Volvo Car Corporation

Volvo Truck Corporation

Uatc, LLC

Volvo Personvagnar Ab

Volvo Autonomous Solutions Ab

Ford Global Technolgoies, LLC

Polestar Performance Ab

Mats Jonasson

Derong Yang

Leo Laine

Sohini Roy Chowdhury

Minming Zhao

Niklas Ohlsson

Rickard Nilsson

Scott C Poeppel

Tony Gustafsson

Srikar Muppirisetty

Leon Henderson

Anton Albinsson

Bengt Jacobson

Thorsten Helfrich

Mats Rydström

Mattias Brannstrom

Kristoffer Tagesson

Esteban Gelso

Jonas Nilsson

Adithya Arikere

Mattias Brännström

Mats Skold

Bengt Johan Henrik Jacobson

José Vilca

Fredrik Hans Bruzelius

Mikael Thor

Peter Nilsson

Mikael Riikonen

Andreas Lindberg

Martin Idegren

Jonathan Olsson

Axel Ceder

Juliette Torinsson

Frederik Hans Bruzelius

Christoffer Modig

Fredrik Broström

David Silva Montemayor

Juliette Utbult

Jonas Sjöberg

Sachin Janardhanan

Ektor Karyotakis

Mats SKÖLD

Fredrik BROSTRÖM

M Derong Yang

Tim Gordon

Sigvard Zetterström

A computer implemented method for determining a road friction condition associated with at least one wheel on a heavy-duty vehicle includes transmitting a radar signal by at least one polarimetric radar transceiver towards a surface supporting the vehicle, and receiving backscatter from the transmitted radar signal, where the radar signal comprises a first polarization component and a second polarization component different from the first polarization component, processing the received backscatter by a processing device to determine a friction parameter related to the road friction condition of the surface, monitoring the friction parameter over time to detect change in the friction parameter, and in case change in the friction parameter is detected, triggering friction estimation by a secondary physical friction estimation system.

Radar-triggered road friction estimation

The disclosure relates to a method for generating a reference trajectory within a lane for a vehicle. The method comprises receiving at least one vehicle current state parameter describing a current state of the vehicle (S). The current state of the vehicle comprises at least a current position of the vehicle. Furthermore, a destination parameter describing a destination to be reached by the vehicle (S), and at least one route parameter describing a route for reaching the destination (S) are received. Moreover, the method comprises estimating a power loss being caused when traveling from the current position of the vehicle to the destination (S). The reference trajectory within the lane is determined such that it minimizes the power loss and leads to the destination (S). Additionally, a method for operating a vehicle is presented. According to this method, a reference trajectory is generated in accordance with the above method (S) and at least one control signal is provided for controlling a motion of the vehicle along the reference trajectory (S). Furthermore, a data processing apparatus, a vehicle and a computer-readable medium are presented.

Method for generating a reference trajectory within a lane, method for operating a vehicle, data processing apparatus, vehicle, and computer-readable medium

A road friction coefficient of a vehicle is estimated by obtaining substantially contemporaneous values associated with a steering angle for a steered axle of the vehicle, a lateral acceleration, a yaw acceleration, an alignment torque and an axle load on the steered axle; estimating a lateral tire force on the basis of the steering angle, lateral acceleration, and yaw acceleration; deriving a pneumatic trail from the alignment torque and estimated lateral tyre force; and estimating a road friction coefficient from the lateral tire force, the axle load, and the pneumatic trail. In embodiments, the derivation of the road friction coefficient includes evaluating a nonlinear function of the pneumatic trail.

On-board road friction estimation

A computer-implemented method for providing control data for at least one driver support system of a vehicle, or for at least one driving assistance system of the vehicle for supporting driving of the vehicle on a desired path through a curvature planning and steering, can comprise: obtaining suspension data of the vehicle, obtaining vehicle data of the vehicle, obtaining vehicle driving sensor data of the vehicle, determining a steering angle data based on the suspension data, the vehicle data, and the vehicle driving sensor data, and determining the control data for the at least one driver support system or the at least one driving assistance system based on the steering angle data and a curvature vehicle model.

Path planning during steer-by-brake or steer-by-torque vectoring

The present disclosure relates to method for controlling a driving operation of an autonomously controlled vehicle. In particular, a navigation system is controlled to autonomously operate the vehicle in a direction from a position of loss of location to a first upcoming stop position; and to controlling the vehicle to a stand-still operation when the vehicle arrives at the stop position for calibration of a sensor arranged to measure an angular velocity of the vehicle.

Method for controlling a driving operation of an autonomously controlled vehicle

The disclosure relates to a method for controlling a motion of a vehicle. The vehicle can comprise an electric powertrain having at least one drive axle with a left output shaft and a right output shaft, a power assisted steering unit, and a propulsion torque distribution unit. The propulsion torque distribution unit can be configured to allocate wheel torques of different magnitudes to the left output shaft and the right output shaft respectively. The method can comprise receiving a total longitudinal force target value, a total lateral force target value and a total yaw moment target value. The method can further comprise determining a first wheel torque for the left output shaft and a second wheel torque for the right output shaft which minimize a total power consumption of the drive axle and the power assisted steering unit.

Method for controlling a motion of a vehicle, data processing apparatus, computer program, computer-readable storage medium, and vehicle propulsion system

A method for determining a tyre normal force range (F, F) of a tyre force (F) acting on a vehicle (), the method comprising; obtaining (S) suspension data () associated with a suspension system of the vehicle (); obtaining (S) inertial measurement unit, IMU, data () associated with the vehicle (); estimating (S), by a suspension-based estimator () a first tyre normal force range (F, F) based on the suspension data (); estimating (S), by an inertial force-based estimator (), a second tyre normal force range (F, F) based on the IMU data (); and determining (S) the tyre normal force range (F, F) based on the first tyre normal force range (F, F) and on the second tyre normal force range (F, F).

Method for estimating tyre normal force

The invention relates to a method for determining a parameter indicative of a road capability of a road segment () supporting a vehicle (). The vehicle () comprises a sensor () adapted to generate an information package on the basis of signals () reflected from the surface of a portion of the road segment () in front of the vehicle (), as seen in an intended direction of travel of the vehicle (). The vehicle () further comprises a plurality of ground engaging members (). The method comprises: —determining a reference content measure indicative of the information content of an information package supplied by the sensor () at a reference time instant (T); —comparing the reference content measure to a previous content measure indicative of the information content of an information package supplied by the sensor () at a previous time instant (T), the previous time instant (T) occurring before the reference time instant (T); —upon detecting that a difference between the reference content measure and the previous content measure is outside a predetermined tolerance range, allowing the execution of a determination procedure for determining the parameter indicative of the road capability of the road segment () supporting the vehicle (); —upon detecting that the difference between the reference content measure and the previous content measure is within the predetermined tolerance range, not allowing the execution of the determination procedure, and —wherein the determination procedure comprises modifying the operation of one or more of the ground engaging members ().

Method and a control unit for determining a parameter indicative of a road capability of a road segment supporting a vehicle

The invention relates to a method for determining a parameter indicative of a road capability of a road segment supporting a vehicle. The vehicle comprises a plurality of ground engaging members. The method comprises: for each ground engaging member in a sub-set of the plurality of ground engaging members, setting a contact force between the ground engaging member and the road segment; determining a target global load vector to be imparted to the vehicle, the target global load vector comprising at least a vertical load and an inclining moment, determining contact forces for the ground engaging members of the plurality of ground engaging members which are not in the sub-set such that the contact forces for the plurality of ground engaging members together result in a resulting global load vector, a difference measure between the resulting global load vector and the target global load vector being equal to or lower than a predetermined difference measure threshold, applying the contact force to each ground engaging member of the plurality of ground engaging members, for at least one ground engaging member in the sub-set, determining a parameter indicative of the road capability of the road segment associated with the ground engaging member.

A system for estimating an articulation angle of a vehicle combination comprises a motion sensor for sensing one or more linear and/or angular motion quantities of the vehicle combination and a dynamics-based estimator configured to estimate state variables, including the articulation angle on the basis of the sensed motion quantities, wherein the dynamics-based estimator is dependent on one or more masses and moments of inertia of the vehicle combination.

Dynamics-based articulation angle estimator for a vehicle combination

Systems and methods are provided for generating data indicative of a friction associated with a driving surface, and for using the friction data in association with one or more vehicles. In one example, a computing system can detect a stop associated with a vehicle and initiate a steering action of the vehicle during the stop. The steering action is associated with movement of at least one tire of the vehicle relative to a driving surface. The computing system can obtain operational data associated with the steering action during the stop of the vehicle. The computing system can determine a friction associated with the driving surface based at least in part on the operational data associated with the steering action. The computing system can generate data indicative of the friction associated with the driving surface.

Driving surface friction estimations using vehicle steering

The present invention relates to a control unit for determining a value indicative of a load bearing capability of a ground segment supporting a vehicle. The control unit is configured to issue a control signal to the vehicle to thereby impart a motion change of the vehicle, and receive response information from the vehicle indicative of the vehicle's response to the imparted motion change. The control unit is further configured to, based on the response information, determine a vertical position change of at least one wheel of the vehicle, and based on the determined vertical position change and the imparted motion change, determine the value indicative of the load bearing capability of the ground segment.

Control unit and a method for determining a value indicative of a load bearing capability of a ground segment supporting a vehicle

A system and method for utilizing aggregated weather data (AWD) for deriving road surface condition (RSC) estimates. This system and method supplements road friction estimates (RFEs) made at the vehicle level with AWD in the cloud to form the RSC estimates, which are then transmitted to the vehicles such that more accurate RFEs can be made locally, and so on. Conventional RFE physics-based models are replaced with enhanced RFE trained machine learning (ML) models accordingly. Global RSC estimates are derived for each geographical region using weather and location constraints. Thus, improved autonomous driving and driver assist functions may be implemented, better driver warnings may be provided, and safer road trips may be planned in advance based on a thorough analysis of the drivable conditions.

System and method for utilizing aggregated weather data for road surface condition and road friction estimates

The disclosure relates to a method to control torque distribution among a plurality of electric machines connected to at least one front wheel and at least one rear wheel of a vehicle during operation, comprising: acquiring the total torque requested; obtaining the most energy efficient torque distribution mode by using a loss model or loss map; evaluating the actual driving situation; determining if a mode switch is allowed depending on the actual driving situation; switching the torque distribution mode, if allowed; and preventing a mode switch, if not allowed.

Method and system to control torque distribution

The present disclosure relates to a steering control system for a vehicle, a vehicle comprising such a steering control system and a method for operating such a steering control system for a vehicle. The steering control system comprises a frequency filter unit, a first control unit, and a second control unit. The frequency filter unit comprises a high pass filter and a low pass filter. The frequency filter unit is configured to receive a request for a steering angle and filter the request into a low-pass filtered request and a high-pass filtered request. The first control unit is configured to determine a first controlling torque based on the low-pass filtered request the second control unit is configured to determine a second controlling torque based on the high-pass filtered request. The first control unit is different of the second control unit.

Steering control system

Growing community of inventors

Partille, Sweden

Mats Jonasson