A METHOD FOR DETERMINING ROAD CONDITIONS

Abstract

The present disclosure relates to a method for determining road conditions, where the road conditions are arranged to be vehicle independent to thereby improve the usability to any form of vehicles to operate along a segment of a road. The present disclosure also relates to a corresponding control arrangement and to a computer program product.

Claims

1. A computer implemented method adapted to determine road conditions for a road, the road comprising at least a first road segment, wherein the method comprises the steps of: determining, by a control unit arranged onboard a first vehicle, a road resistance value for the first road segment where the first vehicle is currently travelling, wherein the road resistance value is dependent on a current operation of the first vehicle at the first road segment and at least one of a weight of the first vehicle, a tire selection for the first vehicle, or a temperature at or a length of the first road segment, providing, by the onboard control unit, a collection of vehicle data to a server arranged in networked communication with the control unit, the collection of vehicle data comprising the road resistance value for the first road segment, operational data for the first vehicle for the first road segment and sensitivity parameters for the first vehicle, and estimating, at the server, a vehicle independent road condition for the first segment based on a plurality of corresponding collections of vehicle data for the first road segment provided to the server from a plurality of different vehicles including the first vehicle.

2. The method according to claim 1, further comprising the steps of: distributing, using the server, the vehicle independent road condition for the first segment to a second vehicle using the networked connection, the second vehicle travelling along the road, and estimating, onboard the second vehicle, an energy consumption for the second vehicle when travelling at the first segment based on the vehicle independent road condition for the first segment and a current operation of the second vehicle at the first road segment.

3. The method according to claim 2, further comprising the step of: estimating, onboard the second vehicle, a total energy consumption for the second vehicle when travelling along the road.

4. The method according to claim 3, wherein the total energy consumption is further dependent on a predicted speed for the first road segment.

5. (canceled)

6. The method according to claim 1, wherein the sensitivity parameters for the first vehicle are related to aerodynamic properties for the first vehicle.

7. The method according to claim 1, wherein the step of estimating the vehicle independent road condition for the first segment is further based on a weather report for the road received at the server.

8. The method according to claim 1, further comprising the step of: estimating an operational range for the second vehicle based on the total energy consumption for the second vehicle.

9. A control arrangement adapted to determine road conditions for a road, the road comprising at least a first road segments, the control arrangement comprises a server arranged in networked communication with a control unit arranged onboard a first vehicle, wherein the control arrangement is adapted to: determine, by the control unit, a road resistance value for the first road segment where the first vehicle is currently travelling, wherein the road resistance value is dependent on a current operation of the first vehicle at the first road segment and at least one of a weight of the first vehicle, a tire selection for the first vehicle, or a temperature at or a length of the first road segment, provide, by the onboard control unit, a collection of vehicle data to the server, the collection of vehicle data comprising the road resistance value for the first road segment, operational data for the first vehicle for the first road segment and sensitivity parameters for the first vehicle, and estimate, at the server, a vehicle independent road condition for the first segment based on a plurality of corresponding collections of vehicle data for the first road segment provided to the server from a plurality of different vehicles including the first vehicle.

10. The control arrangement according to claim 9, further adapted to: distribute, using the server, the vehicle independent road condition for the first segment to a second vehicle using the networked connection, the second vehicle travelling along the road, and estimate, onboard the second vehicle, an energy consumption for the second vehicle when travelling at the first segment based on the current road condition for the first segment and a current operation of the second vehicle at the first road segment.

11. The control arrangement according to claim 10, further adapted to: estimate, onboard the second vehicle, a total energy consumption for the second vehicle when travelling along the road.

12. The control arrangement according to claim 10, wherein the total energy consumption is further dependent on a predicted speed for the first road segment.

13. (canceled)

14. The control arrangement according to claim 9, wherein the sensitivity parameters for the first vehicle are related to aerodynamic properties for the first vehicle.

15. The control arrangement according to claim 9, wherein the step of estimating the vehicle independent road condition for the first segment is further based on a weather report for the road received at the server.

16. The control arrangement according to claim 11, further adapted to: estimate an operational range for the second vehicle based on the total energy consumption for the second vehicle.

17. The control arrangement according to claim 9, further comprising the first and the second vehicle.

18. The control arrangement according to claim 9, wherein at least one of the first and the second vehicle is a truck, a bus or a car.

19. The control arrangement according to claim 18, wherein the truck is autonomously operated.

20. A computer program product comprising a non-transitory computer readable medium having stored thereon computer program means for operating a control arrangement adapted to determine road conditions for a road, the road comprising at least a first road segments, the control arrangement comprises a server arranged in networked communication with a control unit arranged onboard a first vehicle, wherein the computer program product comprises: code for determining, by the onboard control unit, a road resistance value for the first road segment where the first vehicle is currently travelling, wherein the road resistance value is dependent on a current operation of the first vehicle at the first road segment and at least one of a weight of the first vehicle, a tire selection for the first vehicle, or a temperature at or a length of the first road segment, code for providing, by the onboard control unit, a collection of vehicle data to a server arranged in networked communication with the control unit, the collection of vehicle data comprising the road resistance value for the first road segment, operational data for the first vehicle for the first road segment and sensitivity parameters for the first vehicle, and code for estimating, at the server, a vehicle independent road condition for the first segment based on a plurality of corresponding collections of vehicle data for the first road segment provided to the server from a plurality of different vehicles including the first vehicle.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0023] With reference to the appended drawings, below follows a more detailed description of embodiments of the present disclosure cited as examples.

[0024] In the drawings:

[0025] FIG. 1A illustrates a truck, 1B a bus and 1C a car that may be used in conjunction with the control scheme according to the present disclosure;

[0026] FIG. 2 illustrates a conceptual control arrangement in accordance to a currently preferred embodiment of the present disclosure;

[0027] FIG. 3 exemplifies a plurality of vehicles operating along a road comprising a plurality of road segments; and

[0028] FIG. 4 illustrates the processing steps for performing the method according to the present disclosure.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE INVENTION

[0029] The present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which currently preferred embodiments of the present disclosure are shown. This disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided for thoroughness and completeness, and fully convey the scope of the disclosure to the skilled addressee. Like reference characters refer to like elements throughout.

[0030] Referring now to the drawings and to FIG. 1A in particular, there is depicted an exemplary vehicle, here illustrated as a truck 100, where the truck 100 e.g. may be comprised with a control arrangement 200 (as shown in FIG. 2). The control arrangement 200 may of course be implemented, possibly in a slightly different way, in case e.g. a bus 102 as shown in FIG. 1B, a car as shown in FIG. 1C, etc., would be included with the control arrangement 200.

[0031] The vehicle may for example be one of an electric or hybrid vehicle, or possibly a gas, gasoline or diesel vehicle. The vehicle comprises an electric machine (in case of being an electric or hybrid vehicle or an engine (such as an internal combustion engine in case of being a gas, gasoline or diesel vehicle. The vehicle may further be manually operated, fully or semi-autonomous.

[0032] FIG. 2 shows a conceptual and exemplary implementation of the control arrangement 200 according to the present disclosure, presented in a non-limiting manner. Other ways of implementing the control arrangement 200 is possible and within the scope of the present disclosure.

[0033] As is shown, the control arrangement 200 comprises a server 202 and a database 204, where the server 202 is connected to a plurality of vehicles, such as a first 100 and a second 100′ vehicle, using a networked connection, such as the Internet 206. Following such an implementation, the vehicles 100, 100′ are each provided with a transceiver (not shown), allowing the vehicles 100, 100′ to wirelessly communicate with the server 202.

[0034] For reference, the transceivers may be arranged to allow for any form of wireless connections like WLAN, CDMA, GSM, GPRS, 3G mobile communications, 3/4/5G mobile communications, or similar. Other present of future wireless communication protocols are possible and within the scope of the present disclosure, such as any form of Vehicle-to-everything (V2X) communication protocols.

[0035] Furthermore, the vehicles 100, 100′ are each provide with at least one electronic control unit (ECU) (not shown), where the ECU of the respective vehicle 100, 100′ is arranged in communication with one or a plurality of sensors (also not shown) for collecting data relating to the operation of the vehicles 100, 100′. Such sensors may for example be configured to collect data relating to a speed of the vehicle, an inclination at which the vehicle 100, 100′ is currently operate, a sensor for measuring a tire pressure, etc.

[0036] The ECUs may for example be manifested as a general-purpose processor, an application specific processor, a circuit containing processing components, a group of distributed processing components, a group of distributed computers configured for processing, a field programmable gate array (FPGA), etc. The processor may be or include any number of hardware components for conducting data or signal processing or for executing computer code stored in memory. The memory may be one or more devices for storing data and/or computer code for completing or facilitating the various methods described in the present description. The memory may include volatile memory or non-volatile memory. The memory may include database components, object code components, script components, or any other type of information structure for supporting the various activities of the present description. According to an exemplary embodiment, any distributed or local memory device may be utilized with the systems and methods of this description. According to an exemplary embodiment the memory is communicably connected to the processor (e.g., via a circuit or any other wired, wireless, or network connection and includes computer code for executing one or more processes described herein.

[0037] During operation, with further reference to FIGS. 3 and 4, the first vehicle 100 is shown as operating along a road 302 in a first direction. The road 302 in turn comprises a plurality of road segments 304, 306, 308. A second vehicle 100′ is also travelling along the road in the same direction as the first vehicle 100. Additionally, a third vehicle 100″ is shown as travelling in a second direction, the second direction being opposite to the first direction. It is further noted in FIG. 3 that the second vehicle 100′ is “behind” and following the first vehicle 100. Accordingly, the second vehicle 100′ will in the presented example at a later point in time reach a current location of the first vehicle 100. The current location for the first vehicle 100 is in FIG. 3 shown as corresponding to road segment 304. The second vehicle 100′ is in turn currently located at another road segment, here illustrated as road segment 306.

[0038] In accordance to the present disclosure, when the first vehicle 100 is operating at the road segment 304, information indicative of an energy consumption for the first vehicle 100 is determined, S1. The information indicative of the energy consumption for the first vehicle 100 is subsequently provided, S2, to the server 202, in a possible embodiment together with a root mean square of the speed for the first vehicle 100 over the segment 306, as well as a driving direction (here the “first direction”). Additionally, the first vehicle 100 is to communicate its “sensitivity parameters” to the server 202, such as a current aerodynamic property for the first vehicle 100 as has been discussed above.

[0039] Once the information has been made available at the server 202, at least intermediately stored at the database 204, the server 202 estimates vehicle independent road condition for the first segment 304 based on the received information. Arranging the road condition for the first segment 304 to be vehicle independent may for example be done by performing a “normalization” of the received information.

[0040] This normalization can, for example, be done by using an energy consumption model such as:

[00001]$\frac{W_w-W_p-W_k}{{\mathrm{mgC}}_r{S}_h}=\frac{\rho A_{f}S}{2{\mathrm{mgC}}_r{S}_h}\left(a+b.Math.\mathrm{atan}\left(\frac{.Math.V_{wy}.Math.}{{\mathrm{DV}}_{\mathrm{wx}}+\stackrel{\_}{v}}\right).Math.-c{\mathrm{atan}}^2\left(\frac{.Math.V_{wy}.Math.}{{\mathrm{DV}}_{\mathrm{wx}}+\overline{\nu }}\right)\right)\left({\left(\overline{v}+V_{wx}*Dir\right)}^2+V_{wy}^2\right)+C_{r\_\mathrm{roadcond}}$

[0041] where W.sub.w is the net measured energy at the wheels, W.sub.p the change in potential energy over the segment, W.sub.k the change in kinietic energy over the segment, m is the vehicle mass, ρ the air density, A.sub.f the frontal area, a, b and c are coefficients of a second order approximation of the attack angle dependent air resistance coefficient of the vehicle, v the root mean square of the vehicle speed over the segment, g the gravitational constant, C.sub.r the rolling resistance coefficient of the tires, V.sub.wx and V.sub.wy the wind speed components in x (head), and y directions (side wind), Dir the driving direction (either 1 or −1) and finally C.sub.r_roadcond a compensation factor for the rolling resistance at the present road surface conditions.

[0042] The left-hand side (since the road segment is well-defined, it is assumed that the altitude at the starting and end points are well known and that the vehicle speed at the start and end is measured accurately) of the above equation describes the sum of normalized air resistance plus rolling resistance By subtracting changes in kinetic and potential energy from the total wheel energy consumption, the sum of air and rolling resistance is calculated. By dividing this sum with mgC.sub.rS.sub.h, the resistance energy consumption is normalized in the sense that in zero wind conditions at really low vehicle speed (close to zero) this sum will be the same for all vehicles.

[0043] The right-hand side of the above equation includes the three unknown parameters to be estimated, V.sub.wx, |V.sub.wy|and C.sub.r_roadcond. From the information of five scalar values;

[00002]$\frac{W_w-W_p-W_k}{{\mathrm{mgC}}_r{S}_h},\frac{\rho A_f\mathrm{Sa}}{2{\mathrm{mgC}}_r{S}_h},\frac{\rho A_f\mathrm{Sb}}{2{\mathrm{mgC}}_r{S}_h},\frac{\rho A_f\mathrm{Sc}}{2{\mathrm{mgC}}_r{S}_h},$

v, Dir, sent by each vehicle passing the road segment, a non-linear estimation method such as the Extended Kalman Filter can be used to estimate V.sub.wx, |V.sub.wy|and C.sub.r_roadcond. This estimation can be done with or without help of data from weather institutes and road weather measurements.

[0044] The usage of normalized energy consumption may be seen as a key ingredient to be able to make good estimates of local conditions, where such information subsequently may be used for determining an energy consumption for the second vehicle 100′ when, at a possibly slightly later point in time, travelling at the first segment 304.

[0045] As would be apparent, the estimation of the local road conditions is improved by gathering data from many vehicles running on that road segment while as the estimates of vehicle parameters are improved by running a vehicle on many road segments where the road weather conditions are known.

[0046] In line with the present disclosure it is possible to apply a model-based approach for predicting an energy consumption for the second vehicle 100′. In line with the present disclosure, such a model-based vehicle energy prediction algorithm may in some embodiments be bound to include both vehicle parameters and environmental parameters affecting the energy consumption. If the ingoing parameters are more accurate, so will the resulting energy consumption estimate be. This improvement in prediction can be used in many ways, for example in electric vehicle range estimation.

[0047] By correlating stored historical data of estimated local road weather with stored historical general weather information, weather forecast could be used with this correlation to predict the local weather. Also, to improve the short time prediction, information about wind conditions together with local road weather nearby is used in this invention to how local weather is developing over time and space. For example, if the wind is coming from west and the local road weather in west is showing increasing rolling resistance, it is likely that it is raining and that this will spread to road segments further east in the near future. Historical data is in in line with the present disclosure used to model how fast weather is developing in time depending on the present weather conditions.

[0048] Turning again to FIG. 3, where the first vehicle 100 is travelling along the road 302 and its current energy consumption is determined. When exiting the first segment 304, the energy consumption over the section is, at the server 202, normalized with vehicle parameters and vehicle speed. With or without information from external road weather services, the normalized current road conditions estimation is using the normalized energy consumption to improve the estimate. The road weather conditions on the upcoming road segment (i.e. segment 304) is sent to the second vehicle 100′, where the second vehicle 100′ uses this information to improve its own estimation on its vehicle parameters, as well as to improve short term predictive functions, including for example general energy management and eco-roll to be applied by the second vehicle 100′.

[0049] The estimated current road conditions may also be sent to a “road conditions prediction server” (possibly being the same or another server as compared to server 204) together with information about current road weather conditions as well weather forecast from external road weather information sources. This data may possibly be correlated with stored historical data from the external sources, such as holding information relating to present weather conditions, to predict the road weather conditions on different (other) road segments.

[0050] The present disclosure contemplates methods, devices and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure may be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor.

[0051] By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless to a machine, the machine properly views the connection as a machine-readable medium. Thus, any such connection is properly termed a machine-readable medium. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data that cause a general-purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions.

[0052] Although the figures may show a specific order of method steps, the order of the steps may differ from what is depicted. In addition, two or more steps may be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps and decision steps.

[0053] Additionally, even though the disclosure has been described with reference to specific exemplifying embodiments thereof, many different alterations, modifications and the like will become apparent for those skilled in the art.

[0054] Variations to the disclosed embodiments can be understood and effected by the skilled addressee in practicing the claimed disclosure, from a study of the drawings, the disclosure, and the appended claims. Furthermore, in the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality.