EP3679325A1 - Method, device, computer program and computer program product for route planning for a vehicle - Google Patents
Method, device, computer program and computer program product for route planning for a vehicleInfo
- Publication number
- EP3679325A1 EP3679325A1 EP18727738.9A EP18727738A EP3679325A1 EP 3679325 A1 EP3679325 A1 EP 3679325A1 EP 18727738 A EP18727738 A EP 18727738A EP 3679325 A1 EP3679325 A1 EP 3679325A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- charging
- data
- occupation
- charging stations
- route
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000004590 computer program Methods 0.000 title claims abstract description 17
- 230000005611 electricity Effects 0.000 claims description 27
- 230000003466 anti-cipated effect Effects 0.000 abstract 3
- 238000004891 communication Methods 0.000 description 5
- 230000002596 correlated effect Effects 0.000 description 4
- 230000009467 reduction Effects 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000000875 corresponding effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000001627 detrimental effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
- G08G1/096844—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route where the complete route is dynamically recomputed based on new data
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096811—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
- G08G1/096816—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard where the complete route is transmitted to the vehicle at once
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3476—Special cost functions, i.e. other than distance or default speed limit of road segments using point of interest [POI] information, e.g. a route passing visible POIs
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
- G01C21/3682—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities output of POI information on a road map
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
- G01C21/3685—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities the POI's being parking facilities
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
Definitions
- the invention relates to a method, a device, a computer program and a computer program product for
- Occupation of charging stations along a given route is determined.
- the object underlying the invention is to provide a method for route planning for a vehicle as well as a corresponding device, a computer program and a computer program product, which helps to reduce the driving time for a given route.
- the invention relates to a
- a charging strategy is determined, wherein the expected occupation occupy the charging stations at a calculated time of arrival of the Vehicle is at the respective charging station. Depending on the traffic data and the determined expected occupation of the charging stations, a charging strategy is determined
- Charging strategy a charging strategy information for a driver is provided.
- Charging infrastructure can lead to an inhomogeneous occupation of charging stations. This means that some charging stations, such as Charging posts that are located directly on a highway, may have a long queue, while other charging stations are not or only slightly occupied.
- the long waiting time results in a long driving time and could be detrimental to the acceptance of electric vehicle technology.
- the charging strategy is thus determined in the method, depending on traffic data and the determined expected occupation of charging stations.
- the provision of the information about the charging strategy to the driver can then enable a reduction of the driving time for a given route.
- the route may be, for example, a route indicated by the driver, through a starting point and an end point
- the starting point of the route may be, for example, a current position of a vehicle and the end point of the route a driver specified
- the vehicle may be, for example, a plug-in hybrid or an electric vehicle.
- traffic data such as current traffic density data
- the current traffic density of a road contains, for example, information about a current traffic flow and / or number of vehicles in a road and can therefore be correlated with the expected occupation of the charging stations. Furthermore, the number of plug-in hybrid and electric vehicles that are in the specified route, for example, for the
- the charging stations may be either charging stations located directly on the roads of the route and / or charging stations located within a predetermined distance from the roads concerned.
- the charging strategy for this route can be determined.
- the charging strategy comprises, for example, information about a location, the location being, for example, a suggestion for a location at which a vehicle battery is to be charged.
- the charging strategy can, for example, also provide information about one
- Battery charging duration include, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a period of electrical charging of the vehicle battery. Furthermore, the battery charging duration is, for example, a proposal for a
- Charging strategy for example, include information on a number of loads, the number of
- Charging for example, a proposal for a number of charging the vehicle battery for the specified route can be.
- the charging strategy can be updated during the route, for example. The provision of this information to the driver can allow a reduction of the driving time to the given destination.
- the information provided to the driver for the driver is the information provided to the driver for the driver.
- Ladestrategie contains, for example, an indication of a time-efficient charging the vehicle battery for
- the charging strategy helps the driver, for example, to find charging stations with a low occupancy along the route and can relieve the charging stations and / or a homogeneous occupation of the
- Charging columns lead.
- the homogeneous occupation of the charging columns enables a balanced and / or better calculable electrical energy distribution of the charging stations.
- data becomes a historical traffic density
- the data being historical
- Traffic density include information on a traffic density along the route to past times.
- the expected population of charging stations and the charging strategy will be historical depending on the data
- the data on historical traffic density can be any data on historical traffic density.
- the traffic density pattern can eg for a Traffic density at different times of the day and / or on
- Historical traffic density may be expected for one, at the time the vehicle arrives at a charging station
- Traffic density can be representative and allows a better prediction of the expected occupation of the charging stations along the route. This results in a more efficient charging strategy and helps to reduce the driving time.
- weather data are provided which
- the expected occupation of the charging stations and the charging strategy are determined depending on the weather data.
- the weather data may, for example, information on a current weather situation and / or expected at the time of arrival of the vehicle to a charging station
- the weather situation can influence, for example, the traffic density and / or vehicle speed.
- the provision of weather data may therefore allow better determination of the expected loading of the charging stations along the route and a more efficient charging strategy.
- data about a current location and / or consumption and / or speed and / or charging status of the vehicle are provided. Further, the expected
- Speed and / or charging status of the vehicle may affect, for example, the range of the vehicle and the time of arrival of the vehicle at the charging stations.
- the charging status for the charging status of the vehicle may affect, for example, the range of the vehicle and the time of arrival of the vehicle at the charging stations.
- Charging stations The provision of data on the current location and / or consumption and / or speed and / or
- Charging status of the vehicle may therefore allow better determination of the expected charging column occupancy and a more efficient charging strategy.
- data is provided about a current occupation of the charging stations along the route. Furthermore, the expected occupation of the charging stations and the charging strategy are determined depending on the data on the current occupation of the charging stations.
- the current occupation of the charging stations can be relevant for the determination of the expected charging of the charging stations.
- the current population of charging stations located near the vehicle can be correlated with their expected occupancy. For the determination of
- Charging strategy for example, charging stations located near the vehicle and a low current
- the data on the current occupation of the charging stations can better determine the expected occupation of the charging stations and / or a
- the information about the current occupation of the charging stations may be the selection of the next charging point for the driver
- This information is for example relevant if the driver wants to load the vehicle immediately.
- data for a historical occupation of the charging stations along the route is provided, wherein the data for historical occupation comprises information about a filling of the charging stations at past time points. Furthermore, the expected population of charging stations and the charging strategy will be historical depending on the data
- the data for historical occupation of the charging columns may contain information about a population pattern of the charging stations, such as e.g. the cast during different
- Charging columns can be stored, the more detailed the data on historical traffic density can be.
- the expected occupation of a charging station can be correlated with the historical occupation.
- Charging strategy for example, charging stations, the
- the data on the historical occupation of the charging stations can provide a better Determining the expected occupation of the charging stations and the charging strategy.
- data becomes a charging power of
- Charging posts provided along the route Furthermore, the expected occupation of the charging stations and the charging strategy are determined depending on the charging capacity data of the charging stations.
- the data on the charging power of the charging stations can be any type of the charging power of the charging stations.
- the charging power of the charging stations can vary, for example, between 3 kW and 300 kW.
- the charging power of the charging stations can be further increased in the future. Charging stations with a high charging power, which are located on roads with a high
- Traffic density can, for example, have a high expected occupation. Charging columns with a high charging power and a low expected charging, for example, may be preferred for the charging strategy.
- data is provided at a current electricity price of the charging stations. Further, the expected
- the data for a current electricity price of the charging stations can, for example, contain information about a current price of the current of the charging stations, for example ( € / kWh).
- Different charging stations can, for example, have different electricity prices.
- the electricity price of a charging station can for example, vary over time. Charging columns with a high electricity price, for example, a low
- Charging columns with a low electricity price may be preferred for the charging strategy.
- Electricity price of the charging stations is an information to
- the information on the current electricity price of the charging stations allows the driver to choose between one
- the information on the expected filling of the charging stations makes it easier for the driver to decide for one
- Charging point along the route is for example relevant if the driver wants to load the vehicle at a later date.
- the invention relates to a
- the device for route planning for a vehicle, wherein the device is designed to carry out the method according to the first aspect.
- the device comprises
- a data processing device the signal technology is coupled to the vehicle and the charging stations.
- the invention relates to a
- Computer program for route planning for a vehicle The computer program is designed to carry out the method according to the first aspect.
- the invention relates to a
- Computer program product comprising executable program code, the program code being executed by a
- Data processing apparatus performs the method according to the first aspect.
- the computer program product comprises a medium which can be read by the data processing device and on which the program code is stored.
- Figure 1 is a flowchart of a program for
- FIG. 2 shows a system for route planning for a vehicle.
- FIG. 1 shows a flow chart of a route planning program for a vehicle 101 (see FIG. 2).
- a device 102 (see FIG. 2) is designed, for example, to execute the program.
- the device 102 has for this purpose in particular a computing unit, a
- Program and data storage as well as, for example, one or more communication interfaces.
- Communication interfaces may be formed in a unit and / or distributed over several units.
- the device 102 can also be used as a device for
- Route planning for a vehicle 101 are called.
- the device 102 is designed, for example, in a central system.
- the central system can represent, for example, a back end that with vehicles 101 of a
- Vehicle inventory and charging stations 103a, 103b a Vehicle inventory and charging stations 103a, 103b a
- the central system may be, for example, an artificial intelligence-based predictive system.
- the device 102 is embodied in a vehicle 101 and / or in a mobile unit, such as a smartphone.
- the program for route planning for a vehicle 101 is stored on the program and data memory of the device 102.
- the program is started in a step S1 in which, for example, variables are initialized.
- the program is then continued in a step S3.
- step S3 data becomes a specified route
- These data include, for example, a
- Starting point S for example, represents the current position of the vehicle 101, and an end point D, the
- a selected by the driver destination of the specified route can represent.
- step S5 traffic data 15 representative of an actual traffic density of the specified route is provided.
- the current traffic density may be at
- the program is then continued in a step S7.
- step S7 historical traffic density data 17 is provided, the data being historical
- Traffic density 17 include information about a traffic density along the route to past time points.
- the historical traffic density of a road may include information about a traffic density pattern of the road, for example, during certain times of the day or on holidays.
- the program is then continued in a step S9.
- weather data 16 is provided which is representative of a weather condition along the route.
- the program is then continued in a step Sil.
- step S data on a current location and / or consumption and / or speed and / or charging status of the vehicle 21 are provided.
- the device 102 may provide data on a current location and / or consumption and / or
- the charging status for the charging of the vehicle battery can be representative. These data can be used to search for charging stations 103a, 103b near the
- Vehicle 101 and / or the determination of the range of the vehicle battery and / or the prediction of the time of arrival of the vehicle 101 at the respective charging stations 103a, 103b be relevant.
- the program is then continued in a step S13.
- step S13 data for the current occupation of the
- Charging columns 31 are provided.
- the communication between the charging columns 103 and the device 102 enables the
- step S15 information about the current occupation of charging stations 22 for the driver is provided depending on the data for the current occupation of the charging stations.
- the information on the current occupation of the charging stations 22 makes it easier for the driver to choose the next one
- step S17 data for the historical occupation of the charging columns 18 are provided, wherein the data for
- historical occupation of the charging stations 18 includes information on occupation of the charging stations 103a, 103b along the route to past times. For data on the current occupation of the charging stations 31 over time
- Charging columns 18 may for example be provided by a database.
- the program is then continued in a step S19.
- step S19 data about a charging power of the
- Charging posts 32 are provided along the route.
- Charging power of the charging posts 103a, 103b For example, charging stations 103a, 103b that have high traffic densities and high charging power can have high expected occupancy.
- the program is then continued in a step S21.
- step S21 data is provided about a current electricity price of the charging columns 33 along the route.
- charging stations 103a, 103b having a high electricity price may have a low expected population.
- step 23 depending on the data on the current electricity price of the charging stations 33, information about the current electricity price of the charging stations 25 is made available to the driver.
- the information about the current electricity price 25 can enable the selection of charging stations with a favorable electricity price for the driver.
- the program is then continued in a step S25.
- step S25 data for the expected occupation of the charging columns 103a, 103b is determined.
- the traffic data 15 can be used. For a better one
- Determining the expected occupation further data, for example, the data on the historical traffic density 17 can be used. If a charging station 103a, 103b
- Speed and / or battery charge status of the vehicle 21 may also be used to better determine the expected
- This data may be the time of arrival of the vehicle 101 at the charging stations 103a, 103b and / or the charging time of the
- Influence vehicle battery at the respective charging stations 103a, 103b The consideration of the data for the current occupation of the charging stations 31 and / or the data for
- Historical occupation of the charging columns 18 may also allow a better determination of the expected occupation of the charging columns 103a, 103b. For charging stations located near the vehicle 101, the expected occupancy can be correlated with the current occupation. The data for historical occupation of the charging stations 18 included
- a staffing pattern of the charging stations 103a, 103b for example during different times of day and / or on working days and / or holidays. For example, if a charging station 103a, 103b has a high historic cast at the weekend, it is likely that the expected cast at the weekend is also high.
- the charging power data of the charging columns 32 may be better
- charging stations 103a, 103b which are located on roads with a low traffic density and have a high charging power, may have a low expected population.
- the data on the current electricity price of the charging stations 33 can also enable a better determination of the expected charging of the charging stations 103a, 103b.
- charging stations 103a, 103b may be the one
- step S27 information about the expected occupation of the charging stations 23 along the predetermined route for the driver is provided depending on the determined expected occupancy.
- the information on the expected occupation of the charging stations 23 makes it easier for the driver to select a charging point along the specified route, for example, if he wishes to charge the vehicle 101 at a later time. For example, if the expected population of charging stations 103a, 103b in a coming leg of the route is high, the driver may decide to charge the vehicle 101 at one of the next lower load charging stations 103a, 103b, even if the battery is not yet empty.
- This information can, for example, as a graphic for a dashboard and / or a
- a charging strategy for the predetermined route is determined.
- the charging strategy may be determined based on the traffic data 15 and the expected population of the charging posts 103a, 103b. For example, a
- Loading strategy may be preferred charging stations 103a, 103b, which are located on roads with a lower traffic density.
- traffic density is up, for example due to a traffic accident while the route changes, the charging strategy can be redetermined depending on this change.
- the charging strategy can be redetermined depending on this change. If the expected occupation of the charging columns 103a, 103b changes, for example due to the failure of a charging station 103a, 103b, during the route, the charging strategy can be redetermined depending on this change.
- Charging columns 103a, 103b on roads with a lower historical traffic density at the time of arrival of the vehicle 101 may be preferred for determining the charging strategy, for example.
- the onset of weather data 16 may also allow better determination of the charging strategy. Charging columns 103a, 103b which are located on routes of the route with good weather conditions are preferred, for example, for determining the charging strategy.
- Charging status of the vehicle 21 may also be better
- This data can be used, for example, for route planning based on the range of the vehicle battery.
- these data are used, for example, together with other data such as the weather data 16 for the determination of an expected occupation of charging stations 103a, 103b and a charging strategy with the aim of allowing a reduction of the driving time with regard to the range of the vehicle 101.
- the data for historical occupation of the charging columns 18 contain information about a population pattern of the charging columns 103a, 103b, for example, during various Time of day and / or working days and / or public holidays.
- charging stations 103a, 103b which have a low historical occupation at the time of arrival of the vehicle 101, may be preferred.
- Charging power of the charging columns 32 may allow a better determination of the charging strategy. For example,
- Charging columns 103a, 103b which have a high charging power and a low expected occupation for the determination of
- Electricity price of the charging posts 33 can allow a better determination of the charging strategy. Charging columns 103a, 103b with a low electricity price may be preferred for determining the charging strategy.
- the aim of the charging strategy is to reduce the driving time as far as possible for the specified route.
- the charging strategy offers the driver, for example, information about one
- step S31 depending on the determined
- the charging strategy offers the driver an indication for charging the vehicle battery, not only dependent on the battery state of charge but also depending on the utilization of the charging posts 103a, 103b. For example, instead of a driver driving on the highway loading his vehicle 101 into a fast-loading fast-loading tower 103a, 103b, the vehicle 101 may be more time-saving at a charging station 103a, 103b that is not directly on the highway a smaller cast has to load.
- the charging strategy allows both time-efficient and cost-efficient charging of the vehicle 101 for the driver
- Loading strategy 24 to the driver thus leads to reducing the required travel time to reach a predetermined
- this information may include a proposal for a route change, so that the route has one or more proposed charging stations 103a, 103b as intermediate destinations.
- This information can be used as a graphic for example
- Dashboard and / or a central display unit and / or a head-up display and / or a smartphone are displayed.
- a step S33 the program is ended and may optionally be started again in the step S1.
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Applications Claiming Priority (2)
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DE102017215792.5A DE102017215792B4 (en) | 2017-09-07 | 2017-09-07 | Method, device, computer program and computer program product for route planning for a vehicle |
PCT/EP2018/063059 WO2019048086A1 (en) | 2017-09-07 | 2018-05-18 | Method, device, computer program and computer program product for route planning for a vehicle |
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WO (1) | WO2019048086A1 (en) |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US11060877B2 (en) * | 2018-12-03 | 2021-07-13 | Ford Global Technologies, Llc | Opportunistic fueling for autonomous vehicles |
CN112298290B (en) * | 2019-07-31 | 2021-12-07 | 比亚迪股份有限公司 | Train operation control method and device and non-transitory computer readable storage medium |
JP2023018846A (en) * | 2021-07-28 | 2023-02-09 | トヨタ自動車株式会社 | Operation system, operation method, and operation program |
CN113607179A (en) * | 2021-07-30 | 2021-11-05 | 车主邦(北京)科技有限公司 | Navigation end point determining method and device, electronic equipment and storage medium |
US11913797B2 (en) * | 2021-11-18 | 2024-02-27 | Honda Motor Co., Ltd. | Systems and methods for selecting a charging entity based on occupancy status |
Family Cites Families (33)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2010033517A2 (en) * | 2008-09-19 | 2010-03-25 | Better Place GmbH | System and method for operating an electric vehicle |
DE102009016869A1 (en) * | 2009-04-08 | 2010-10-14 | Li-Tec Battery Gmbh | Method for operating a vehicle |
JP5017398B2 (en) * | 2010-03-09 | 2012-09-05 | 日立オートモティブシステムズ株式会社 | Route planning apparatus and route planning system |
EP2385349A1 (en) * | 2010-05-06 | 2011-11-09 | Leica Geosystems AG | Method and guidance unit for guiding battery-operated transportation means to reconditioning stations |
US8538694B2 (en) * | 2010-05-21 | 2013-09-17 | Verizon Patent And Licensing Inc. | Real-time route and recharge planning |
US20110225105A1 (en) * | 2010-10-21 | 2011-09-15 | Ford Global Technologies, Llc | Method and system for monitoring an energy storage system for a vehicle for trip planning |
US8577528B2 (en) * | 2010-11-16 | 2013-11-05 | Honda Motor Co., Ltd. | System and method for updating charge station information |
US8538677B2 (en) * | 2010-12-30 | 2013-09-17 | Telenav, Inc. | Navigation system with constrained resource route planning mechanism and method of operation thereof |
DE102011015777A1 (en) | 2011-04-01 | 2012-10-04 | Volkswagen Aktiengesellschaft | Method and apparatus for carrying out itinerary planning for a vehicle |
JP5516550B2 (en) * | 2011-05-09 | 2014-06-11 | 株式会社デンソー | Vehicle navigation device |
JP6399928B2 (en) * | 2011-08-16 | 2018-10-03 | チャージ ピーク リミテッド | Load estimation and management in electric vehicle networks |
US8838385B2 (en) * | 2011-12-20 | 2014-09-16 | Ford Global Technologies, Llc | Method and apparatus for vehicle routing |
CN104145224B (en) * | 2012-01-09 | 2016-08-24 | 爱尔比奎特公司 | Electric vehicle charging network service method |
JP5774534B2 (en) * | 2012-03-30 | 2015-09-09 | 株式会社日立製作所 | Electric vehicle route search system and method |
DE102012210698A1 (en) * | 2012-06-25 | 2014-01-02 | Robert Bosch Gmbh | Method for carrying out an energy management of a vehicle |
WO2014074722A1 (en) * | 2012-11-07 | 2014-05-15 | Intertrust Technologies Corporation | Vehicle charging path optimization systems and methods |
US9644969B2 (en) * | 2013-02-26 | 2017-05-09 | Polaris Industries Inc. | Recreational vehicle interactive telemetry, mapping, and trip planning system |
EP2826688B1 (en) * | 2013-07-17 | 2020-09-09 | Volvo Car Corporation | Method for optimizing the power usage of a vehicle |
US9285240B2 (en) * | 2013-08-07 | 2016-03-15 | Qualcomm Incorporated | EV route optimization through crowdsourcing |
US9205754B2 (en) * | 2013-09-30 | 2015-12-08 | Elwha Llc | Communication and control regarding electricity provider for wireless electric vehicle electrical energy transfer |
US9448083B2 (en) * | 2014-02-25 | 2016-09-20 | Ford Global Technologies, Llc | Method and apparatus for providing a navigation route with recommended charging |
JP6376619B2 (en) * | 2014-04-04 | 2018-08-22 | テスラ・インコーポレーテッド | Itinerary planning under energy constraints |
US10112497B2 (en) * | 2014-04-11 | 2018-10-30 | Nissan North America, Inc. | System and method of monitoring usage of a charging station |
US9513135B2 (en) * | 2014-09-16 | 2016-12-06 | Ford Global Technologies, Llc | Stochastic range |
US20160332585A1 (en) | 2015-05-15 | 2016-11-17 | Richard Gary John BAVERSTOCK | Systems and methods for efficient resource management during vehicular journeys |
DE102016005630A1 (en) * | 2016-05-06 | 2017-11-09 | Audi Ag | Data processing unit for communication between at least one motor vehicle and between a plurality of charging stations for charging an energy storage device of a motor vehicle |
US10525848B2 (en) * | 2016-08-02 | 2020-01-07 | Here Global B.V. | Vehicle charging lanes |
CN106505657B (en) * | 2016-10-19 | 2019-07-26 | 上海工业控制安全创新科技有限公司 | Charging pile charging system and method for the distribution based on user's geographical location information |
US10515390B2 (en) * | 2016-11-21 | 2019-12-24 | Nio Usa, Inc. | Method and system for data optimization |
US10288439B2 (en) * | 2017-02-22 | 2019-05-14 | Robert D. Pedersen | Systems and methods using artificial intelligence for routing electric vehicles |
US10464547B2 (en) * | 2017-07-13 | 2019-11-05 | GM Global Technology Operations LLC | Vehicle with model-based route energy prediction, correction, and optimization |
US20190107406A1 (en) * | 2017-10-09 | 2019-04-11 | Nio Usa, Inc. | Systems and methods for trip planning under uncertainty |
GB2572962A (en) * | 2018-04-16 | 2019-10-23 | Morgan Brown Consultancy Ltd | Vehicle Routing |
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US11705001B2 (en) | 2023-07-18 |
DE102017215792A1 (en) | 2019-03-07 |
CN111033179A (en) | 2020-04-17 |
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