Auxiliary driving decision-making method for large truck passing through continuous long and steep downhill

Abstract

The invention belongs to the technical field of auxiliary driving, and particularly relates to an auxiliary driving decision-making method for a large truck during continuous long and steep downhill driving. The auxiliary decision-making method comprises the following steps of a braking decision-making method, wherein a braking strategy decision is provided for a driver during downhill according to the predicted slope bottom hub temperature. The following decision-making method comprises the following steps: calculating the following running parking gap of the truck according to the hub temperature of the truck, and proposing decisions of the following distance and the running speed of the truck. According to the overspeed decision-making method, the maximum driving speed decision-making method when the truck passes through the cutting circle curve is provided based on the truck critical speed calculated according to the brake distance side length caused by hub temperature rise. The real-time driving behavior auxiliary decision making of the truck in the downhill process can be achieved, and brake failure accidents, fixture collision accidents and rear-end collision accidents when the truck runs in a continuous downhill scene are reduced. According to the method, support can be provided for traffic operation risk blocking of continuous long and steep downhill road sections, and an auxiliary decision-making library of automatic driving behaviors of trucks can be enriched.

Description

Technical Field

[0001] The present invention belongs to the technical field of assisted driving, and in particular relates to an assisted driving decision method for a large truck traveling on a continuous long and steep downhill slope. Background Art

[0002] With the development of heavy trucks and large trucks, the driving safety of trucks on long and steep downhill sections will become more and more prominent. In the past, the safety issues of trucks on continuous downhill sections focused on the impact of brake failure and wheel hub fire. Therefore, there are many studies on the prediction model and early warning method of the wheel hub temperature of truck groups at different sections of the highway. Most of them are based on the theory of conservation of energy and energy conversion, and the mathematical simulation method of measured data to establish the wheel hub temperature change law of truck groups. However, the wheel hub temperature of different trucks is related to the vehicle's own vehicle power performance, the total weight of the vehicle and cargo when passing through a long and steep downhill section, and the driver's choice strategy for using braking measures (large trucks include engine braking, wheel hub braking, and exhaust braking). Therefore, the group wheel hub temperature prediction model cannot be applied to a single large truck. Therefore, it is necessary to fully consider the characteristics of specific large trucks and the habitual characteristics of drivers to establish a temperature rise model of the wheel hub temperature.

[0003] During the downhill process of large trucks, spontaneous combustion of the wheel hub and brake failure can cause serious accident consequences, but the frequency of such accidents is very low. For example, the Technical Guidelines for Special Actions to Improve the Safe Traffic Capacity of Continuous Long and Steep Downhill Sections of Highways classifies continuous long and steep downhill sections as the standard for classification of any 3km range with three or more accidents in the past three years. In addition to brake failures with low frequency and high accident severity, the frequency of rear-end collisions of trucks on continuous downhill sections is very high, but due to the low severity of the accidents, the degree of attention is low, so there are few related studies. The rear-end collision of trucks during the downhill process is the distance side length that reaches the same braking efficiency after the wheel hub temperature rises, but the driver does not recognize the longer braking distance and causes a decision-making error. Therefore, in order to improve the driving safety level of trucks during the downhill process, dynamic reminders of the changes in braking distance during real-time driving are given to the driver to prevent and reduce rear-end collisions during continuous downhill processes.

[0004] Therefore, it is necessary to propose an assisted driving decision-making method for large trucks when traveling on continuous long and steep downhill slopes to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to design an assisted driving decision-making method for large trucks when traveling on a continuous long and steep downhill slope, so as to avoid brake failure accidents, rear-end collisions and accidents of hitting fixed objects on circular curves that block the line of sight caused by the driver's inability to correctly recognize the braking distance decay.

[0006] The present invention provides a method for early warning of a truck traveling on a continuous downhill slope, comprising the following steps:

[0007] S1: When it is detected that the driver is driving on a long and steep downhill slope and the data sent back by the wheel hub temperature sensor exceeds 600s, the wheel hub temperature prediction of the truck's downhill process begins.

[0008] S2: Based on the time series data sent back by the wheel hub temperature sensor, use T 测 =ARIMA(4,2,5) is used to predict the data of vehicle wheel hub temperature. The sample length of the model is 30s, the prediction length is 9s, and the total prediction time t is calculated based on the length of the continuous long steep downhill slope and the average driving speed of the truck downhill.

[0009] S3: The hub temperature of the vehicle when it reaches the end of the continuous long steep longitudinal slope predicted from the current position is compared with the hub temperature in the decision library to obtain the braking selection behavior that needs to be proposed.

[0010] S4: The formulated driver's braking selection behavior is reported to the driver, and the reporting continues at the next moment.

[0011] The total duration t of the prediction is calculated as shown in formula (1).

[0012]

[0013] Where L is the length of the continuous long steep downhill slope that the large truck travels. The system has collected this information and can be directly called. t It is the distance that a large truck has traveled from the starting point of a long and steep downhill slope to the current position. It is calculated based on the sum of the products of the speed collected by the truck from the starting point of the downhill slope and the interval between speed collection events. It is the average speed of the vehicle from the top of the slope to the current predicted position, collected by the vehicle speed collector.

[0014] The decision library is shown in Table 1.

[0015] Table 1 Driver's braking selection behavior decision library

[0016]

[0017] The method for early warning and prediction of vehicle following behavior of the present invention comprises the following steps:

[0018] S1: When a vehicle is detected ahead, the vehicle starts to predict and warn the vehicle-following behavior, and measures the distance L between the vehicle and the vehicle ahead through the Raytheon integrated device. 前后 , the speed of the front vehicle V 前 .

[0019] S2: Assuming that the front vehicle suddenly brakes, calculate the distance S traveled by the front vehicle during emergency braking 前 .

[0020] S3: The large truck following the vehicle notices that the vehicle in front has decelerated urgently. The vehicle behind follows the vehicle and brakes urgently and stops. Calculate the distance S that the large truck travels from the time it notices that the vehicle in front has decelerated to the time it stops. 后 .

[0021] S4: Calculate the parking gap L between the front vehicle and the large truck c .

[0022] S5: According to the parking space L c Query the vehicle-following behavior decision database to determine the rear-end collision risk of the truck, and report the corresponding rear-end collision warning strategy to the driver.

[0023] The travel distance S of the front vehicle during emergency braking 前 The calculation of is as follows:

[0024]

[0025] Where: V 前 is the speed of the preceding vehicle measured by the Ray's integrated device; a 前 is the emergency braking deceleration of the front vehicle, with a value of 3.0m / s 2 ;i 前 It is the longitudinal slope of the road section where the front vehicle is traveling, with uphill being positive and downhill being negative.

[0026] The large truck following the vehicle finds that the vehicle ahead has slowed down to a stop and travels a distance S 后 The calculation of is as follows:

[0027]

[0028] Where: V is the speed of the large truck following the vehicle; τ is the driver's reaction time, which is 3s; i 后 is the longitudinal slope of the road section where the large truck following the vehicle is traveling, with uphill being positive and downhill being negative. a is the acceleration of the large truck following the vehicle under different wheel hub temperature conditions, calculated as formula (4):

[0029] a=min(a T ,a 前 )=min(-0.0071T+3.3791, 3.0) (4)

[0030] Where: T is the actual measured temperature of the wheel hub.

[0031] The difference L between the front and rear vehicle stopping distances c , calculated as formula (5):

[0032] Lc =S 前 -S 后 +L 前后 (5)

[0033] Where: L 前后 is the measured distance between the front and rear vehicles.

[0034] The decision library is shown in Table 2.

[0035] Table 2 Rear-end collision risk warning decision library

[0036] Warning level Judgment conditions Information broadcast I <![CDATA[L c ≤10]]> The distance to the vehicle in front is too close, and the risk of rear-end collision is high. Slow down or increase the distance between you and the vehicle in front. II <![CDATA[10<L c ≤15]]> The distance to the vehicle in front is close, and there is a possibility of rear-ending the vehicle in front, so be highly alert to the emergency braking of the vehicle in front. III <![CDATA[15<L c ≤20]]> The risk of rear-ending the vehicle in front is small, so be alert to the brakes of the vehicle in front. IV <![CDATA[L c >20]]> No rear-end collision warning is given to the driver.

[0037] The speed warning method for free travel of the present invention comprises the following steps:

[0038] S1: When a large truck is driving on a circular curve section of a cut section and no vehicle is detected ahead, a speed warning for free driving begins.

[0039] S2: Assuming that a large truck is traveling on the center line of the lane, calculate the sight distance S of the truck 视 .

[0040] S3: Calculate the maximum allowable speed V of the truck during emergency braking based on the sight distance of the truck. 临 .

[0041] S4: Based on the truck's travel speed V and the maximum permissible speed V 临 The speed difference ΔV is used to calculate the speeding risk of the truck and report the speed selection strategy to the driver.

[0042] The sight distance S of the truck 视 , calculated as formula (6):

[0043]

[0044] Where: R is the design radius of the circular curve for large trucks to pass through; m is the horizontal clearance provided by the cut circular curve. The calculation of the horizontal clearance m is as follows:

[0045] m = 0.3 + lane width / 2 + hard shoulder width + earth shoulder width + side ditch + debris platform + 2.0 × slope gradient (7)

[0046] Maximum permissible speed V for trucks during emergency braking 临 , calculated as formula (8):

[0047]

[0048] The symbols in the formula are the same as before.

[0049] The difference ΔV between the truck speed and the critical speed is calculated as follows:

[0050] ΔV=V 临 -V (9)

[0051] The decision library is shown in Table 3.

[0052] Table 3 Speeding risk warning decision library

[0053] Warning level Judgment conditions Information broadcast I <![CDATA[V 临 ≤0]]> The vehicle was turning too fast, there was an obstacle ahead, and it did not have time to brake. II <![CDATA[0<V 临 ≤5]]> The speed of cornering is relatively fast, so you need to pay close attention to whether there are obstacles ahead on the road. III <![CDATA[5<V 临 ≤10]]> Pay attention to changes in road conditions ahead when turning. IV <![CDATA[V 临 >10]]> The driver is not given a cornering speed reminder.

[0054] Compared with the prior art, the present invention has the following advantages and technical effects:

[0055] The present invention can continuously provide warnings of braking behavior, following behavior and speeding behavior for large trucks during the downhill process, achieving a technical breakthrough in assisted driving of trucks on continuous long and steep downhill sections, and providing a rule library for expanding the safety guarantee of truck automatic driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor:

[0057] Figure 1 This is a braking behavior warning flow chart of the present invention;

[0058] Figure 2 This is a flow chart of the vehicle following behavior warning of the present invention;

[0059] Figure 3 This is a flow chart of the speeding behavior warning of the present invention;

[0060] Figure 4 Schematic diagram of hub temperature prediction results. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] The present invention provides an auxiliary decision-making method for braking behavior, following behavior and speeding behavior of a large truck passing through a continuous long steep downhill section. In the claims, no claim is made for data collection, but data collection is essential to realize the functions of the present invention. Therefore, in the description of the flow chart, the method for obtaining parameters is supplemented, and the methods for obtaining these data can be easily collected through existing equipment.

[0064] Reference Figure 1 The present invention provides a method for assisting decision-making on braking behavior when a large truck passes through a continuous downhill section. In order to assist in decision-making on braking behavior, it is necessary to calculate decision indicators through vehicle-mounted equipment. The specific required collection equipment and collected data indicators include:

[0065] The driving position of the truck: obtained through the vehicle GPS or mobile phone GPS;

[0066] The length of the continuous long steep downhill slope: obtained through roadside traffic signs or by inputting data into the system in advance;

[0067] The wheel hub temperature of the truck: obtained through the temperature sensor;

[0068] Truck speed: obtained through the CAN bus on the vehicle, mobile phone position difference or speedometer.

[0069] The acquired information enters the vehicle terminal, such as a mobile phone or a vehicle computing unit, through wireless transmission.

[0070] Based on the above data, the decision on the truck braking behavior is made, including the following steps:

[0071] The conditions for starting the truck braking behavior decision module are: the truck is traveling on a continuous long and steep downhill section, and the driving time is greater than 600s.

[0072] Calculation of total wheel hub temperature prediction time: Where L is the length of the continuous long steep downhill slope that the large truck travels. t is the distance between the large truck and the starting point of the continuous long steep downhill slope at this moment, which is obtained by multiplying the speed collected by the truck at each moment by the time interval between speed collections. It is the average speed of the truck from the top of the slope to the current position, which is calculated by averaging all the detected speeds.

[0073] Hub temperature prediction: Hub temperature is predicted using an iterative method with an iteration step of 9 seconds until the cumulative time is t. In each iteration, the hub temperature data 30 seconds before the prediction time is used to calculate the hub temperature using the formula: T 测=ARIMA(4,2,5) calculates the predicted wheel hub temperature at the next moment. For the prediction example, refer to Figure 4 .

[0074] Truck braking behavior decision: Through T 测 The corresponding decision is searched in the formulated decision database and reported to the driver through a mobile terminal or loudspeaker.

[0075] Reference Figure 2 The present invention provides a method for assisting decision-making for following a large truck when it passes through a continuous downhill section. In order to assist in decision-making for following a large truck, it is necessary to calculate the decision index through the vehicle-mounted equipment. The specific collection equipment and collected data indexes include:

[0076] The driving position of the truck: obtained through the vehicle GPS or mobile phone GPS;

[0077] The longitudinal profile of a continuous long and steep downhill slope: obtained through the downhill slope input into the system, or calculated through the ratio of the elevation data obtained by the vehicle GPS to the driving distance;

[0078] The wheel hub temperature of the truck: obtained through the temperature sensor;

[0079] Truck speed: obtained through the CAN bus on the vehicle, mobile phone position difference or speedometer.

[0080] The speed and distance of the vehicle in front: obtained through the integrated radar vision device or the vehicle-mounted binocular camera.

[0081] The acquired information enters the vehicle terminal, such as a mobile phone or a vehicle computing unit, through wireless transmission.

[0082] Based on the above data, the decision on the truck following behavior is made, including the following steps:

[0083] The activation conditions for the truck following behavior warning are: the speed of the vehicle in front of the truck in the lane and the distance data from the vehicle in front can be monitored, and both are not zero.

[0084] Calculate the driving distance of the front vehicle when it stops in an emergency: Consider the most unfavorable situation, when the front vehicle brakes in an emergency, the truck following the vehicle can detect the front vehicle and stop the vehicle. Assuming that the front vehicle stops according to the law of uniform deceleration when it brakes in an emergency, the emergency stopping distance of the front vehicle is: When calculating the stopping distance of the vehicle ahead, the effect of the longitudinal slope on the driver's acceleration is fully considered.

[0085] Calculate the maximum deceleration value that can be obtained by the rear vehicle under the wheel hub temperature condition at the current moment: the increase in wheel hub temperature will seriously affect the value of the braking deceleration of the truck during the downhill process. The present invention reversely calculates the acceleration of the truck's emergency braking based on the emergency braking distance of the truck at different wheel hub temperatures during the downhill process, and then regresses to obtain the formula: a=min(a T ,a 前 )=min(-0.0071T+3.3791, 3.0).

[0086] Calculate the distance traveled by the truck from the time it discovers the front vehicle brakes to the time it stops: Assume that the truck's speed remains unchanged during the process of discovering the front vehicle brakes, and the time it takes to discover is τ. The process of the truck starting to brake and decelerate is a uniform deceleration process, so the truck's stopping distance consists of two parts. The distance traveled by the rear vehicle is:

[0087] Calculate the distance between the front and rear vehicles when parking: The deceleration formula is: L c =S 前 -S 后 +L 前后 .

[0088] According to L c Value, to determine the risk of rear-end collision. c When it is less than or equal to 10, it includes two situations: the truck collides with the vehicle in front or the distance between the truck and the vehicle in front is close. The classification index is determined based on the accuracy of distance judgment and the tolerance of the driver's reaction time during the driving of the truck.

[0089] Reference Figure 3 The present invention provides a method for assisting decision-making on speeding behavior when a large truck passes through a continuous downhill section. In order to assist in decision-making on speeding behavior, it is necessary to calculate the decision index through the vehicle-mounted equipment. The specific required collection equipment and collected data indicators include:

[0090] The driving position of the truck: obtained through the vehicle GPS or mobile phone GPS;

[0091] Longitudinal slope of continuous long and steep downhill slope: obtained through the downhill slope input into the system, or calculated through the ratio of elevation data obtained by the vehicle GPS to the driving distance;

[0092] Cross-sectional width of continuous long and steep downhill slope: obtained by inputting cross-sectional information into the system, or by video camera or 3D laser scanning.

[0093] The circular curve radius of the continuous long steep downhill slope is obtained through the circular curve radius information input into the system.

[0094] The wheel hub temperature of the truck: obtained through the temperature sensor;

[0095] Truck speed: obtained through the CAN bus on the vehicle, mobile phone position difference or speedometer.

[0096] The acquired information enters the vehicle terminal, such as a mobile phone or a vehicle computing unit, through wireless transmission.

[0097] Based on the above data, the decision on the speeding behavior of the truck is made, including the following steps:

[0098] The starting conditions for the truck speeding behavior warning: The speeding behavior of a truck refers to the situation where the truck is driving on a circular curve in a cut section. Because of the obstruction of the road cut, the distance that the truck can see ahead is limited. At this time, a traffic accident may occur because the truck fails to discover the road conditions ahead in time. Considering the most unfavorable situation, that is, there is an obstacle on the road ahead, an obstacle is placed on the road ahead at the critical point of the visible distance. The driving distance from the driver discovering the obstacle to stopping is just enough not to hit the obstacle. The critical driving speed of the truck is calculated and a reminder is issued whether the truck is speeding. Therefore, according to the application scenario of the speeding warning, when the truck is driving on a cut circular curve section located on a continuous long steep longitudinal slope section, the truck speeding warning process is started.

[0099] Calculate the visible distance of trucks on the cut circular curve section: First calculate the horizontal clearance when the truck is driving on the cut circular curve, the calculation formula is: m = 0.3 + lane width / 2 + hard shoulder width + earth shoulder width + ditch width + debris platform width + 2 × slope gradient. Calculate the visible distance of the truck based on the horizontal clearance and the circular curve radius:

[0100] Calculate the maximum deceleration value that can be obtained by the rear vehicle under the wheel hub temperature condition at the current moment: the increase in wheel hub temperature will seriously affect the value of the braking deceleration of the truck during the downhill process. The present invention reversely calculates the acceleration of the truck's emergency braking based on the emergency braking distance of the truck at different wheel hub temperatures during the downhill process, and then regresses to obtain the formula: a=min(a T ,a 前 )=min(-0.0071T+3.3791, 3.0).

[0101] Calculate the maximum allowed running speed of a truck during emergency braking: Assume that the truck's braking process is divided into two stages, namely the uniform motion stage when the truck finds an obstacle in front and the emergency braking stage after finding the obstacle. The distance traveled by the truck is calculated as If the truck is to avoid colliding with the obstacle in front, the critical condition is S 临 =S 视 , by solving the equation, we get the calculation formula of critical speed:

[0102] The difference between the truck speed and the critical speed is ΔV=V 临 -V.

[0103] According to the value of ΔV, the risk of vehicle speeding is judged. This method makes full use of the early warning system technology, provides a new method for the safe driving behavior of truck drivers, and has a relatively reliable success rate.

[0104] The above shows and describes the basic principles, main features and advantages of the embodiments of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An assisted driving decision method for a large truck driving down a long and steep slope, characterized in that: It can provide early warning for braking, following and speeding behaviors of large trucks while driving downhill. Braking behavior warning: Based on the predicted wheel hub temperature when a large truck reaches the bottom of a slope, the driver is warned of braking behavior. Following behavior warning: According to the impact of wheel hub temperature on braking distance, the driver's following speed and distance are warned. Speeding behavior warning: Based on the sight distance and stopping distance, the turning speed of large trucks on circular curves in the road cutting will be warned.

2. The auxiliary driving decision method for a large truck driving down a long and steep slope according to claim 1, characterized in that: The braking behavior warning is characterized by: S1: According to the position information of the truck, when the truck reaches the starting point of the continuous downhill slope 600s, the wheel hub temperature prediction begins. S2: Predict the hub temperature T through the time series data of hub temperature 测 =ARIMA(4,2,5), sample length 30s, single prediction length 9s, total iteration time t. S3: Compare the predicted wheel hub temperature with the driver's braking behavior decision library, determine the broadcast information, and broadcast it to the driver.

3. The braking behavior warning according to claim 2, characterized in that: Total iteration time Where L is the total length of the continuous long steep downhill slope for large trucks to travel; L t The distance that a large truck has traveled on a continuous downhill section. It is the average speed of the vehicle on the continuous downhill section.

4. The auxiliary driving decision method for a large truck driving down a long and steep slope according to claim 1, characterized in that: The following vehicle behavior warning is characterized by: S1: When a vehicle is detected ahead, the system starts to issue a warning for vehicle following behavior. Calculate the emergency braking distance S of the vehicle ahead 前 . S2: Calculate the distance S that a large truck travels from the time it finds the vehicle ahead slows down to the time it stops. 后 . S3: Calculate the parking gap L between the front vehicle and the large truck c . S4: According to the parking space L c Query the following vehicle behavior decision database, determine the risk level and broadcast information of the following vehicle behavior, and broadcast it to the driver.

5. The vehicle following behavior warning according to claim 4 is characterized in that: Where: V 前 is the speed of the front vehicle; a 前 is the emergency braking deceleration of the front vehicle, with a value of 3.0m / s 2 ; i 前 It is the longitudinal slope of the road section where the front vehicle is traveling, with uphill being positive and downhill being negative.

6. The vehicle following behavior warning according to claim 4 is characterized in that: Where: V is the speed of the large truck; τ is the driver's reaction time, which is 3s; i 后 is the longitudinal slope of the road section where the large truck is traveling, with uphill being positive and downhill being negative. a is the acceleration of the large truck under different wheel hub temperature conditions, and the calculation formula is: a = min (a T ,a 前 )=min(-0.0071T+3.3791,3.0). Where: T is the measured temperature of the wheel hub.

7. The vehicle following behavior warning according to claim 4 is characterized by: L c =S 前 -S 后 +L 前后 Where: L 前后 is the measured distance between the front and rear vehicles.

8. The auxiliary driving decision-making method for a large truck driving down a long and steep slope according to claim 1, characterized in that: The speeding warning is characterized by: S1: Based on the driving position of the truck, when it is judged that the truck is driving to the entrance of the circular curve of the road cut on a continuous long steep downhill section, an overspeed behavior warning is started. S2: Calculate the sight distance S of the truck 视 and the critical speed V of the truck 临 . S3: According to the difference ΔV between the truck's running speed and the critical speed, the speeding behavior decision database is queried to determine the risk level and broadcast information of the speeding behavior, and then the information is broadcast to the driver.

9. The speeding warning according to claim 8 is characterized in that: In the formula: R is the design radius of the circular curve for large trucks to pass through; m is the horizontal clearance provided by the cut circular curve, and the calculation formula is: m = 0.3 + lane width / 2 + hard shoulder width + earth shoulder width + ditch width + debris platform width + 2×slope gradient.

10. The speeding warning according to claim 8 is characterized in that: The symbols in the formula are the same as before.

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