Context adaptive cruise control system for climbing vehicles

Abstract

A contextual adaptive cruise control system for a vehicle, the contextual adaptive cruise control of the vehicle including one or more controllers in electronic communication with a plurality of perceptual sensors and a prime mover. The one or more controllers execute instructions to receive perceptual data from a plurality of perceptual sensors. The one or more controllers determine a longitudinal slope of the road on which the vehicle is currently traveling based on the perceived data, compare the longitudinal slope to a threshold slope value stored in the memory, and determine that the vehicle is climbing in response to determining that the longitudinal slope is at least equal to the threshold slope value. The one or more controllers instruct the contextual adaptive cruise control system to modify behavior of the vehicle based on at least one of a target speed of the vehicle and an output torque of a prime mover of the vehicle.

Description

Technical Field

[0001] The present disclosure relates to a contextual adaptive cruise control system that modifies the behavior of a vehicle based on a target speed of the vehicle, an output torque of a prime mover of the vehicle, or a target speed and output torque of the vehicle when climbing a hill. Background Art

[0002] Many vehicles include various driver assistance systems that assist the driver in a variety of ways. For example, an adaptive cruise control (ACC) system can relieve the driver from conventional longitudinal vehicle control by ensuring that the host vehicle is within an acceptable headway distance from the vehicle immediately adjacent to the host vehicle (referred to as the lead vehicle). The adaptive cruise control system determines the motion of the host vehicle based on the motion of the lead vehicle and the target speed.

[0003] The adaptive cruise control system attempts to accelerate the vehicle in order to reach the target speed relatively quickly. Therefore, when the vehicle is climbing a hill, this behavior causes the vehicle to experience a relatively high degree of jerk, which is the rate of change of an object's acceleration. Some occupants may find the relatively high degree of jerk to be uncomfortable. The occupant can apply the brakes to disengage the adaptive cruise control and reduce the speed of the vehicle in an effort to mitigate the jerk. However, applying the brakes reduces the fuel or energy economy of the vehicle. It should also be understood that when the vehicle is traveling downhill, the speed of the vehicle increases due to gravity. The speed of the vehicle continues to increase until it exceeds the target speed. Even if there is no obstacle in front of the vehicle, the adaptive cruise control system will apply the brakes to reduce the speed of the vehicle, thereby reducing the energy efficiency of the vehicle.

[0004] Therefore, while adaptive cruise control systems achieve their intended purpose, there is a need in the art for an improved method of controlling the behavior of a vehicle when climbing a hill. Summary of the invention

[0005] According to several aspects, a contextual adaptive cruise control system for a vehicle is disclosed. The vehicle includes a prime mover and a plurality of perception sensors. The contextual adaptive cruise control system includes one or more controllers that are in electronic communication with the plurality of perception sensors and the prime mover. The one or more controllers execute instructions to receive perception data from the plurality of perception sensors, wherein the perception data represents an environment around the vehicle, and the environment includes a road on which the vehicle is traveling. The one or more controllers determine the longitudinal slope of the road on which the vehicle is currently traveling based on the perception data. The one or more controllers compare the longitudinal slope with a threshold slope value stored in a memory, wherein the threshold slope value indicates that the vehicle is traveling along a hill. In response to determining that the longitudinal slope is at least equal to the threshold slope value, the one or more controllers determine that the vehicle is climbing a hill and instruct the contextual adaptive cruise control system to modify the behavior of the vehicle based on at least one of a target speed of the vehicle and an output torque of the prime mover of the vehicle.

[0006] In another aspect, one or more controllers execute instructions to modify the behavior of the vehicle by reducing a target speed of the vehicle by a predetermined threshold.

[0007] In yet another aspect, one or more controllers execute instructions to determine that the vehicle is at a first position at the bottom of a hill based on perception data from a plurality of perception sensors, and to reduce a target speed by a predetermined threshold in response to determining that the vehicle is at the first position at the bottom of a hill.

[0008] In one aspect, one or more controllers receive map data via a communication network, wherein the map data indicates a distance between a first location at the bottom of a mountain and a second location at the top of a mountain.

[0009] In another aspect, the one or more controllers execute instructions to reduce a target speed for the vehicle based on a distance between a first location at the bottom of a hill and a second location at the top of a hill.

[0010] In yet another aspect, one or more controllers execute instructions to modify the behavior of the vehicle by maintaining a target speed for the vehicle and allowing an actual speed of the vehicle to deviate from the target speed by a predetermined threshold.

[0011] In one aspect, one or more controllers execute instructions to determine a first position of the vehicle at the bottom of a hill based on perception data from a plurality of perception sensors, and in response to determining that the vehicle is at the bottom of the hill, allow an actual speed of the vehicle to deviate from a target speed by a predetermined threshold until the vehicle reaches the bottom of the hill.

[0012] In another aspect, the predetermined threshold ranges from about 5% to about 10% of the target speed.

[0013] In another aspect, one or more controllers execute instructions to modify behavior of a vehicle based on an output torque of a prime mover, wherein the output torque of the vehicle is determined based on a plurality of driving objectives.

[0014] In yet another aspect, the plurality of driving objectives include ride comfort for one or more occupants of the vehicle, energy efficiency of the prime mover, and a target speed of the vehicle while climbing a grade.

[0015] In one aspect, one or more controllers store the ride comfort cost function, the energy efficiency cost function, and the target speed cost function in memory.

[0016] On the other hand, the ride comfort cost function is expressed as a function of the output torque of the prime mover and one or more environmental variables, the energy efficiency cost function is expressed as a function of the output torque of the prime mover and one or more environmental variables, and the target speed cost function is expressed as a function of the output torque of the prime mover and one or more environmental variables.

[0017] In yet another aspect, the one or more environmental variables include one or more of: a measured grade of the road, a vehicle weight, a road friction value, a target speed, and a driving habit of a vehicle driver.

[0018] In one aspect, the output torque of the prime mover is based on a weighted cost function that is a sum of a ride comfort cost function multiplied by a first weight value, an energy efficiency cost function multiplied by a second weight value, and a target speed cost function multiplied by a third weight value.

[0019] In another aspect, the one or more controllers minimize a weighted cost function based on a multi-objective optimization algorithm.

[0020] In yet another aspect, the multi-objective optimization is an a priori multi-objective optimization algorithm.

[0021] In one aspect, one or more controllers minimize a weighted cost function based on one or more machine learning algorithms.

[0022] In another aspect, the one or more machine learning algorithms include a deep neural network.

[0023] In yet another aspect, a method for modifying the behavior of a vehicle by a contextual adaptive cruise control system is disclosed. The method includes receiving, by one or more controllers, sensory data from a plurality of sensory sensors, wherein the sensory data represents an environment surrounding the vehicle, and the environment includes a road on which the vehicle is traveling. The method includes determining, based on the sensory data, a longitudinal slope of a road on which the vehicle is currently traveling. The method includes comparing the longitudinal slope with a threshold slope value stored in a memory, wherein the threshold slope value indicates that the vehicle is traveling along a hillside. In response to determining that the longitudinal slope is at least equal to the threshold slope value, the method includes determining that the vehicle is climbing a hill. Finally, the method includes instructing the contextual adaptive cruise control system to modify the behavior of the vehicle based on at least one of a target speed of the vehicle and an output torque of a prime mover of the vehicle.

[0024] In one aspect, a contextual adaptive cruise control system for a vehicle is disclosed. The contextual adaptive cruise control system includes a prime mover; a plurality of perception sensors for collecting perception data representing an environment surrounding the vehicle, wherein the environment includes a road on which the vehicle is traveling; and one or more controllers in electronic communication with the plurality of perception sensors. The one or more controllers execute instructions to receive the perception data from the plurality of perception sensors. The controller determines a longitudinal slope of a road on which the vehicle is currently traveling based on the perception data. The one or more controllers compare the longitudinal slope to a threshold slope value stored in a memory, wherein the threshold slope value indicates that the vehicle is traveling along a hill. In response to determining that the longitudinal slope is at least equal to the threshold slope value, the one or more controllers determine that the vehicle is climbing a hill. Finally, the one or more controllers instruct the contextual adaptive cruise control system to modify the behavior of the vehicle based on at least one of a target speed of the vehicle and an output torque of the prime mover of the vehicle.

[0025] Further areas of applicability will become apparent from the description provided herein.It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way.

[0027] Figure 1 is a schematic diagram of a vehicle including a disclosed contextual adaptive cruise control system according to an exemplary embodiment, the contextual adaptive cruise control system including one or more controllers in electronic communication with a plurality of perception sensors, a prime mover, a braking system, and a communication network;

[0028] Figure 2 According to an exemplary embodiment Figure 1 A block diagram of the software architecture of one or more controllers shown;

[0029] Figure 3A is a graph of a first option for modifying the behavior of a vehicle based on a target speed according to an exemplary embodiment;

[0030] Figure 3B is a graph of a second option for modifying the behavior of a vehicle based on a target speed according to an exemplary embodiment;

[0031] Figure 4A is a graph of a method of controlling an actual speed of a vehicle based on map data according to an exemplary embodiment; and

[0032] Figure 4B is a graph of another method for controlling an actual speed of a vehicle based on map data according to an exemplary embodiment. DETAILED DESCRIPTION

[0033] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses.

[0034] refer to Figure 1 , a schematic diagram of an exemplary contextual adaptive cruise control system 10 for a vehicle 12 including a plurality of wheels 14 is shown. It should be understood that the vehicle 12 can be any type of vehicle, but is not limited to a car, a truck, a sport utility vehicle, a van, or an RV. In one embodiment, the contextual adaptive cruise control system 10 is part of an advanced driver assistance system (ADAS) of the vehicle 12. The contextual adaptive cruise control system 10 includes one or more controllers 20 that electronically communicate with a plurality of perception sensors 22, a prime mover 24, and a braking system 26. In an embodiment, the one or more controllers 20 also wirelessly communicate with one or more communication networks 28, wherein the one or more controllers 20 obtain map data of the road on which the vehicle 12 is currently traveling via the communication network 28. Alternatively, the map data may also be stored locally.

[0035] The plurality of perception sensors 22 are configured to collect perception data indicating the environment around the vehicle 12. The one or more controllers 20 determine contextual information about the road on which the vehicle 12 is currently traveling based on the perception data. Specifically, the contextual information of the road indicates the longitudinal slope of the road on which the vehicle 12 is currently traveling. The longitudinal slope represents the slope of the road. In one embodiment, the slope of the road can be expressed as a percentage (e.g., 100%×distance of vertical change / distance of horizontal change). It should be understood that in response to determining that the longitudinal slope of the road includes a positive slope of at least about 5 seconds, the one or more controllers 20 determine that the vehicle 12 is climbing a slope, wherein the positive slope is a slope of at least 0.5%. Similarly, in response to determining that the longitudinal slope of the road includes a negative slope of at least about 5 seconds, the one or more controllers 20 determine that the vehicle 12 is going downhill, wherein the negative slope is a negative slope of at least 0.5%. However, it should be understood that the 0.5% slope and the time period of at least about five seconds are exemplary in nature and can be adjusted based on the application.

[0036] In such Figure 1In the non-limiting embodiment shown, the plurality of perception sensors 22 include one or more cameras 30, an inertial measurement unit (IMU) 32, a global positioning system (GPS) 34, a radar 36, and a LiDAR 38, however, it should be understood that additional sensors may also be used. The one or more controllers 20 determine the slope of the road based on the linear acceleration, angular velocity, and magnetic field strength received by the IMU 32. The prime mover 24 represents a power source for propelling the vehicle 12 and includes an internal combustion engine, one or more electric motors, or a combination of an internal combustion engine and one or more electric motors. The braking system 26 includes a set of brakes corresponding to each wheel 14 of the vehicle 12.

[0037] Figure 2 yes Figure 1 1 is a block diagram of the software architecture of one or more controllers 20 of the contextual adaptive cruise control system 10 shown. The one or more controllers 20 include a context module 60, a target speed module 62, an output torque module 64, and a downhill module 66. The context module 60 of the one or more controllers 20 receives perception data from a plurality of perception sensors 22, and determines the longitudinal slope of the road on which the vehicle 12 is currently traveling based on the perception data. Specifically, the context module 60 of the one or more controllers 20 determines the slope of the road based on the linear acceleration, angular velocity, and magnetic field strength received by the IMU 32. The context module 60 compares the longitudinal slope with a threshold slope value stored in a memory, wherein the threshold slope value indicates that the vehicle 12 is traveling along a hillside. In one embodiment, the threshold slope value is a slope of one percent. In response to determining that the longitudinal slope is at least equal to the threshold slope value, the context module 60 determines that the vehicle 12 is climbing a hill and instructs the contextual adaptive cruise control system 10 to determine the target speed of the vehicle 12 and one of the output torques of the prime mover 24 of the vehicle 12 ( Figure 1 ) to modify the behavior of the vehicle 12. The one or more controllers 20 determine the longitudinal control command 58 that instructs the vehicle 12 to accelerate or decelerate to achieve the behavior of the vehicle 12 modified by the contextual adaptive cruise control system 10. It should be understood that the behavior of the vehicle 12 is based on the actual speed of the vehicle 12, the acceleration of the vehicle 12, and the turbulence experienced by the occupants. The actual speed, acceleration, and turbulence of the vehicle 12 are directly affected by the output torque of the vehicle 12.

[0038] It should be appreciated that modifying the behavior of the vehicle 12 based on the target speed generally improves the overall fuel or energy efficiency of the vehicle 12 when climbing a grade. Changing the behavior of the vehicle 12 based on the output torque of the prime mover 24 generally improves the overall ride comfort for the occupants of the vehicle 12 by reducing the occurrence of jolts when the vehicle 12 climbs a grade. Modifying the behavior of the vehicle 12 based on the target speed will now be described. Figure 3A and Figure 3BBoth include graphs 70, 72 illustrating different exemplary methods of modifying the behavior of the vehicle 12 based on the target speed. Specifically, Figure 3A A graph 70 is shown of a first option for modifying the behavior of the vehicle 12 based on a target speed, wherein the x-axis of the graph 70 shows the position relative to the hill, the y-axis represents the vehicle speed, and the target speed is represented along the y-axis as TS. Figure 3B A graph 72 shows a second option for modifying the behavior of the vehicle 12 based on the target speed. Figure 3A and Figure 3B In the illustrated embodiment, the x-axis of the graphs 70 , 72 indicates a first position 1 located along the beginning or foot of a mountain, a second position 2 located at the top of the mountain, and a third position 3 located at the bottom of the mountain.

[0039] refer to Figure 2 and Figure 3A In one non-limiting embodiment, the target speed module 62 of the one or more controllers 20 modifies the behavior of the vehicle 12 by reducing the target speed of the vehicle 12 by a predetermined threshold TS', wherein the predetermined threshold TS' ranges from about 5% to about 10% of the target speed TS. Figure 3A In the illustrated embodiment, when the vehicle 12 is at the first position 1 at the bottom of the hill, the actual speed 74 of the vehicle 12 is approximately equal to the target speed TS. The target speed module 62 determines that the vehicle 12 is at the first position at the bottom of the hill based on the sensing data from the plurality of sensing sensors 22. In response to determining that the vehicle 12 is at the first position 1 at the bottom of the hill, the target speed module 62 modifies the target speed TS by a predetermined threshold TS'. Figure 3A As shown, when the vehicle 12 is at the second position 2 at the top of the hill, the actual speed 74 of the vehicle 12 is reduced by a predetermined threshold TS'. In response to determining that the vehicle 12 is at the second position 2 at the top of the hill, the target speed module 62 instructs the vehicle 12 to continue traveling at the target speed TS. Figure 3A As shown, when the vehicle 12 is at the third position 3 at the bottom of the hill, the actual speed 74 of the vehicle 12 is approximately equal to the target speed TS. However, it should be understood that Figure 3A This is merely exemplary in nature, and in some cases, the actual speed 74 of the vehicle 12 is equal to the target speed TS when the vehicle 12 is traveling downhill, or after the vehicle 12 has reached the third position 3 at the bottom of a hill.

[0040] refer to Figure 2 and Figure 3B In another embodiment, the target speed module 62 of the one or more controllers 20 modifies the behavior of the vehicle 12 by maintaining a target speed for the vehicle 12 and allowing the actual speed 74 of the vehicle 12 to deviate from the target speed TS by a predetermined threshold TS′. Figure 3BIn the illustrated embodiment, the vehicle 12 is located at the first position 1 at the bottom of the hill, and the actual speed of the vehicle 12 is approximately equal to the target speed TS. In response to determining that the vehicle 12 is at the first position 1 at the bottom of the hill, the target speed module 62 allows the actual speed 74 of the vehicle 12 to deviate from the target speed TS by a predetermined threshold TS' until the vehicle 12 reaches the third position 3 at the bottom of the hill. Once the vehicle 12 reaches the third position 3 at the bottom of the hill, the target speed module 62 no longer allows the actual speed 74 of the vehicle 12 to deviate from the target speed TS by a predetermined threshold TS'.

[0041] refer to Figure 1 , Figure 2 and Figure 3A In an embodiment, the target speed module 62 of the one or more controllers 20 receives map data via the communication network 28. The map data indicates the distance between the first position 1 at the bottom of the mountain and the second position 2 at the top of the mountain. If the distance between the first position 1 at the bottom of the mountain and the second position 2 at the top of the mountain is known, the target speed module 62 of the one or more controllers 20 will control the actual speed 74 of the vehicle 12 between the first position 1 at the bottom of the mountain and the second position 2 at the top of the mountain. Specifically, Figure 4A-4B Two exemplary methods of reducing the actual speed of the vehicle 12 when the distance between a first location 1 at the bottom of a hill and a second location 2 at the top of a hill is known are shown.

[0042] Figure 4A A graph 80 is shown of one method for controlling the actual speed 74 of the vehicle 12. Figure 2 and Figure 4A In response to determining that the vehicle 12 is at the first position 1 at the bottom of the hill, the target speed module 62 reduces the actual speed 74 of the vehicle 12 by the predetermined threshold TS' as quickly as possible while taking into account factors such as traffic and speed limits before the vehicle 12 reaches the second position 2 at the top of the hill. As an example, the vehicle 12 controls the actual speed 74 according to the graph 80 by coasting downhill with zero applied torque.

[0043] Figure 4B A graph 82 is shown of another method for controlling the actual speed 74 of the vehicle 12. Figure 2 and Figure 4B In response to determining that the vehicle 12 is at the first position 1 at the bottom of the hill, the target speed module 62 steadily decreases the actual speed 74 of the vehicle 12 by the predetermined threshold TS', so that when the vehicle is at the second position 2 at the top of the hill, the actual speed 74 of the vehicle 12 is approximately equal to the predetermined threshold TS'. Figure 4B As shown, the actual speed 74 of the vehicle 12 gradually decreases, so the ramp line representing the actual speed 74 of the vehicle 12 remains constant.

[0044] refer to Figure 2, which describes modifying the behavior of the vehicle 12 based on the output torque of the prime mover 24. It should be understood that the output torque module 64 of the one or more controllers 20 determines the output torque of the prime mover 24 based on multiple driving goals. In one embodiment, the multiple driving goals include ride comfort for one or more occupants of the vehicle 12, the output torque of the prime mover 24 ( Figure 1 ) and the target speed of the vehicle 12 when climbing a hill. The ride comfort of one or more occupants of the vehicle 12 is based on the maximum acceptable propulsion-induced acceleration value and the maximum acceptable turbulence value when the vehicle 12 climbs the hill, wherein the maximum acceptable propulsion-induced acceleration value and the maximum acceptable turbulence value are stored in the memory of the output torque module 64 of the one or more controllers 20.

[0045] In an embodiment, the maximum acceptable acceleration value caused by propulsion and the maximum acceptable jolt value are default values. It should be understood that the default values ​​may vary depending on the type of vehicle, because the occupants of one type of vehicle may have a higher tolerance for jolt and acceleration caused by propulsion when compared to another type of vehicle, because some vehicles are specially designed for activities with higher acceleration and jolt caused by propulsion. For example, the occupants of a sports car tend to have a higher tolerance for acceleration and jolt caused by propulsion when compared to the occupants of a minivan or sedan. Therefore, the maximum acceptable acceleration value caused by propulsion and the maximum acceptable value of a sports car may be higher when compared to a minivan or sedan. Alternatively, in another embodiment, the maximum acceptable acceleration value caused by propulsion and the maximum acceptable jolt value are adjusted based on occupant preferences. For example, in one embodiment, based on occupant preferences, there may be mild, medium and high maximum acceptable acceleration values ​​caused by propulsion and maximum acceptable jolt values, because some people may be able to tolerate more than the maximum acceptable acceleration and jolt values ​​caused by propulsion of others.

[0046] It should be understood that the driving objectives are each expressed as a unique cost function of the output torque of the prime mover 24 of the vehicle 12 and one or more environmental variables. Some examples of environmental variables include, but are not limited to, the measured slope of the road, the weight of the vehicle, the road friction value, the target speed, and the driving style of the individual operating the vehicle 12. For example, the driving maneuvers performed by the human driver of the vehicle 12 when regaining control of the vehicle 12 from automatic or semi-automatic driving, or the driving style is inferred from the way the human driver brakes and accelerates on flat and hilly roads. The output torque module 64 of one or more controllers 20 stores the ride comfort cost function, the energy efficiency cost function, and the target speed cost function in a memory. The ride comfort cost function is expressed as a function of the output torque of the prime mover 24 and one or more environmental variables. The ride comfort cost function corresponds to the difference between the current value of the acceleration caused by the propulsion and the maximum acceptable value of the acceleration caused by the propulsion and the difference between the current value of the bump and the maximum acceptable value of the bump. Similarly, the energy efficiency cost function is expressed as a function of the output torque of the prime mover 24 and one or more environmental variables, wherein the energy efficiency cost function corresponds to the energy consumption of the prime mover 24. The target speed cost function is a function of the output torque of the prime mover 24 and one or more environmental variables and corresponds to the difference between the actual speed and the target speed of the vehicle 12. It should be understood that the output torque of the prime mover 24 is determined based on a weighted cost function, which is a sum of a ride comfort cost function multiplied by a first weight value, an energy efficiency cost function multiplied by a second weight value, and a target speed cost function multiplied by a third weight value, wherein the weighted cost function is represented by the following equation:

[0047] Weighted cost function = w1×(riding comfort cost function)+w2×(energy efficiency cost function)+w3×(target speed cost function),

[0048] Among them, w1, w2 and w3 are the first weight value, the second weight value and the third weight value respectively.

[0049] In one embodiment, the output torque module 64 of one or more controllers 20 determines the output torque of the prime mover 24 by minimizing the weighted cost function. Specifically, the output torque module 64 determines the value of the output torque of the prime mover 24 that minimizes the weighted cost function based on a multi-objective optimization algorithm. Specifically, in one embodiment, the multi-objective optimization is an automatic a priori multi-objective optimization algorithm. Alternatively, in another embodiment, the output torque module 64 of one or more controllers 20 minimizes the weighted cost function based on one or more machine learning algorithms. Specifically, in one embodiment, the output torque module 64 of one or more controllers 20 minimizes the weighted cost function based on a deep neural network.

[0050] refer to Figure 1and Figure 2 In one embodiment, a downhill module 66 of one or more controllers 20 receives sensory data from a plurality of sensory sensors 22 and determines based on the sensory data that the vehicle 12 has passed a second location at the top of a hill and is currently traveling toward a third location at the bottom of the hill. In response to determining that the vehicle 12 is traveling toward the third location at the bottom of the hill, the downhill module 66 modifies the behavior of the vehicle 12 by increasing the target speed by a tolerance window and allowing the vehicle 12 to slide down the hill until the actual speed of the vehicle 12 equals the target speed plus the tolerance window. In one non-limiting embodiment, the tolerance window is approximately 16 kilometers per hour (ten miles per hour). In response to determining that the actual speed of the vehicle 12 equals the target speed plus the tolerance window, the downhill module 66 of the one or more controllers 20 instructs the braking system 26 to apply one or more sets of brakes to the wheels 14 of the vehicle 12 to reduce the actual speed of the vehicle 12. The actual speed of the vehicle 12 may be reduced to the target speed or another speed specified to avoid a collision. It should be understood that allowing the vehicle 12 to slide above the target speed results in gaining momentum in an energy-efficient manner before the vehicle 12 reaches the next uphill.

[0051] Referring generally to the accompanying drawings, the disclosed contextual adaptive cruise control system provides various technical effects and benefits. Specifically, the disclosed contextual adaptive cruise control system provides a method for enhancing occupant comfort and improving energy efficiency by modifying the behavior of the vehicle based on the vehicle's target speed, the output torque of the prime mover, or the target speed and output torque when the vehicle is climbing a hill. Modifying the behavior of the vehicle based on the target speed generally improves the overall energy efficiency of the vehicle, while modifying the behavior of the vehicle based on the output torque of the prime mover generally improves the overall ride comfort of the vehicle occupants by reducing the jolt that occurs when the vehicle climbs a hill. In addition, it should be understood that the contextual adaptive cruise control system adjusts the actual speed of the vehicle when climbing a hill without braking, which in turn improves energy efficiency.

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

[0053] The description of the present disclosure is merely exemplary in nature, and variations that do not depart from the gist of the present disclosure are intended to fall within the scope of the present disclosure. Such variations should not be regarded as departing from the spirit and scope of the present disclosure.

Claims

1. A contextual adaptive cruise control system for a vehicle, wherein: The vehicle includes a prime mover and a plurality of perception sensors, and the contextual adaptive cruise control system includes: one or more controllers in electronic communication with the plurality of sensory sensors and the prime mover, the one or more controllers executing instructions to: receiving perception data from the plurality of perception sensors, wherein the perception data represents an environment surrounding the vehicle, and the environment includes a road on which the vehicle is traveling; determining a longitudinal slope of a road on which the vehicle is currently traveling based on the perception data; comparing the longitudinal slope to a threshold slope value stored in a memory, wherein the threshold slope value indicates that the vehicle is traveling along a hillside; In response to determining that the longitudinal slope is at least equal to the threshold inclination value, determining that the vehicle is climbing a hill; and The contextual adaptive cruise control system is instructed to modify a behavior of the vehicle based on at least one of a target speed for the vehicle and an output torque of a prime mover of the vehicle.

2. The context-adaptive cruise control system according to claim 1, wherein: The one or more controllers execute instructions to: The behavior of the vehicle is modified by reducing a target speed of the vehicle by a predetermined threshold.

3. The context-adaptive cruise control system according to claim 2, wherein: The one or more controllers execute instructions to: determining that the vehicle is at a first position at the bottom of a mountain based on the perception data from the plurality of perception sensors; as well as In response to determining that the vehicle is in the first position at the bottom of the hill, the target speed is reduced by the predetermined threshold.

4. The context-adaptive cruise control system according to claim 3, wherein: The one or more controllers receive map data via a communication network, wherein the map data indicates a distance between a first location at the bottom of the mountain and a second location at the top of the mountain.

5. The context-adaptive cruise control system according to claim 4, wherein: The one or more controllers execute instructions to: A target speed of the vehicle is reduced based on a distance between a first location at the bottom of the hill and a second location at the top of the hill.

6. The context-adaptive cruise control system according to claim 1, wherein: The one or more controllers execute instructions to: The behavior of the vehicle is modified by maintaining a target speed for the vehicle and allowing an actual speed of the vehicle to deviate from the target speed by a predetermined threshold.

7. The context-adaptive cruise control system according to claim 6, wherein: The one or more controllers execute instructions to: determining that the vehicle is at a first position at the bottom of the hill based on the perception data from the plurality of perception sensors; and In response to determining that the vehicle is located at the bottom of the hill, the actual speed of the vehicle is allowed to deviate from the target speed by a predetermined threshold until the vehicle reaches the bottom of the hill.

8. The context-adaptive cruise control system according to claim 6, wherein: The predetermined threshold value ranges from about 5% to about 10% of the target speed.

9. The context-adaptive cruise control system according to claim 1, wherein: The one or more controllers execute instructions to: A behavior of the vehicle is modified based on an output torque of the prime mover, wherein the output torque of the vehicle is determined based on a plurality of driving objectives.

10. The context-adaptive cruise control system according to claim 9, wherein: The plurality of driving objectives include ride comfort for one or more occupants of the vehicle, energy efficiency of the prime mover, and a target speed of the vehicle when climbing a hill.

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