn arrow laser beam to induce the vehicles in the accident lane to change lanes; the light induction module executes a left red light always-on mode, and the right lane change position executes a green flashing mode to prompt the driver to change lanes; when H i = 0, the projection imaging module emits green warning imaging information into the air and magnifies and displays it in the air. The displayed information is "accident ahead, slow down and wait for the opportunity to change lanes"; at the same time, the light induction module executes a left red light always-on mode, and the right lane change position executes a yellow flashing mode to prompt the driver to change lanes.

[0050] The present invention also provides a device for the above-mentioned freeway lane-level guidance method under foggy conditions, including:

[0051] An information acquisition unit for real-time obtaining the visibility value S at the current moment t n,t and the driving information of vehicle i that is about to enter the foggy sudden section and is passing through the foggy sudden section; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t and the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,tThe distance ΔS between vehicle i and the nearest vehicle f in the same lane ahead i,t ;

[0052] A cloud platform service unit for storing an estimation model of the safe operating speed of vehicles under low visibility conditions and a determination model of vehicle operating safety under different visibility conditions;

[0053] An information processing unit for calling the estimation model of the safe operating speed of vehicles under low visibility conditions in the cloud platform service unit according to the visibility value S at the current moment t collected by the information collection unit n,t and the driving information of vehicle i about to enter and passing through the sudden fog section, and estimating the recommended operating speed v of vehicle i to ensure vehicle operation safety at the current moment t c,i,t and the safe distance SS of vehicle i; i,t ; and, calling the determination model of vehicle operating safety under different visibility conditions in the cloud platform service unit to determine the operating safety level of vehicle i at the current moment t, and further determining the vehicle control strategy corresponding to vehicle i at the current moment t;

[0054] A lane-level active induction device for actively inducing the lane-level driving safety of vehicle i according to the vehicle control strategy of vehicle i at the current moment t, so that vehicle i can safely pass through the sudden fog section.

[0055] A method and device for lane-level guidance on expressways under fog conditions provided by the present invention have the following advantages:

[0056] The method and device for lane-level guidance on expressways under fog conditions provided by the present invention utilize optoelectronic technology to achieve precise intervention and active guidance on the operation state of road traffic flow. Based on highway electromechanical facilities, the present invention integrates optoelectronic active guidance technology to achieve early warning ahead of the section and lane-level active guidance under fog conditions. The present invention effectively improves the safety of road vehicle operation and road traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flowchart of the method for lane-level guidance on expressways under fog conditions provided by the present invention;

[0058] Figure 2 is a schematic diagram of the device for lane-level guidance on expressways under fog conditions provided by the present invention;

[0059] Figure 3 is an arrangement diagram of the device for lane-level guidance on expressways under fog conditions provided by the present invention.

[0060] Wherein: 1 - lane-level active induction device; 2 - visibility detector; 3 - information processor; 4 - edge controller; 5 - information display board. Detailed implementation manners

[0061] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0062] A freeway lane-level guiding method and device provided by the present invention, in view of the actual characteristics of vehicle operation on freeway sections with frequent occurrence of patchy fog, based on precise control and safe passage, constructs a vehicle operation safety speed estimation model under low visibility conditions, and at the same time, by means of existing technical means, proposes a multi-mode collaborative lane-level driving safety active induction method to achieve lane-level guiding of freeway vehicles under patchy fog conditions.

[0063] Referring to Figure 1 , the present invention provides a freeway lane-level guiding method under patchy fog conditions, including the following steps:

[0064] Step S1, for vehicle i about to enter the patchy fog sudden section and vehicle i passing through the patchy fog sudden section, the visibility value S at the current moment t is obtained in real time n,t and the driving information of vehicle i; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t , the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , and the distance ΔS between vehicle i and the nearest vehicle f in front of it in the same lane i,t ;

[0065] Step S2, using the vehicle operation safety speed estimation model under low visibility conditions, according to the visibility value S at the current moment t n,t and the driving information of vehicle i, the recommended running speed v of vehicle i to ensure vehicle operation safety at the current moment t is estimated c,i,t and the safe vehicle distance SS of vehicle i i,t ;

[0066] Step S3, using the vehicle operation safety determination model under different visibility conditions, comprehensively considering the relationship between the safe vehicle distance SS of vehicle i i,t and the distance ΔS between vehicle i and the nearest vehicle f in front of it in the same lane i,t , the relationship between the vehicle running speed v of vehicle i i,t and the recommended running speed v of vehicle i c,i,t , and the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , to determine the running safety level of vehicle i at the current moment t;

[0067] Step S4: According to the operating safety level of vehicle i at the current moment t, execute the corresponding vehicle control strategy for vehicle i at the current moment t;

[0068] Step S5: According to the vehicle control strategy of vehicle i at the current moment t, perform active lane-level driving safety induction for vehicle i in a multi-mode collaboration manner, so that vehicle i can safely and efficiently pass through the sudden fog section.

[0069] The following is a detailed introduction to each step:

[0070] Step S1: For vehicle i that is about to enter the sudden fog section and is passing through the sudden fog section, obtain the visibility value S at the current moment t in real time n,t and the driving information of vehicle i; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t and the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,t and the distance ΔS between vehicle i and the nearest vehicle f in front of it in the same lane i,t ;

[0071] Step S2: Use the vehicle operating safety speed estimation model under low visibility conditions. According to the visibility value S at the current moment t n,t and the driving information of vehicle i, estimate the recommended vehicle running speed v of vehicle i to ensure vehicle operation safety at the current moment t c,i,t and the safe vehicle distance SS of vehicle i i,t ;

[0072] Specifically, sudden fog has characteristics such as local sudden occurrence and relatively small affected areas, which will cause a sudden huge change in the driving vision of road vehicles, leading to road traffic accidents, especially on highways. According to the statistical analysis of traffic accidents under low visibility conditions on highways, most accidents are rear-end accidents caused by unreasonable vehicle running speeds due to limited vision (on the one hand, the running speed is too fast, and on the other hand, the speed reduction is too fast). Therefore, a reasonable vehicle running speed under low visibility conditions is the key to solving vehicle operation safety under fog conditions. Based on this, based on the actual characteristics of the impact of sudden fog on drivers on roads, combined with the actual impacts such as the reaction time and psychological pressure of drivers driving vehicles, the vehicle operating safety speed under low visibility conditions is estimated.

[0073] The vehicle operating safety speed estimation model under low visibility conditions includes a recommended vehicle running speed estimation sub-model under low visibility conditions and a safe vehicle distance estimation sub-model under low visibility conditions.

[0074] Specifically, since visibility affects both the driver's physiology and psychology, and the degree of influence intensifies as visibility decreases, but there is no strict linear relationship between the two. Based on this, aiming to improve the safety of vehicle operation and more accurately fit and match the influence relationship between the two, the present invention adopts a piecewise fitting method and proposes a sub-model for estimating the recommended operating speed of a vehicle under low visibility conditions as shown in formula (1), giving the recommended operating speed v of the vehicle to ensure the safety of vehicle operation under different visibility S n,t at which c,i,t .

[0075] The sub-model for estimating the recommended operating speed of a vehicle under low visibility conditions is as follows:

[0076]

[0077] where: v o is the recommended speed value for vehicle operation under extremely low visibility, and its value is related to the road linear environment, section speed limit, traffic volume, and accident rate, generally 40 km / h; m1, m2, and m3 are respectively the vehicle operation speed control coefficients in different visibility intervals; m1 < m2 < m3. S n,t is the visibility value at the current moment t, which is directly and real-time obtained by the information acquisition unit. Generally, the visibility value of the current period is obtained by the sliding window + threshold limit method to avoid the problem of large calculation amount caused by frequent data changes.

[0078] The sub-model for estimating the safe distance between vehicles under low visibility conditions is as follows:

[0079]

[0080] where:

[0081] S 1,i,t represents the reaction distance of vehicle i when driving at vehicle operating speed v i,t at time t; t0 is the driver's reaction time in a normal driving environment; α and b are the first relationship coefficient and the second relationship coefficient respectively;

[0082] S 2,i,t represents the braking distance required for vehicle i when driving at vehicle operating speed v i,t at time t;

[0083] b i,m is the maximum allowable deceleration of vehicle i and is a configuration parameter of vehicle i.

[0084] Step S3, adopt the vehicle operation safety determination model under different visibility conditions, and comprehensively consider the safe distance SS i,t of vehicle i and the distance ΔS i,tThe relationship between the vehicle running speed v of vehicle i i,t and the recommended running speed v of vehicle i c,i,t , as well as the vehicle running speed v of the nearest vehicle f in the same lane in front of vehicle i f,t , to determine the running safety level of vehicle i at the current moment t;

[0085] Specifically, the vehicle running safety determination model under different visibility conditions is:

[0086]

[0087] Where: B c,i,t represents the running safety level of vehicle i at the current moment t;

[0088] B c,i,t The running safety level is divided into four levels, namely level 0, level 1, level 2 and level 3.

[0089] Step S4, according to the running safety level of vehicle i at the current moment t, execute the corresponding vehicle control strategy for vehicle i at the current moment t;

[0090] Specifically, the vehicle control strategies for each running safety level B c,i,t are:

[0091] When the running safety level B c,i,t is level 0, it means that vehicle i runs absolutely safely, and its vehicle control strategy is: vehicle i moves forward at a constant speed according to the vehicle running speed v at the current moment t i,t through the sudden fog section, or starts to accelerate from the current moment t to pass through the sudden fog section; the recommended value of its vehicle running speed is max{v f,t , v c,i,t};

[0092] When the running safety level B c,i,t is level 1, it means that vehicle i runs relatively safely, and its vehicle control strategy is: vehicle i starts to decelerate from the current moment t until the vehicle running speed reaches the recommended value v c,i,t ;

[0093] When the running safety level B c,i,t is level 2, it means that vehicle i runs unsafely, and its vehicle control strategy is: vehicle i starts to decelerate emergently from the current moment t until the vehicle running speed reaches the vehicle running speed v of the nearest vehicle f in the same lane in front f,t ;

[0094] When the running safety level B c,i,tWhen it is at level 3, it represents that vehicle i is operating in a seriously unsafe manner, and its vehicle control strategy is: comprehensively determine whether to execute a lane-changing induction decision or an emergency stop. The specific process of comprehensively determining whether to execute a lane-changing induction decision or an emergency stop is as follows:

[0095] Obtain the state of the adjacent lane of vehicle i at time t, that is: determine whether there are vehicles passing through in the set area before and after the position of vehicle i in the adjacent lane; if not, it means that the adjacent lane of vehicle i has abnormal traffic, and execute an emergency stop operation; if so, it means that the adjacent lane of vehicle i has normal traffic, and execute a lane-changing induction decision. The lane-changing induction decision is as follows:

[0096] Obtain the vehicle position x of the nearest vehicle yi+1 in front of vehicle i in the adjacent lane yi+1 , the vehicle running speed v yi+1 and the vehicle running acceleration a yi+1 ;

[0097] Obtain the vehicle position x of the nearest vehicle yi-1 behind vehicle i in the adjacent lane yi-1 , the vehicle running speed v yi-1 and the vehicle running acceleration a yi-1 ;

[0098] Obtain the vehicle position x of vehicle i in its own lane i ;

[0099] Use the lane-changing induction decision model in formula (4) to determine whether to execute a lane-changing operation:

[0100]

[0101] Among them:

[0102] H i is the lane-changing induction decision variable; 1 means it can change lanes, and 0 means it cannot change lanes;

[0103] x1(v i ,v yi+1 ) is the constraint condition function of vehicle i's decision to change lanes and the vehicle in front in the adjacent lane at the current time t; x2(v i ,v yi-1 ) is the constraint condition function of vehicle i's decision to change lanes and the vehicle behind in the adjacent lane at the current time t; the expressions are as follows:

[0104]

[0105] Among them: L i represents the distance traveled by vehicle i during the lane-changing process along the lane line direction; D represents the lateral movement distance for lane-changing, generally 3.5m; a Hrepresents the maximum acceleration allowed for lane change, and its value is related to the vehicle running speed; t H represents the shortest duration required for lane change; d safe is the minimum safe stopping distance.

[0106] Step S5: According to the vehicle control strategy of vehicle i at the current moment t, perform active lane-level driving safety induction for vehicle i in a multi-mode collaborative manner, so that vehicle i can safely and efficiently pass through the sudden fog section.

[0107] Based on the determination conclusion of the vehicle running safety determination model under different visibility conditions, combined with the functions of single devices and the coordination between devices, and fully integrating the characteristics of the vehicle running environment under fog conditions, this system realizes active lane-level driving safety induction in a multi-mode collaborative manner: First, the projection imaging module, that is, based on the theory of water mist refraction and magnification imaging in the air under fog, uses the lane-level active induction device to emit projection images, and the images are magnified and displayed in front of the driver to realize the transmission of induction information to the driver, mainly including vehicle running speed, vehicle distance, vehicle running acceleration, etc.; Second, the light induction module, that is, actively induces the safe vehicle distances before and after the vehicle through the collaborative light flashing of multiple devices, mainly through the light stroboscopic mode between the devices on both sides of the lane; Third, the light beam module, that is, based on the perception of the lane-level active induction device, obtains the road state information between lanes and executes the vehicle lane change induction or emergency stop braking induction function.

[0108] Step S5 is specifically as follows:

[0109] When the running safety level B c,i,t is level 0, the projection imaging module emits blue prompt imaging information into the air and magnifies it for display in the air, and the display information is "suggested vehicle speed and dynamic vehicle distances before and after"; at the same time, the light induction module executes the green flashing mode to prompt the driver of the current running safety state;

[0110] When the running safety level B c,i,t is level 1, the projection imaging module emits yellow prompt imaging information into the air and magnifies it for display in the air, and the display information is "suggested vehicle speed and dynamic vehicle distances before and after"; at the same time, the light induction module executes the yellow flashing mode to prompt the driver of the current running safety state;

[0111] When the running safety level B c,i,t is level 2, the projection imaging module emits red warning imaging information into the air and magnifies it for display in the air, and the display information is "restricted vehicle speed and dynamic vehicle distances before and after"; at the same time, the light induction module warns the driver that the vehicle distance in front and behind is too close through the red light flashing mode;

[0112] When the running safety level B c,i,tWhen it is at level 3, if an emergency stop operation is executed, the projection imaging module emits red warning imaging information into the air and magnifies and displays it in the air. The displayed information is "Accident ahead, please slow down"; meanwhile, the light induction module executes the mode of keeping the red light on constantly, prompting the driver of the current running safety status;

[0113] If the lane change induction decision is executed; when H i = 1, the projection imaging module emits green warning imaging information into the air and magnifies and displays it in the air. The displayed information is "Accident ahead, please change lanes to the right"; meanwhile, the beam module emits a right-turn arrow laser beam to induce the vehicles in the accident lane to change lanes; the light induction module executes the mode of keeping the left red light on constantly, and the right lane change position executes the mode of green flashing, prompting the driver to change lanes; when H i = 0, the projection imaging module emits green warning imaging information into the air and magnifies and displays it in the air. The displayed information is "Accident ahead, slow down and wait for the opportunity to change lanes"; meanwhile, the light induction module executes the mode of keeping the left red light on constantly, and the right lane change position executes the mode of yellow flashing, prompting the driver to change lanes.

[0114] The present invention also provides a highway lane-level guiding device under foggy conditions, which mainly realizes the collection of information on fog-prone sections, as well as the active induction of the running lanes of vehicles. At the same time, based on big data analysis and self-optimization feedback, it realizes the active induction of vehicle running under foggy conditions and gives light and shadow prompts, effectively avoiding the occurrence of road traffic accidents and improving the road traffic operation efficiency.

[0115] As Figure 2 shown, based on the functional requirements of the highway lane-level guiding device under foggy conditions, this device mainly includes an information collection unit, an information processing unit, a cloud platform service unit, a lane-level active induction device, and other accessory components such as power supply and communication. The specific design is as follows:

[0116] The information collection unit is used to obtain the visibility value S at the current moment t n,t and the driving information of vehicle i that is about to enter the foggy sudden section and is passing through the foggy sudden section; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t , the vehicle running speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , and the distance ΔS between vehicle i and the nearest vehicle f in front of it in the same lane i,t ;

[0117] Therefore, the information collection unit is mainly composed of an environmental information acquisition subunit and a vehicle information acquisition subunit. The environmental information acquisition subunit can be a visibility meter to obtain the visibility of the fog. The vehicle information acquisition subunit realizes the collection of the driving information of running vehicles.

[0118] A cloud platform service unit for storing an estimation model of the safe operating speed of a vehicle under low visibility conditions and a determination model of the operating safety of a vehicle under different visibility conditions;

[0119] The cloud platform service unit is composed of a cloud data processing and storage module and a telematics transmission module, which realizes the storage of the information collected by the information collection unit and the optimization of data information. At the same time, based on the historical storage and optimized data information of the platform, the system information processing unit is used to self-optimize the active induction information and control strategies.

[0120] An information processing unit for, according to the visibility value S at the current moment t collected by the information collection unit n,t and the driving information of vehicle i that is about to enter the sudden fog section and is passing through the sudden fog section, calling the estimation model of the safe operating speed of a vehicle under low visibility conditions in the cloud platform service unit to estimate the recommended operating speed v of vehicle i that ensures the safe operation of the vehicle at the current moment t c,i,t and the safe stopping distance SS of vehicle i i,t ; and, calling the determination model of the operating safety of a vehicle under different visibility conditions in the cloud platform service unit to determine the operating safety level of vehicle i at the current moment t, and further determining the vehicle control strategy corresponding to vehicle i at the current moment t;

[0121] The information processing unit can be composed of a high-performance data processing computer to realize the processing and analysis of vehicle information and the processing of current environmental information, so as to judge the operating state of the vehicle and the development trend information of the current environmental fog situation, and based on this, determine the vehicle control strategy.

[0122] A lane-level active induction device for, according to the vehicle control strategy of vehicle i at the current moment t, performing lane-level driving safety active induction on vehicle i to enable vehicle i to safely pass through the sudden fog section.

[0123] The lane-level active induction device mainly consists of lane-level active induction equipment and an upstream reminder display screen in the oncoming direction, and adopts multiple modes to perform active induction prompts and operating speed induction control on passing vehicles.

[0124] The layout of this device is mainly to solve the problem of the safe operation of highway vehicles in fog sections, and realizes precise induction of lane-level safe driving of vehicles under low visibility conditions through lane-level active induction. The specific application cases are described as follows:

[0125] Such as Figure 3 shown, is a layout diagram of a lane-level guidance device on a highway under fog conditions provided by the present invention, including:

[0126] (1) Front-end information perception device

[0127] The front-end information perception device mainly consists of an information collection unit and an information release device, which can obtain the operating environment of highway vehicles and vehicle information, and at the same time prompt vehicle information when entering the lane-level active induction section. Among them, the information collection unit is deployed in the core center area of the fog in the fog-prone section, including Figure 3 The visibility detector represented by 2 in it; and the information release device is mainly deployed at the upstream position of the oncoming traffic flow in the fog-prone section, generally about 2-5 km away from the core center area of the fog in the fog-prone section, that is, before the vehicle enters the fog, including Figure 3 The information release board represented by 5 in it and the edge controller represented by 4.

[0128] (2) Information processing device

[0129] As the core unit of this device, this device mainly consists of a brain-like core processing unit, a cloud platform service unit, etc., and is mainly deployed at the center of the fog-prone section of the highway to process the information obtained by the information collection unit of the fog-prone section of the highway, etc., and to release information for the front-end information release device, so as to use the embedded core processing algorithm to issue induction information and control strategy instructions for the current road section state, and at the same time, based on historical data and control effects, intelligently optimize the control strategy and early warning information, including Figure 3 The information processor represented by 3 in it.

[0130] (3) Lane-level active induction device

[0131] The lane-level active induction device 1 mainly consists of a warning unit, an information release unit, etc., which can execute the instructions of the brain-like core information processing unit. Generally, it is symmetrically deployed at the lane dividing line position according to the number of lanes at equal intervals, and the deployment quantity is determined according to the scope of the fog-affected section. Information can be transmitted between devices, and then through device light, shadow technology, information detection and sensing technology, etc., the lane-level active induction work of road vehicle operation can be realized.

[0132] (4) Cloud platform service device

[0133] The cloud platform service device mainly consists of a cloud platform service unit, which can realize functions such as system cloud data storage, early warning control and decision-making strategy optimization, and at the same time, based on virtual reality technology, simulate and reproduce the operation of road vehicles, so as to realize real-time virtual simulation of vehicle operation under low visibility conditions. After logging in to the system, the dynamic virtual control of the road vehicle operation state can be realized.

[0134] In the present invention, the lane-level active induction on the highway means that under the condition of highway vehicle passing, through road auxiliary facilities, equipment, etc., by using sound, light or electricity, etc., the vehicle can be actively guided lane by lane under bad vision conditions such as thick fog and other harsh environments.

[0135] A method and device for lane-level guidance on expressways under the condition of group fog provided by the present invention utilize optoelectronic technology to achieve precise intervention and active guidance on the operating state of road traffic flow. Based on highway electromechanical facilities, the present invention integrates optoelectronic active guidance technology to achieve early warning ahead of sections and lane-level active guidance under the condition of group fog, effectively improving the safety of road vehicle operation and road traffic efficiency.

[0136] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A highway lane-level guidance method under fog conditions, characterized in that: The following steps are involved: Step S1: for a vehicle i that is about to enter or is passing through a fog burst section, obtain the visibility value S at the current time t in real time. n,t and driving information of vehicle i; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t , the vehicle speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , the distance ΔS between vehicle i and the nearest vehicle f in the same lane i,t ; Step S2: using a vehicle safety speed estimation model under low visibility conditions, according to the visibility value S at the current time t n,t And the driving information of vehicle i, estimate the recommended vehicle running speed v of vehicle i to ensure vehicle running safety at the current time t c,i,t and the safe distance SS of vehicle i i,t ; Step S3, using the vehicle operation safety judgment model under different visibility conditions, comprehensively considering the safe vehicle distance SS of vehicle i i,t and the distance ΔS between vehicle i and the nearest vehicle f in the same lane i,t The relationship between the vehicle speed v of vehicle i i,t The recommended speed v of vehicle i c,i,t and the vehicle speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , determine the operational safety level of vehicle i at the current time t; Step S4, executing a corresponding vehicle control strategy for vehicle i at the current time t according to the operation safety level of vehicle i at the current time t; Step S5, according to the vehicle control strategy of vehicle i at the current time t, multi-mode coordinated lane-level driving safety active guidance is performed on vehicle i, so that vehicle i can pass through the fog burst section safely and efficiently.

2. The lane-level guidance method for highways under foggy conditions according to claim 1 is characterized in that: In step S2, the vehicle running safety speed estimation model under low visibility conditions includes a vehicle recommended running speed estimation sub-model under low visibility conditions and a safe vehicle distance estimation sub-model under low visibility conditions.

3. The highway lane-level guidance method under foggy conditions according to claim 2 is characterized in that: The sub-model for estimating the recommended vehicle running speed under the low visibility condition is: Where: v o is the recommended speed value for vehicle operation under ultra-low visibility; m1, m2, m3 are the vehicle speed control coefficients in different visibility ranges; m1<m2<m3.

4. The highway lane-level guidance method under foggy conditions according to claim 2 is characterized in that: The sub-model for estimating safe vehicle distance under low visibility conditions is: in: S 1,i,t Represents the vehicle i at time t at the vehicle running speed v i,t When driving, the driver's reaction distance; t0 is the driver's reaction time under normal driving conditions; α and b are the first relationship coefficient and the second relationship coefficient respectively; S 2,i,t Represents the vehicle i at time t at the vehicle running speed v i,t The distance required for the vehicle to brake while driving; b i,m is the maximum deceleration allowed for vehicle i and is the configuration parameter of vehicle i.

5. The highway lane-level guidance method under fog conditions according to claim 1 is characterized in that: The vehicle operation safety judgment model under different visibility conditions is: Among them: B c,i,t represents the operational safety level of vehicle i at the current time t; B c,i,t The operational safety level is divided into four levels, namely level 0, level 1, level 2 and level 3.

6. A highway lane-level guidance method under fog conditions according to claim 5, characterized in that: Each operating safety level B c,i,t The vehicle control strategy is: When operating at safety level B c,i,t When it is level 0, it means that vehicle i is absolutely safe to operate, and its vehicle control strategy is: vehicle i runs at the vehicle speed v at the current time t i,t Drive at a constant speed through the sudden fog section, or accelerate from the current time t to pass through the sudden fog section; the recommended vehicle speed is max{v f,t ,v c,i,t }; When operating at safety level B c,i,t When it is level 1, it means that vehicle i is relatively safe to operate. Its vehicle control strategy is: vehicle i starts to decelerate from the current time t to the recommended vehicle speed value v c,i,t ; When operating at safety level B c,i,t When it is level 2, it means that vehicle i is running unsafely, and its vehicle control strategy is: vehicle i starts emergency deceleration from the current time t, and decelerates to the vehicle running speed v of the nearest vehicle f in the same lane f,t ; When operating at safety level B c,i,t When it is level 3, it means that the operation of vehicle i is seriously unsafe, and its vehicle control strategy is: comprehensive judgment to execute lane change induction decision or emergency stop.

7. The highway lane-level guidance method under foggy conditions according to claim 6 is characterized in that: The comprehensive judgment of executing lane change induction decision or emergency stop is specifically as follows: The state of the adjacent lane of vehicle i at time t is obtained, that is, whether there is a vehicle passing through the adjacent lane of vehicle i in the set area before and after the position of vehicle i; if not, it means that the adjacent lane of vehicle i is abnormal, and an emergency stop operation is performed; if yes, it means that the adjacent lane of vehicle i is normal, and a lane change induction decision is executed.

8. The highway lane-level guidance method under foggy conditions according to claim 7 is characterized in that: The lane change induction decision is: Get the vehicle position x of the nearest vehicle yi+1 in front of vehicle i in the adjacent lane yi+1 , vehicle running speed v yi+1 and the vehicle running acceleration a yi+1 ; Get the vehicle position x of the nearest vehicle yi-1 behind vehicle i in the adjacent lane yi-1 , vehicle running speed v yi-1 and the vehicle running acceleration a yi-1 ; Get the vehicle position x of vehicle i in its lane i ; The lane change induction decision model of formula (4) is used to determine whether to execute the lane change operation: in: H i is the lane-changing induction decision variable; 1 means lane-changing is allowed, 0 means lane-changing is not allowed; x1(v i ,v yi+1 ) is the lane change decision function of vehicle i and the constraint condition function of the preceding vehicle in the adjacent lane at the current time t; x2(v i ,v yi-1 ) is the lane change decision function of vehicle i and the constraint condition function of the vehicle behind in the adjacent lane at the current time t; the expression is as follows: Where: L i Represents the distance traveled by vehicle i during the lane change process along the lane line; D represents the lateral movement distance of lane change; a H Represents the maximum acceleration allowed for lane change, and its value is related to the vehicle's running speed; t H Represents the shortest time required for lane change; d safe The minimum safe stopping distance.

9. The highway lane-level guidance method under foggy conditions according to claim 8, characterized in that: Step S5 is specifically as follows: When operating at safety level B c,i,t When it is level 0, the projection imaging module emits blue prompt imaging information into the air and displays it in an amplified form in the air, showing "recommended vehicle speed and dynamic distance between front and rear vehicles". At the same time, the light induction module executes green flashing mode to remind the driver of the current safe operating status. When operating at safety level B c,i,t At level 1, the projection imaging module emits yellow prompt imaging information into the air and displays it in an amplified form in the air, showing "recommended vehicle speed and dynamic distance between front and rear vehicles". At the same time, the light induction module executes a yellow flashing mode to remind the driver of the current safe operating status. When operating at safety level B c,i,t At level 2, the projection imaging module emits red warning imaging information into the air and displays it in an amplified form in the air, with the displayed information being "limited speed and dynamic distance between front and rear vehicles". At the same time, the light induction module flashes red lights to warn the driver that the distance between front and rear vehicles is too close. When operating at safety level B c,i,t At level 3, if an emergency stop is performed, the projection imaging module will emit red warning imaging information into the air and display it in an amplified form in the air, with the message "Accident ahead, please slow down"; at the same time, the light induction module will keep the red light on to remind the driver of the current safe operating status; If the lane change induction decision is executed; when H i =1, the projection imaging module emits green warning imaging information into the air and displays it in an amplified form in the air, with the message "Accident ahead, please change lanes to the right"; at the same time, the light beam module emits a right-turn arrow laser beam to induce vehicles in the accident lane to change lanes; The light guidance module implements the left side red light constant on mode, and the right side lane change position implements the green flashing mode, prompting the driver to change lanes; when H i =0, the projection imaging module emits green warning imaging information into the air and displays it in an amplified form in the air, with the displayed information being "accident ahead, slow down and wait for the opportunity to change lanes"; at the same time, the lighting induction module executes the left side red light mode and the right side lane change position executes the yellow flashing mode, prompting the driver to change lanes.

10. A device for a highway lane-level guidance method under fog conditions as claimed in any one of claims 1 to 9, characterized in that: include: Information collection unit, used to obtain the visibility value S at the current time t in real time n,t and the driving information of vehicle i that is about to enter the sudden fog section and is passing through the sudden fog section; the driving information of vehicle i includes the vehicle running speed v of vehicle i i,t , the vehicle speed v of the nearest vehicle f in front of vehicle i in the same lane f,t , the distance ΔS between vehicle i and the nearest vehicle f in the same lane i,t ; A cloud platform service unit, used to store a vehicle running safety speed estimation model under low visibility conditions and a vehicle running safety determination model under different visibility conditions; An information processing unit is used to process the visibility value S at the current time t collected by the information collection unit. n,t As well as the driving information of vehicle i that is about to enter the fog burst section or is passing through the fog burst section, the vehicle running safety speed estimation model under low visibility conditions of the cloud platform service unit is called to estimate the vehicle recommended running speed v of vehicle i that ensures vehicle running safety at the current time t c,i,t and the safe distance SS of vehicle i i,t ; as well as , calling the vehicle operation safety determination model under different visibility conditions of the cloud platform service unit to determine the operation safety level of vehicle i at the current time t, and then determining the vehicle control strategy corresponding to vehicle i at the current time t; The lane-level active induction device is used to actively guide vehicle i for lane-level driving safety according to the vehicle control strategy of vehicle i at the current time t, so that vehicle i can safely pass through the sudden fog section.

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