CN117037538B - System for determining AGS distance of special expressway of small bus - Google Patents
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Abstract
The invention relates to the technical field of highway traffic, and discloses a system for determining AGS distance of a special expressway for a small bus, which comprises a data acquisition module and an AGS distance determination module; the data acquisition module is used for acquiring road condition information, vehicle condition information of a simulated vehicle and visual cognition characteristic information; the road condition information comprises a special expressway grade of the small bus, a special expressway main line design speed of the small bus, the number of lanes, the width of lanes and the speed limit speed of a ramp; the vehicle condition information comprises an automation level of the simulated vehicle; the AGS distance determining module is used for acquiring output data by adopting a preset calculation model according to the data acquired by the data acquisition module; the output data comprises a preposed distance calculation value; the scheme overcomes the defect that the traditional prepositive distance determining method is not suitable for the ultra-high speed running condition of the expressway special for the future minibus, and simultaneously provides scientific basis for determining the prepositive distance of the exit forecast sign of the expressway special for the future minibus.
Description
Technical Field
The invention relates to the technical field of highway traffic, in particular to a system for determining an AGS distance of a special expressway for a small bus.
Background
Along with the increase of the freight traffic of the highway and the development of the freight car towards the heavy load, the contradiction between the freight car and the traffic safety of the highway is increasingly remarkable, and as the heavy load freight car is far behind a minibus in the aspect of maneuver performance, the driving speed is lower, the car body size is large, a larger gap is easy to form in the driving process, the overtaking requirement of the minibus is increased, traffic accidents are easy to occur, the mutual interference between the carriage and the freight car is large, and the road traffic capacity is reduced. The special expressway for the minibus has the characteristics of small outline size, strong maneuvering performance, small carrying capacity and the like, so that the requirements of the special expressway for the geometric line index of the road, the pavement structure, the material and the bridge structure load are reduced, the whole life cycle manufacturing cost of the road is reduced, and the sustainable industry development concept is met, so that the concept of passenger-cargo separation is gradually proposed for improving the road service level, improving the road safety, promoting the effective utilization of resources and the like.
Meanwhile, on the basis of the gradual increase of traffic volume, the design speed of the expressway is new, the expressway with the design speed exceeding 120km/h is possible to be built, the passenger-cargo separation concept is put forward, the expressway special for the passenger car with 120km/h-240km/h appears in the future, the line shape of the road is continuously balanced and coordinated, and the design is more standardized. To ensure safe and comfortable driving under the ultra-high-speed environment, the development of automobile performance needs to be further promoted, the driving speed of the automobile is higher, the intelligent degree is higher, the minibus gradually tends to develop to an intelligent automobile, the task of ultra-high-speed driving is completed by replacing human beings through intelligent decision and control, and compared with the operation of a driver, the intelligent automobile has more strict control of the speed in the on-line driving process and smaller generated transverse movement.
Under the condition that the road construction technology and the automobile performance are continuously developed and improved, the front distance of the existing highway exit forenotice mark AGS is a fixed value and a unified value which are set according to experience, even if a researched data model is used, data acquisition and calculation are only carried out according to the running environment of the highway, but in the ultra-high speed running environment, the road design is different, the running environment is different, the performance, the intelligent degree and the running speed of the passenger car are greatly improved, the front distance value set according to the existing experience does not consider the influences of various factors such as the main line and ramp speed of the highway, the number of lanes and the mark setting mode of the passenger car, if the front distance value is used in the running environment which is not changed in amplitude according to the fixed experience value, the distance value is unreasonable, the requirements of the passenger car running out at one time under the ultra-high speed working condition and the safety running out of the exit are met, the driver is not missed the exit or the traffic flow disturbance is caused even the car collision is caused, and the like safety problems of the passenger car are solved, and the front distance value set according to the fixed experience is not suitable for the special highway of the passenger car in the future.
Disclosure of Invention
The invention aims to provide a system for determining the AGS distance of a special expressway for a small bus, which is used for solving the technical problem that the empirical value of the AGS front distance of the existing expressway exit advance notice sign is not suitable for being used in the special expressway driving scene of the small bus with high safety requirements.
The basic scheme provided by the invention is as follows: a system for determining AGS distance of a special expressway of a small bus comprises a data acquisition module and an AGS distance determination module;
the data acquisition module is used for acquiring road condition information, vehicle condition information of a simulated vehicle and visual cognition characteristic information; the road condition information comprises a special expressway grade of the small bus, a special expressway main line design speed of the small bus, the number of lanes, the width of lanes and the speed limit speed of a ramp; the vehicle condition information comprises an automation level of the simulated vehicle; the visual cognition characteristic information comprises a reading time, a decision time, a channel changing waiting time, a channel changing time and a visual recognition angle of the exit forenotice mark;
the AGS distance determining module is used for acquiring output data by adopting a preset calculation model according to the data acquired by the data acquisition module; the output data includes a preamble distance calculation.
The working principle and the advantages of the invention are as follows: the prior art considers that the recognition condition of the exit forecast sign cannot influence the front distance no matter the ultra-high speed or the high-speed working condition, because the safety of entering the exit is not completely determined by the front distance, but is more determined by controlling the driving vehicle, the safety can be ensured to a great extent only by adopting a conventional experience distance value, then the driving safety is improved by arranging a warning sign along the highway, and if the driving safety is improved, the driving safety is not lengthened by a certain distance according to the experience value. However, in the actual research process, it is found that along with the upgrade of the expressway and the improvement of the performance of the automobile, the identification of the exit forecast flag is actually affected by various factors such as the grade of the expressway, the speed of the main line, the number of lanes, the width of the lanes, the speed limit speed of the ramp, the grade of the vehicle, and the like, and the determination of the prepositive distance can be referred only by integrating the above-mentioned influencing factors in the determination of the prepositive distance, so that the scheme performs creative labor.
The scheme breaks through the previous mode that the front distance of the expressway exit advance notice mark is fixedly and uniformly set through experience, considers the development of the expressway and the automobile performance in the future, comprehensively considers the expressway grade, the design speed of the main line of the expressway, the number of lanes, the width of the lanes, the speed limit speed of the ramp and other road condition factors, the vehicle automation grade and other vehicle condition factors and visual cognition characteristic information in the front distance determining process, and enables the scene of the front distance determination to be closer to the situation of the expressway running of the future minibus on the special expressway, so that the obtained calculation result of the front distance is more reasonable. The scheme overcomes the defect that the traditional prepositive distance determining method is not suitable for the ultra-high speed running condition of the expressway special for the future minibus, and simultaneously provides scientific basis for determining the prepositive distance of the exit forecast sign of the expressway special for the future minibus.
Further, the system also comprises a test scene building module and a calculation model selection module;
the test scene building module is used for building different test scenes according to the special expressway grade of the passenger car and the automation grade of the simulated vehicle, which are acquired by the data acquisition module;
the computing model selection module is used for selecting a first computing model or a second computing model as a preset computing model to be input into the AGS distance determination module by adopting a preset selection strategy according to different testing scenes.
The beneficial effects are that: the scheme designs a multi-scene multi-model front distance determination method under the condition of ultra-high speed driving of a future small bus on a special expressway, different test scenes are constructed according to road conditions and vehicle conditions under the special driving environment of the expressway, and the ultra-high speed working conditions of future possible design and construction are covered, so that the determination method of the scheme has high universality and high reference value; meanwhile, according to different running operation conditions, different calculation models are adopted, so that a running scene is more matched with the calculation models, and a calculation result is more reasonable.
Further, the grades of the special expressways of the minibuses are super grade, super grade two and super grade three; the automation level comprises autonomous driving assistance, autonomous automatic driving, internet connection driving assistance and internet connection automatic driving; the test scenes comprise a super-first-level-autonomous driving auxiliary scene, a super-first-level-networked driving auxiliary scene, a super-second-level-autonomous driving automatic scene and a super-third-level-networked driving automatic scene.
The beneficial effects are that: according to the current research results of the expressway and the intelligent vehicle, a running scene which possibly appears in the future is constructed, and a multi-dimensional front distance calculation result is obtained by utilizing a multi-scene mode, so that the front distance determination has a reference value.
Further, the preset selection strategy is to select a first calculation model when the test scene is a super-level-autonomous driving auxiliary scene; and when the test scene is a super-level-networking driving auxiliary scene, a super-level-autonomous driving scene or a super-three-level-networking driving scene, selecting a second calculation model.
The beneficial effects are that: compared with other scenes, the super-first-level autonomous driving auxiliary scene is lower in expressway level and automobile intelligent degree, and is closer to the existing high-speed driving scene, so that when the front distance is determined, the super-first-level autonomous driving auxiliary scene is different from other scenes with higher speed and higher intelligent degree, different calculation models are adopted, and the obtained distance result accords with the driving environment.
Further, the first and second calculation models include the steps of:
s1: after the last AGS is found, the read distance r from the read mark to the read mark content is started; wherein r=v 0 Is the design speed of the main line of the expressway special for the minibus, t 1 Is read time;
s2: calculating a decision distance j from the completion of reading the mark to the beginning of operation; wherein,v 0 is the design speed of the main line of the expressway special for the minibus, t 2 Is the decision time;
s3: calculating an action distance L from the start of operation to the completion of operation; wherein l=l 1 +L 2 ，L 1 Distance L for lane change 2 The driving distance is the deceleration process;k is the number of lanes, t d For the channel change waiting time, t h For lane change time, v x To start the speed before deceleration v 1 The speed limiting speed of the ramp is phi, the friction coefficient of the expressway and the tire is phi, i is the road longitudinal slope, and g is gravity acceleration;
s4: calculating a visual recognition distance S and a vanishing distance M from the mark position to the mark position;
s5: the leading distance D of the flag is calculated, d=r+j+l-S.
The beneficial effects are that: the method is characterized in that a calculation model of the front distance of the exit forenotice sign under the ultra-high speed working condition of the small bus is built by combining the main line design speed, the number of lanes, the lane width, the ramp speed limit speed and other road condition factors, the vehicle automation level and other vehicle condition factors and visual cognition characteristic information of the small bus, and the calculated value of the front distance of the small bus under the ultra-high speed running condition of the small bus on the special expressway is given, so that the small bus can effectively visually recognize the exit forenotice sign, quickly determine the front position information, facilitate effective decision making, ensure that the vehicle runs off the exit smoothly, and improve the running safety.
Further, in the first calculation model S4, the visual recognition distance S is: s= -272.33h 2 +408.31h-25.72+ε, h is Chinese character height and ε is stroke complexity correction coefficient.
The beneficial effects are that: the scene using the first calculation model is a super-level-autonomous driving auxiliary scene, the super-highway and the common highway have overlapped parts on the design speed of the main line, and the running vehicle is basically a common vehicle, and is mainly judged by a driver, so that the visual recognition distance in the first calculation model is more considered as a direct recognition mode of the driver, the visual recognition distance calculated by the font per se is more consistent with the scene, and the result is more reasonable and has reference value.
Further, in the second calculation model S4, the visual recognition distance S is:
when the exit forenotice sign is roadside standing, s= ((k-0.5) ×wl+st) ×cotθ, where k is the number of lanes and wl is the lane width; st is the transverse offset of the vertical installation mark, and θ is the visual angle;
when the exit forenotice sign is a road cross type, s=max (S1, S2), s1= (k-1) ×wl×cotθ, s2=sv×cotθ, where k is the number of lanes, wl is the lane width, S1 is the distance from the visual point to the sign considering the lateral shift, S2 is the distance from the visual point to the sign considering the longitudinal shift, sv is the longitudinal shift amount across the installation sign, and θ is the visual point.
The beneficial effects are that: when the method is used in a super-level-internet-access driving auxiliary scene, a super-level-autonomous driving scene or a super-three-level-internet-access automatic driving scene, compared with a word height, the method has the advantages that the overall setting mode of the marks, the overall environment set by the marks and the determination influence of different visual capacities of drivers and vehicles on the visual recognition distance are larger, so that the traditional calculation model related to the word height is not applicable any more, the calculation model related to the mark setting mode, the lane width and the visual recognition angle of the drivers is adopted, the visual recognition distance of the existing mode is more met, and the calculation of the visual recognition distance in the whole front distance confirmation is more accurate.
Further, the vanishing distance M is:
when the exit forenotice sign is roadside standing, m= ((k-0.5) wl+wx+wy)/tan θ, where k is the number of lanes, wl is the lane width, θ is the visual recognition angle, wx is the hard shoulder width, wy is the sign edge-to-hard shoulder distance;
when the exit forenotice sign is crossing over the road, m= (HF-hs)/tan θ, HF is the sign height crossing over the road, hs is the driver's visual height, and θ is the visual angle.
Further comprising S6: calculating the distance R between two exit forenotice marks, wherein R=S+q-M, and q is the distance between memory intervals; the output data of the minimum distance determination module further comprises a distance calculation value between the two exit forenotice marks.
The beneficial effects are that: the vanishing distance refers to the distance that an object is invisible from the sight of an observer, in the driving process, when the object is positioned at a certain distance in front of the marks, the exit forenotice marks disappear from the sight of the driver, the distance from the beginning of the vanishing to the positions of the marks is the vanishing distance M in the calculation model, the distance can be combined with a time interval with clear short-time memory quantity, the memory interval of mark information when the object passes through the two exit forenotice marks is calculated, the setting distance between the two forenotice marks is further calculated, and reference data are provided for the intervals of a plurality of forenotice marks.
Further, the system also comprises a recommended distance determining module, which is used for outputting a minimum recommended value of the front distance based on the most unfavorable principle according to the front distance calculated value acquired by the AGS distance determining module.
The beneficial effects are that: the reasonable prepositive distance of the exit forenotice sign is set to ensure that a driver or a vehicle has sufficient preparation time and comfortable operation space, and can complete driving operation smoothly and drive into a ramp; the value calculated according to the formula is the minimum value satisfying safe driving and is not necessarily an integer, so that the calculated front distance needs to be rounded up in the most unfavorable principle, and a more reasonable recommended value is obtained for practical application, so that safer driving distance and safer use environment are provided.
Drawings
FIG. 1 is a logic block diagram of a system for determining AGS distance of a highway dedicated for a small bus according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a calculation process of a calculation model according to an embodiment of the present invention;
FIG. 3 is a flow chart of a visual indication and driving operation process provided by an embodiment of the present invention;
FIG. 4 is a schematic view of the vanishing distance of the road side standing mark during driving according to the embodiment of the present invention;
FIG. 5 is a schematic diagram of vanishing distance of a cross-over sign on a road during driving according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a short-time memory-based distance setting between marks according to an embodiment of the present invention.
Detailed Description
The following is a further detailed description of the embodiments:
the labels in the drawings of this specification include: the system comprises a data acquisition module 100, a test scene construction module 200, a calculation model selection module 300, an AGS distance determination module 400 and a recommended distance determination module 500.
Examples are shown in fig. 1: the system for determining the AGS distance of the expressway special for the small bus comprises a data acquisition module 100, a test scene building module 200, a calculation model selection module 300, an AGS distance determination module 400 and a recommended distance determination module 500; the road condition information and the vehicle condition information acquired by the data acquisition module 100 are transmitted to the test scene building module 200 to create different test scenes; the test scene data is transmitted to the calculation model selection module 300 to select a corresponding calculation model of the test scene, the selected calculation model and the data acquired by the data acquisition module are transmitted to the AGS distance determination module 400 together to acquire corresponding output data, calculation of the minimum front distance under the test scene is completed, and further, the calculated value of the minimum front distance is transmitted to the recommended distance determination module 500 to obtain a recommended value, so that the given front distance has a higher reference value.
Specifically, the data acquisition module 100 is configured to acquire road condition information, vehicle condition information of a simulated vehicle, and visual cognition characteristic information; the road condition information comprises a special expressway grade of the small bus, a special expressway main line design speed of the small bus, the number of lanes, the width of lanes and the speed limit speed of a ramp; the grade of the special expressway for the small bus is super grade, super grade and super three grade.
In this embodiment, because the test is performed, the data is transmitted to the data acquisition module 100 for data acquisition by adopting a manner of user side input, and in other embodiments, the related data transmission and acquisition can be completed by adopting technology fusion with other systems. According to the existing highway grading research results, the design speed of the main line of the common highway is 20-100km/h, the expressways are divided into common expressways and super highways, and the design speed of the main line of the common highway is 60-120km/h; the design speed of the main line of the expressway is 100-240km/h, and the expressway is divided into more than one grade of 100-160km/h, more than two grades of 140-200km/h and more than three grades of 180-240km/h. The main line speed of the special expressway of the passenger car in the planned construction is 120-240km/h, in the actual development process, overlapping parts exist between development stages, such as the expressway with the main line design speed of 100-120km/h, and the special expressway can be used as a common expressway or a super grade expressway, so that in the process of carrying out the prepositive distance determination test scene construction, or the special expressway grade of the passenger car is classified by the super grade, and the scene simulation is closer to the future actual scene.
The vehicle condition information comprises an automation level of the simulated vehicle;
in the embodiment, according to the construction of the future ultra-high speed highway, the automobile performance is required to be synchronously improved to ensure the safe and comfortable running under the ultra-high speed working condition, and according to the related research of the existing automobile, the intelligent automobile is classified from two dimensions of intellectualization and networking, and the intelligent automobile is mainly divided into autonomous driving assistance and autonomous automatic driving; network driving assistance and network automatic driving; the driving assistance mainly takes the driver as the main part, the system is used as the assistance to control the vehicle, the automatic driving mainly takes the system as the main part, and the manual assistance is used to control the vehicle; the network connection is more intelligent than the autonomous mode; the degree of automation is different, in the process of determining the prepositive distance, the influence factors and the relation complexity are different, and the final determining steps and methods are also different, so that the accuracy of the data can be effectively ensured.
The test scene building module 200 is configured to build different test scenes according to the expressway grade special for the passenger car and the automation grade of the simulated vehicle acquired by the data acquisition module 100;
in this embodiment, during system initialization, data related to the future expressway grade of the passenger car and the automation grade of the simulated vehicle are input into the data acquisition module 100, and then transmitted to the test scene building module 200 for all test scene building, including super-first-grade-autonomous driving assistance scene, super-first-grade-networked driving assistance scene, super-second-grade-autonomous driving assistance scene and super-third-grade-networked automatic driving scene. Because the design speed range of the main line of the super-grade expressway is 100km/h-160km/h, wherein the speed range of 100km/h-120km/h is overlapped with the main line speed of the common expressway, the design of the first calculation model is compared with the experience setting of the common expressway, and the design of the first calculation model and the second calculation model is used for setting and distinguishing the speed ranges, so that the determination of the front distance is more reasonable. At the time of testing, the corresponding calculation model selection is directly performed according to the road grade and the automation grade of the simulated vehicle transmitted by the data acquisition module 100.
The computing model selecting module 300 is configured to select, according to different test scenarios, a first computing model or a second computing model as a preset computing model by adopting a preset selecting policy, and input the selected first computing model or the selected second computing model to the agsag distance determining module 400.
In this embodiment, when the system is initialized, after all test scenes are built, corresponding calculation model selection is performed, where the preset selection strategy is to select a first calculation model when the test scene is a super-level-autonomous driving auxiliary scene, specifically, when the special high-speed level of the small client is a super-level and the design speed of the main line is in the range of 100km/h-120km/h, the speed and the vehicle performance are similar as the existing common high speed, so that the first calculation model is selected; when the test scene is a super-level-network-connected driving auxiliary scene, a super-level-autonomous automatic driving scene or a super-three-level-network-connected automatic driving scene, specifically, when the design speed of the main line of the expressway special for the small client is above 120km/h, and the automobile is network-connected driving auxiliary, autonomous automatic driving scene or network-connected automatic driving, the second calculation model is selected.
Specifically, as shown in fig. 2 and fig. 3, firstly, it should be noted that, when the driving behavior in the AGS distance determining process is that the last exit forecast flag port is found in the driving process, the flag is read, the read information is judged, reacted and then decided, a suitable lane change gap is found to perform multiple lane change, and after lane change is completed, the speed is reduced to adjust the driving, and the driving is carried out away from the exit, and the whole behavior process can be defined as passing 7 points in sequence: a finding point A, the driver finds the position of the last exit forenotice mark; a start reading point B, a position where a driver starts to read the information on the mark; a read-out point C, a position where the information on the mark is read out by the driver; vanishing point M, where the driver cannot see the sign; an operation point D at which the driver starts a lane change operation; marking point F, the position of the last exit forenotice mark; the lane change completion point H, the driver changes to the position where the operation is completed and the deceleration adjustment is started.
AGS distance determination, wherein the first calculation model and the second calculation model comprise the following steps:
s1: after the last AGS is found, the read-recognizing distance r from the read-recognizing mark to the read-out mark content is calculated, namely the distance from the start point B to the read-out point C; wherein,v 0 is the design speed of the main line of the expressway special for the minibus, t 1 Is read time;
s2: calculating a decision distance j from the finishing reading mark to the starting operation, namely, a distance from the finishing reading point C to the operating point D; wherein,v 0 is the design speed of the main line of the expressway special for the minibus, t 2 Is the decision time;
s3: calculating an action distance L from the start of operation to the completion of operation; wherein l=l 1 +L 2 ；
L 1 The driving distance is the distance between the operating point D and the lane changing completion point H in the lane changing process;
k is the number of lanes, t d For the channel change waiting time, t h The channel changing time is;
L 2 the driving distance is the distance between the lane change completion point H and the diversion point E in the deceleration process;
v x to start the speed before deceleration v 1 The speed limiting speed of the ramp is phi, the friction coefficient of the expressway and the tire is phi, i is the longitudinal slope of the road, and g is gravity acceleration; in the present embodimentThe phi of the asphalt pavement can be 0.4; the longitudinal slope of the road is generally 0; g is gravity acceleration, 9.8m/s 2 。
S4: calculating a visual recognition distance S and a vanishing distance M from the mark position to the mark position;
in the first calculation model S4, the visual recognition distance S is: s= -272.33h 2 +408.31h-25.72+ε, h is Chinese character height and ε is stroke complexity correction coefficient.
In this embodiment, the Chinese character height is generally 60-70cm according to the speed of 100-120km/h in the existing specification, wherein the value of ε is referred to in Table 1.
Table 1 correction coefficient ε value standard
In the second calculation model S4, the visual recognition distance S is:
when the exit forenotice sign is roadside standing, s= ((k-0.5) ×w) l +S t ) X cotθ, where k is the number of lanes, w l Is the lane width; s is S t The horizontal offset of the vertical installation mark is that theta is the visual angle; in the present embodiment, S t Taking 3.03m;
when the exit forenotice sign is a road cross type, s=max (S1, S2), s1= (k-1) ×wl×cotθ, s2=sv×cotθ, where k is the number of lanes, wl is the lane width, S1 is the distance from the visual point to the sign considering the lateral shift, S2 is the distance from the visual point to the sign considering the longitudinal shift, sv is the longitudinal shift amount across the installation sign, and θ is the visual point. In this example, sv is 2.5m.
Vanishing distance M, i.e. the distance between vanishing point M and mark F:
as shown in fig. 4, when the exit forenotice sign is the roadside standing type, m= ((k-0.5) wl+wx+wy)/tan θ, where k is the number of lanes, wl is the lane width, θ is the viewing angle, wx is the hard shoulder width, and in this embodiment, 2.5M is taken; wy is the distance from the edge of the mark to the hard shoulder, which is 0.25m in this example;
as shown in fig. 5, when the exit forenotice sign is a road crossing sign, m= (HF-hs)/tan θ, HF is a sign height of the road crossing, hs is a driver's visual height, and 1.2M is taken in this embodiment, θ is a visual angle.
When the number of the unidirectional lanes is not more than 3, the setting mode of the marks is selected as roadside upright, and if the number of the lanes exceeds 3, the road crossing type marks are adopted; when the calculation model is selected, the number of lanes in the road condition information is also required to be judged, and the corresponding calculation modes of the visual recognition distance S and the vanishing distance M are selected according to the number of lanes.
After the visual recognition distance S and the vanishing distance M are calculated, the visual recognition distance S and the vanishing distance M are determined, and if the visual recognition distance S is smaller than the vanishing distance M, it is indicated that such a distance cannot give an appropriate reading time, so that S is equal to M, and the next calculation is performed.
S5: the leading distance D of the flag is calculated, d=r+j+l-S.
As shown in fig. 6, after S5, S6 is further included: calculating the distance R between two exit forenotice marks, wherein R=S+q-M, q is the distance between a memory interval, namely the distance between a vanishing point M and another initial reading point is the memory interval q,＝6.94v 0 wherein v is 0 The design speed of the main line of the highway special for the minibus is designed, T is a time interval with clear short-time memory, and 25s is taken in the embodiment.
In conclusion, the establishment of the whole calculation model is completed, meanwhile, the calculation model is fused with a test scene established based on road conditions and vehicle conditions, compared with the empirical value determination in the prior art, the calculation model in the scheme fuses the influence of the road conditions and the vehicle conditions on the setting of the front distance of the exit forenotice sign, so that the determination of the front distance of the whole exit forenotice sign is closer to a future construction scene, and the result is more referential.
After the embodiment calculation model is established, testing is performed. And visually displaying the test data result at the system terminal so as to allow a user to visually check, compare and analyze.
The visual cognition characteristic information acquired by the data acquisition module comprises the recognition time, decision time, channel switching waiting time, channel switching time and visual recognition angle of the exit forenotice mark;
in this embodiment, through test and research, the reading time may be 2.5s, the decision time may be 2-2.5 s, the channel changing waiting time may be 6.6s, the channel changing time may be 1.5s, and the viewing angle may be 7-10 °. Compared with road condition data, vehicle condition data and visual cognition characteristic information are easier to change along with the development of technology, so that in actual test, corresponding data can be determined in a more accurate range according to different test equipment and different test research methods, and the determination of the front distance of the special expressway exit advance notice sign of the passenger car is more accurate.
The first test scene is a super-first-class-autonomous driving auxiliary scene, the unidirectional three-lane is adopted as an exit predictive marker, the height of Chinese characters on the marker is 70cm, the design speed of a main line is 120km/h, the design speed of a ramp is 50km/h, the width of a lane is 3.5m, the width of a hard shoulder is 2.5m, the distance from the edge of the marker to the hard shoulder is 0.25m, and the longitudinal gradient of a road is 0.
The above data is input from the user end and transmitted to the data acquisition module 100, and meanwhile, road condition and vehicle condition information is transmitted to the test scene construction module 200 to select a super-class-autonomous driving auxiliary scene, and then the selected test scene is transmitted to the calculation model selection module 300, the first model is selected according to a preset selection strategy, and the calculation of the visual recognition distance S and the vanishing distance M is vertical.
The AGS distance determining module 400 outputs data according to the data collected by the data collecting module 100 and the first calculation model and the upright type selected by the calculation model selecting module 300:
(1) Calculate the read distance, r=v 0 t 1 /3.6＝0.694v 0 ＝83.28m。
(2) Calculating a decision distance, j=v 0 t 2 /3.6＝0.556v 0 ＝66.72m。
(3) Calculate the action distance, l=l 1 +L 2 ,L 1 ＝(k-1)(t d +t h )v 0 /3.6＝2.25(k-1)v 0 ＝2.25×2×120＝540m，L 2 ＝v x 2 -v 1 2 /254(φ+i)＝120 2 -50 2 254 (0.4+0) = 117.13m, then l=l 1 +L 2 ＝540+117.13＝657.13m。
(4) Calculate the visual recognition distance, s= -272.33h 2 +408.31h-25.72+ε＝-272.33×0.7 2 +408.31×0.7-25.72+10＝136.66m。
(5) The lead distance D of the last block of exit forenotice signs was calculated, d=r+j+l-s=83.28+66.72+657.13-136.66 = 670.47m.
The leading distance to the last block of exit forenotice flag is 671m.
(6) The vanishing distance, M= ((k-0.5) wl+wx+wy)/tan θ= (2.5×3.5+2.5+0.25)/tan 10 = 65.22M, M.ltoreq.S, was calculated.
(7) Calculating the distance between two blocks of forenotice marks, r=s+q-M, q=v 0 T/3.6＝6.94v 0 ＝6.94×120＝833.33m，R＝136.66+833.33-65.22＝904.77m。
The distance between the two exit forenotes is found to be 905m.
The recommended distance determining module 500 outputs a minimum recommended value of the front distance based on the most unfavorable principle according to the calculated value of the front distance acquired by the AGS distance determining module 400. The recommended value takes value rule, according to the most unfavorable principle, the value is rounded up by a multiple of 50 on the basis of the calculated value of the front distance. The most disadvantageous principle is that the problem is considered from the 'extremely bad' condition, and the recommended value of the scheme is considered to be increased by a minimum guarantee value on the basis of the calculated value so as to ensure that the recommended value is the closest distance value capable of guaranteeing the minimum safety required by entering an exit.
Under the first test scene, a front distance recommended value is 750m; the recommended distance between the two exit forenotes is 950m.
The second test scene is a super-first grade-network driving auxiliary scene, a unidirectional four-lane road is adopted as an exit forenotice sign, the lateral offset of the sign is 3.03m, the design speed of a main line is 140km/h, the design speed of a ramp is 50km/h, the lane width is 3.5m, the width of a hard road shoulder is 2.5m, the distance from the edge of the sign to the hard road shoulder is 0.25m, and the road longitudinal gradient is 0; the data acquisition module acquires the input information.
The above data is input from the user end and transmitted to the data acquisition module 100, meanwhile, road condition and vehicle condition information is transmitted to the test scene building module 200 to select a super-level-networking driving auxiliary scene, then the selected test scene is transmitted to the calculation model selection module 300, a second model is selected according to a preset selection strategy, and the calculation of the visual recognition distance S and the vanishing distance M adopts a road cross type.
The AGS distance determining module 400 outputs data according to the data collected by the data collecting module 100 and the second calculation model and the road cross type selected by the calculation model selecting module 300:
(1) Calculate the read distance, r=v 0 t 1 /3.6＝0.694v 0 ＝97.16m。
(2) Calculating a decision distance, j=v 0 t 2 /3.6＝0.556v 0 ＝77.84m。
(3) Calculate the action distance, l=l 1 +L 2 ,L 1 ＝(k-1)(t d +t h )v 0 /3.6＝2.25(k-1)v 0 ＝2.25×3×140＝945m，L 2 ＝v x 2 -v 1 2 /254(φ+i)＝140 2 -50 2 254 (0.4+0) = 168.31m, then l=l 1 +L 2 ＝945+168.31＝1113.31m。
(4) The viewing distance was calculated as s1= (4-1) ×3.5×cot7=85.52 m, s2=2.5×cot7=20.36 m, and s=max (S1, S2) = 85.52m.
(5) The lead distance D of the last block of exit forenotice flag is calculated, d=r+j+l-s=97.16+77.84+1113.31-85.52 = 1202.79m.
The leading distance to the last exit forenotice sign is 1203m.
(6) The vanishing distance is calculated, m= (HF-hs)/tan θ= (5.5-1.2)/tan 7 = 35.02M, M is less than or equal to S.
(7) Calculate twoDistance between block advance notice flags, r=s+q-M, q=v 0 T/3.6＝6.94v 0 ＝6.94×140＝971.6m，R＝85.52+971.6–35.02＝1022.09m。
The distance between the two exit forenotes was 1022m.
Under the second test scene, a minimum prepositive distance recommended value of 1250m is given; the recommended distance between the two exit foresigns is 1100m.
According to the test results, AGS (highway exit prepositive indication sign) is uniformly arranged at the positions of 500 meters, 1000 meters and 2000 meters upstream of the exit ramp in three stages according to the prior art, the requirement for the prepositive distance under the upper superhigh speed working condition cannot be met at all, and the obtained prepositive distance result has more reference value by considering the influences of various factors such as the speed of the main line and ramp of the highway, the number of lanes, the sign setting mode and the like.
In summary, the scheme has the following advantages:
according to the method, according to possible ultra-high speed working conditions of a future passenger car driving on a special expressway, an AGS distance determination test scene is built, according to different grade division of the expressway, two calculation models are built under the condition that the expressway has an overlapping part with the existing common expressway, and the test scene and the calculation models are associated, so that the determined AGS distance is more consistent with the future passenger car driving scene, and the AGS distance value obtained in a multi-scene multi-model mode is more referential.
In the process of constructing the calculation model, various road condition factors such as the design speed of a main line of the expressway, the number of lanes, the width of the lanes, the speed limit speed of a ramp and the like, vehicle condition factors such as the automation level of a vehicle and visual cognition characteristic information are comprehensively considered, so that the scene of determining the front distance is more similar to the situation that a future minibus runs at an ultrahigh speed on a special expressway, and the obtained calculation result of the front distance is more reasonable.
The whole test can simulate and test various modes to obtain a large amount of test data, and the test data are sufficiently analyzed and used, so that value information can be provided for actual traffic construction design; meanwhile, the method can repeatedly provide the same road condition, ensures the stability of multiple test results, has the advantages of low cost, repeatability, rapidness, reality and the like, and is suitable for popularization and use.
The foregoing is merely an embodiment of the present invention, and a specific structure and characteristics of common knowledge in the art, which are well known in the scheme, are not described herein, so that a person of ordinary skill in the art knows all the prior art in the application day or before the priority date of the present invention, and can know all the prior art in the field, and have the capability of applying the conventional experimental means before the date, so that a person of ordinary skill in the art can complete and implement the present embodiment in combination with his own capability in the light of the present application, and some typical known structures or known methods should not be an obstacle for a person of ordinary skill in the art to implement the present application. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent.
Claims (4)
1. The system for determining the AGS distance of the expressway special for the small bus is characterized by comprising a data acquisition module and an AGS distance determination module;
the data acquisition module is used for acquiring road condition information, vehicle condition information of a simulated vehicle and visual cognition characteristic information; the road condition information comprises a special expressway grade of the small bus, a special expressway main line design speed of the small bus, the number of lanes, the width of lanes and the speed limit speed of a ramp; the vehicle condition information comprises an automation level of the simulated vehicle; the visual cognition characteristic information comprises a reading time, a decision time, a channel changing waiting time, a channel changing time and a visual recognition angle of the exit forenotice mark;
the AGS distance determining module is used for acquiring output data by adopting a preset calculation model according to the data acquired by the data acquisition module; the output data comprises a preposed distance calculation value;
the system also comprises a test scene building module and a calculation model selection module;
the test scene building module is used for building different test scenes according to the special expressway grade of the passenger car and the automation grade of the simulated vehicle, which are acquired by the data acquisition module;
the computing model selection module is used for selecting a first computing model or a second computing model as a preset computing model to be input into the AGS distance determination module by adopting a preset selection strategy according to different testing scenes;
the grades of the special expressways of the minibuses are super-grade, super-grade and super-grade; the automation level comprises autonomous driving assistance, autonomous automatic driving, internet connection driving assistance and internet connection automatic driving; the test scene comprises a super-first-level-autonomous driving auxiliary scene, a super-first-level-networked driving auxiliary scene, a super-second-level-autonomous driving automatic scene and a super-third-level-networked driving automatic scene;
the preset selection strategy is to select a first calculation model when the test scene is a super-level-autonomous driving auxiliary scene; when the test scene is a super-level-networking driving auxiliary scene, a super-level-autonomous driving scene or a super-three-level-networking automatic driving scene, selecting a second calculation model;
the first calculation model and the second calculation model comprise the following steps:
s1: after the last AGS is found, the read distance r from the read mark to the read mark content is started; wherein r=，v 0 Is the design speed of the main line of the expressway special for the minibus, t 1 Is read time;
s2: calculating a decision distance j from the completion of reading the mark to the beginning of operation; wherein j=，v 0 Is the design speed of the main line of the expressway special for the minibus, t 2 Is the decision time;
s3: calculation ofAn action distance L from the start of the operation to the completion of the operation; wherein l=l 1 +L 2 ，L 1 Distance L for lane change 2 The driving distance is the deceleration process; l (L) 1 = ，L 2 = />K is the number of lanes, t d For the channel change waiting time, t h For lane change time, v x To start the speed before deceleration v 1 The speed limiting speed of the ramp is phi, the friction coefficient of the expressway and the tire is phi, i is the road longitudinal slope, and g is gravity acceleration;
s4: calculating a visual recognition distance S and a vanishing distance M from the mark position to the mark position;
s5: calculating the prepositive distance D of the mark, wherein D=r+j+L-S;
in S4, the visual recognition distance S of the first calculation model is: s= -272.33h 2 +408.31h-25.72+ε, h is Chinese character height and ε is stroke complexity correction coefficient;
the visual recognition distance S of the second calculation model is:
when the exit forenotice sign is roadside standing, s= ((k-0.5) ×wl+s) t ) X cotθ, where k is the number of lanes and wl is the lane width; s is S t The horizontal offset of the vertical installation mark is that theta is the visual angle;
when the exit forenotice sign is a road cross type, s=max (S1, S2), s1= (k-1) ×wl×cotθ, s2=sv×cotθ, where k is the number of lanes, wl is the lane width, S1 is the distance from the visual point to the sign considering the lateral shift, S2 is the distance from the visual point to the sign considering the longitudinal shift, sv is the longitudinal shift amount across the installation sign, and θ is the visual point.
2. The system for determining the AGS distance of a highway dedicated to a passenger car according to claim 1, wherein the vanishing distance M is:
when the exit forenotice sign is roadside standing, m= ((k-0.5) wl+wx+wy)/tan θ, where k is the number of lanes, wl is the lane width, θ is the visual recognition angle, wx is the hard shoulder width, wy is the sign edge-to-hard shoulder distance;
when the exit forenotice sign is crossing over the road, m= (HF-hs)/tan θ, HF is the sign height crossing over the road, hs is the driver's visual height, and θ is the visual angle.
3. The system for determining the AGS distance for a passenger car according to claim 2, further comprising S6: calculating the distance R between two exit forenotice marks, wherein R=S+q-M, and q is the distance between memory intervals; the output data of the AGS distance determining module further comprises a distance calculated value between the two exit forenotice marks.
4. The system for determining the AGS distance of the expressway special for a passenger car according to claim 1, further comprising a recommended distance determining module configured to output a minimum recommended value of the front distance based on the least favorable principle according to the calculated front distance value obtained by the AGS distance determining module.
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