METHODS, CONTROL UNIT AND COMPUTING UNIT FOR ASSISTING A DRIVER OF A VEHICLE IN REDUCING ENERGY CONSUMPTION
TECHNICAL FIELD
This document discloses methods, a control unit and a computing unit for reducing energy consumption in a vehicle. More particularly, methods, a control unit and a computing unit is described, for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle.
BACKGROUND
Reducing energy consumption and other costs for maintenance etc., associated with vehicle transportation is important for the vehicle owner. Reduced energy consumption also results in decreased environmental impact.
Driver support systems are known, which aims to highlight, enhance and maintain a good driving behaviour while reducing energy consumption and wear of supported vehicles. These systems may assess how the driver is handling the vehicle in different situations that can affect energy consumption, or wear of the vehicle. Driver behaviour in a given situation may be fed back through grades and, recommendations may be provided to the driver. These grades and recommendations are however based on detailed map data in combination with a positioning unit. These known driver support systems are primarily dedicated towards long haulage drivers.
However, it is difficult, or with previously known technology impossible to know the intentions of the driver, or why he/ she is behaving in a certain manner in a particular situation. That makes it difficult to provide appropriate feedback.
Further, there are requirements for providing support to the driver also when detailed map data is missing. Further there are requirements for providing support to the driver of any kind of vehicle, not only Long Haulage Trucks.
Yet another problem of previously known technology is that there are only limited solutions for adapting a cruise control functionality of the vehicle to speed limitations or traffic regulating structures such as traffic lights, roundabouts, road bumps, road crossings, etc.
Document US2012022781 describes a method for determining a vehicle travel route based on associated vehicle cost value. Factors like road elevation, repair condition of the road, friction coefficient of the road, etc., are measured for different road segments and stored in a database associated with the respective road segment. A user may then select between different alternative roads to the same destination based on an estimation of a predicted fuel consumption of the respective alternative.
Document US2008208451 describes a map information updating system for use with a navigation system in a vehicle for calculating fuel consumption in a vehicle. Data associated with fuel consumption of a vehicle on different roads is stored in a database. The driver may then use this stored data for selecting road to a destination.
Document EP1973078 reveals a method for improving driving efficiency of a vehicle. Various indications of the vehicle are collected and presented to the driver, reflecting the efficiency of his driving. Such indications are based on a comparison of the currently recorded parameters and parameters recorded during previous drives of the same route or with parameters recorded by similar systems of other vehicles.
Document US2013245943 concerns a longitudinal speed profile data creating method for digital maps used for displaying road or pathway information and used by e.g. navigation systems involves associating longitudinal speed profiles with road segment and storing longitudinal speed profiles in a digital medium.
However, none of these documents describes a mechanism for providing driving recommendations to the driver when no relevant map data is available.
As these described scenarios, and similar variants of them, will lead to increased energy consumption, or increased maintenance costs, it is desired to find a solution.
SUMMARY
It is therefore an object of this invention to solve at least some of the above problems and reduce energy consumption in a vehicle.
According to a first aspect of the invention, this objective is achieved by a method for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle. The method comprises determining geographical position of the vehicle. Further, the method also comprises determining a set of vehicle related data comprising vehicle velocity at the determined geographical position wherein the set of vehicle related data comprises the weight of the vehicle. The method also comprises determining driving direction of the vehicle. In addition the method also comprises storing the determined set of vehicle related data comprising vehicle velocity and the determined driving direction associated with the determined geographical position of the vehicle in a database. Further the method also comprises establishing the probability map of geographical positions for which a velocity reduction is expected, based on the stored set of vehicle related data associated with the determined geographical position of the vehicle and previously stored vehicle related data associated with the same geographical position.
In a first possible implementation of the method according to the first aspect, the steps of determining and storing the set of vehicle related data may further comprise acceleration, selected gear, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters.
In a second possible implementation of the method according to the first aspect, or according to the first possible implementation thereof, the probability map may be established, based on computing maximum value, minimum value, average value and / or variance of the stored vehicle velocities on at least some geographical positions.
According to a second aspect of the invention, this objective is achieved by a control unit, configured for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle. The control unit is configured for determining geographical position of the vehicle. Also, the control unit is configured for determining a set of vehicle related data comprising vehicle velocity at the determined geographical position wherein the set of vehicle related data comprises the weight of the vehicle. Additionally, the control unit is further configured for storing the determined set of vehicle related data associated with the determined geographical position of the vehicle in a database. Furthermore, the control unit is configured for establishing the probability map of geographical positions for which a velocity reduction is expected, based on the stored set of vehicle related data associated with the determined geographical position of the vehicle and previously stored set of vehicle related data associated with the same geographical position.
In a first possible implementation of the control unit according to the second aspect, the steps of determining and storing the set of vehicle related data may further comprise acceleration, selected gear, weight of the vehicle, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters.
In a second possible implementation of the control unit according to the second aspect, or according to the first possible implementation thereof, the probability map may be established, based on computing maximum value, minimum value, average value and / or variance of the stored vehicle velocities on at least some geographical positions.
According to a third aspect of the invention, this objective is achieved by a computer program comprising program code for performing a method according to the first aspect, or any possible implementation thereof, when the computer program is executed in the control unit, according to the second aspect.
According to a fourth aspect of the invention, this objective is achieved by a method for assisting a driver of a vehicle in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected. The method comprises determining geographical position of the vehicle. Further the method also comprises determining a set of vehicle related data comprising vehicle velocity at the determined geographical position wherein the set of vehicle related data comprises the weight of the vehicle. The method in addition comprises determining driving direction of the vehicle. Also, the method further comprises extracting a stored geographical position from the probability map in a database, for which a velocity reduction is expected in the determined driving direction. The method further comprises calculating a retardation distance, for reducing the determined vehicle velocity into the expected reduced velocity at the extracted geographical position.
In a first possible implementation of the method according to the fourth aspect, the method further comprises presenting an instruction to the driver to release the accelerator, when the vehicle is positioned at the calculated retardation distance from the extracted geographical position, for arriving at said geographical position with the expected reduced velocity of the vehicle.
In a second possible implementation of the method according to the fourth aspect, or the first possible implementation thereof, the step of determining the set of vehicle related data further comprises: acceleration, selected gear, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or similar parameter, and using the determined set of parameters for filtering when extracting the stored geographical position from the probability map in the database, for which a velocity reduction is expected in the determined driving direction.
In a third possible implementation of the method according to the fourth aspect, or according to any previous possible implementation thereof, the driving direction of the vehicle is determined based on navigation data input from the driver.
In a fourth possible implementation of the method according to the fourth aspect, or according to any previous possible implementation thereof, the method further comprises releasing the accelerator when the vehicle is positioned at the calculated retardation distance from the extracted geographical position, for arriving at said geographical position with the expected reduced velocity of the vehicle autonomously, when the driver has activated a cruise control on the vehicle.
In a fifth possible implementation of the method according to the fourth aspect, or according to any previous possible implementation thereof, the method further comprises providing feedback to the driver, based on the driver's adaptation to the presented instructions to release the accelerator.
According to a fifth aspect of the invention, this objective is achieved by a computing unit, configured for assisting a driver of a vehicle in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected. The computing unit is configured for determining geographical position of the vehicle and the weight of the vehicle. Also, the computing unit is configured for determining a set of vehicle related data comprising vehicle velocity at the determined geographical position. The computing unit is also configured for determining driving direction of the vehicle. In addition the computing unit is configured for extracting a stored geographical position from the probability map in a database, for which a velocity reduction is expected in the determined driving direction. Further the computing unit is configured for calculating a retardation distance, for reducing the determined vehicle velocity into the expected reduced velocity at the extracted geographical position. The computing unit is furthermore configured for presenting an instruction to the driver via an interface to release the accelerator, when the vehicle is positioned at the calculated retardation distance from the extracted second geographical position, for arriving at the second geographical position with the expected reduced velocity of the vehicle.
In a first possible implementation of the computing unit according to the fifth aspect, the interface comprises any of a display of the vehicle, a portable electronic device, a navigator of the vehicle, a loud speaker, or a tactile device.
In a second possible implementation of the computing unit according to the fifth aspect, or the first possible implementation thereof, the computing unit is further configured for determining the set of vehicle related data comprising: vehicle velocity, acceleration, selected gear, weight of the vehicle, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or similar parameter, and using the determined set of parameters for filtering when extracting the stored geographical position from the probability map in the database, for which a velocity reduction is expected in the determined driving direction.
In a third possible implementation of the computing unit according to the fifth aspect, or according to any previous possible implementation thereof, the computing unit is further configured for determining the driving direction of the vehicle based on navigation data input from the driver.
In a fourth possible implementation of the computing unit according to the fifth aspect, or according to any previous possible implementation thereof, the computing unit is further configured for releasing the accelerator when the vehicle is positioned at the calculated retardation distance from the extracted geographical position, for arriving at said geographical position with the expected reduced velocity of the vehicle autonomously, when the driver has activated a cruise control on the vehicle.
In a fifth possible implementation of the computing unit according to the fifth aspect, or according to any previous possible implementation thereof, the computing unit is further configured for providing feedback to the driver, based on the driver's adaptation to the presented instructions to release the accelerator.
According to a sixth aspect of the invention, this objective is achieved by a computer program comprising program code for performing a method according to the fourth aspect, or any possible implementation thereof, when the computer program is executed in the computing unit, according to the fifth aspect.
According to a seventh aspect of the invention, this objective is achieved by a vehicle comprising a control unit according to the second aspect, or a computing unit according to the fifth aspect.
Thanks to the described aspects, by collecting and storing parameters related to vehicle velocity and geographical positions and establishing a probability map, it is possible to predict when a vehicle will stop or reduce vehicle velocity. Further it may be calculated when the driver of the vehicle will have to release the accelerator in order to roll to the predicted stop. Thereby energy is saved at the vehicle and the driver is given a tool for assisting him/ her in saving energy. An advantage with the provided solution is that it may be used by any kind of vehicle, also distribution trucks, city busses or private vehicles, in any kind of environment, comprising also urban environment.
Other advantages and additional novel features will become apparent from the subsequent detailed description.
FIGURES
Embodiments of the invention will now be described in further detail with reference to the accompanying figures, in which:
Figure 1 illustrates a vehicle according to an embodiment of the invention;
Figure 2 illustrates a vehicle driving along a route according to an embodiment of the invention;
Figure 3A illustrates a vehicle interior according to an embodiment of the invention;
Figure 3B illustrates a vehicle interior according to an embodiment of the invention;
Figure 4 is a flow chart illustrating an embodiment of a first method;
Figure 5 is an illustration depicting a control unit according to an embodiment;
Figure 6 is a flow chart illustrating an embodiment of a second method;
Figure 7 is an illustration depicting a computing unit according to an embodiment.
DETAILED DESCRIPTION
Embodiments of the invention described herein are defined as methods, a control unit and a computation unit, which may be put into practice in the embodiments described below. These embodiments may, however, be exemplified and realised in many different forms and are not to be limited to the examples set forth herein; rather, these illustrative examples of embodiments are provided so that this disclosure will be thorough and complete.
Still other objects and features may become apparent from the following detailed description, considered in conjunction with the accompanying drawings. It is to be understood, however, that the drawings are designed solely for purposes of illustration and not as a definition of the limits of the herein disclosed embodiments, for which reference is to be made to the appended claims. Further, the drawings are not necessarily drawn to scale and, unless otherwise indicated, they are merely intended to conceptually illustrate the structures and procedures described herein.
Figure 1 illustrates a scenario with a vehicle 100 driving in a driving direction 105 on a road 110.
The vehicle 100 may comprise e.g. a truck, a bus, a car, a motorcycle or any similar vehicle or other means of conveyance.
The vehicle 100 may be driver controlled or driverless autonomously controlled vehicles in different embodiments. However, for enhanced clarity, the vehicle 100 is subsequently described as having a driver.
The depicted vehicle 100 is approaching a stop sign 120 at a road crossing 130.
According to some embodiments, the energy consumption and vehicle behaviour when driving a route with the vehicle 100 is measured and stored in a database. The vehicle behaviour may comprise vehicle related data such as e.g. vehicle velocity, acceleration, selected gear, weight of the vehicle 100, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters. Also the geographical position of the vehicle 100 is determined. In some embodiments geographical positioning may be performed, e.g. by a Global Positioning System (GPS) receiver in the vehicle 100. The determined vehicle related data is then stored in the data base together with the determined geographical position of the vehicle 100. This methodology is repeated for example at certain periodic time intervals, or at certain traffic situations, such as before road crossings 130, hills, traffic lights, pedestrian crossings etc.
The stored vehicle related data associated with geographical positions are stored in the database for establishing a probability map of geographical positions, where a velocity reduction is expected.
When the probability map has been established, it may be used by any vehicle 100, driving at the same geographical position in the same direction 105, for determining where a velocity reduction is expected for the vehicle 100 and a calculation may be made for computing a retardation distance to the geographical position where the velocity reduction is expected for the vehicle 100. Then, an instruction may be sent to the driver of the vehicle 100 to release the accelerator, when the vehicle 100 is arriving at the retardation distance from the geographical position where the velocity reduction is expected.
The retrieved driving instructions may be given by displaying the previously stored data associated with a geographical position, when the vehicle 100 reach that geographical position.
Thereby, the driver will be learned to adapt the driving in order to reduce the energy consumption, thus adapting an ecological driving behaviour.
In some embodiments, the saved vehicle related data may also be used by another, similar vehicle and may thus be used for knowledge transfer. Thereby, an inexperienced driver quickly could learn and adapt an energy saving driving style by copying the driving commands of more experienced driver, which shortens the time it takes to become a skilful driver.
Further, the collected and stored data may be sent to the vehicle producer in some embodiments, in order for the engineers to get a deeper understanding of how customers use their vehicles 100. The support that the customer then receive would be more customised when it is known more precisely how customers use their vehicles 100.
Not just energy consumption would be reduced, but also wear on the vehicle 100 may be reduced and possibly optimised for the most common route.
Yet an advantage is that the disclosed method may be applied also in environments where no detailed map data is available, or only limited map data exists.
Furthermore, the disclosed method is applicable for any kind of vehicle, such as city buses, distribution trucks and private cars, for example. This is a clear difference in comparison with previously known solutions, which are dedicated towards long haulage.
Figure 2 illustrates the vehicle 100, approaching the road crossing 130, seen from an above perspective. As the vehicle 100 is approaching the road crossing 130, the velocity of the vehicle 100, and possibly also other vehicle related data, is measured at certain positions A, B and C, which may be positions in time (i.e. the velocity of the vehicle 100 is measured and stored at a certain time interval, such as every second, every third second etc.), or positions in distance (i.e. the velocity of the vehicle 100 is measured and stored at a certain length interval such as every 10 meters in a non-limiting example), or predetermined geographical positions in different embodiments, or a combination thereof.
The measured velocity data is thus associated with the respective position A, B, C where the measurement was made and then stored in a database.
In some embodiments, the database may be situated in the vehicle 100, and only vehicle related data from the own vehicle 100 is then stored in the data base, each time 1, 2, ..., n the vehicle 100 passes the respective positions A, B, C, where n is an arbitrary integer.
However, in other embodiments, the database may be external to the vehicle 100, and vehicle related data from any vehicle 100 that passes the respective positions A, B, C may be stored, associated with the respective measured vehicle related data.
The stored data in the database may then be analysed and a probability for a certain vehicle velocity at a certain position A, B, C may be estimated. Thus a probability map for velocities at the certain positions A, B, C, or at least some of them, may be made.
In the illustrated case in Figure 2, the probability of driving at zero km/h at position A is very high, for example. Based on that information, a retardation distance for the vehicle 100 may be computed, starting from position A and backwards against the driving direction 105. It may thereby be determined when the driver of the vehicle 100 has to release the accelerator and let the vehicle 100 roll in order to arrive at position A at zero km/h, without having to brake away any energy. Then, next time the vehicle 100 passes the discussed positions A, B, C, an instruction may be presented to the driver, encouraging him/ her to release the accelerator.
The determined velocity in the established velocity probability map established based on the recorded and stored data does not have to be zero km/h, it may be reduced velocity e.g. in roundabouts, ramps, access roads, sharp turns etc., where it often may be required to drive at lower velocity than actually permitted by traffic regulations, due to constraints of the vehicle 100.
Thanks to the disclosed method, a preferred strategy for saving energy of the vehicle 100 may be extracted, independently of how the driver may perceive the ahead traffic situation.
In some embodiments, energy may be saved also when the driver is using a cruise control functionality of the vehicle 100. Thus the cruise control may adapt the velocity of the vehicle 100, e.g. when the vehicle 100 arrives at a road crossing 130, or passes a roundabout.
Figure 3A illustrates an example of how the previously scenario in Figure 1 or Figure 2 may be perceived by the driver of the vehicle 100.
The vehicle 100 may comprise, or be associated with a display 310, where e.g. instructions may be displayed. The display 310 may be integrated in the dashboard of the vehicle 100, or comprise a separate unit in different embodiments such as e.g. a mobile device, a cellular telephone, as will be further illustrated in an example in Figure 3B. The display 310 may also, or alternatively comprise a loud speaker or a tactile device in some embodiments, or be integrated in a positioning unit 330 of the vehicle 100.
The positioning unit 330 may be based on a satellite navigation system such as the Navigation Signal Timing and Ranging (Navstar) Global Positioning System (GPS), Differential GPS (DGPS), Galileo, GLONASS, or the like. Thus the positioning unit 330 may comprise a GPS receiver.
The geographical position of the vehicle 100 may be determined continuously or at certain predetermined or configurable time intervals according to various embodiments.
Positioning by satellite navigation is based on distance measurement using triangulation from a number of satellites 340-1, 340-2, 340-3, 340-4. The satellites 340-1, 340-2, 340-3, 340-4 continuously transmit information about time and date (for example, in coded form), identity (which satellite 340-1, 340-2, 340-3, 340-4 which broadcasts), status, and where the satellite 340-1, 340-2, 340-3, 340-4 are situated at any given time. GPS satellites 340-1, 340-2, 340-3, 340-4 sends information encoded with different codes, for example, but not necessarily based on Code Division Multiple Access (CDMA). This allows information from an individual satellite 340-1, 340-2, 340-3, 340-4 distinguished from the others' information, based on a unique code for each respective satellite 340-1, 340-2, 340-3, 340-4. This information can then be transmitted to be received by the appropriately adapted positioning unit 330 in the vehicle 100.
Distance measurement can according to some embodiments comprise measuring the difference in the time it takes for each respective satellite signal transmitted by the respective satellites 340-1, 340-2, 340-3, 340-4, to reach the positioning unit 330. As the radio signals travel at the speed of light, the distance to the respective satellite 340-1, 340-2, 340-3, 340-4 may be computed by measuring the signal propagation time.
The positions of the satellites 340-1, 340-2, 340-3, 340-4 are known, as they continuously are monitored by approximately 15-30 ground stations located mainly along and near the earth's equator. Thereby the geographical position, i.e. latitude and longitude, of the vehicle 100 may be calculated by determining the distance to at least three satellites 340-1, 340-2, 340-3, 340-4 through triangulation. For determination of altitude, signals from four satellites 340-1, 340-2, 340-3, 340-4 may be used according to some embodiments.
In the illustrated embodiment, the vehicle 100 also may comprise a control unit 500 in some embodiments. The control unit 500 is configured for collecting and storing a set of vehicle related parameters such as e.g. vehicle velocity during driving. The control unit 500 may in some embodiments be external to the vehicle 100.
Having determined the geographical position of the vehicle 100 via the positioning unit 330, and also determined the driving direction 105 of the vehicle 100, the control unit 500 may collect the set of vehicle related parameters of the vehicle 100, when driving in the driving direction 105 at certain geographical positions A, B, C of the vehicle 100. The vehicle related parameters, or data, may then be stored associated with the determined geographical position A, B, C in a memory or database 350. The memory or database 350 may be situated in the vehicle 100 in some embodiments, as illustrated in the embodiment depicted in Figure 3A. However, in other embodiments, the collected parameter data may be stored in a database 350 external to the vehicle 100, as illustrated in Figure 3B.
Further the vehicle 100 may comprise a computation unit 700. The computational unit 700 may also be connected to the database 350.
In some embodiments, vehicle related data comprising vehicle velocity etc. at the geographical position is detected and stored in the database 350, associated with the driving direction 105 of the vehicle 100 and the geographical position. The collected data is then utilised for establishing a probability map of geographical positions where a velocity reduction is expected, e.g. a vehicle stop. This probability map of geographical positions may then be used the next time the vehicle 100 passes the same geographical position; or by any other vehicle passing the same geographical position in different embodiments. Using the current geographical position and driving direction 105 of the vehicle 100 as input values, a stored geographical position may be extracted from the probability map in the database 350, where a velocity reduction is expected. Further, a retardation distance may be calculated, for reducing the vehicle velocity into the expected reduced velocity at the extracted geographical position. When the vehicle 100 is at the calculated retardation distance, an instruction may be displayed to the driver at the display 310.
Figure 3B illustrates yet an example of how the previously scenario in Figure 1 or Figure 2 may be perceived by the driver of the vehicle 100.
The illustrated embodiment is similar to the set up illustrated in Figure 3A, but with the main difference that the control unit 500 and the database 350 are external to the vehicle 100 and comprises e.g. a server or a cloud based solution.
The computation unit 700 is however situated in the vehicle 100 and may communicate via a transceiver 360 with the control unit 500 over a wireless communication interface.
The mentioned wireless communication may be based on, or at least inspired by wireless communication technology such as e.g., 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE), LTE-Advanced, Vehicle-to- Vehicle (V2V) communication, Wi-Fi, Wireless Local Area Network (WLAN), Ultra Mobile Broadband (UMB), Bluetooth (BT), or infrared transmission to name but a few possible examples of wireless communications.
In an illustrative example, the vehicle 100 may determine the geographical position using the positioning unit 330, and the driving direction 105 of the vehicle 100 at the geographical position.
The determined geographical position and the driving direction 105 may be used as input values for extracting instructions from the database 350, associated with that geographical position and driving direction 105 of the vehicle 100.
Further, a retardation distance may be calculated by the calculating unit 500, for reducing the vehicle velocity into the expected reduced velocity at the extracted geographical position. When the vehicle 100 is at the calculated retardation distance, an instruction may be displayed to the driver at the display 310.
Figure 4 illustrates an example of a method 400 according to an embodiment. The flow chart in Figure 4 shows the method 400 for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle 100.
The vehicle 100 may be any arbitrary kind of means for conveyance, such as a truck, a bus, a car or a motorcycle.
In order to correctly be able to collect and store the parameters, the method 400 may comprise a number of steps 401-405. Some of the described steps may be performed in various different variants. Further, the described steps 401-405 may be performed in a somewhat different chronological order than the numbering suggests. For example, step 403 may be performed before step 401 or step 402. The method 400 may comprise the subsequent steps:
Step 401 comprises determining geographical position of the vehicle 100.
The geographical position may be determined based on GPS positioning in some embodiments, e.g. at certain time intervals, continuously, triggered by some driver action such as changing vehicle velocity, slowing down the vehicle 100 etc., or at request by the driver. The geographical position of the vehicle 100 may in some alternative embodiments be indicated by the driver.
Step 402 comprises determining a set of vehicle related data comprising vehicle velocity at the determined geographical position.
The determined set of vehicle related data comprising vehicle velocity may further comprise acceleration, selected gear, weight of the vehicle 100, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters.
Step 403 comprises determining driving direction 105 of the vehicle 100.
The driving direction 105 of the vehicle 100 may be determined based on the location of the destination of the journey, or by extrapolating the driving direction based on previously determined 401 geographical positions and possibly knowledge of the road direction, e.g. from stored map data.
Step 404 comprises storing the determined 402 set of vehicle related data comprising vehicle velocity and the determined 403 driving direction 105 associated with the determined 401 geographical position of the vehicle 100 in a database 350, or data memory.
The stored set of vehicle related data comprising vehicle velocity may further comprise acceleration, selected gear, weight of the vehicle 100, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters.
Step 405 comprises establishing the probability map of geographical positions for which a velocity reduction is expected, based on the stored 404 set of vehicle related data associated with the determined 401 geographical position of the vehicle 100 and previously stored vehicle related data associated with the same geographical position.
The probability map may be established based on computing of maximum value, minimum value, average value and / or variance of the stored 404 vehicle velocities on at least some geographical positions.
Figure 5 illustrates an embodiment of a control unit 500 configured for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle 100.
The control unit 500 may be situated in the vehicle 100 in some embodiments (see Figure 3A), or alternatively be external to the vehicle 100 in other embodiments (see Figure 3B).
The control unit 500 is configured to perform at least some of the steps 401-405 according to the method 400 for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in the vehicle 100.
The control unit 500 is configured for determining geographical position of the vehicle 100. The control unit 500 is also configured for determining a set of vehicle related data comprising vehicle velocity at the determined geographical position. In addition the control unit 500 is furthermore configured for storing the determined set of vehicle related data associated with the determined geographical position of the vehicle 100 in a database 350, or in a memory 525.
The control unit 500 is also configured for establishing the probability map of geographical positions for which a velocity reduction is expected, based on the stored set of vehicle related data associated with the determined geographical position of the vehicle 100 and previously stored set of vehicle related data associated with the same geographical position.
The control unit 500 may comprise a receiving circuit 510 configured for receiving a signal from a positioning unit 330, or from a communication unit 360.
The control unit 500 may also comprise a processor 520 configured for performing at least some of the calculating or computing of the control unit 500. Thus the processor 520 may be configured for performing at least some of the steps 401-405 according to the method 400 for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in the vehicle 100.
Such processor 520 may comprise one or more instances of a processing circuit, i.e. a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions. The herein utilised expression “processor” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones enumerated above.
Furthermore, the control unit 500 may comprise a memory 525 in some embodiments. The optional memory 525 may comprise a physical device utilised to store data or programs, i.e., sequences of instructions, on a temporary or permanent basis. According to some embodiments, the memory 525 may comprise integrated circuits comprising silicon-based transistors. The memory 525 may comprise e.g. a memory card, a flash memory, a USB memory, a hard disc, or another similar volatile or non-volatile storage unit for storing data such as e.g. ROM (Read-Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable PROM), EEPROM (Electrically Erasable PROM), etc. in different embodiments.
Further, the control unit 500 may comprise a signal transmitter 530. The signal transmitter 530 may be configured for transmitting a control signal over a wired or wireless interface to be received by the display 310 in the vehicle 100, or by the database 350.
The previously described steps 401-405 to be performed in the control unit 500 may be implemented through the one or more processors 520 within the control unit 500, together with computer program product for performing at least some of the functions of the steps 401 405. Thus a computer program product, comprising instructions for performing the steps 401-405 in the control unit 500 may perform the method 400 according to at least some of the steps 401-405 for creating a probability map of geographical positions for which a velocity reduction is expected, for assisting a driver in reducing energy consumption in a vehicle 100, when the computer program is loaded into the one or more processors 520 of the control unit 500.
The computer program product mentioned above may be provided for instance in the form of a data carrier carrying computer program code for performing at least some of the steps 401-405 according to some embodiments when being loaded into the one or more processors 520 of the control unit 500. The data carrier may be, e.g., a hard disk, a CD ROM disc, a memory stick, an optical storage device, a magnetic storage device or any other appropriate medium such as a disk or tape that may hold machine readable data in a non-transitory manner. The computer program product may furthermore be provided as computer program code on a server and downloaded to the control unit 500 remotely, e.g., over an Internet or an intranet connection.
Further, some embodiments may comprise a vehicle 100 comprising a control unit 500 as illustrated in Figure 3A.
Some embodiments may comprise a vehicle external structure comprising a control unit 500 as illustrated in Figure 3B.
Figure 6 illustrates an example of a method 600 according to an embodiment. The flow chart in Figure 6 shows the method 600 for assisting a driver of a vehicle 100 in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected.
The vehicle 100 may be any arbitrary kind of means for conveyance, such as a truck, a bus, a car or a motorcycle.
In order to correctly be able to collect and store the parameters, the method 600 may comprise a number of steps 601-607. However, some of these steps 601-607 may be performed in different alternative ways. Further, the described steps 601-607 may be performed in a somewhat different chronological order than the numbering suggests. Step 606 and step 607 may only be performed in some alternative embodiments. For example, step 603 may be performed before step 601 or step 602. The method 600 may comprise the subsequent steps:
Step 601 comprises determining geographical position of the vehicle 100.
The geographical position may be determined based on GPS positioning in some embodiments, e.g. at certain time intervals, continuously, triggered by some driver action such as changing vehicle velocity, slowing down the vehicle 100 etc., or at request by the driver. The geographical position of the vehicle 100 may in some alternative embodiments be indicated by the driver.
Step 602 comprises determining a set of vehicle related data comprising vehicle velocity at the determined 601 geographical position.
The determined set of vehicle related data comprising vehicle velocity may further comprise e.g. acceleration, selected gear, weight of the vehicle 100, engine load, road slope, vehicle type, date, day of the week, time of the day, above or below zero degrees, or other similar parameters.
Step 603 comprises determining driving direction 105 of the vehicle 100.
The driving direction 105 of the vehicle 100 may be determined based on the location of the destination of the journey, or by extrapolating the driving direction based on previously determined 601 geographical positions and possibly knowledge of the road direction, e.g. from stored map data.
The driving direction 105 of the vehicle 100 may in some embodiments be determined based on navigation data input from the driver.
Step 604 comprises extracting a stored geographical position from the probability map in a database 350 or memory, for which a velocity reduction is expected in the determined 603 driving direction 105.
The determined 602 set of vehicle related data, or parameters, may be used for filtering when extracting the stored geographical position from the probability map in the database 350 or memory for which a velocity reduction is expected in the determined 603 driving direction 105.
Step 605 comprises calculating a retardation distance, for reducing the determined 602 vehicle velocity into the expected reduced velocity at the extracted 604 geographical position.
Step 606 may be comprised only in some embodiments. The optional step 606 may comprise presenting an instruction to the driver to release the accelerator, when the vehicle 100 is positioned at the calculated 605 retardation distance from the extracted 604 geographical position, for arriving at said geographical position with the expected reduced velocity of the vehicle 100.
According to some embodiments, feedback may be provided to the driver, based on the driver's adaptation to the presented 606 instructions to release the accelerator.
Step 607 may be comprised only in some embodiments. The optional step 607 may comprise releasing the accelerator when the vehicle 100 is positioned at the calculated 605 retardation distance from the extracted 604 geographical position, for arriving at said geographical position with the expected reduced velocity of the vehicle 100 autonomously, when the driver has activated a cruise control of the vehicle 100.
Figure 7 illustrates an embodiment of a computing unit 700 configured for assisting a driver of a vehicle 100 in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected. The computing unit 700 is configured to perform at least some of the steps 601-607 according to the above described method 600 for assisting a driver of a vehicle 100 in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected.
The computing unit 700 is configured for determining geographical position of the vehicle 100. Further, the computing unit 700 is further configured for determining a set of vehicle related data comprising vehicle velocity at the determined geographical position. Furthermore, the computing unit 700 is also configured for determining driving direction 105 of the vehicle 100. The computing unit 700 is additionally configured for extracting a stored geographical position from the probability map in a database 350 or memory, for which a velocity reduction is expected in the determined driving direction 105. Also, the computing unit 700 is configured for calculating a retardation distance, for reducing the determined vehicle velocity into the expected reduced velocity at the extracted geographical position. Furthermore, the computing unit 700 is configured for presenting an instruction to the driver via an interface 310 to release the accelerator, when the vehicle 100 is positioned at the calculated retardation distance from the extracted second geographical position, for arriving at the second geographical position with the expected reduced velocity of the vehicle 100.
The interface 310 may comprise any of a display of the vehicle 100, a portable electronic device, a navigator 320 of the vehicle 100, a loud speaker, a tactile device or similar device.
The computing unit 700 may comprise a receiving circuit 710 configured for receiving a signal from one or more sensors in the vehicle 100, a positioning unit 330 or a database 350.
The computing unit 700 may also comprise a processor 720 configured for performing at least some of the calculating or computing of the computing unit 700. Thus the processor 720 may be configured for performing at least some of the steps 601-607 according to the above described method 600 for assisting a driver of a vehicle 100 in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected.
Such processor 720 may comprise one or more instances of a processing circuit, i.e. a Central Processing Unit (CPU), a processing unit, a processing circuit, a processor, an Application Specific Integrated Circuit (ASIC), a microprocessor, or other processing logic that may interpret and execute instructions. The herein utilised expression “processor” may thus represent a processing circuitry comprising a plurality of processing circuits, such as, e.g., any, some or all of the ones enumerated above.
Furthermore, the computing unit 700 may comprise a memory 725 in some embodiments. The optional memory 725 may comprise a physical device utilised to store data or programs, i.e., sequences of instructions, on a temporary or permanent basis. According to some embodiments, the memory 725 may comprise integrated circuits comprising silicon-based transistors. The memory 725 may comprise e.g. a memory card, a flash memory, a USB memory, a hard disc, or another similar volatile or non-volatile storage unit for storing data such as e.g. ROM (Read-Only Memory), PROM (Programmable Read-Only Memory), EPROM (Erasable PROM), EEPROM (Electrically Erasable PROM), etc. in different embodiments.
Further, the computing unit 700 may comprise a signal transmitter 730. The signal transmitter 730 may be configured for transmitting a control signal over a wired or wireless interface to be received by the interface 310 i.e. display 320 in the vehicle 100.
The previously described steps 601-607 to be performed in the computing unit 700 may be implemented through the one or more processors 720 within the computing unit 700, together with computer program product for performing at least some of the functions of the steps 601-607. Thus a computer program product, comprising instructions for performing the steps 601-607 in the computing unit 700 may perform the method 600 comprising at least some of the steps 601-607 for assisting a driver of a vehicle 100 in reducing energy consumption by using a probability map of geographical positions for which a velocity reduction is expected, when the computer program is loaded into the one or more processors 720 of the computing unit 700.
The computer program product mentioned above may be provided for instance in the form of a data carrier carrying computer program code for performing at least some of the steps 601-607 according to some embodiments when being loaded into the one or more processors 720 of the computing unit 700. The data carrier may be, e.g., a hard disk, a CD ROM disc, a memory stick, an optical storage device, a magnetic storage device or any other appropriate medium such as a disk or tape that may hold machine readable data in a nontransitory manner. The computer program product may furthermore be provided as computer program code on a server and downloaded to the computing unit 700 remotely, e.g., over an Internet or an intranet connection.
Further, some embodiments may comprise a vehicle 100 comprising a computing unit 700 and optionally a control unit 500 as illustrated in Figures 1, 2, 3A, and / or 3B.
As used herein, the term "and/ or" comprises any and all combinations of one or more of the associated listed items. The term “or” as used herein, is to be interpreted as a mathematical OR, i.e., as an inclusive disjunction; not as a mathematical exclusive OR (XOR), unless expressly stated otherwise. In addition, the singular forms "a", "an" and "the" are to be interpreted as “at least one”, thus also possibly comprising a plurality of entities of the same kind, unless expressly stated otherwise. It will be further understood that the terms "includes", "comprises", "including" and / or "comprising", specifies the presence of stated features, actions, integers, steps, operations, elements, or components, but do not preclude the presence or addition of one or more other features, actions, integers, steps, operations, elements, components, or groups thereof. A single unit such as e.g. a processor may fulfil the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. A computer program may be stored/ distributed on a suitable medium, such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, but may also be distributed in other forms such as via Internet or other wired or wireless communication system.