792 results about "Cruise control" patented technology

The invention relates to the technical field of vehicle cruise control, and discloses a neural network driven vehicle adaptive cruise control method. Real-time driving data are collected through a multi-modal sensor, spatial-temporal feature fusion is carried out through a multi-layer convolutional neural network to generate dynamic environment sensing data, and a pre-trained adaptive decision model is input to obtain driving strategy parameters. And constructing a mixed integer programming model on the basis, globally planning a cruise path by adopting an incremental branch and bound algorithm integrating a dynamic relaxation threshold and a heuristic pruning strategy, and outputting optimal cruise trajectory data. A hierarchical control framework comprising a planning layer, a coordination layer and an execution layer is constructed, the planning layer generates a global trajectory sequence, the coordination layer dynamically corrects a local trajectory, and the execution layer achieves vehicle longitudinal acceleration and transverse steering angle tracking based on a robust sliding mode control algorithm and outputs a vehicle control instruction to complete self-adaptive cruise control. And the cruise control performance, safety and stability of the vehicle in a complex environment are improved.

The present application relates to the technical field of autonomous driving functions, and in particular to a control method and device integrating predictive cruise and lane changing decision-making. The method comprises: receiving the accelerations, speeds and positions of a controlled autonomous driving vehicle and surrounding traffic vehicles at a current moment so as to construct an IDM microscopic following model to predict surrounding traffic vehicle states in a preset future long time domain; on the basis of the surrounding traffic vehicle states in the preset future long time domain, constructing an optimization cost function, so as to plan a lane keeping strategy or lane changing strategy; on the basis of the lane keeping strategy or lane changing strategy, using a quintic polynomial to solve for a reference path; on the basis of the reference path, establishing an optimal control problem cost function for continuous intersection predictive cruise control, so as to solve for the optimal cruise speed within a traveling lane; and sending the reference path and the optimal cruise speed within the traveling lane to the controlled autonomous driving vehicle for control. Thus, the problems that existing lane changing decision-making only considers longitudinal motion and fails to pay attention to a development trend of the surrounding environment, possible dangers and the like are solved.

The invention discloses an intelligent automobile longitudinal driving assistance system based on driving characteristics. The intelligent automobile longitudinal driving assistance system comprises a driver state and environment sensing module, a driver characteristic real-time identification module, an intelligent decision-making and mode switching module and a style self-adaption longitudinal control module. The driver state and environment perception module analyzes environment information and driving behavior characteristics by constructing an extended intelligent driver model, and defines acceleration deviation to perform driving style clustering. And the driver feature real-time identification module deploys the BP neural network model in an online system to realize real-time identification of the driving style. The intelligent decision-making and mode switching module intelligently assesses risks in combination with driving styles and environment information, and dynamically switches four modes of cruise control, car following, early warning and emergency braking. And the style self-adaptive longitudinal control module adaptively adjusts a control strategy according to the driving style and the expected acceleration, and converts the expected acceleration into driving torque or braking pressure through a dynamic weight mechanism, so that personalized longitudinal control is realized.

The invention relates to a multi-target adaptive cruise control method based on fuzzy model predictive control. The multi-target adaptive cruise control method comprises the following steps: collecting real-time operation data of a vehicle; inputting the real-time operation data of the vehicle into the improved vehicle longitudinal dynamic model, and predicting the future motion state of the vehicle; on the basis of the output of the vehicle longitudinal dynamics model, a feedback correction ACC system vehicle following prediction model is used for predicting and correcting the vehicle following behavior in real time, and a vehicle following control strategy is dynamically adjusted; dynamically adjusting the weight of a target function under model prediction control by adopting a fuzzy variable weight adjustment strategy; and performing model prediction control according to the target function and considering multiple constraint conditions, generating accurate acceleration and deceleration control parameters, acting on the controlled vehicle, and realizing multi-target adaptive cruise control. Compared with the prior art, safe, energy-saving and efficient self-adaptive vehicle following control can be achieved in a complex and changeable traffic environment, and an effective technical scheme is provided for improving the response speed and adaptability of an intelligent cruise control system.

The invention discloses an intelligent automobile cooperative cruise safety control method under Dos attacks and physical faults, and relates to automobile intelligent safety and automatic driving. A hierarchical control framework is adopted and comprises an observer layer and a tracking layer. The method comprises the following steps: establishing a vehicle longitudinal dynamics model and a DoS attack model for DoS attack in a V2X communication network and the problems of sensor and actuator faults and parameter isomerism of a vehicle; a completely distributed self-adaptive preset time observer based on event triggering is designed for each following vehicle in the observer layer, and rapid and accurate estimation of the state of the pilot vehicle is achieved; the method comprises the following steps: constructing an augmentation system at a tracking layer, designing a distributed intermediate observer, carrying out online estimation and compensation on faults of a sensor and an actuator, designing a distributed active fault-tolerant controller based on a fault estimation value and a pilot vehicle state estimation value, and calculating a wheel driving torque to realize safe cruise control. Multiple threats of coexistence of network attacks and physical faults are effectively handled, and the stability and safety of the cooperative cruise system are ensured.

The invention relates to the technical field of underwater desilting robot cruise control, in particular to an underwater desilting robot intelligent cruise control method based on environmental perception, and the method comprises the steps: determining a track deviation distance by measuring the position distance of an underwater desilting robot between each moment and all moments within a preset duration before; and determining a second gain adjustment coefficient based on the variation trend of the track deviation distance at all moments within a preset time period before the current moment, and determining a gain adjustment coefficient in combination with the first gain adjustment coefficient so as to optimize the gain coefficient of the sliding mode controller and control the attitude of the underwater dredging robot. According to the method, the problem of hysteresis course errors of the underwater dredging robot caused by fixed gain in traditional sliding mode control is solved, gain adaptive optimization is realized by dynamically fusing multi-source trend data, and the dredging efficiency of the underwater dredging robot is improved.

The invention discloses a commercial vehicle team cruise control method and system, computer equipment and a storage medium, and relates to the technical field of automatic driving and vehicle infrastructure cooperative control, and the method comprises the steps: carrying out the vehicle role interaction of a team vehicle according to a cooperative relation and a vehicle role interaction logic; establishing a surrounding environment potential field model, and describing an interaction relationship between vehicles inside and outside the motorcade; calculating the longitudinal and transverse potential fields of the vehicles of the fleet, and controlling the distance between the vehicles and the safe distance; a model prediction controller for team cruise is constructed by considering the target speed and the environmental influence; and the safety, speed and control constraints of vehicle movement are set, and the driving performance is optimized. The stability of formation control is enhanced, the formation requirements of complex scenes are met, the real-time dynamic control capability is improved, and the formation energy efficiency is optimized.

A control system for a vehicle is provided, the control system comprising one or more controllers, the control system configured to receive an acceleration or deceleration demand signal from an automatic cruise control system, and request modification of one or more parameters of the vehicle suspension system in response to the received acceleration or deceleration demand signal. In this way, the vehicle suspension system may be modified in preparation for an acceleration or deceleration of the vehicle, to inhibit or at least reduce the occupants of the vehicle experiencing an undesirable pitching movement of the vehicle during the course of the change in speed of the vehicle.

The invention discloses a predictive cruise control method and system for a commercial vehicle. The method comprises the steps that road gradient information provided by a high-precision map and a target cruise vehicle speed corrected by a deep belief network driving style model are obtained to serve as input parameters; according to the rotating speed and the torque of the engine, a weighted moving average algorithm is adopted to carry out averaging processing on the power value within a short period of time, and the current engine power is generated; on the basis of an automobile power balance equation, according to the current position and the slope value of the front road, the driving power requirement of the next slope section is predicted; and in combination with the efficient output power interval of the engine, the recommended gear and the optimal accelerator opening degree of the next slope section are generated according to different power demand conditions. Therefore, according to the predictive cruise control method for the commercial vehicle, the gears and the accelerator can be adjusted in a self-adaptive mode according to the road gradient and the driving habit, the driving efficiency and the fuel economy are improved, and the individuation of the driving experience is enhanced.

The present invention refers to a method for performing pre-boost acceleration prior to overtaking a preceding third party vehicle (34) driving on a road (26) with multiple driving lanes (28, 30, 32) for driving in a forward driving direction (34) with an ego vehicle (10), wherein the ego vehicle (10) is following the preceding third party vehicle (36) on an ego lane (28) with an initial distance (d) to the ego vehicle (10), comprising the steps of detecting third party vehicles (38) on the neighboring driving lane (30), determining an acceleration profile with an acceleration phase for accelerating the ego vehicle (10) compared to the preceding third party vehicle (36) on the ego lane (28) while following the preceding third party vehicle (36), wherein an acceleration of the acceleration phase is determined based on the detection of third party vehicles (38) on the neighboring driving lane (30), a maximum acceleration value and a maximum change of acceleration, receiving a trigger for performing the pre-boost acceleration prior to overtaking the preceding third party vehicle (36) driving on the ego lane (28) using the neighboring driving lane (30), and performing the pre-boost acceleration according to the determined acceleration profile. The present invention also refers to a driving support system (12) for use in an ego vehicle (10) for following a preceding third party vehicle (36), in particular for performing adaptive cruise control, when driving on a road (26) with multiple driving lanes (28, 30, 32) for driving in a forward driving direction (34) of the ego vehicle (10), wherein the driving support system (12) is adapted to perform the method for pre-boost acceleration prior to overtaking a preceding third party vehicle (34) according to the above method.

An electrified vehicle includes a human-machine interface to enable a towed vehicle mode to enable electric pumps to lubricate and / or cool vehicle components and to disable driver assistance features while the electrified vehicle is being towed by another vehicle. The electrified vehicle includes a drivetrain having an electric machine configured to provide propulsive torque to vehicle wheels, a high-voltage traction battery selectively connected to the electric machine, a battery powered fluid pump configured to pump fluid to the drivetrain, and a controller programmed to, after receiving a signal enabling towed vehicle operation of the electrified vehicle, control operation of the battery powered fluid pump while the electrified vehicle is being towed. The controller may disable one or more driver assistance features and alerts such as automatic emergency braking, automatic shifting of the drivetrain, automatic parking brake operation, automatic headlights, automatic steering, cruise control, parking assistance, and external object distance detection.

The invention relates to the technical field of automatic driving trajectory planning control, in particular to an optimal inter-vehicle time interval control method for cooperative cruise of a truck under a communication delay condition. According to the method, a layered control framework of truck cooperative cruise control is designed, and a vehicle safety inter-vehicle time interval model, a communication delay model and a queue collision safety model are constructed; the inter-vehicle time interval, the communication delay coefficient and the safety coefficient are quantified into space particles, optimization is carried out based on a particle swarm algorithm, and the optimal inter-vehicle time interval on the basis of guaranteeing the queue safety and the fuel economy is obtained; designing a longitudinal model predictive control (MPC) expected acceleration decision controller of truck cooperative cruise by considering multi-target constraints of safety and fuel economy in a vehicle following process to obtain an expected acceleration; and a load change-considered feedforward and active-disturbance-rejection control brake driving error compensation model is established, so that the anti-jamming capability of the model is enhanced, and the actual acceleration of the queue truck accurately follows the expected acceleration under the load change condition.

The present disclosure generally relates to managing cruise control settings. A cruise control indicator is displayed at a location that corresponds to a cruise control speed concurrently with a textual indication of the cruise control speed. In response to receiving an input to change the cruise control speed, the cruise control indicator and the textual indication of the cruise control speed move along at least a portion of the path corresponding to speed.

The invention discloses an unmanned ship automatic cruise control system and a control method thereof, and particularly relates to the field of unmanned ship automatic cruise, and the unmanned ship automatic cruise control system comprises a cruise area division module, a cruise data acquisition module, a cruise data analysis module and a control module. According to the method, a self-adaptive control system is constructed through a four-dimensional linkage mechanism of the course deviation correction value, the environmental disturbance force, the control efficiency index and the path tracking deviation rate, a water flow and wind power square term modeling and steerage coefficient dynamic conversion mechanism is adopted, the transient disturbance suppression effect is remarkably improved, and the control efficiency is improved. By monitoring the nonlinear relation between the product of the accelerator and the rudder angle and the attitude of the ship body in real time, dynamically constraining the output of the actuator, avoiding attitude instability and ensuring the safety under the four-level sea condition, the system improves the course correction weight at the end point stage and starts waypoint preview and smoothing coefficient adjustment at the long leg based on the conjoint analysis of the deviation ratio threshold and the residual distance, and the ship body attitude is optimized. And the full-voyage tracking precision is optimized.

The invention relates to a vehicle cruise control method and device, vehicle-mounted computing equipment and a vehicle, relates to the technical field of intelligent driving, and can improve the driving safety and stability of the vehicle under ice and snow weather conditions. The method comprises the following steps: predicting a future road surface state of a driving road surface of a vehicle according to meteorological data and road surface state information; under the condition that the future road surface state is the ice and snow road surface state, actual friction information of the driving road surface is obtained; determining a target driving state of the vehicle according to the actual friction information and a vehicle cruise condition, controlling the driving of the vehicle according to the target driving state, and obtaining an actual driving state in the driving process; and according to the actual driving state and a braking compensation strategy corresponding to the ice and snow pavement state, braking control information is determined, and driving of the vehicle is adjusted according to the braking control information.

The invention discloses a predictive cruise control method and device, a storage medium and a vehicle, and the method comprises the steps: obtaining the traffic environment information of a road where the vehicle is located, and carrying out the road reconstruction of the road according to the traffic environment information, and obtaining at least one road section; determining the driving feature classification of the target driver according to the driving feature data of the vehicle driven by the target driver; determining influence coefficients corresponding to different influence indexes in a cruise control algorithm based on driving feature classification; the minimum cost of a cruise control algorithm is determined based on the preset vehicle speed range, the gear range and the influence coefficients corresponding to the different influence indexes; and determining a target vehicle speed and a target gear of each road section based on the minimum cost, and performing predictive cruise control on the vehicle based on the target vehicle speed and the target gear. According to the method, predictive cruise control of the fuel oil heavy commercial vehicle in a high-speed scene can be achieved, and the purposes of reducing fuel oil consumption, relieving driving fatigue of a driver and improving driving experience are achieved.

The present application provides a vehicle cruise control method and system, a medium, an electronic device, and in-vehicle infotainment. The vehicle cruise control method comprises: calculating a speed deviation on the basis of a preset speed of a vehicle and an ego-vehicle speed; on the basis of a speed deviation range where the speed deviation is located, selecting variable control parameters, and performing segmented control on a requested acceleration, wherein the speed deviation range is a range obtained by division on the basis of the magnitude of speed deviation, and includes a negative large deviation zone, a negative small deviation zone, a positive small deviation zone, and a positive large deviation zone; and calculating a PID control quantity of vehicle cruise control on the basis of the variable control parameters and the speed deviation. The present application can improve the control precision of cruise control, and reduce the speed fluctuation generated in the control process.

The invention discloses a vehicle cruise control method and system based on traffic prediction, and relates to the technical field of vehicle intelligent control. The method comprises the following steps: preprocessing vehicle state data and driving environment data by utilizing edge calculation; performing information fusion and mapping on the preprocessed data by using a cloud control platform to obtain a road traffic condition simulation result, and generating an optimal vehicle driving strategy according to the road traffic condition simulation result by using reinforcement learning; a hierarchical control strategy is constructed by considering traffic constraints and economic vehicle speed factors, and the vehicle is dynamically regulated and controlled; and the real-time driving state of the vehicle is fed back to the cloud control platform, and parameter optimization is carried out on the optimal driving strategy of the vehicle. According to the invention, traffic information is efficiently mined and fused by using the powerful information processing and fusion capability of the cloud control platform, predictive cruise control of the vehicle is realized in combination with a vehicle control optimization algorithm, and the energy-saving effect and the driving efficiency of the vehicle in a complex traffic environment are improved.

A method for selecting a following target when changing lanes during adaptive cruise control, comprising: receiving signals for detecting front objects in the own lane and the adjacent lane that are located in front of the own vehicle and judging whether the respective front objects are vehicles; detecting whether a lane change of the own vehicle is occurring by determining the degree of lateral deviation of the own vehicle from the own lane;Detecting the distance between the front objects of the own vehicle in the own lane and the adjacent lane into which the own vehicle will change lanes and the own vehicle, as well as the coincidence rate between the own trajectory and the front objects of the own vehicle in the own lane when the own vehicle changes lanes, and selecting a front object in the own lane or the adjacent lane as a provisional follow-up target; if it is determined that the provisional follow-up target is a vehicle, determining the provisional follow-up target as the final follow-up target;Repeating the above steps at fixed time intervals until the host vehicle has completely changed lanes into the adjacent lane. A system for selecting a follow-up destination when changing lanes during adaptive cruise control, comprising a sensor, a processor, and an adaptive cruise control module, the processor configured to execute the method described above.

The invention discloses a car following control method and a related product. According to the scheme, multi-source data are acquired, and the multi-source data are fused to obtain a fusion result; based on the fusion result, performing multi-modal trajectory prediction on the driving behavior of the preceding vehicle to obtain a prediction result of the driving behavior of the preceding vehicle; the multi-modal trajectory prediction comprises longitudinal motion prediction and transverse motion prediction; quantifying a car following risk by using a multi-dimensional risk index to obtain a risk level; constructing a multi-target cost function based on the fusion result, the front vehicle driving behavior prediction result and a control vector, and solving the multi-target cost function by using a preset constraint condition to obtain an initial control parameter of the vehicle; and on the basis of the risk level, initial control parameters of the vehicle are adjusted, and target control parameters of the vehicle are obtained. Compared with the problem of response lag in adaptive cruise control in the prior art, the adaptive cruise control method has obvious advantages.

The invention discloses a predictive cruise control method, device and equipment and a storage medium, relates to the technical field of cruise control, and discloses a predictive cruise control method which comprises the steps that current gradient type information, target gradient storage information and a cruise set vehicle speed are obtained; determining a target cruise control strategy according to the current gradient type information; when the target cruise control strategy is a slope rushing control strategy or a downhill control strategy, a target vehicle speed deviation value and a deviation starting point are determined based on the target cruise control strategy according to the target slope storage information and the cruise set vehicle speed, and when the vehicle reaches the deviation starting point, the target vehicle speed deviation value and the deviation starting point are determined; and predictive cruise control is carried out on the vehicle based on the target vehicle speed deviation value and the cruise set vehicle speed, accurate control over the vehicle speed in the slope rushing or downhill process is achieved, and driving comfort and safety are improved.

The invention discloses a vehicle cruise control method, device and equipment, a medium and a product. The method comprises the following steps: acquiring a target planning state of each planning position point in a slope road section, wherein the target planning state comprises a target planning speed and a target planning gear; determining a current planning request torque according to the target planning state of the current planning position point, the target planning speed of the next planning position point, the slope value of the next planning position point and a preset distance step length; performing intention recognition based on the current planning request torque and a preset torque interval to obtain a current intention, and performing cruise control on the vehicle according to the current intention; the current intention is driving or braking. According to the technical scheme, it is ensured that the actual control process of the vehicle speed conforms to the planning intention corresponding to each planning position point, and energy consumption in the actual driving process of the vehicle is reduced.

The invention discloses a commercial vehicle cruise control method and system giving consideration to physiological strain and energy conservation. The method comprises the following steps that a human body physiological strain index is constructed, a vehicle oil consumption and energy conservation index is constructed, an optimal cruise speed planning model is established, and the vehicle oil consumption and energy conservation index and passing time are comprehensively considered to form an overall reward function; a reinforcement learning algorithm is introduced for solving, and the optimal cruise speed within the predicted duration is obtained; constructing a vehicle-seat-human body system longitudinal and vertical coupling dynamic model, and calculating a human body physiological strain index under the optimal cruise speed; vehicle state constraints and optimal cruise speed sequence tracking constraints are coded as control constraints, and a longitudinal model prediction control strategy is formed based on a human body physiological strain index, a vehicle fuel consumption energy-saving index and tracking deviation; and a pitching regulation and control mechanism is added to realize vertical ceiling hybrid control, and the vehicle suspension is regulated and controlled. The vehicle cruising performance can be improved, and collaborative optimization of human body physiological strain and vehicle energy saving is achieved.

The invention discloses a thermal power generating unit transition peak regulation intelligent cruise control method based on an intelligent control algorithm, and relates to the technical field of intelligent control algorithms, and the method comprises the steps: constructing a distributed sensor network through deploying distributed sensors at all key positions of a thermal power generating unit, and obtaining the operation parameters of the thermal power generating unit in real time; external data are introduced and integrated, and short-term load demand prediction is generated according to an intelligent control algorithm; constructing a dynamic optimization function by combining a power grid dispatching instruction and a load prediction result and by taking the minimum coal consumption, the shortest peak regulation response time and the minimum equipment life loss as targets; adopting a hybrid algorithm of model predictive control and reinforcement learning to obtain an optimal control instruction; the control instruction is transmitted to a boiler combustion system and a steam turbine speed regulating system, and the fuel amount, the water supply amount and the valve opening degree are regulated; and dynamically adjusting model parameters and fuzzy rule weights of model prediction control through reinforcement learning to realize adaptive control of the thermal power generating unit.

An unmanned aerial vehicle autonomous electric power facility inspection method based on three-dimensional semantic driving relates to the technical field of unmanned aerial vehicle cruise control, and comprises the following steps: constructing a three-dimensional semantic representation containing key components under a unified world coordinate system, and generating a three-dimensional semantic point cloud with component category labels in real time in combination with airborne visual perception; and the inspection requirements in the operation and maintenance regulation are analyzed into an ordered component-level task sequence, and on the basis, the unmanned aerial vehicle autonomously plans an observation pose and a local flight path according to the three-dimensional semantic distribution of the target component, so that the adaptive approaching and coverage of the key component are realized. According to the invention, operation and maintenance semantics can be precisely followed, fine-grained sensing of key parts is realized, an inspection path is enabled to be close to a concern point, environment adaptability is realized, the inspection efficiency is effectively improved, the cost is reduced, and the problems that current electric power facility unmanned aerial vehicle inspection depends on a preset mode, the operation and maintenance semantics are difficult to meet, and key part sensing and adaptability are lacked are solved. And the inspection tour effect is not good enough.

According to the excavator constant-speed cruise control device and method, a user presses a rocker switch to the position corresponding to the cruise direction, the rocker switch gives an electric signal corresponding to the cruise direction to a controller, the user turns on the cruise switch in the controller, the controller gives an electric signal corresponding to the opening of an oil outlet of a proportional electromagnetic valve, and the proportional electromagnetic valve is switched on. The proportional electromagnetic valve receives electric signals and outputs hydraulic oil, the hydraulic oil enters the shuttle valve and is injected into a pilot control oil way in the corresponding direction, constant-speed cruising is achieved, the cruising speed can be steplessly adjusted between zero and the maximum walking speed, walking is stable, the working intensity of a driver is reduced, and the service life of the driver is prolonged. The manual walking system and the cruise system are independent of each other and do not affect each other, safety and stability are improved, normal manual operation of walking of the excavator is not affected, installation of an existing excavator is facilitated, damage is small, and good practicability is achieved.

The invention relates to a method for operating a driver assistance system (3) in a vehicle (1), wherein - an adaptive cruise control of the vehicle (1) is carried out with the driver assistance system (3) depending on a vehicle (5) driving ahead of the vehicle (1), comprising: - Providing at least one piece of environmental information of an environmental area (7) located in front of the preceding vehicle (5) to an electronic evaluation unit (8) of the driver assistance system (3), - analyzing at least one environmental situation (17) in the environmental area (7) in front of the preceding vehicle (5) on the basis of the at least one item of environmental information by the electronic evaluation unit (8), - predicting a potential future driving behavior (19) of the preceding vehicle (5) on the basis of the analyzed at least one environmental situation (17) by the electronic evaluation unit (8), - Adapting the adaptive cruise control of the vehicle (1) based on the potential future driving behavior (19) of the vehicle (1) driving ahead. Furthermore, the invention relates to an electronic driver assistance system (3) and a vehicle (1).

Provided is a driver assistance system (DAS) including: a storage configured to store driver tendency data including an amount of decrease in acceleration when a vehicle approaches a specific section, in a state in which an adaptive cruise control (ACC) of the vehicle is deactivated; and a controller including at least one processor configured to process the driver tendency data, wherein the controller is configured to, upon the vehicle re-entering the specific section during travel of the vehicle with the ACC, control the vehicle to perform one of acceleration control and deceleration control based on the driver tendency data.

A road driving optimization method and system having a vehicle sensor configured to collect external sensor data, vehicle status data, and communication data; a control module configured to analyze the collected data to detect a trigger event, a state of the target vehicle, an achievable speed range, and an instantaneous traction; a decoupling estimator module configured to analyze the trigger event, a state of the target vehicle, an achievable speed range, and the personalized driver profile to determine a maximum free flow distance and an arrival speed at the free flow distance; a machine learning model configured to predict a speed profile of the host vehicle during approaching the trigger event based on the determined free flow distance, the determined arrival speed at the determined free flow distance, and the instantaneous traction; and a cruise control system configured to implement the predicted speed profile.

Systems, methods, and apparatus related to sensor data processing for a vehicle to improve operation when sunlight or other bright light enters a sensor of the vehicle. In one approach, adjustable filtering is configured for a sensor of a vehicle. In one example, an optical filter is positioned on the path of light that reaches an image sensor of a camera. For example, the filtering improves ability to stay in adaptive cruise control when driving into direct sunlight at sunset. The optical filters can have controllable properties such as polarization. In one example, a controller of the vehicle is configured to automatically adjust the properties of the optical filter to improve image quality to improve object recognition. In another example, a camera is configured with composite vision that uses sensors in different radiation spectrums (e.g., visible light, and infrared light). The composite vision can provide enhanced vision capability for an autonomous vehicle that is driving in the direction of the sun.