Transport vehicle and transport work system

Abstract

The purpose of the present invention is to accurately ascertain the road surface state, such as the ease of slipping on the road surface, on the basis of the state of a vehicle during travel, and to obtain a travel speed that can achieve both the safety and work efficiency of a transport vehicle. A control device for a transport vehicle is provided with: a [mu] calculation unit that calculates a friction coefficient of a road surface on the basis of measurement results from a sensor; a [omega] calculation unit that calculates the slip ratio of the wheel with respect to the road surface on the basis of the measurement results of the sensor; a parameter estimation unit that estimates a parameter indicating the state of the road surface; a maximum friction estimation unit that estimates the maximum friction coefficient of the road surface; and a speed limiting unit that calculates an upper limit speed of the transport vehicle corresponding to the maximum friction coefficient and limits the target speed. The parameter estimation unit estimates a parameter indicating the state of the road surface in a linear region in which the relationship between the friction coefficient and the slip rate is linear. The maximum friction estimation unit estimates the maximum friction coefficient on the basis of the parameter in the linear region.

Description

Technical Field

[0001] This invention relates to transport vehicles and transport operation systems. Background Technology

[0002] Among transport vehicles such as dump trucks used to transport ore and sand excavated in open-pit mines, there are vehicles that use electricity generated by a generator connected to an engine to drive an electric motor. By using an electric motor as the drive source, transport vehicles can not only eliminate the need for a transmission and reduce maintenance costs, but also improve energy efficiency through electrification and enable precise management of drive torque.

[0003] Such transport vehicles load cargo into their buckets at the loading yard of the excavated minerals, travel along the transport route to the unloading yard, and then unload (discharge) the loaded cargo. The transport vehicles are configured to tilt the buckets for unloading, causing the cargo to fall to the rear of the vehicle. Furthermore, transport vehicles with empty buckets continue traveling along the transport route back to the loading yard, similarly performing the loading, transporting, and unloading operations repeatedly. To optimize the overall efficiency of operations across the mining site, a control system has been constructed to manage the operations of the transport vehicles within the site. This control system issues various operation-related instructions to each transport vehicle via wireless communication, including predetermined routes and target speeds.

[0004] As an indicator of operational efficiency in such transportation operations, a metric representing the weight of goods transported per unit time is generally used. This metric shows that loading as much cargo as possible into a transport vehicle and traveling at the fastest possible speed increases operational efficiency. The load capacity of each transport vehicle is determined individually, and a target speed for safe operation is set for each mining site; therefore, there is an upper limit to operational efficiency. Furthermore, when road conditions deteriorate due to inclement weather, such as muddy surfaces, the target speed is set lower than in clear weather, or operators assess the road conditions and reduce speed to a safe level. Thus, it is unavoidable that operational efficiency will decrease in inclement weather compared to clear weather. To ensure safety and minimize efficiency reduction under such conditions, speed reduction must be minimized within the safe operating range.

[0005] Therefore, in such transport vehicles and control devices, it is important to accurately grasp the road conditions based on the vehicle's status during travel, such as the ease of slippage, and to accurately determine the deterioration of the road conditions before slippage occurs, so as to set a target speed that can achieve a travel speed that balances safety and operational efficiency.

[0006] Patent Document 1 is known as a technology for ensuring vehicle driving stability by determining the maximum value of the friction coefficient (road surface μ) of the road surface based on the road surface condition. Patent Document 1 describes the following: the road surface μ slope value of each wheel is estimated based on the wheel speed detected by the wheel speed sensor, and the target braking force setting unit of each wheel sets (allocates) the target braking force of each wheel based on the vehicle target braking force and the road surface μ slope value of each wheel.

[0007] Existing technical documents

[0008] Patent documents

[0009] Patent Document 1: Japanese Patent Application Publication No. 2001-287635 Summary of the Invention

[0010] The problem that the invention aims to solve

[0011] In the technology described in Patent Document 1, the maximum value of road surface μ is determined by the road surface slope value approaching zero. Therefore, in the technology described in Patent Document 1, to determine the road surface condition, it is necessary to actually brake the vehicle until the road surface μ reaches its maximum value and measure the vehicle's state at that point. Thus, the technology described in Patent Document 1 requires a difficult driving operation, such as achieving high friction on slippery surfaces, making it difficult to obtain the maximum value of road surface μ.

[0012] Furthermore, in transport vehicles such as dump trucks, to ensure the stability of the loaded cargo, forced movement requiring high friction levels typical of passenger cars is almost never performed except during emergency stops. Therefore, in transport vehicles, only measurements of the vehicle's condition during normal driving are available, and measurements of the vehicle's condition during emergency stops are rarely obtained. Consequently, even if the technology described in Patent Document 1 is applied to transport vehicles, the road surface gradient μ value will almost never reach near zero, making it extremely difficult to obtain the maximum value of the road surface gradient μ.

[0013] The present invention was made in view of the above circumstances, and its purpose is to accurately grasp the road surface condition, such as the slipperiness of the road surface, based on the state of the vehicle during driving, so as to obtain a driving speed that can take into account both the safety of the transport vehicle and the work efficiency.

[0014] Methods for solving problems

[0015] To address the aforementioned issues, the present invention provides a transport vehicle that travels at a target speed along a predetermined path. The transport vehicle includes: a control device that controls the travel of the transport vehicle; and a sensor that measures the state of the wheels of the transport vehicle during travel. The control device comprises: a μ calculation unit that calculates the coefficient of friction of the road surface in contact with the wheels along the predetermined path based on the sensor's measurement results; an ω calculation unit that calculates the slip ratio of the wheels relative to the road surface based on the sensor's measurement results; a parameter estimation unit that estimates a parameter representing the road surface state along the predetermined path, expressed as a relationship between the coefficient of friction and the slip ratio, based on the calculation results of the μ calculation unit and the ω calculation unit; and a maximum friction estimation unit that estimates a parameter based on the parameter estimation unit's calculation results. The determined parameters are used to estimate the maximum friction coefficient in the predetermined driving path; the speed limiting unit calculates the upper limit speed of the transport vehicle corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit, and limits the target speed according to the calculated upper limit speed; the parameter estimation unit estimates the parameters representing the road surface state in a linear region where the slip ratio and the friction coefficient are linearly related based on the measurement results of the sensors when traveling on the predetermined driving path at the target speed; the maximum friction estimation unit estimates the maximum friction coefficient based on the parameters in the linear region estimated by the parameter estimation unit and a table that associates the parameters in the linear region with the maximum friction coefficient.

[0016] Invention Effects

[0017] According to the present invention, the road surface condition, such as the slipperiness of the road surface, can be accurately grasped based on the vehicle's condition during driving, so as to obtain a driving speed that can balance the safety and operational efficiency of the transport vehicle.

[0018] The issues, structural elements, and effects other than those described above become clear through the following description of the implementation methods. Attached Figure Description

[0019] Figure 1 This is a side view of the transport vehicle.

[0020] Figure 2 It is a graph showing the relationship between tire force and slip ratio.

[0021] Figure 3 It is a graph showing the relationship between the friction coefficient and the slip ratio of the road surface.

[0022] Figure 4 This is a diagram showing the functional structure of the transport vehicle according to this embodiment.

[0023] Figure 5It is a diagram illustrating the movement of loads within the wheels of a transport vehicle.

[0024] Figure 6 It means Figure 4 A flowchart illustrating an example of the processing performed by the control device shown.

[0025] Figure 7 It is a diagram showing the structure of a transportation operation system. Detailed Implementation

[0026] Hereinafter, embodiments of the present invention will be described using the accompanying drawings. Furthermore, structural elements labeled with the same reference numerals in each embodiment are identical unless specifically mentioned otherwise, and their descriptions are omitted.

[0027] [First Implementation Method]

[0028] use Figures 1-6 The first embodiment of the present invention will now be described. Figure 1 This is a side view of transport vehicle 10.

[0029] The transport vehicle 10 is a transport vehicle equipped with the function of autonomously traveling along a predetermined path at a target speed. The transport vehicle 10 is, for example, a dump truck. In this embodiment, as an example of the transport vehicle 10, a mining dump truck used for transporting ore and sand excavated in open-pit mines or the like will be described.

[0030] The transport vehicle 10 consists of a frame 11, a cargo box 12 that can be undulatingly supported on the frame 11 via a support axle 16, a lifting cylinder 18 that makes the cargo box 12 undulate, a cab 13 installed at the front of the frame 11, and a pair of front wheels 14 and rear wheels 15 installed at the front and rear of the frame 11.

[0031] The driver's cab 13 has a driver's seat (not shown) where the operator can sit and operate the accelerator pedal, brake pedal, or steering wheel. The transport vehicle 10 is equipped with autonomous driving capabilities, and is therefore configured to directly input operating inputs to these pedals or steering wheel, or indirectly input operating inputs via analog signals. Furthermore, the transport vehicle 10 determines the amount of operation input for the operating devices and performs the operation inputs based on its own position obtained from a GNSS device, a travel path map including a pre-set travel route and target speeds for each route, and vehicle status measurements obtained from internal sensors, thereby enabling autonomous driving.

[0032] Furthermore, the vehicle frame 11 is equipped with a drive system including an engine and generator that generate electricity to power the transport vehicle 10, an electric motor that drives and regenerates braking the rear wheels 15 (which serve as drive wheels), and a suspension system that supports the front and rear wheels 14 and 15 by allowing them to move vertically. The transport vehicle 10 is configured to move freely on the road surface via its wheels 14 and 15. To support the very large load on the frame 11, the suspension incorporates hydraulic components called support rods instead of mechanical springs. The support rod is a spring-damping mechanism consisting of a piston and a cylinder, configured such that working oil is sealed inside the cylinder, and the spring effect is achieved through the compression of this working oil. Therefore, the pressure of the working oil inside the support rod is proportional to the load supported by the support rod.

[0033] In addition, wheel speed sensors for measuring the rotational speed of each wheel are installed on each of the front wheels 14 and the rear wheels 15. The wheel speed sensors are generally composed of a rotary encoder mounted on the axle or the shaft of an electric motor of the drive wheel. The rotary encoder is configured to generate electrical pulses based on the rotation angle of the wheel. Therefore, the rotational speed of each wheel is measured based on the time interval (frequency) of the electrical pulses from the rotary encoder.

[0034] The cargo bucket 12 is loaded with transport materials 17, such as sand, which are loaded by excavating machinery such as hydraulic excavators or wheel loaders. The transport vehicle 10 extends the lifting cylinder 209, thereby rotating the cargo bucket 12 around the rear support shaft 16 as a rotation center, causing the front end of the cargo bucket 12 to rise. As a result, the transport vehicle 10 can discharge the transport materials 17 loaded into the cargo bucket 12 from the rear end of the cargo bucket 12.

[0035] Here, we will explain the operation of mining dump trucks. Mining dump trucks are machines used to repeatedly transport sand, soil, or minerals within a mining site. At the mining site, excavating machinery such as hydraulic excavators strips topsoil or excavates minerals until the ore vein is reached. The mining dump truck approaches the vicinity of the excavating machinery, where the excavated sand, soil, etc., is loaded. This location is called the loading yard. Although the destination of the loaded transported goods varies depending on their contents, the goods are transported to the appropriate location via a transport route. For example, if the transported goods are topsoil sand, they are transported to a site used for landfilling sand; if the transported goods are minerals, they are transported to a stockpile or a silo where minerals are transported by conveyor. Regardless of the location, the mining dump truck tilts its hopper to unload the transported goods. This location is called the unloading yard. The empty mining dump truck then returns to the loading yard to reload and repeat the operation.

[0036] Typically, multiple mining dump trucks operate at a mining site, and multiple mining dump trucks also operate at the excavation locations that serve as loading yards. Additionally, multiple unloading yards exist, varying in location from ore to topsoil. To ensure efficient operation of the excavating machinery and transport vehicles, control devices operate at the mining site, enabling transport vehicles to travel between them to the required locations at appropriate times. In mining sites employing unmanned and automated transport operation systems, a fundamental function of the control devices for transport vehicles is to include driving instructions in map data representing driving paths and send these instructions to each vehicle. These instructions specify the route from which loading yard to which unloading yard, along which path, and at what target speed. Typically, the target speed included in the driving path map is set under stable weather conditions and on dry road surfaces.

[0037] However, since mining sites are outdoor environments, transport routes sometimes become wet or muddy due to rainfall. Furthermore, because the transport routes are unpaved, dust can rise during travel if they are too dry; therefore, water is sometimes intentionally sprayed using water trucks to make the road surface wet. When it is believed that the road surface is slippery due to wetness, the control device may send a command to change the target speed along with the predetermined route. In other words, the transport route surface may become wet due to watering operations, or, especially in large mining areas, only a portion may become wet due to rainfall; therefore, driving commands, represented by target speeds, are very important.

[0038] For example, when transport vehicles are traveling at target speeds included in the route map, control personnel may, upon receiving information about severe weather such as rain or about water truck operations, sometimes instruct all vehicles (or designated sections) to slow down for safety reasons. In this situation, the control personnel operating the control devices in the control room are unaware of the extent of the road condition deterioration and therefore instruct slightly lower target speeds, ensuring an excessive safety margin, based on weather conditions and past experience. However, at low target speeds, transport time is longer than usual, resulting in a significant reduction in transport volume per unit time, which is a measure of operational efficiency. Therefore, if the road conditions are accurately known and the target speed is not unnecessarily reduced, the reduction in operational efficiency can be minimized by issuing driving instructions with appropriate target speeds.

[0039] Figure 2 This indicates the relationship between tire force and slip ratio.

[0040] Here, the tire characteristics related to the slippage of the tires installed on wheels 14 and 15 are explained. Figure 2A graph is shown illustrating general tire characteristics related to tire slippage. In this description, the tire forces generated by the tire relative to the road surface, specifically the tire forces in the longitudinal (rotational) direction, are explained. The longitudinal tire forces primarily function as the tire's braking force. However, the lateral (width direction) tire forces associated with the turning of the transport vehicle 10 also exhibit the same characteristics.

[0041] Regardless of the longitudinal or lateral directions, when considering tire forces, a tire has the characteristic of generating force through a small slippage with the road surface. For example, in the longitudinal direction of the tire, due to the braking torque applied to the axle, a small longitudinal slippage occurs between the tire and the road surface. Considering the tire as a whole, a speed difference is generated between the tire's rotational speed (wheel speed) and the vehicle's speed relative to the road surface (vehicle speed). If we denote the tire's rotational speed (wheel speed) as Vw and the vehicle's speed relative to the road surface (vehicle speed) as Vb, then the ratio of their speed difference, i.e., the slip ratio ω, is expressed as in Equation 1.

[0042]

[0043] In this region of small slip ratio, tire force is proportional to slip ratio. As slip ratio increases, as... Figure 2 As shown in curve 51, the rate of increase in tire force decreases, eventually saturating and reaching the maximum tire force Fmax. This Fmax is the maximum force that the tire can generate on that road surface (maximum tire force). Moreover, it is known that the slip ratio ω1 at which the tire force is at its maximum is generally a value of around 0.2.

[0044] However, since the tire force is frictional, the maximum tire force Fmax that can be generated is proportional to the vertical load applied to wheels 14 and 15. Figure 2 The tire force characteristic curves shown illustrate the characteristics under constant loads applied to wheels 14 and 15. However, unlike typical automobiles, in transport vehicle 10, the load weight is very large relative to its own weight, often exceeding its own weight significantly. Furthermore, in transport vehicle 10, due to the cargo bed 12 being located on the upper part of the vehicle body, the center of gravity is at a very high position. Therefore, the load displacement of wheels 14 and 15 increases significantly with acceleration, deceleration, or cornering. To consistently handle road conditions under such circumstances where the loads applied to wheels 14 and 15 can vary considerably, the tire force is standardized by dividing the load and treated as the coefficient of friction μ. Figure 3 This represents the characteristic curve at this point.

[0045] Figure 3 This indicates the relationship between the friction coefficient and the slip ratio of the road surface.

[0046] Similar to the discussion of tire forces above, in this region of small slip ratio, the coefficient of friction is proportional to the slip ratio. As the slip ratio increases, as... Figure 3 As shown in curve 52, the rate of increase in the coefficient of friction decreases until it saturates and reaches its maximum value μmax. That is, the maximum coefficient of friction μmax represents the maximum value of the coefficient of friction in the entire region, including both the linear region where the relationship between the coefficient of friction and the slip ratio is linear and the nonlinear region where the relationship is nonlinear. This maximum coefficient of friction μmax is the maximum coefficient of friction on the road surface along the predetermined travel path, and its magnitude indicates the ease of slippage of the road surface. If the load applied to wheels 14 and 15 (wheel load) is set as W, the tire force Fd required for braking drive of the transport vehicle 10 is expressed as shown in Equation 2.

[0047]

[0048] That is, when the relationship of Equation 2 is achieved, the frictional force becomes unbearable, and wheels 14 and 15 transition to complete slippage (tires lock-up). In the state of complete slippage, the tires lose control, making it difficult to maintain the vehicle body in the desired direction of travel, thus becoming a very dangerous state. Therefore, in order to avoid the state of Equation 2, the magnitude of the tire force Fd required for braking and driving the transport vehicle 10 must always be limited to W·μmax or less.

[0049] When dump trucks are operating in mines, a target speed is determined to bring them to a stop within a predetermined stopping distance. However, on slippery surfaces such as wet roads, the maximum coefficient of friction μmax is unknown. Therefore, by limiting the speed to a level that provides a sufficient safety margin, even a small tire force can bring the stopping distance below the specified limit. However, this results in a longer transport time due to the reduced speed, leading to decreased operational efficiency, thus creating a trade-off. Therefore, in this embodiment, the target speed is limited by estimating the maximum coefficient of friction μmax and envisioning stopping with the largest possible tire force Fd.

[0050] Figure 4 This describes the functional structure of the transport vehicle 10 in this embodiment. Figure 5 This describes the load movement of wheels 14 and 15 of transport vehicle 10.

[0051] The transport vehicle 10 is equipped with a control device 100 for controlling the movement of the transport vehicle 10 and a sensor 110 for measuring the state of the wheels 14 and 15 when the transport vehicle 10 is in motion.

[0052] The control device 100 is composed of a computer including a CPU, ROM and RAM, etc. The CPU executes the program stored in RAM to realize the various functions of the control device 100.

[0053] like Figure 4 As shown, the control device 100 includes a μ calculation unit 101, an ω calculation unit 102, a parameter estimation unit 103, a maximum friction estimation unit 104, and a speed limiting unit 105 to perform the aforementioned functions. Furthermore, the control device 100 includes a storage unit 107 for storing a pre-set driving path map 106.

[0054] As mentioned above, in estimating the maximum coefficient of friction μmax, it is necessary to... Figure 3 The vertical and horizontal axes of the graph represent the coefficient of friction and the slip ratio, respectively. The coefficient of friction and the slip ratio are calculated based on tire force, the load applied to wheels 14 and 15 (i.e., wheel load), wheel speed, and travel speed. These physical quantities are calculated based on values ​​measured by sensors 110 provided with the transport vehicle 10.

[0055] The tire force is calculated based on the drive current value supplied to the electric motors that drive the wheels 14 and 15. Sensor 110 includes a current sensor that measures the drive current value. Although not shown, the control device 100 may include a tire force calculation unit that calculates the tire braking torque based on the drive current value measured by the current sensor, and calculates the tire force in the fore-and-aft direction based on the calculated braking torque.

[0056] The wheel load is calculated based on the suspension load supporting wheels 14 and 15. The suspension load is calculated based on specifications such as the pressure of the working oil inside the support rod and the cylinder bore, and then converted into a wheel load. Sensor 110 includes a pressure sensor that measures the pressure of the working oil inside the support rod. Although not shown, the control device 100 may include a wheel load calculation unit that calculates the suspension load based on the pressure of the working oil inside the support rod measured by the pressure sensor, and calculates the wheel load based on the calculated suspension load.

[0057] Wheel speed is calculated based on the rotation angle of the tire or wheel. Sensor 110 includes a wheel speed sensor, such as a rotary encoder, which generates electrical pulses based on the rotation angle of the tire or wheel. Although not shown, control device 100 may include a wheel speed calculation unit that calculates the wheel speed based on the time interval of the electrical pulses generated from the wheel speed sensor.

[0058] The transport vehicle 10 is driven by an electric motor located on the rear wheels 15, which serve as drive wheels, and deceleration and stopping are essentially achieved through the regenerative torque of the electric motor. Therefore, during normal driving, no braking drive torque is applied to the front wheels 14, which operate purely as driven wheels. Thus, the wheel speed of the front wheels 14 can be used as the vehicle's speed relative to the road surface (driving speed). The control device 100 may include a driving speed calculation unit that calculates the average wheel speed of the left and right front wheels 14 (which are driven wheels) and uses this calculated average value as the driving speed.

[0059] The μ calculation unit 101 calculates the friction coefficient of the road surface based on the measurement results of the sensor 110. Specifically, the μ calculation unit 101 calculates the friction coefficient by dividing the tire force in the longitudinal direction calculated by the tire force calculation unit by the wheel load calculated by the wheel load calculation unit. Furthermore, the μ calculation unit 101 may also be configured to include both the tire force calculation unit and the wheel load calculation unit.

[0060] The ω calculation unit 102 calculates the tire slip ratio based on the measurement results from the sensor 110. Specifically, the ω calculation unit 102 substitutes the wheel speed calculated by the wheel speed calculation unit and the travel speed calculated by the travel speed calculation unit into Vw and Vb of Equation 1 to calculate the slip ratio of the rear wheel 15, which is the drive wheel. Furthermore, the ω calculation unit 102 may also be configured to include the wheel speed calculation unit and the travel speed calculation unit described above.

[0061] Based on the calculation results of the μ calculation unit 101 and the ω calculation unit 102, the parameter estimation unit 103 estimates parameters representing the road surface condition, which are expressed by the relationship between the friction coefficient and the slip ratio. These parameters representing the road surface condition are parameters representing the characteristics of the tire corresponding to the road surface condition, and are parameters used to obtain the maximum friction coefficient μmax; preferably, they are parameters used to obtain... Figure 3 The parameters of curve 52. For example, the parameters representing the road surface condition are... Figure 3 The initial gain 53 of the friction coefficient in curve 52 (tire characteristic curve) represents the ratio of the friction coefficient to the slip ratio in the linear region where the relationship between the friction coefficient and the slip ratio is linear. That is, the parameter estimation unit 103 estimates the ratio of the friction coefficient to the slip ratio (initial gain 53) in the linear region where the relationship between the friction coefficient calculated by the μ calculation unit 101 and the slip ratio calculated by the ω calculation unit 102 is linear, as a parameter representing the road surface condition. For example, the parameter estimation unit 103 estimates the parameter representing the road surface condition by dividing the friction coefficient calculated by the μ calculation unit 101 by the slip ratio calculated by the ω calculation unit 102.

[0062] The maximum friction estimation unit 104 estimates the maximum friction coefficient in the entire region, including linear regions where the relationship between the friction coefficient and the slip ratio is linear and nonlinear regions where the relationship is nonlinear, based on parameters representing road surface conditions estimated by the parameter estimation unit 103. Specifically, the maximum friction estimation unit 104 estimates the maximum friction coefficient based on parameters representing road surface conditions in the linear regions estimated by the parameter estimation unit 103 and a table relating the parameters in the linear regions to the maximum friction coefficient. For example, the control device 100 pre-stores a table that represents the relationship between the ratio of the friction coefficient to the slip ratio in the linear regions estimated by the parameter estimation unit 103 as parameters representing road surface conditions and the maximum friction coefficient. The maximum friction estimation unit 104 refers to the pre-stored table to determine the maximum friction coefficient in the table corresponding to the ratio estimated by the parameter estimation unit 103, thereby estimating the maximum friction coefficient. This table can be generated based on test results from driving tests of the transport vehicle 10 or simulation results obtained by simulating such driving tests. Alternatively, for example, the maximum friction estimation unit 104 can also estimate the maximum friction based on the ratio of the friction coefficient to the slip ratio in the linear region estimated by the parameter estimation unit 103. Figure 3 The maximum coefficient of friction is estimated based on curve 52.

[0063] The speed limiting unit 105 calculates the upper limit speed of the transport vehicle 10 corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit 104, and limits the target speed based on the calculated upper limit speed. Regarding the calculation conditions for the upper limit speed of the transport vehicle 105, two main calculation conditions are considered. The first calculation condition is to calculate the upper limit speed such that the stopping distance of the transport vehicle 10 corresponding to the estimated maximum friction coefficient at deceleration is below a predetermined value. The second calculation condition is to calculate the upper limit speed to ensure the turning centripetal force of the transport vehicle 10 corresponding to the estimated maximum friction coefficient during turning. However, it is also possible to calculate the upper limit speed such that only one of these two calculation conditions is satisfied, or to calculate the upper limit speed such that both calculation conditions are satisfied. Furthermore, the calculation conditions for the upper limit speed are not limited to these; other calculation conditions may also be used.

[0064] In this embodiment, the case in which the upper limit speed of the transport vehicle 10 is calculated using the calculation condition of "calculating the upper limit speed so that the stopping distance of the transport vehicle 10 corresponding to the estimated maximum friction coefficient when decelerating to a stop is below a predetermined value" will be described.

[0065] The stopping distance d of a transport vehicle 10 traveling at a speed of V when braking at a deceleration a is expressed by Equation 3.

[0066]

[0067] On the other hand, since the transport vehicle 10 only uses the rear wheel 15 for braking, when the total weight of the transport vehicle 10 is set as Wb and the load applied to the rear wheel 15 is set as Wr, the deceleration a of the maximum friction coefficient μmax on the road surface is represented by Equation 4.

[0068]

[0069] Due to the load shift caused by deceleration, the load Wr applied to the rear wheel 15 is less than that in the stationary state. If using... Figure 5 To explain the load movement of wheels 14 and 15, the load Wr in the stationary state is represented by Equation 5 using the distances Lf and Lr from the center of gravity G to the front wheel 14 and the rear wheel 15.

[0070]

[0071] If the acceleration due to gravity is set as g, then the load movement ΔWr based on deceleration is represented by Equation 6.

[0072]

[0073] Therefore, if the height of the center of gravity G above the road surface is set as Lh, the load Wr applied to the rear wheel 15 during deceleration is represented by Equation 7.

[0074]

[0075] By substituting Equation 7 into Equation 4, and then into Equation 3, the lower limit of the stopping distance at the maximum friction coefficient μmax of the road surface can be calculated. This distance only needs to not exceed the pre-set stopping distance Dlim. That is, the driving speed V satisfying Equation 8 becomes the upper limit speed of the transport vehicle 10.

[0076]

[0077] Here, the speed limiting unit 105 uses the acceleration and deceleration of the transport vehicle 10 to calculate the load movement in order to calculate the load Wr applied to the rear wheel 15. The speed limiting unit 105 may also directly calculate the load Wr applied to the rear wheel 15 based on the measured pressure of the working oil inside the support rod, as described above.

[0078] The speed limit unit 105 compares the calculated upper limit speed with the target speed contained in the preset driving path map 106. If the upper limit speed is lower than the target speed, the speed limit unit 105 resets the target speed so that the target speed is lower than the upper limit speed. If the upper limit speed is higher than the target speed, the speed limit unit 105 maintains the target speed contained in the driving path map 106.

[0079] The driving control unit 108 controls the driving of the transport vehicle 10, causing the transport vehicle 10 to travel at a target speed reset or maintained by the speed limit unit 105 on the predetermined driving path included in the driving path map 106. The driving control unit 108 determines the operation amount of the operating device such as the accelerator pedal and makes operation input based on the vehicle's own position obtained by the GNSS device of the transport vehicle 10, the predetermined driving path and the target speed, and the vehicle state measurement values ​​obtained by internal sensors (vehicle acceleration and deceleration, wheel speed, braking drive torque and other driving-related measurement values). This controls the autonomous driving of the transport vehicle 10.

[0080] Figure 6 It means by Figure 4 A flowchart illustrating an example of the processing performed by the control device 100 shown.

[0081] In step S1, the control device 100 obtains the actual driving data of the transport vehicle 10 traveling at the target speed on the predetermined path, i.e., the measurement results of the sensor 110.

[0082] In step S2, the control device 100 calculates the friction coefficient (μ) of the road surface and the slip ratio (ω) of the tire based on the measurement results of the sensor 110.

[0083] In step S3, the control device 100 estimates parameters representing the road surface condition based on the calculated friction coefficient and slip ratio. The control device 100 estimates the ratio of the friction coefficient to the slip ratio in a linear region where the relationship between the friction coefficient and the slip ratio is linear as a parameter representing the road surface condition.

[0084] In step S4, the control device 100 estimates the maximum friction coefficient of the road surface based on the estimated parameters representing the road surface condition.

[0085] In step S5, the control device 100 determines whether the estimated maximum friction coefficient is less than a preset threshold. This threshold can also be a value obtained by converting the target speed contained in the driving path map 106 into a friction coefficient using the calculation method described in Equations 3 to 8. If the estimated maximum friction coefficient is less than the threshold, the control device 100 proceeds to step S6. If the estimated maximum friction coefficient is greater than or equal to the threshold, the control device 100 proceeds to step S7.

[0086] In step S6, the control device 100 sets a speed limit. Specifically, the control device 100 calculates the upper limit speed of the transport vehicle 10 using the calculation method described in Equations 3 to 8, and limits the target speed contained in the travel path map 106. Afterwards, the control device 100 terminates the process. Figure 6The process shown controls the movement of the transport vehicle 10 so that it travels at a restricted target speed.

[0087] In step S7, the control device 100 releases the speed limit. Specifically, the control device 100 assumes the road conditions are acceptable and maintains the target speed contained in the driving path map 106. Afterward, the control device 100 terminates the process. Figure 6 The process shown controls the movement of the transport vehicle 10 so that it travels at a maintained target speed.

[0088] As described above, the transport vehicle 10 of the first embodiment is a vehicle that travels at a target speed along a predetermined path. The transport vehicle 10 includes a control device 100 for controlling the travel of the transport vehicle 10, and a sensor 110 for measuring the state of the wheels of the transport vehicle 10 during travel. The control device 100 includes a μ calculation unit 101 that calculates the coefficient of friction of the road surface where the wheels 14 and 15 are in contact with the road surface based on the measurement results of the sensor 110. The control device 100 includes a ω calculation unit 102 that calculates the slip ratio of the wheels 14 and 15 relative to the road surface based on the measurement results of the sensor 110. The control device 100 includes a parameter estimation unit 103 that estimates a parameter representing the road surface state along the predetermined path, expressed as a relationship between the coefficient of friction and the slip ratio, based on the calculation results of the μ calculation unit 101 and the ω calculation unit 102. The control device 100 includes a maximum friction estimation unit 104 that estimates the maximum coefficient of friction along the predetermined path based on the parameter estimated by the parameter estimation unit 103. The control device 100 includes a speed limiter 105 that calculates the upper limit speed of the transport vehicle 10 corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit 104, and limits the target speed based on the calculated upper limit speed. The parameter estimation unit 103 estimates parameters representing the road surface condition in a linear region where the slip ratio and friction coefficient are linearly related, based on measurement results from the sensor 110 traveling at the target speed along a predetermined path. The maximum friction estimation unit 104 estimates the maximum friction coefficient based on the parameters in the linear region estimated by the parameter estimation unit 103 and a table relating the parameters in the linear region to the maximum friction coefficient.

[0089] Therefore, the transport vehicle 10 of the first embodiment brakes before the road surface friction coefficient reaches its maximum value. Even without measuring the state of the transport vehicle 10 at this time, the maximum friction coefficient of the road surface can be easily estimated based on the measurement results during normal driving. Thus, the transport vehicle 10 of the first embodiment can immediately determine the slippage ease of the road surface when, for example, the road surface condition deteriorates to a wet or muddy surface due to a sudden change in weather, and can limit the target speed by the necessary minimum reduction before the transport vehicle 10 slips. As a result, the transport vehicle 10 of the first embodiment can set a target speed that balances the safety and operational efficiency of the transport vehicle 10 even when the road surface condition deteriorates. Therefore, according to the first embodiment, the road surface condition can be accurately grasped based on the vehicle's state during driving, and a driving speed that balances the safety and operational efficiency of the transport vehicle 10 can be obtained.

[0090] Furthermore, in the transport vehicle 10 of the first embodiment, if the upper limit speed is lower than the preset target speed, the speed limiting unit 105 resets the target speed so that the target speed is lower than the upper limit speed. If the upper limit speed is higher than the preset target speed, the speed limiting unit 105 maintains the preset target speed.

[0091] Therefore, the transport vehicle 10 of the first embodiment can reliably ensure safety by limiting its speed when road conditions deteriorate, and reliably ensure operational efficiency by releasing the speed limit without delay when road conditions recover. Thus, according to the first embodiment, the road conditions can be accurately grasped based on the vehicle's condition during travel, resulting in a travel speed that effectively balances the safety and operational efficiency of the transport vehicle 10.

[0092] Furthermore, in the transport vehicle 10 of the first embodiment, the speed limiting unit 105 calculates the upper limit speed so that the stopping distance of the transport vehicle 10 corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit 104 is below a predetermined value.

[0093] Therefore, the transport vehicle 10 of the first embodiment can reliably stop within a preset stopping distance when decelerating, thus actively preventing collisions with preceding vehicles and ensuring safety more reliably. Therefore, according to the first embodiment, the road conditions can be accurately grasped based on the vehicle's state during travel, resulting in a travel speed that more effectively balances the safety and operational efficiency of the transport vehicle 10.

[0094] Furthermore, in the transport vehicle 10 of the first embodiment, the control device 100 pre-stores a table showing the relationship between the ratio and the maximum friction coefficient in the linear region. The maximum friction estimation unit 104 estimates the maximum friction coefficient by referring to the pre-stored table. Such tables can be various types provided, for example, based on the external environment that affects the road surface condition. Examples include tables that link the relationship between parameters representing the road surface condition and the maximum friction coefficient differently depending on the weather conditions, and tables that link the relationship differently depending on the road surface material (type of minerals or sand), road surface roughness (size of sand or rock constituting the road surface), etc. Additionally, the travel path of the transport vehicle 10 can be divided into multiple travel sections. The maximum friction estimation unit 104 can estimate the maximum friction coefficient for each travel section based on the obtained sensor data (measurement results from sensor 110) and reflect this to the target speed (output to the speed limit unit 105).

[0095] Therefore, the transport vehicle 10 of the first embodiment can significantly shorten the calculation time when estimating the maximum coefficient of friction during travel, thus making it easier to estimate the maximum coefficient of friction. Therefore, according to the first embodiment, the road surface condition can be accurately and easily grasped based on the vehicle's condition during travel, and a travel speed that balances the safety and operational efficiency of the transport vehicle 10 can be easily obtained.

[0096] [Second Implementation]

[0097] Next, a second embodiment of the present invention will be described. In the description of the second embodiment, structural elements that are the same as those in the first embodiment will be omitted.

[0098] In the second embodiment, the speed limiting unit 105 calculates the upper limit speed of the transport vehicle 10 using calculation conditions such as "calculating the upper limit speed to ensure the turning centripetal force of the transport vehicle 10 corresponding to the estimated maximum coefficient of friction when turning." Then, the speed limiting unit 105 limits the target speed based on the calculated upper limit speed.

[0099] The centripetal acceleration a when the transport vehicle 10 is traveling at a speed V and making a circular turn with a turning radius r is expressed by Equation 9.

[0100]

[0101] On the other hand, if the lateral load movement of the transport vehicle 10 is ignored, the maximum centripetal acceleration on the road surface with the maximum friction coefficient μmax becomes μmax. That is, the upper limit of the speed at which turning is possible, Vmax, is represented by Equation 10.

[0102]

[0103] Therefore, Vmax, as expressed by Equation 10, becomes the upper limit speed of the transport vehicle 10. A turning radius r is set within the predetermined travel path included in the travel path map 106. The speed limit unit 105 can obtain the turning radius r by reading it from the travel path map 106.

[0104] As described above, in the transport vehicle 10 of the second embodiment, the speed limiting unit 105 calculates the upper limit speed to ensure the turning centripetal force of the transport vehicle 10 corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit 104.

[0105] Therefore, the transport vehicle 10 of the second embodiment can reliably ensure that it does not deviate from the predetermined driving path when turning. To avoid instability such as path deviation on curves, it is necessary to reduce speed in advance. The transport vehicle 10 of the second embodiment can measure the state of the transport vehicle 10 while driving on a curve and immediately determine the ease of road slippage, limiting the target speed before the transport vehicle 10 slips, thus ensuring that it does not deviate from the predetermined driving path. Therefore, the transport vehicle 10 of the second embodiment can actively prevent collisions with parallel or oncoming vehicles in adjacent lanes, ensuring safety more reliably. Therefore, according to the second embodiment, the road surface condition can be accurately grasped based on the vehicle's state during driving, resulting in a driving speed that more effectively balances the safety and operational efficiency of the transport vehicle 10.

[0106] [Third Implementation Method]

[0107] Next, use Figure 7 A third embodiment of the present invention will be described. In the description of the third embodiment, structural elements that are the same as those in the first or second embodiment are omitted.

[0108] In the third embodiment, a speed limiting unit 105 and a storage unit 107 are provided in the control device 20 to realize a transportation operation system 1 in which the transport vehicle 10 travels according to the driving instructions from the control device 20.

[0109] Figure 7 This is a diagram showing the structure of transportation operation system 1.

[0110] The transportation operation system 1 includes: a control device 20, which generates driving instructions for the transport vehicle 10 to travel according to a predetermined route and target speed; and the transport vehicle 10, which travels according to the driving instructions from the control device 20.

[0111] The transport vehicle 10 includes: a control device 100 that controls the movement of the transport vehicle 10; a sensor 110 that measures the state of the wheels 14 and 15 when the transport vehicle 10 is in motion; and a communication device 120 that communicates with the control device 20.

[0112] The control device 100 includes: a μ calculation unit 101, which calculates the friction coefficient of the road surface based on the measurement results of the sensor 110; an ω calculation unit 102, which calculates the slip ratio based on the measurement results of the sensor 110; and a parameter estimation unit 103, which estimates parameters representing the road surface condition based on the calculation results of the μ calculation unit 101 and the ω calculation unit 102. The control device 100 also includes: a maximum friction estimation unit 104, which estimates the maximum friction coefficient on a predetermined driving path based on the parameters estimated by the parameter estimation unit 103. The control device 100 further includes: a driving control unit 108, which controls the driving of the transport vehicle 10 according to driving commands sent from the control device 20. The parameter estimation unit 103 estimates parameters representing the road surface condition in a linear region. The maximum friction estimation unit 104 estimates the maximum friction coefficient based on the parameters estimated by the parameter estimation unit 103 in the linear region and a table relating the parameters in the linear region to the maximum friction coefficient.

[0113] The communication device 120 sends the maximum friction coefficient estimated by the maximum friction estimation unit 104 to the control device 20. The communication device 120 receives the driving command sent from the control device 20 and sends it to the driving control unit 108.

[0114] The control device 20 includes a processing device 200 for generating driving instructions for the transport vehicle 10 and a communication device 210 for communicating with the transport vehicle 10.

[0115] The processing device 200 includes a storage unit 107 that stores a pre-set driving path map 106. The processing device 200 also includes a speed limiting unit 105 that calculates the upper limit speed of the transport vehicle 10 corresponding to the maximum coefficient of friction transmitted from the transport vehicle 10, and limits the target speed based on the calculated upper limit speed. The processing device 200 further includes a command generation unit 201 that generates a driving command corresponding to the target speed limited by the speed limiting unit 105.

[0116] The communication device 210 receives the maximum coefficient of friction sent from the transport vehicle 10 and sends it to the speed limit unit 105. The communication device 210 sends the driving command generated by the command generation unit 201 to the transport vehicle 10.

[0117] Therefore, the transportation operation system 1 of the third embodiment, like the first embodiment, can accurately grasp the road surface condition based on the vehicle's condition during travel, such as the ease of road slippage, and obtain a travel speed that can balance the safety and operational efficiency of the transport vehicle 10.

[0118] Furthermore, the present invention is not limited to the embodiments described above, and includes various modifications. For example, the embodiments described above are detailed for the purpose of easily understanding and illustrating the present invention, and are not necessarily limited to having all the structural elements described.

[0119] For example, in the above embodiment, the transport vehicle 10 is described as being configured to drive autonomously, but the transport vehicle 10 may also be configured to drive part or all of its own manually following the operator's commands.

[0120] Furthermore, it is possible to replace a portion of the structural elements of a certain embodiment with structural elements of other embodiments, and it is also possible to add structural elements of other embodiments to the structural elements of a certain embodiment. Additionally, for a portion of the structural elements of each embodiment, it is possible to add, delete, or replace other structural elements.

[0121] Furthermore, some or all of the aforementioned structural elements, functions, processing units, or processing modules can be implemented in hardware, such as through integrated circuit design. Alternatively, the aforementioned structural elements or functions can be implemented in software by a processor interpreting and executing programs that implement each function. The programs, tables, or files implementing each function can be stored in recording devices such as memory, hard disks, or SSDs (solid-state drives), or recording media such as IC cards, SD cards, or DVDs.

[0122] Furthermore, control lines and information lines represent lines that are considered necessary for the specifications, but may not represent all control lines and information lines on the product. In fact, almost all structural elements can be considered interconnected.

[0123] Explanation of reference numerals in the attached figures

[0124] 1…Transportation operation system, 10…Transportation vehicle, 14, 15…Wheels, 100…Control device, 101…μ calculation unit, 102…ω calculation unit, 103…Parameter estimation unit, 104…Maximum friction estimation unit, 105…Speed ​​limiting unit, 110…Sensor, 120…Communication device, 20…Control device.

Claims

1. A transport vehicle that travels at a target speed along a predetermined path, characterized in that, The transport vehicle is equipped with: A control device that controls the movement of the transport vehicle; Sensors that measure the state of the wheels of the transport vehicle as it moves. The control device has: The μ calculation unit calculates the coefficient of friction of the road surface in contact with the wheels during the predetermined driving path based on the measurement results of the sensor. The ω calculation unit calculates the slip ratio of the wheel relative to the road surface based on the measurement results of the sensor; The parameter estimation unit estimates, based on the calculation results of the μ calculation unit and the ω calculation unit, a parameter representing the road surface condition of the predetermined driving path, which is expressed by the relationship between the friction coefficient and the slip ratio; The maximum friction estimation unit estimates the friction coefficient in the predetermined driving path to be the maximum maximum friction coefficient based on the parameters estimated by the parameter estimation unit. The speed limiting unit calculates the upper limit speed of the transport vehicle corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit, and limits the target speed based on the calculated upper limit speed. Based on the measurement results of the sensors when traveling on the predetermined travel path at the target speed, the parameter estimation unit estimates the parameter representing the road surface condition within the linear region where the slip ratio and the friction coefficient have a linear relationship. The maximum friction estimation unit estimates the maximum friction coefficient based on the parameters in the linear region estimated by the parameter estimation unit and a table that associates the parameters in the linear region with the maximum friction coefficient.

2. The transport vehicle according to claim 1, characterized in that, If the upper limit speed is lower than the preset target speed, the speed limiting unit resets the target speed so that the target speed is below the upper limit speed; if the upper limit speed is above the preset target speed, the unit maintains the preset target speed.

3. The transport vehicle according to claim 2, characterized in that, The speed limiting unit calculates the upper limit speed such that the stopping distance of the transport vehicle corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit is below a preset value.

4. The transport vehicle according to claim 2, characterized in that, The speed limiting unit calculates the upper limit speed to ensure the turning centripetal force of the transport vehicle corresponding to the maximum friction coefficient estimated by the maximum friction estimation unit.

5. A transportation operation system, comprising: Control device, which generates driving instructions that cause the transport vehicle to travel at a target speed on a predetermined path; The transport vehicle travels according to the driving instructions from the control device. Its features are, The transport vehicle is equipped with: A control device that controls the movement of the transport vehicle; Sensors that measure the state of the wheels of the transport vehicle while it is in motion; and A communication device that communicates with the control device. The control device has: The μ calculation unit calculates the coefficient of friction of the road surface in contact with the wheels during the predetermined driving path based on the measurement results of the sensor. The ω calculation unit calculates the slip ratio of the wheel relative to the road surface based on the measurement results of the sensor; The parameter estimation unit estimates, based on the calculation results of the μ calculation unit and the ω calculation unit, a parameter representing the road surface condition of the predetermined driving path, which is expressed by the relationship between the friction coefficient and the slip ratio; The maximum friction estimation unit estimates the friction coefficient in the predetermined driving path to be the maximum maximum friction coefficient based on the parameters estimated by the parameter estimation unit. Based on the measurement results of the sensors when traveling on the predetermined travel path at the target speed, the parameter estimation unit estimates the parameter representing the road surface condition within the linear region where the slip ratio and the friction coefficient have a linear relationship. The maximum friction estimation unit estimates the maximum friction coefficient based on the parameters in the linear region estimated by the parameter estimation unit and a table relating the parameters in the linear region to the maximum friction coefficient. The communication device sends the maximum friction coefficient estimated by the maximum friction estimation unit to the control device. The control device has a speed limiting unit that calculates an upper limit speed of the transport vehicle corresponding to the maximum friction coefficient sent from the transport vehicle, and limits the target speed according to the calculated upper limit speed. The control device generates a driving command corresponding to the target speed limited by the speed limiting unit and sends it to the transport vehicle.

Images