CN103868518A - Navigation path planning computer program product for electric vehicles - Google Patents

Abstract

The invention discloses a computer program product for planning a path of an electric traffic carrier, which is characterized in that a navigation system loads a navigation path planning program, wherein the navigation system comprises a map database, an input interface, a processing module and an output interface; the navigation path planning computer program product defines the starting point as the current planning point by using the map information of the map database, and calculates the navigation path with the minimum total mileage cost of each path as the best by using the path objective function. The route objective function comprises consumed mileage cost, namely the distance cost of the mileage to be consumed and the route multiplied by the residual cost of the whole power consumption weight; the overall power consumption weight can be further divided into a charging station active weight related to the charging station characteristic and a road priority weight related to the road characteristic. Therefore, the navigation planning of the optimal path can be provided for the electric transportation vehicle.

Description

Navigation path planning computer program product for electric vehicles

technical field

The invention relates to a computer program product for planning a navigation route of an electric transportation vehicle, in particular to a computer program product for planning an electric transportation vehicle by executing a path objective function including an overall power consumption weight related to charging station characteristics and road characteristics A computer program product for an optimized path.

Background technique

With the advancement of science and technology and the development of the times, people's concept of life has gradually changed, so they gradually pay attention to the quality of life, which in turn led to the prevalence of car travel. In order to facilitate people to go to their destinations more quickly and accurately, so satellite navigation Route planning computer program products have become an essential tool for people to travel by car. It uses electronic maps and Global Positioning System (Global Positioning System; GPS) to plan routes and navigate, that is to say, users only need to input the destination they want to go to After landing, the satellite navigation route planning computer program product will assist the user to find the optimal route to the destination according to the user's location.

However, with the rising awareness of environmental protection in recent years, the development of electric vehicles has been paid attention to. In the existing satellite navigation route planning computer program products, although the optimized route can be planned, the location of the charging station is generally not included in the optimized route plan. And because electric vehicles have the limitation of battery life, therefore, although the satellite navigation route planning computer program product can plan the optimized route, the battery life of existing electric vehicles is limited, so that electric vehicles still need to find a place to charge The station deviates from the optimal path, and cannot reach the destination according to the planned optimal path, which makes the navigation effect poor.

At present, various navigation path planning methods such as Ant Colony Optimization (ACO), Dijkstra (Dijkstra) algorithm, A* algorithm or Moore (Moore/Pape) algorithm; ant colony algorithm usually For the planning of random paths, the Dijkstra algorithm starts from the periphery of the starting point and determines the shortest path to each node one by one; the Moore/Pape algorithm is the calculation method of the shortest path, which is the fastest in many-to-many calculations. But it is not suitable for one-to-many calculation; and the calculation with less calculation amount and suitable for one-to-many calculation is A* algorithm, which mainly defines an objective function, and then differentiates this objective function to obtain the maximum value of the objective value (Minimum value), the objective function usually uses F=G+H to calculate the cost, and find the minimum cost as the result to plan the path; where F is the estimated cost from the initial point to the target point, G is from the initial point to a certain node The actual cost, H is the estimated cost of the best path from a node to the target point; and this algorithm usually uses the road attributes, length and required time of the electronic map data as the calculation basis.

In the prior art of various navigation path planning methods, such as the navigation prompt method disclosed in Taiwan Patent No. TW201122433, the cost difference between the deviated route and the optimized route is generated by calculating the cost of different paths, and the path with the smallest difference is The path of navigation prompts; another example is Taiwan Patent No. TW201211508, which discloses the use of map data and the identification of the minimum cost path to determine the route from the starting point to the destination; these disclosed technologies only consider the mileage-related costs in the objective function, The most relevant power consumption characteristics of a car cannot be used directly. In addition to the mileage of an electric vehicle, the overall power consumption characteristics are directly related to the type of road, whether there is a charging station or what type of charging station it is. U.S. Patent Publication No. US20120010767 discloses that a hybrid electric vehicle (HEV) uses the Battery State-of-charge (SoC) as an optimized objective function, as shown in Figure 1, in the driving path 9 from the starting point Ps to the end point Pt passes through several nodes (Pr1, Pr2, Pr3 and Pr4), calculates the battery power state of each node and lists the possible battery power states (SoC ¹ , SoC ² , ..., SoC ⁿ ), through the optimized Calculation, calculate the combination of the best SoC of each node, and then add the road level to the consideration of path selection in the follow-up navigation, but the road characteristics are not included in the calculation of the objective function in the disclosed technology; moreover, the US patent US8204638 incorporates the driving speed into the objective function of the hybrid vehicle to calculate the optimal dynamic path; US5913917 uses the quantitative characteristics of the roadway as the weight.

However, due to the limited power of electric transportation vehicles, when the existing navigation route planning computer program products or calculation methods are applied to electric vehicles, the consideration factors for the optimized route planning are only calculated based on the mileage cost or the fraction of the number of roadways added. is the weight, and does not include the overall power consumption; but in fact, the cost of road mileage is not only related to the distance, but should consider the overall power consumption and the power consumption of different road attributes (such as expressways, expressways, Provincial roads, county roads, township roads, general roads, and other roads have different power consumption characteristics) and whether there are charging stations, etc., only use the mileage cost, time cost, or the quantity characteristics of the roadway as the weight and other calculation methods , which is different from the power consumption of the actual electric vehicle, it cannot be specifically applied to the navigation system of the electric vehicle.

Contents of the invention

The main purpose of the present invention is to provide a computer program product for navigation route planning of electric transportation vehicles. The route objective function is defined by the mileage cost and the overall power consumption weight. After calculating the total mileage cost of each route, an optimized route is planned. In this way, a navigation computer program product more suitable for the electric vehicle is provided.

To achieve the above object, the present invention adopts the following technical solutions:

A navigation path planning computer program product, which mainly considers the overall power consumption factor in the consideration factors of planning an optimized path; the navigation path planning computer program product is suitable for a navigation system, and the navigation system is configured in a vehicle-mounted computer, a notebook computer, Map navigation computer, handheld computer, smart phone, etc. are not limited; the navigation system includes a map database, an input interface, a processing unit and an output interface; the navigation system (navigation system) is loaded with navigation path planning program, perform the following steps:

S1: The user uses the input interface and the map database to define the starting point (starting point) as the current planning point (current point), and the navigation path planning program plans at least two paths n from the current planning point to the end point;

S2: The processing module uses the map database and the current planning point to load the map information including at least two relay nodes and the map information of the charging station location; find out each relay node adjacent to the current planning point for each path i( i=1, 2,..., i,...N paths), each path i includes a relay node, if there is a charging station on the path i, then the path i also includes the location of the charging station;

S3: The processing module calculates the total mileage cost Fi of each route i of the current planning point through the relay node through the route objective function (route objective function) F(n) of the navigation route planning program; wherein the route objective function F(n) is as follows Formula (1) defined:

F(n)＝G(n)+H(n) ...(1)

Among them, F(n) is the total mileage cost function of path n, G(n) is the cost function of the consumed mileage, and H(n) is the residual mileage cost function; among them, the cost function of H(n) residual mileage is shown in formula (2) Expanded:

F(n)=G(n)+H(n)

＝G(n)+h(n)·W(n)  …(2)

Among them, h(n) is the straight-line distance cost function from the current planning point to the end point, W(n) is the overall power consumption weight function; formula (2) represents the residual mileage cost function H(n) is the straight-line distance cost function of the residual mileage The product of h(n) and the overall power consumption weight function W(n), which means that the residual mileage cost is not only the cost of the distance, but should still be multiplied by the weight of the overall power consumption;

S4: The navigation path planning program minimizes the path objective function F(n), that is, finds the minimum total mileage cost F* of the path, and calculates the relay node corresponding to the minimum total mileage cost, which is defined as the continuing node (approaching node); wherein, the optimized path is a set of paths from the starting point to the end point along at least one of the above-mentioned continuous travel nodes; wherein, the total mileage cost F _i and the path objective function optimization of each path i are as formula (3) and formula ( 4):

F _i =G+(h _i ·W) ......(3)

${\mathrm{<span\; class="notranslate">\; f</span>}}^{<span\; class="notranslate">\; *</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; G</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&CenterDot;</span>\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

S5: when the electric vehicle travels to the next traveling node, the navigation route planning program judges whether the following traveling node is an end point; and

S6: When the judgment result of step S5 is negative, the navigation route planning program redefines the continuation travel node as the above starting point, and repeats the above steps S1 to S5; the output interface outputs the execution process or execution result of the navigation route planning program.

Wherein, in step S3, the mileage cost function G(n) is the actual mileage cost function G ₁ (n) of each relay node that has actually traveled from the starting point and the mileage cost function G ₂ ( The sum of n), the overall power consumption weight W is the product of the charging station weight Ws defined by the charging station location and the road weight Wr, such as formula (5) and formula (6);

F(n)=G(n)+H(n)

=G ₁ (n)+G ₂ (n)+h(n)·W ...... (5)

Use formula (5) to calculate the i-th path with the path objective function F(n), the mileage cost function G(n), the actual mileage cost function G ₁ (n) and the mileage cost function G ₂ (n) to be consumed When the total mileage cost F _i of , find out the consumed mileage cost G _i of each route i of each relay node adjacent to the current planning point and the residual mileage cost H _i corresponding to each route i in the open list; , the consumed mileage cost G _i is the sum of the actual consumed mileage cost G _1i and the upcoming mileage cost G _2i of each relay node that has actually traveled from the starting point; the remaining mileage cost Hi is the straight line from the relay node to the end point The distance cost h _i and the overall power consumption weight W of each path i are calculated.

Preferably, in a navigation system of the present invention, the navigation route planning program of the navigation system further performs the following steps in step S1:

S11: The navigation path planning program puts each relay node adjacent to the current planning point into an open list (open list).

In step S5, the following steps are further performed:

S51: The navigation path planning program puts the next traveling node into a close list (close list).

与道路权重

的积如式(6)；Preferably, the present invention is a navigation route planning computer program product. When the processing module calculates the total mileage cost Fi of each route i through the route objective function F(n ₎ of the navigation route planning program, the overall power consumption weight W is given by Charging station weight defined by charging station location

with road weight

The product is as formula (6);

$\mathrm{<span\; class="notranslate">\; W</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; \&Pi;</span>}<span\; class="notranslate">\; (</span>\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; ,</span>\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

Among them, the charging station weight It can be decomposed into the mileage cost contribution due to the location of the charging station (the active weight Ws of the charging station) and the mileage cost contribution due to the type of charging station (the weight Wst of the charging station type), as shown in formula (7);

$\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; \&Pi;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; Wst</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

可分解为因道路等级所产生的里程成本贡献(道路优先权重Wr)、因不同道路等级所产生的耗电贡献(耗电速率权重Wc)及因不同的道路连接等级所产生的耗电贡献(连结道路种类权重Wct)，如式(8)：road weight

It can be decomposed into mileage cost contribution due to road grades (road priority weight Wr), power consumption contribution due to different road grades (power consumption rate weight Wc), and power consumption contribution due to different road connection grades ( Link road type weight Wct), such as formula (8):

$\stackrel{<span\; class="notranslate">\; ^</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; \&Pi;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; Wr</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; wc</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; Wct</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; .</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

Preferably, a computer program product for navigation route planning in the present invention further includes a weight database, which stores various weight data, including charging station active weight Ws, charging station type weight Wst, road priority weight Wr, power consumption The data of the speed weight Wc and the weight Wct of the connected road type; can be pre-input and updated by the user through the input interface, or downloaded and updated in advance through the navigation system, or built into the weight database. The weight database can also be combined with the map database. limited.

道路权重

可自行定义其态样：In the subsequent implementation, the proposed example weights the charging station

road weight

You can define its appearance yourself:

The value of the active weight Ws of the charging station, such as: the weight value of the charging station in service, the weight value of the charging station without service, is not limited;

The value of the weight Wst of the type of charging station, such as: the weight value of the type of fast charging station, the weight value of the type of rechargeable battery replacement station, and the weight value of the type of mobile charging station are not limited;

The value of road priority weight Wr, such as: expressway priority weight value, express road priority weight value, provincial road priority weight value, county road priority weight value, township road priority weight value, urban main road priority weight value, urban secondary road priority weight value, There is no limit to the priority weight values of roads and alleys;

The value of power consumption rate weight Wc, such as: power consumption weight value of expressways, power consumption weight value of express roads, power consumption weight value of provincial roads, power consumption weight value of county roads, power consumption weight value of township roads, power consumption weight value of main roads in urban areas The power weight value, the power consumption weight value of the secondary roads in the urban area, and the power consumption weight value of the alleys are not limited;

The value of the weight Wct of the link road type, such as: the weight value of the ring type, the general road type weight value, the main road type weight value, the system interchange type weight value, the integrated intersection type weight value, the interchange type weight value, the side road type The weight value and the weight value of the rest stop type are not limited.

The computer program product for navigation route planning of an electric vehicle of the present invention may have one or more of the following advantages:

The navigation route planning computer program product of the transportation vehicle of the present invention can plan the navigation route of the electric transportation vehicle through the map information of the map database through the processing module, and calculate that the electric transportation vehicle arrives at the end point from the starting point via the relay node The optimal path; it can make the electric vehicle use the minimum total mileage cost to reach the destination from the starting point.

The navigation route planning computer program product of the transportation vehicle of the present invention adopts the mileage cost and power consumption weight as the path objective function in the optimized route planning, so that the most important power consumption factor of the electric transportation vehicle can be weighted to the mileage cost , so that the path objective function is consistent with the most basic requirements of electric transportation vehicles, the optimal path obtained by calculation not only considers the mileage cost, but also weighs the power consumption factor; compared with the existing technology, due to the existing satellite navigation path When planning computer program products to be applied to electric transportation vehicles, the factors considered in the optimized route planning do not include power consumption factors, so that the total mileage cost of electric vehicles will increase due to different road conditions or charging, that is, The driving path is not the shortcoming of the real optimized path of the electric transportation vehicle; further explanation, due to the limited power of the electric transportation vehicle, it often needs to be charged due to insufficient power in the middle, and the navigation path planning of the electric transportation vehicle in the prior art does not consider the The mileage cost caused by charging makes the electric vehicle still need to find a charging station and deviate from the optimal route to a certain location, which makes the navigation effect poor.

The computer program product for navigation route planning of transportation vehicles of the present invention can be closer to electric transportation vehicles in terms of optimized route planning, and the weighted power consumption factors can be comprehensively added with various power consumption factors, Such as the active weight of charging stations, the weight of charging station types, the weight of road priority, the weight of power consumption rate, the weight of connecting road types, etc., which improve the accuracy and practicality of electric vehicle navigation.

The present invention proposes a navigation computer program product for electric transportation vehicles. The navigation system can be used to load the navigation path planning program, and the user uses the input interface and the map database to define the starting point and the end point. The navigation path planning program is based on the map information of the map database. And data data, can calculate the route with the minimum mileage and cost that has considered the factor of power consumption, and display it on the display interface, and provide it to the driver of the electric vehicle for reference.

Description of drawings

FIG. 1 is a schematic diagram of a prior art path planning method;

Fig. 2 structure diagram of computer program product of navigation route planning of the present invention;

Fig. 3 is a schematic diagram of the application of the navigation path planning computer program product of the present invention;

Fig. 4 shows a schematic diagram of the execution steps of the navigation route planning program of the navigation route planning computer program product in a preferred embodiment of the present invention;

FIG. 5 shows a schematic diagram of route planning of a navigation route planning computer program product according to a preferred embodiment of the present invention; and

6A to 6D are schematic diagrams showing a preferred embodiment of the present invention applied to route planning of a navigation route planning computer program product.

[Description of main component symbols]

10: Navigation route planning computer program product 11: Navigation system

111: Map database 112: Input interface

113: Processing module 114: Output interface

12: Navigation path planning program 13: Weight database

A: starting point B1, B2, B3: relay nodes

C1, C2, C3: relay nodes Cs, Cs1, Cs2, Cs3, Cs4, Cs5, Cs6: charging stations

D1, D2, D3: Relay nodes E, Pt: Terminal

Pa: Continuing travel node Pc: Current planning point

Pr, Pr1, Pr2, Pr3: relay nodes Ps: starting point

R*: Optimization path S1～S6: Execution steps

Detailed ways

In order to make the present invention clearer and more specific, preferred embodiments are listed hereby together with the following diagrams, and the structure and technical features of the present invention are described in detail below.

Please refer to FIG. 2 , which is a structure diagram of a navigation route planning computer program product of the present invention. In the figure, a navigation route planning computer program product 10 includes a navigation system 11 and a navigation route planning program 12, and the navigation system 11 uses the navigation route planning program 12 Loading to execute navigation route planning, the navigation system 11 is composed of a map database 111, an input interface 112, a processing module 113 and an output interface 114; the map database 111 stores locations, road types, connecting road types, and distances within the driving range. (or the coordinates of each location), and even the map database 111 stores data such as the location of the charging station, whether the charging station is available for charging, the type of the charging station, etc.; the processing module 113 is usually composed of hardware, software and firmware, and can Accept the data entered by the input interface 112 , acquire data from the map database 111 or other databases (such as the weight database 13 ), execute software programs, perform mathematical or logical operations, etc., and display the calculated information on the output interface 114 . Please refer to FIG. 3 , which is a schematic diagram of the application of the navigation route planning computer program product of the present invention. The navigation system 11 is illustrated by a map navigation computer, and the weight database 13 can be read in the form of a storage card (such as an SD card). It is not limited thereto; the calculated optimal route can be displayed on the screen of the map navigation computer (output interface 114 ).

Please refer to FIG. 5 , which shows a schematic diagram of the planning method of the navigation route planning method according to the embodiment of the present invention. In the figure, the navigation route planning method plans and calculates the electric vehicle from the starting point Ps via the relay node Pr1 and the relay node Pr2 (path 1: Pr1→Pr2) or the optimal route (optimal route) to reach the destination Pt via the relay node Pr1 via the charging station Cs and the relay node Pr3 (path 2: Pr1→Cs→Pr3). Please refer to FIG. 4 , which shows a schematic flow chart of a method for planning a navigation path according to an embodiment of the present invention. In the figure, the method for planning a navigation path includes the following steps:

S1: Utilize the map database 111 to define a current planning point Pc, and plan at least two paths n from the current planning point Pc to the terminal point Pt; list each relay node (Pr) adjacent to the current planning point Pc into open list; wherein, if the electric vehicle starts from the starting point Ps, when planning the path for the first time, the starting point Ps defines a current planning point Pc; if the electric vehicle travels to the relay node Pr1 when planning the next path, The relay node Pr1 is the defined current planning point Pc;

S2: Using the map database 111, load the map information of each relay node (Pr) adjacent to the current planning point Pc and load the map information of each charging station location (Cs) adjacent to the current planning point Pc; find out the adjacent Each relay node at the current planning point Pc is each path i (i=1, 2, ..., i, ... N paths), each path i includes at least one relay node, if the path i If there is a charging station, the path i also includes the location of the charging station;

In steps S1 and S2, taking the preferred embodiment of the navigation route planning computer program product 10 applied to the transportation vehicle of the present invention as an example, the starting point Ps is defined as the current planning point by the navigation system 11 or by the user using the input interface 112 Pc, the navigation system 11 uses the map information of the map database 111 to put each relay node adjacent to the current planning point Pc into the open list. Furthermore, after the user sets the start point Ps and the end point Pt through the navigation route planning computer program product 10 in the electric vehicle, and confirms to start planning the route, the navigation system 11 will start the navigation route planning program 12 to automatically In the map database 111 (the map database 111 is located in the database of the navigation route planning computer program product 10 or in the cloud system database), load the map information including at least two charging station positions Cs and at least two relay nodes Pr, and list At least two relay nodes that need to pass through in the optimized path from the start point Ps to the end point Pt, then define the start point Ps as a current planning point Pc, and then list each relay node Pr adjacent to the start point Ps into the open list. For example, if the user takes Taichung as the starting point Ps and Taipei as the ending point Pt, then the relay nodes (Pr) adjacent to Taichung include Dajia, Houli and Fengyuan, so the system will use Dajia, Houli The three relay nodes in Li and Fengyuan are included in the opening list; for different display screen designs, the navigation system 11 can display the opening list or other information on the output interface 114 .

S3: Through the path objective function F(n), calculate the total mileage cost F _i of each path i; where the total mileage cost F _i is defined according to the path objective function F(n), as shown in formula (9):

F _i =G _i +H _i ... (9)

Among them, F _i is the total mileage cost of route i, G _i is the consumed mileage cost, and H _i is the residual mileage cost; among them, the H _i residual mileage cost of route i can be calculated as defined in formula (2), and the total mileage cost F _i is calculated as formula (10):

F _i =G _i +H _i

＝G _i +h _i ·W _i ......(10)

的乘积。Among them, h _i is the straight-line distance cost from the current planning point Pc to the end point Pt of path i, W _i is the weight value of the overall power consumption of path i; formula (10) represents that the residual mileage cost function H _i is equal to the straight-line distance cost h _i of the residual mileage and the overall power consumption weight value W _i ; where, the mileage cost G _i of path i is the actual mileage cost G _1i of each relay node that has actually traveled from the starting point Ps and the cost function of the mileage to be consumed The sum of G _2i and the overall power consumption weight W _i is the weight of the charging station defined by the location of the charging station with road weight

product of .

可为充电站现役权重Ws与充电站种类权重Wst的乘积；道路权重

可为道路优先权重Wr、耗电速率权重Wc及连接道路种类权重Wct的乘积；因此，总里程成本F_i计算如式(11)；And charging station weight

It can be the product of the active weight Ws of the charging station and the weight Wst of the charging station type; the road weight

It can be the product of road priority weight Wr, power consumption rate weight Wc and connection road type weight Wct; therefore, the total mileage cost F _i is calculated as formula (11);

F _i =G _1i +G _2i +h _i ·W _i

=G _1i +G _2i +h _i ·(Ws·Wst·Wr·Wc·Wct) ...(11)

In step S3, taking the preferred embodiment of the navigation system 10 applied to the vehicle of the present invention as an example, the processing module 113 and the navigation path planning program 12 calculate the total mileage cost F _i for each path i according to the path objective function F(n) , taking the above-mentioned three relay nodes of Dajia, Houli and Fengyuan as examples, the processing module 113 and the navigation route planning program 12 calculate the total mileage cost F ₁ via Dajia, the total mileage cost F ₂ via Houli, and The total mileage cost F ₃ via Fengyuan; for different display screen designs, the navigation system 11 can display the total mileage cost of each route and its order of magnitude or other information on the output interface 114 .

S4: Minimize the path objective function F(n), that is, find the minimum total mileage cost (F _i , i=1, n) of the path in each path as F*, and calculate the minimum total mileage cost corresponding to A relay node is defined as an approaching node Pa (approaching node); wherein, the optimized path is a set of paths traveling from the starting point Ps along at least one of the aforementioned approaching nodes Pa to the end point Pt.

In step S4, taking the preferred embodiment applied to the navigation route planning computer program product 10 of the present invention as an example, the processing module 113 and the navigation route planning program 12 find the minimum total mileage cost F* in the total mileage cost F _i , and The corresponding relay node is defined as the next traveling node Pa. Furthermore, taking the above three nodes of Dajia, Houli and Fengyuan as examples, assuming that the route to Dajia has a charging station and the total mileage cost F is the lowest, then the navigation route planning computer program product 10 immediately selects The relay node Pr of Dajia is used as the continuing travel node Pa, indicating that Dajia is the relay node for the next driving; for different display screen designs, the navigation system 11 can use each path and the preferred continuous traveling node Pa or other information as Icons or text are displayed on the output interface 114 .

S5: When the electric vehicle travels to the next node Pa, determine whether the next node Pa is the end point Pt; if the next node Pa is the end point Pt, enter the next node Pa into the closed list.

In step S5, taking the preferred embodiment applied to the navigation route planning computer program product 10 of the present invention as an example, in step S5, when the electric vehicle travels to the next traveling node Pa, the next traveling node Pa is included in the closing list. Continuing to take the above-mentioned three nodes of Dajia, Houli and Fengyuan as an example, since Dajia has been selected as the next node Pa in step S4, the user drives the electric vehicle to Dajia, and at this time the navigation The path planning computer program product 10 will put Dajia, the next node Pa, into the closed list, so as to indicate that Dajia has passed by and will not be included in the calculation category in the next calculation. In addition, it is worth mentioning that in step S5, each of the above-mentioned relay nodes Pr adjacent to the current planning point Pc is included in the open list, that is to say, the two relay nodes Houli and Fengyuan will be listed Enter the open list for the next calculation. For different display screen designs, the navigation system 11 can display a closed list, an open list, or other information on the output interface 114 as icons or text.

S6: When the judgment result of step S5 is negative, redefine the next traveling node Pa as the above-mentioned starting point Ps, and repeatedly execute the above-mentioned steps S1 to S5.

In step S6, taking the preferred embodiment applied to the navigation route planning computer program product 10 of the present invention as an example, the navigation route planning computer program product 10 judges whether Dajia is the destination Pt, and if Dajia is not set by the user In the case of the end point Pt, then redefine the continuing traveling node Pa as the starting point Ps, and repeat steps S1 to S5, that is, take Dajia as the starting point Ps again, and then continue to plan the path until the continuing traveling node Pa is the ending point Ps , so as to plan the optimization path; and if Dajia is the end point Ps set by the user, then proceed to the end of the step. For different display screen designs, the navigation system 11 can display the real-time status of the navigation route planning or other information on the output interface 114 as icons or text.

In order to make the preferred embodiment of the present invention more clear, please refer to FIG. 5 , which shows a schematic diagram of the navigation route planning method of the navigation route planning computer program product 10 according to the preferred embodiment of the present invention. As shown in Figure 5, Ps is the starting point, Pr1, Pr2 and Pr3 are the relay nodes, and Pt is the end point. When the starting point for the next path planning is the current planning point Pc), there will be two relay nodes Pr2 and Pr3 (path 1 and path 2) to calculate the total mileage cost F _i (i=1, two of 2 path). G ₁ is the actual mileage cost from the starting point Ps to the relay node Pr1, and G _2i (i=1, 2) is the distance from the relay node Pr1 to the relay node Pr2 (path 1) or from the relay node Pr1 to the relay node. The mileage cost of node Pr3 (path 2) is about to be consumed; further, G _2i is the product of the distance from the i-th path relay node Pr1 to the relay node (Pr2 or Pr3) and the road priority weight Wri, and hi(i = 1, 2), _h1 is the straight-line distance cost from the relay node Pr1 to the terminal Pt (path 1) or from the relay node Pr2 to the terminal Pt (path 1), h2 is the cost from the relay node Pr3 to the terminal Pt (path 2 ) straight-line distance cost.

Among them, taking the total mileage cost F1 of the relay node Pr2 (path 1) as an example, its G1 is the actual mileage cost from the starting point Ps to the relay node Pr1, and its _G21 is the distance from the relay node Pr1 to the relay node Pr2 (Path 1) is about to consume mileage cost. Further speaking, G ₂₁ is the product of the distance from relay node Pr1 to relay node Pr2 and the road priority weight Wr1, and h ₁ is the product of the distance from relay node Pr2 to terminal Pt (path 1) the straight-line distance cost, h ₂ is the straight-line distance cost from the relay node Pr3 to the end point Pt (path 2).

与道路权重

的数据，对于不限定实施例，可由使用者输入、内建于导航路径规划计算机程序产品10中，或可自云端下载资料，如下例的态样：For another specific embodiment, as shown in FIG. 3 , the navigation route planning computer program product 10 includes a navigation system 11, a navigation route planning program 12, and a weight database 13, wherein the weight database 13 includes charging station weights

with road weight

For non-limiting embodiments, the data can be input by the user, built into the navigation route planning computer program product 10, or can be downloaded from the cloud, as shown in the following example:

The value of the active weight Ws of the charging station, such as:

Charging station active weight Ws value Weight of charging station in service 0.5 Charging stations have no service weight 1.0

Different weights are given to whether the charging stations on the route are in service (in business) or not in service (out of business).

The value of the weight Wst of the charging station type, such as:

Charging station type weight Wst value Fast charging station weight 1 Rechargeable Battery Swap Station Weights 0.4 Mobile charging station weight 0.4

Different weights are given to different types of charging stations on the route. For example, fast charging stations require a higher mileage cost, while rechargeable battery replacement stations with replaceable batteries (remove the entire set of batteries and replace them with another set of batteries) and Mobile charging stations (such as dragging a battery behind the car for quick replacement) cost close to the mileage cost, and are given the same weight in this embodiment.

The value of road priority weight Wr, such as:

Road priority weight Wr value expressway priority 0.8 express road priority 1 Provincial road priority 3 County road priority 4 Township priority 6 Urban main road priority weight 3.5 Urban secondary road priority weight 4.5 alley priority 8

For the selection of various roads on the route, different weights are given according to their different mileage costs.

The value of the power consumption rate weight Wc, and it is mainly set according to the reference rate of the road type, such as:

Power consumption rate weight Wc value reference rate Expressway Power Consumption Weight 0.033 110km/h express road power consumption weight 0.045 80km/h Provincial road power consumption weight 0.06 60km/h County road power consumption weight 0.072 50km/h Township road power consumption weight 0.09 40km/h Power consumption weight of main roads in urban area 0.06 60km/h Urban secondary road power consumption weight 0.072 50km/h Alley Power Consumption Weight 0.18 20km/h

There are different power consumption benchmarks for various roads on the route, and different weights are given according to their different mileage costs; usually the power consumption benchmarks can be referenced by the driving speed of various roads.

Link the value of road type weight Wct, such as:

Link road type weight Wct value Ring Type Weight 1 General road type weight 1 Main road type weight 1 System interchange type weight 1 Integrated intersection type weight 1 Interchange type weight 0.5 Side channel type weight 1

Rest stop type weight 1.5

There are different mileage costs for various connecting roads connected by roads on the route, and different weights are given according to their different mileage costs.

The overall power consumption weight Wi is the product of the charging station active weight Ws, the charging station type weight Wst, the road priority weight Wr, the power consumption rate weight Wc, and the product of the connected road type weight Wct in path i; therefore, for path 1 (relay node Pr2 To the end point Pt), the overall power consumption weight W ₁ =Ws ₁ *Wst ₁ *Wr ₁ *Wc ₁ *Wct ₁ . If the route from relay node Pr1 to relay node Pr2 does not have a charging station, but the road type of the traveling path is a highway, and the connecting road type is a system interchange, so the active weight Ws ₁ of the charging station is 1; road priority The weight Wr ₁ is 0.8; the power consumption rate weight Wc ₁ is 0.033; the link road type weight Wct ₁ is 1; and the charging station type weight Wst ₁ can be 1. Accordingly, the product of the overall power consumption weight W ₁ is 1 *0.8*0.033*1*1.

Similarly, taking the total mileage cost F2 of the relay node Pr3 (path 2), its G1 is the actual mileage cost from the starting point Ps to the relay node Pr1, and its G22 is the relay node Pr1 to the relay node Pr3 Further, G22 is the product of the distance from the relay node Pr1 to the relay node Pr3 and the road priority weight Wr, and h2 is the straight-line distance cost from the relay node Pr3 to the terminal Pt.

In addition, if the route from relay node Pr1 to relay node Pr3 has charging station Cs, and the type of charging station Cs is a rechargeable battery replacement station, and the road type of its travel path is expressway, and the connecting road type is system AC Therefore, the active weight Ws of the charging station is 0.5; the road priority weight Wr is 0.8; the power consumption rate weight Wc is 0.033; the link road type weight Wct is 1 and the charging station type weight Wst can be 0.4. According to this, the overall power consumption The product result of weight W is 0.5*0.8*0.033*1*0.4. Therefore, after comparing the total mileage cost F of the relay nodes Pr2 and Pr3, it can be found that the total mileage cost F2 of the relay node Pr3 is smaller, so that the planned route takes the relay node Pr3 as the optimal route.

In order to make the preferred embodiment of the present invention more clear, please refer to FIG. 2 and FIGS. 6A to 6D together. FIGS. 6A to 6D show schematic diagrams of the planned route applied to the navigation system according to the preferred embodiment of the present invention. As shown in the figure, after the above steps are started, proceed to step S1 using map information to define the starting point as a current planning point Pc, and list each relay node Pr adjacent to the current planning point Pc into the open list. Furthermore, the user sets A as the starting point and E as the end point, and when starting to plan the route, the system will define the starting point A as the current planning point Ps, and assign three relay nodes B1, B2 and B3 Included on the open list.

In step S2 , the navigation system 11 enables the processing module 113 to start calculating the total mileage cost F _i of each route i via B1 , B2 and B3 according to the aforementioned route objective function F(n). More specifically, since the overall power consumption weight W of the remaining mileage cost H includes the active weight Ws of the charging station, and only the path from the departure point A to the relay node B1 has the charging station Cs1, the total power consumption of the relay node B1 The mileage cost F is small, and the route from the starting point A to the relay nodes B2 and B3 will not pass through the charging station, so the total mileage cost F will be larger than that of the relay node B1.

In step S3, the processing module 113 and the navigation route planning program 12 calculate the total mileage cost F _i corresponding to each relay node (each route i) adjacent to the current planning point Pc in the open list. Furthermore, after the above calculation, the processing module 113 and the navigation route planning program 12 will calculate the total mileage cost F _i of each relay node B1, B2 and B3 in step S3 according to formula (11). F1 of node B1 is 30, F2 of relay node B2 is 60, and F3 of relay node B3 is 70.

In step S4, the processing module 113 and the navigation route planning program 12 find the minimum total mileage cost F* in the total mileage cost F _i , and define the corresponding relay node as the next travel node Pa. Furthermore, since in step S3, the F1 system 30 of the relay node B1, the F2 system 60 of the relay node B2, and the F3 system 70 of the relay node B3 are found, therefore, the processing module 113 and the navigation route planning The program 12 further finds out the relay node B1 in step S4, because its F1 is the smallest, and then defines the relay node B1 as the continuing travel node Pa. At this time, the output interface 114 of the navigation route planning computer program product 100 is displayed as shown in FIG. 6A screen.

In step S5, it is judged whether the next traveling node Pa is the end point Pt. Furthermore, when the user drives the electric vehicle to the relay node B1, the navigation route planning computer program product 10 will include the relay node B1 in the closed list, so as to indicate that the relay node B1 has been passed and in the next calculation, Not included in the calculation category, in addition, the navigation path planning computer program product 10 will include the relay nodes B2 and B3 in the open list. In addition, since the next traveling node Pa is the relay node B1 and the end point is E, the judgment result is no, so step S6 will be directly performed to redefine the continuing traveling node Pa as the starting point Ps, that is, the relay node B1 Redefine it as the starting point Ps, and then repeat steps S1 to S5. It is worth mentioning that in the process of repeated execution, the navigation path planning computer program product 10 will include the relay nodes B2, B3, C1, C2 and C3 in the open list starting from the relay node B1. The open list, and in a preferred embodiment, because the relay nodes B2 and B3 are considered to be backtracked through an authentication mechanism, the relay nodes B2 and B3 will be immediately excluded from the open list.

In the next repeated execution process, the relay node B1 is the starting point Ps, there are relay nodes C1, C2 and C3 on the path, and the charging station Cs2, and a better path is selected according to formula (11) through the navigation 10 , for example, there is a charging station Cs2 on the route to the relay node C2, and its total mileage cost F after calculation is relatively small so that the next traveling node is C2. At this time, the output interface 114 of the navigation route planning computer program product 10 is displayed as follows As shown in FIG. 6B , since the relay node C2 is not the destination E, steps S1 to S5 will be repeated.

During the second repeated execution, the navigation route planning computer program product 10 will select a better route from the relay nodes D1, D2 and D3, for example, although there is a charging station Cs4 on the route to the relay node D1, But its path passes through alleys, the road priority weight Wr and the power consumption rate weight Wc are both high, so its total mileage cost F is relatively large, and the total mileage cost F of the relay node D2 is small, so that the continuous travel node Pa is D2, at this time the output interface 114 of the navigation route planning computer program product 10 displays the screen shown in FIG. 6C, and since the relay node D2 is not the destination E, steps S1 to S5 will be repeated.

Subsequently, in the process of repeated execution for the third time, a path to the end point E is planned, and then an optimized path P* as shown in FIG. 6D is planned.

The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (10)

1. a kind of navigation path planning computer program product, is to be loaded navigation path planning program by navigation system, described navigation system comprises map database, input interface, processing module and output interface; Described navigation system performs the following steps: S1: The user uses the input interface and the map database to define the starting point as the current planning point, and the navigation path planning program plans at least two paths from the current planning point to the end point; S2: The processing module uses the map database and the current planning point to load the map information including at least two relay nodes and the map information of the location of the charging station, wherein each path includes the relay node; S3: The processing module calculates the total mileage cost of each path passing through the relay node from the current planning point through the path objective function of the navigation path planning program; S4: The navigation path planning program minimizes the total mileage cost, calculates the relay node corresponding to the minimum total mileage cost, and defines it as a continuous travel node; wherein, the optimized path is from the starting point along at least one of the above-mentioned continuous travel nodes. A collection of paths traveling to the destination; S5: when the electric vehicle travels to the next traveling node, the navigation route planning program judges whether the following traveling node is an end point; and S6: When the judgment result of step S5 is negative, the navigation path planning program redefines the continuation travel node as the above-mentioned starting point, and repeatedly executes the above-mentioned steps S1 to S5; the output interface outputs the execution process or execution result of the navigation path planning program; Among them, the path objective function is the total mileage cost function of each path, which is an additive combination of the consumed mileage cost function and the residual mileage cost function; Among them, the mileage cost function is an additive combination of the mileage cost function to be consumed and the mileage cost function actually consumed; where the mileage cost function is the actual mileage cost of the above-mentioned relay nodes that have actually traveled from the starting point on the route The cost function of the actual mileage consumed is the mileage cost to be consumed from the current planning point to the relay node on the route; Among them, the residual mileage cost is the product of the straight-line distance cost from the relay node to the destination and the overall power consumption weight. 2. The navigation route planning computer program product according to claim 1, the navigation system also includes step S11 in executing step S1: S11: Put each relay node adjacent to the current planning point into the open list; Step S51 is also included in the execution of step S5: S51: Put the next traveling node into the closing list. 3. The navigation path planning computer program product according to claim 1, the navigation path planning program uses the path objective function to calculate the total mileage cost of each path of the current planning point through the relay node in step S3, wherein the overall cost The electric weight is the product of the charging station weight defined by the charging station location and the road weight. 4. The navigation route planning computer program product according to claim 3, in step S3 of the navigation route planning program, the weight of the charging station is the product of the active weight of the charging station and the weight of the type of charging station; wherein the road weight is the road priority weight, consumption The product of the electric rate weight and the connecting road type weight. 5. The computer program product for navigation route planning according to claim 4, the navigation system further includes a weight database, the weight database stores the data of charging station weights and road weights, which is pre-input by the user using the input interface and downloaded in advance via the navigation system Or built into the weight database. 6. The computer program product for navigation route planning according to claim 5, wherein the weight database includes data of charging station active weight, charging station type weight, road priority weight, power consumption rate weight and connected road type weight. 7. The navigation route planning computer program product according to claim 6, the power consumption rate weight data of the weight database includes: expressway power consumption weight, express road power consumption weight, provincial road power consumption weight, county road power consumption weight, Data on the power consumption weight of township roads, main roads in urban areas, secondary roads in urban areas or alleys. 8. The computer program product for navigation path planning according to claim 6, the weight data of connected road types in the weight database comprises: ring type weights, general road type weights, main road type weights, system interchange type weights, and integrated intersection types Data for weights, interchange category weights, sidewalk category weights, or rest stop category weights. 9. The computer program product for navigation route planning according to claim 6, the charging station type weight data in the weight database includes: fast charging station type weight, rechargeable battery replacement station type weight or mobile charging station type weight data; wherein, The active weight data of the charging station in the weight database includes: the weight of the charging station in service or the data of the weight of the charging station not in service. 10. The navigation route planning computer program product according to claim 6, the road priority weight data of the weight database comprises: expressway priority weight, express road priority weight, provincial road priority weight, county road priority weight, township road priority weight, Data for priority weights for major roads in urban areas, priority weights for secondary roads in urban areas, or priority weights for alleys.

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