CN114550482B - Navigation method based on low-carbon target and parking lot navigation method - Google Patents
Navigation method based on low-carbon target and parking lot navigation method Download PDFInfo
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- CN114550482B CN114550482B CN202210111131.1A CN202210111131A CN114550482B CN 114550482 B CN114550482 B CN 114550482B CN 202210111131 A CN202210111131 A CN 202210111131A CN 114550482 B CN114550482 B CN 114550482B
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- 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
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
Abstract
The invention provides a navigation method based on a low-carbon target and a parking lot navigation method, which are carried out according to the following steps: step by stepStep 1: determining a starting point o and an end point d; step 2: obtain a set K, K= { K of all feasible paths among od in the whole city 1 ，k 2 ，k 3 ，…，k m Defining a road sections in all feasible paths among the od to obtain a road section set A= {1,2,3 … a }; solving MinZ (X) according to a road network carbon emission optimization principle, and calculating carbon emission of each path in the set K to obtain an optimal path K 'when the carbon emission is minimum, and navigating the vehicle to a destination according to the optimal path K'; according to the invention, the real-time road condition destination dynamic parking lot planning is used as a guided travel path optimization scheme, so that the optimization of the carbon dioxide emission of the whole road traffic network vehicle is realized, and the distance or time cost efficiency discussed by the traditional method is not optimal. Therefore, a new method is provided for realizing the goal of blocking and emission reduction in the urban infrastructure planning technology.
Description
Technical Field
The invention belongs to the technical field of urban building planning, and particularly relates to a navigation method based on a low-carbon target and a parking lot navigation method.
Background
The "parking difficulty" and "congestion normalization" have become important reasons for the increase of the carbon emission of traffic caused by the travel of urban residents. However, recent researches show that the parking lot is used as a starting and ending point of private car travel, and the blocking and emission reduction can be realized by influencing the selection of a driving path. However, this theory presents a series of problems in practical applications. Firstly, driving path planning taking a parking lot as a destination lacks dynamic linkage with road condition and parking lot use information, and traffic flow distribution of a road network cannot be dynamically regulated and controlled through parking navigation. Second, current navigation systems recommend driving paths to users only in time or distance optimizations. However, the carbon emission amount of the vehicle running is not in a linear relation with the running time or distance, and the minimum carbon emission amount of the whole vehicle on the road network cannot be ensured by the individual driving path planning with the shortest time or distance. More importantly, due to the linkage missing of the dynamic parking information and the driving plan, when a driver arrives at a destination, the driver often finds that no empty parking space exists, and parking waiting, illegal parking, parking cruising and the like caused by the missing of the dynamic parking information and the driving plan further aggravate road traffic burden and congestion carbon emission. According to the prior art, in a heavy traffic area, the vehicle takes 3.5 to 14 minutes to find a parking place, which causes the traffic flow to increase by 20 to 45 percent, and causes serious problems of high carbon emission. An illegal in-road parking for 18 minutes on a road with a traffic capacity of 1200veh/h will increase the carbon emission of the vehicle by 26.5%. Therefore, how to quickly and effectively provide a parking lot navigation scheme beneficial to urban carbon emission reduction for drivers is an important problem facing the technical field of low-carbon urban infrastructure planning.
With the advent of the 5G communications era, internet big data-based parking decisions and traffic guidance systems have become a trend. When a driver uses a mobile phone or an in-vehicle device to navigate, the vehicle becomes a terminal that generates, transmits, and receives data and executes a navigation result. Dynamic data flow generated by automobile driving realizes cloud bi-directional communication and calculation through the technology of the Internet of vehicles, and lays a low-carbon path planning innovation in the form of parking navigation.
Disclosure of Invention
Aiming at the defects and shortcomings of the prior art, the invention aims to provide a navigation method based on a low-carbon target and a parking lot navigation method, which solve the problem that a parking site selection and path induction method considering the linkage of real-time road conditions and the carbon emission of an integral road network is lacking in the prior art.
In order to solve the technical problems, the invention adopts the following technical scheme:
the navigation method based on the low-carbon target is carried out according to the following steps:
step 1: determining a starting point o and an end point d;
step 2: obtaining all feasible paths k among od in whole city 1 ，k 2 ，k 3 ，…，k m Is set K, k= { K 1 ，k 2 ，k 3 ，…，k m Defining a road sections in all feasible paths among the od to obtain a road section set A= {1,2,3 … a };
solving MinZ (X) according to a road network carbon emission optimization principle, calculating carbon emission of each path in the set K to obtain carbon emission of each path in the set K, and obtaining an optimal path K ', K and K ' E K when the carbon emission is minimum, and navigating the vehicle to a destination according to the optimal path K ';
the optimal principle of the carbon emission of the road network is calculated according to the following formula:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
k represents the kth path in set K;
a is a road section number;
L a the unit is m, which is the length of the road section a;
the unit is s, namely the zero-flow impedance of the road section a, which is the free-flow time of the road section a;
c a the traffic capacity of the road section a is pcu/h;
alpha and beta are blocking coefficients, and 0.15 and 4 are taken respectively;
the unit is pcu for the flow on the kth path between od points with the starting point of o and the end point of d;
a road section-path variable, which is 0 or 1 variable; if the road section a belongs to the kth path between od points with the starting point of o and the end point of d, the road section a is +.>Otherwise->
The vehicle speed is designed for the road section a, and the unit is m/s;
f is a sixth order function subject to a speed-to-carbon emission rate conversion.
A parking lot navigation method based on a low-carbon target comprises the following steps:
step (1): determining a starting point o and an end point d;
step (2): based on an open source map platform, acquiring real-time road condition information and parking facility use information at the current moment, wherein the real-time road condition information and the parking facility use information comprise the number of remaining vehicles, average parking time length and parking space turnover rate; judging whether the matched parking lot has a free parking space when reaching the destination d according to the estimated arrival time S of the real-time road condition information, if the matched parking lot has the free parking space when reaching the destination d, executing the step (3), if the matched parking lot has no free parking space when reaching the destination d or the destination d has no matched parking lot, executing the step (4),
for example: early 10:00, according to real-time road condition information (table 2) provided by the hundred-degree map platform, the expected arrival time is 10:07 minutes. According to the usage information of the parking facilities, the hour utilization rate of the parking spaces is 0.8, 1000 parking spaces are reserved in the parking facilities, 1000 (1-0.8) =200 remaining parking spaces at the moment, the turnover rate of the hour parking spaces is 1, and after the estimated 7 minutes, the empty parking spaces of the parking facilities are reserved: 200-1 x (7/60) =200. And d is known to have a free space to build a parking lot when arriving. And (3) calculating according to the formula (1) to obtain an optimal path, and navigating the vehicle to d to a parking lot according to a path planning scheme.
Step (3): carrying out path planning according to the optimal carbon emission principle of the road network, and navigating the vehicle to a destination d according to a path planning scheme to construct a parking lot;
the optimal principle of the carbon emission of the road network is calculated according to the following formula:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
b represents the B-th path in set B;
p is the road section number;
L p the unit is m, which is the length of the road section p;
the free flow time of the road section p is s;
c p the traffic capacity of the road section p is pcu/h;
alpha and beta are blocking coefficients, and 0.15 and 4 are taken respectively;
the unit is pcu for the flow on the b-th path between od points with the starting point of o and the end point of d;
a road section-path variable, which is 0 or 1 variable; if the road section p belongs to the b-th path between od points with the starting point of o and the end point of d, the road section p is +.>Otherwise->
f is a sixth order function subject to a speed-to-carbon emission rate conversion.
If no parking space exists, executing the step 4;
when the destination is a built parking lot, the navigation path calculation process does not need to divide the road network structure again, so that the solving process does not influence the running paths of other vehicles, and the path with the minimum carbon emission of the vehicle represents the calculation result with the minimum carbon emission of the whole road network. Since the carbon emission is a sixth order function of the vehicle speed, the vehicle travel path is determined by the road flow. When the carbon emission model is built, a relation between the vehicle speed and the flow (Da) is built, and the carbon emission model is built and solved by expressing the flow through the vehicle speed.
The derivation of equation one is as follows:
the second principle of wardrop (system equalization) is solved for target formula (I).
Wherein D is a Is road section a flow (pcu/h);
t a as road resistance, it can be understood as the actual time(s) to travel through road segment a;
t a (D a ) Is a BPR function taking the flow of the road section a as an independent variable;
according to the second principle of the wardrop, the equation (I) solves an optimization problem which is actually an objective function of the road flow Da. And because the carbon emission and the vehicle speed are in a sixth-order functional relation, the flow is expressed through the vehicle speed, and a carbon emission model is established for solving. The method mainly comprises the following steps:
(1) Determining the relation between the running time and the actual flow, wherein the relation is shown in a formula (II):
wherein, c a Traffic capacity (pcu/h) for road segment a;
the zero flow impedance, namely the time(s) for the vehicle to freely travel through the road section in the road idle state, can be regarded as the quotient of the road section length and the design vehicle speed;
alpha and beta are blocking coefficients, and 0.15 and 4 are taken in the U.S. federal road agency allocation program, respectively.
(2) Determining the relation between the running time and the average vehicle speed:
wherein L is a The length (m) of the road segment a is represented.
(3) Determining the relation between the vehicle speed and the carbon emission rate:
Q a ＝w(V a )(V)
in which Q a Represents the carbon emission amount of one vehicle per kilometer on road section a,
obeying a sixth order function of the speed-to-carbon emission rate conversion, see formula VI:
(3) Target carbon emission
The objective function is that the carbon emission of the system is minimum, and according to the second balance principle: the optimal principle of the system is established as a target type:
wherein, the liquid crystal display device comprises a liquid crystal display device,obeying a sixth order function of the speed-to-carbon emission rate conversion.
(4) The fitness function is constructed as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
wherein X is the carbon emission of the road network; z represents the overall carbon emission level of the traffic network; d (D) a Is the traffic flow of road segment a; l (L) a Is the length of road segment a; t is t a Is at D a The time it takes for the vehicle to pass through segment a under flow conditions; c (C) a Road traffic capacity for road segment a;the road zero-current impedance is obtained by taking the free-current time of the road section a;alpha and beta are blocking coefficients, and 0.15 and 4 are taken respectively;the unit is pcu for the flow on the kth path between the od point pairs with the starting point of o and the end point of d; />Taking 1 when the road section a is on the path k, and otherwise taking 0; />The vehicle speed is designed for the road section a, and the unit is m/s; and sending a request to the map platform at intervals of time T, wherein the update frequency of the calculation result is T+nt.
Thus, formula (VII) is derived as (1):
step (4): acquiring real-time road condition information and public parking lot use information at the current moment, and pre-judging whether available public parking lots exist in 300 meters around the destination d;
if not, recommending the user to change the destination;
if so, N public parking lots with vacant parking spaces in the whole city range at the current moment are obtained, and the mass centers (N x ，N y ) The Thiessen polygons are divided for the feature points to obtain a set O= {1,2, … i … j … N } (i is greater than or equal to 1 and less than or equal to N,1 and less than or equal to j and less than or equal to N, i is equal to j) of parking partitions, wherein i is (i) x ，i y ) Thiessen polygon partition starting at point, j is represented by (j x ，j y ) A Thiessen polygon partition for the endpoint;
selecting N '(N' is more than or equal to 2 and less than or equal to N) parking lots from N public parking lots to form a public parking lot combination alternative scheme {1,2}; {1,2}, {1,3}, {2,3}, {1,2,3}; …; {1,2}, {1,3} … {1, N '}, {1,2,3} … {1,2, N' } … {1,2,3 … N '-1, N' }, in totalDividing the urban road network by the boundary of the alternative public parking lot combination alternative scheme to obtain a road section set R= {1,2,3 … R };
solving MinZ (X) according to the principle of optimal road network carbon emission, and calculating the carbon emission of the urban road network divided by the combination alternative scheme of all public parking lots to obtain an optimal running path S' of the vehicle;
programming according to the step 4 on a Matlab platform according to a formula (2), realizing dynamic solution of MinZ (X) through a single parent genetic algorithm, calculating to obtain a public parking lot combination scheme M ' under the condition of minimum carbon emission of the whole road network, obtaining a Thiessen polygon i ' to which a starting point belongs and a Thiessen polygon j ' to which an end point belongs, and navigating the vehicle obtained through calculation of the combination scheme M ' to d according to an optimal driving path S '.
The specific formula is as follows:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
r is the road section number;
ζ is the coefficient of the gravity model;
L r the unit is m, which is the length of the road section r;
f is the proportion of travel in a self-driving mode in the Thiessen polygon partition;
D rk calculating the traffic quantity distributed on the r road section among the cells according to the gravity model; d (D) pr The number (capacity) of the public parking lot vehicle positions on the r-section road is used as the exit;
D er the number of parking places (saturation) is set for the buildings with the exits on the r sections;
E er the method comprises the steps of establishing a parking lot peak hour berth turnover rate for a building;
U pr the utilization rate of berths is the peak hour of the public parking lot;
U er peak hours of parking lot for buildingBerth utilization rate;
E pr the berth turnover rate is equal to the peak hour berth turnover rate of the public parking lot;
P j representing traffic volume generated by Thiessen polygonal partitions starting at i;
B j representing the traffic attraction generated by the Thiessen polygonal partition ending with j;
t r (D r ) Traffic impedance for a Thiessen polygon partition starting at i to a Thiessen polygon partition starting at j; taking the shortest time estimated from i to j according to the road condition at the current moment;
D r the traffic flow on the road section r is pcu/h;
the unit is s, namely the zero-flow impedance of the road section r, which is the free-flow time of the road section r;
c r the traffic capacity of the road section r is pcu/h;
g is the number of jj pairs, G is the number of jj pairs;
s is the number of feasible paths, H is the number of paths through r road sections in the feasible paths;
e is a natural logarithmic base;
μ is the expected value, which is the shortest time most vehicles spend from i to j;
θ is a traffic conversion parameter, θ=3 to 3.5;
is any one of the possible paths +.>Is set, the total travel time of (a);
α and β are blocking coefficients, and α=0.15 and β=4 are taken according to empirical values;
f is a sixth order function subject to a speed-to-carbon emission rate conversion.
Because this time the navigation of public parks is discussed, default built parks are saturated
The derivation of equation 3 is as follows:
under the condition of system balance according to the second principle of the wardrop, road network traffic flows are distributed according to the minimum average or total travel cost, so that when the road network traffic flows are navigated to a public parking lot for parking, the adaptability function is constructed as follows:
wherein r is the road section number re-divided according to the Thiessen polygon boundary; d (D) r Is the traffic flow (pcu/h) on road segment r; l (L) r Is the length of the road segment r; q (Q) r The carbon emission of a vehicle per kilometer in a road section r is a function of the average speed:
Q r ＝f(V r ) (XI)
average velocity V r Can be expressed as:
wherein L is r Is the length of the road r; t is t r Is at D r Time taken for vehicle to pass through road under flow condition, t r (D r ) For road section r with flow (D r ) Impedance function, also called travel time function, as an independent variable:
formula (X) can be further expressed as:
wherein: c (C) r The traffic capacity of the road section of the r road section is obtained by taking (pcu/h) and t 0 The zero flow impedance of the road, namely the time of the vehicle running freely through the road section in the state of empty road, is expressed in units of(s), and can be recognizedAt t 0 Is the quotient of the road length and the road design vehicle speed, in the above formula, alpha and beta are the blocking coefficients,representing traffic flow from i to j over road segment r; d (D) rk Is the total flow from i to j; d (D) r For r road section actual flow, C r Is road capacity.
Since the Thiessen polygonal partition divides the road network into r segments, the actual flow of the r segments is equal to the flow allocated to the r segments minus the flow into the public and public parking lots built on the r segments. According to the principle of nearby, the parking attraction generated by the district is considered to be solved in the architectural parking lot preferentially, and the excess part is solved by the public parking lot, the architectural parking lot of the default road section of formula (XIV) is saturated,
thus:
D r ＝FD rk -D pr U pr E pr -D er U er E er (XIV)
in the method, in the process of the invention,
f is the proportion of travel in a self-driving mode in the Thiessen polygon partition;
D r the actual traffic flow of the road section r;
D rk calculating the traffic quantity distributed on the r road section among the cells according to the gravity model;
D rr the number (capacity) of the public parking lot vehicle positions on the r-section road is used as the exit;
D er the number of parking places (saturation) is set for the buildings with the exits on the r sections;
E er the method comprises the steps of establishing a parking lot peak hour berth turnover rate for a building;
U pr the utilization rate of berths is the peak hour of the public parking lot;
U er the method comprises the steps of building a parking lot peak hour berth utilization rate for a building;
E pr the berth turnover rate is equal to the peak hour berth turnover rate of the public parking lot;
thus, the problem of optimizing the carbon emissions translates into the problem of distributing traffic flows between traffic cells.
According to the gravity model, the method comprises the following steps:
wherein D is ij The traffic volume from the i cell to the j cell (i not equal to j) takes the centroid of the Thiessen polygon where the i and j cells are located as a characteristic point;
ζ is a gravity model parameter;
P i traffic volume generated for i cells;
B j traffic attraction generated for the j cell;
t r (D r ) Traffic impedance for a Thiessen polygon partition starting at i to a Thiessen polygon partition starting at j; taking the shortest time of i to j.
D r Is the traffic flow on road section r (pcu/h)
P i ＝∑ζ h M h (XVI)
Wherein:
h is the land type of the land parcel;
ζ h the travel generation rate of the h-class land is used;
M h the building area for class h land.
B j And P i Is similar to the algorithm of (a),
B j ＝∑b h M h (XVII)
in the method, in the process of the invention,
b h the traffic attraction coefficient for the h-class land;
g is the number of ij pairs;
g is ij pair number;
w gr for the g < th > ij pair (D ij ) g The proportion allocated to the r road segment;
taking an od pairAssuming that there are S possible paths from the i cell to the j cell, and that there are H paths through the K-th road segment, the travel from the i cell to the j cell is selectedThe probability of a path is:
u＝t r (D r ) And taking the shortest time from i to j for the traffic minimum impedance from i cell to j cell.
In the method, in the process of the invention,to select +.>Probability of a path;
total travel time for each path;
θ is a traffic conversion parameter, taking 3.0-3.5.
Assuming that among the possible paths i to j, the probability that the road with the smaller impedance is selected as the optimal path is larger, the distribution number is the largest. Thus, the probability of selecting the optimal path conforms to a positive-ethernet distribution curve, where there are H paths through the r-segment.
The total ratio of the g-th ij to the r-section allocation is:
the determination steps of the feasible paths S and H are as follows:
step1 determines the valid road segments: if the road section node numbers are aa and bb, calculating the shortest travel time T (aa) and T (bb) from the road section node to the starting point, wherein T (aa) > T (bb) aa to bb are effective road sections;
step2 is composed of effective road sections to form an effective path;
the number of times that aa-bb section searches that traffic flow is distributed to the section in step3 distribution is H.
Will D rk ，w gr ，P s Substituting formula (XIV) to find Min Z (X),
in the fourth step, if an emergency occurs:
(1) and if the traffic accident occurs along the optimal path b', returning to the step2 to recalculate and judge.
If the destination d is matched with the parking lot and has spare parking spaces, path planning is carried out according to the formula (2) to obtain an optimal path until navigation to the end point is finished.
If no available vehicle position exists in the matched parking lot, executing the step 4 according to the road condition at the time of T+nt to obtain the vehicle running path s under the condition of minimum carbon emission of the whole road network T+nt Navigating to d.
(2) If the public parking lot where the destination d is located is saturated (the utilization rate is 100%), judging whether the current running position of the vehicle is within the range of the destination d300 m or not;
if not, repartitioning the Thiessen polygonal mesh according to the mass center of the public parking lot with the vacant parking space at the time of T+nt as the characteristic point. Recalculating the public parking place and the optimal path s 'according to the formula (3)' T+nt ；
If yes, navigating to a public parking lot where a Thiessen polygon partition where a road section where the vehicle is located when T+nt;
and (5) until the navigation to the destination is finished.
Because the formula (2) relates to dynamic optimization of road traffic induction and has a plurality of variable parameters, a genetic algorithm is adopted to solve the problem, and the coordinates (xd ', yd ') of the mass center of the public parking place d ' and the navigation path within the range of the end point d300 meters are obtained under the condition of the optimal total carbon emission of the road network.
Because the request is sent to the map platform every time T during navigation, the update frequency of the formula calculation result is T+nt. The method can send an instruction to the map platform at each interval time T to acquire real-time road condition information and parking facility use information at the moment of T+nt again, and then the formulas 1 and 2 can be as follows:
compared with the prior art, the invention has the following technical effects:
according to the invention, the optimization scheme of the travel path is realized by taking the dynamic parking lot (position) planning of the destination of the real-time road condition as the guiding, so that the optimization of the carbon dioxide emission of the vehicles in the whole road traffic network is realized, and the distance or time cost efficiency discussed by the traditional method is not optimized. Therefore, a new method is provided for realizing the goal of blocking and emission reduction in the urban infrastructure planning technology.
And (II) the dynamic public parking lot partition method based on the Thiessen polygons is developed and practically realized in an open source map navigation system. The geometric features of the Thiessen polygonal partitions, the feedback of the open source data platform and the dynamic traffic network system are utilized to realize dynamic optimization, the response to urban road traffic emergency is realized, a parking lot is rapidly selected, and the beneficial methods of improving the road traffic induction efficiency and reducing carbon emission are simplified in calculation steps. This zoning approach provides an accurate approach to traffic distribution and parking demand estimation that is not quadrilateral or radial zoning, but rather focuses more on the time-varying features of parking spaces and their impact on the congested carbon emissions caused by dynamic traffic routing. More importantly, the optimization method for parking site selection and partitioning is carried out by applying the Thiessen polygon nearest neighbor principle, and the shortest distance common target can be realized by combining the functions. Aiming at complex path optimization research, real-time path planning and application of a navigation system, the method is very important to improving the calculation and feedback efficiency aiming at the real-time navigation and path planning system.
(III) the present invention uses Genetic Algorithm (GA) to find the optimal public parking lot set. The GA has great application value in the aspect of accelerating global optimization of random search. It is particularly suitable for simulating complex and high capacity problems related to practical solutions. Most importantly, the method provides a practically operable application method for regulating and controlling the static traffic and the dynamic traffic, and proves that the static traffic has strong influence capability on the dynamic traffic. Especially in terms of congestion control, this dynamic partitioning approach can be explored for a larger range of real-time. With real-time traffic information provided by the roadside sensors of the ITS, dynamic zoning-based parking guidance would be possible to improve the performance of the traffic system with the support of the smart city infrastructure. By applying the dynamic partitioning and modeling method to the intelligent traffic system, the parking induction efficiency and the dynamic optimization of traffic distribution of future intelligent travel can be ensured.
Drawings
FIG. 1 is a schematic illustration of an exemplary base site location;
FIG. 2 is a schematic view of an example base road field situation for a built-up area;
FIG. 3 is a schematic view of a base building status quo;
FIG. 4 is a schematic illustration of a base parking lot;
FIG. 5 is a block diagram of a public parking lot plan based on Thiessen polygons;
FIG. 6 is an optimization process of the genetic algorithm for dynamically solving the formula (3) to obtain the total carbon emission;
FIG. 6.1 is a Matlab model calculation work interface;
FIG. 6.2 is an iteratively generated 5 sets of road segment traffic matrices;
FIG. 6.3 is a graph of flow distribution for 48 road segments in each set of matrices;
FIG. 7 is a plan of best fit for public parking in a condition of minimum overall carbon emissions from the road network;
FIG. 8 is a flowchart of a genetic algorithm;
fig. 9 shows real-time road condition information of a road obtained by mining according to open source map data.
FIG. 10 is a schematic view of a path to a destination in a parking lot
FIG. 11 is a schematic view of a path to a public parking lot where a destination is located
FIG. 12 shows a parking path planning procedure under the optimal condition of road network carbon emission
FIG. 13 parking site selection and path planning method based on dynamic open source map information
The following examples illustrate the invention in further detail.
Detailed Description
The following specific embodiments of the present invention are provided, and it should be noted that the present invention is not limited to the following specific embodiments, and all equivalent changes made on the basis of the technical solutions of the present application fall within the protection scope of the present invention.
The general idea of the invention is as follows:
navigation to the built parking lot:
real-time road condition information at the moment T provided by the open source map platform and parking facility use information predict whether an arrival time S end d has a built parking lot and an available parking space.
If a built parking lot and available parking spaces exist, the vehicle starts from a starting point o, advances to an ending point d along a road section between road network intersections, and when each intersection passes through, the vehicle judges a feasible road section in the advancing direction, the feasible road section forms a feasible path k in the advancing direction of o-d from the head to the tail, and a running path k 'with the minimum carbon emission of all the feasible paths is calculated according to a formula 1 and navigated to a destination built parking lot along an optimal path k'.
Navigating to a public parking lot:
if no parking lot is built, judging whether a public parking lot exists in the range of 300 meters at the destination d.
If public parking lots and available parking lots exist, acquiring all N public parking lots with vacant parking lots in the whole city range at the moment T, and selecting N '(N' is more than or equal to 2 and less than or equal to N) public parking lots from N to formConstructing Thiessen polygon partition by taking the mass centers of the public parking lots in the alternative scheme as characteristic points, calculating traffic travel and traffic attraction generated by covering buildings in the partition, constructing mass center connecting rods and connectingAnd (3) the Thiessen polygon centroid reaches the nearest road intersection, and the traffic volume generated by the buildings in the subarea is distributed to the road network through centroid connecting rods. According to formula 2, carrying out dynamic optimization solving on the formula by utilizing a genetic algorithm, calculating a public parking lot combination scheme when the total carbon emission of the road network is minimum in the alternative scheme, obtaining a Thiessen polygon i ' to which a starting point o belongs and a Thiessen polygon j ' to which a destination point d belongs in the combination scheme, and obtaining a running path from i ' to j ' according to the vehicle distribution result in each road section under the optimal parking lot combination scheme, and navigating the running path to the public parking lot j ' where d is positioned and then walking to a destination d.
In general, there are several specific methods for solving the multi-objective optimization problem, such as a weight coefficient modification method, a parallel selection method, an arrangement selection method, a shared function method, and a hybrid method. In order to reduce programming complexity, and simultaneously meet traffic and parking requirements, and recombination, the research adopts a single-factor genetic parallel selection method. The specific programming process is as follows:
1) Encoding operations
In the study, the gene (alternative public parking lot) is initially encoded by a real number encoding method, and the encoding sequences are 1,2,3,4 and m.
2) Generating an initial population
Each chromosome (a possible combination of public parking lots) is composed of genes. The collection of randomly selected candidate public parking lots constitutes the initial gene. For example, if there are 10 alternative public parking lots within 300 meters of endpoint D, numbered 1,2,3 …, the chromosome may be defined as {1,3,7} or {1,2,9, 10}, etc.
3) Defining fitness functions
The fitness function (equation 3) is used to calculate the solution of the genetic algorithm.
4) Population selection
The purpose of population (collection of possible combinations of public parks) selection is to select a better individual in the initial park set as the father for the next generation genetic cross. The criterion for determining whether an individual is excellent is the result of an individual solution set fitness function. The better the fitness value of an individual, the greater the likelihood of being selected by the next generation.
5) Recombination
Solutions in mating pools will continually produce a combination that reduces the overall carbon emissions of the road network due to the effects of duplication between generations. Since the replication, genetic process does not create a new alternative parking lot, the fitness of the best individuals in the group is not reduced. The population used in the gene recombination process is randomly selected from the pool of mating. By selecting a parking lot with better individuality, the last generation will contain the best genetic genes in the father.
6) Variation of
For example, a current value of 0 for one gene indicates that the parking lot is not to be selected in a genetic iteration. If a mutation occurs, the value will change to 1, which means that an opportunity can be selected for the next iteration. For each public parking lot in the chromosome, mutation will be performed with the same probability.
To sum up, as shown in fig. 8, the urban whole road traffic network CO is realized by using the genetic algorithm 2 The emission amount is optimized, and the specific steps are as follows:
and step1, initializing. The population size is set to be 8, the chromosome length is 7, the iteration times are 5, and the gene recombination mode (transposition, filling, shift and inversion) and mutation probability are 1/7.
And 2, applying the binary integer to the codes of the coordinates of each public parking lot, and randomly generating an initial population.
And 3, calculating the fitness function of each generation by using an iteration method. The method is divided by three parallel parts, namely traffic distribution and emission calculation based on the zoning of Thiessen polygons. All individuals in the father are classified, better individuals are selected, and inferior individuals are eliminated to create a combination of new public parking site selection schemes.
And 4, performing crossover between individuals with random connection according to crossover probability. And carrying out mutation on the single parking lot combination mode according to the probability of mutation.
And 5, confirming whether the maximum iteration number of 5 is reached or not, and calculating the result to not generate a result with lower carbon emission. If so, the best solution for the public parking lot location is output. Otherwise, please return to step3 to perform the next round of iterative computation.
Example 1:
the parking lot navigation method of the low-carbon target is carried out according to the following steps:
taking a newcastle area in western city as an example, calculating a parking navigation planning scheme under the condition that the whole carbon emission of a road network of the newcastle area is optimal as a destination. And the efficiency of the dynamic traffic system is optimized.
Inputting the east street (o) at the beginning and Xu Ji seafood (d) at the end of the newcastle square. Fig. 2 is drawn from the current situation map of the western city, based on the tile build environment information. Based on the open source map platform, acquire early 8: real-time road condition information at the moment 00 and parking facility use information, and estimating the time for reaching the destination according to the real-time road condition.
In the early rush hour, most cars are driven into a common parking space, while relatively few vehicles are driven out, which is negligible. Thus, without loss of generality, we directly use the incoming traffic to derive the net road segment flow. According to the parking space use characteristics of the area where the example parking lot is located in table 1, calculating the number of remaining parking spaces of the destination parking lot, and obtaining the average parking duration and the turnover rate of the parking spaces: the utilization rate of the parking space is 0.5, the turnover rate is 3, the utilization rate of the matched parking space is 1, and the turnover rate is 1.
Table 1 parking space usage
According to the real-time road condition information (table 3) provided by the hundred-degree map platform at the early 10:00, the parking facility uses information, and the estimated arrival time is 10:07 minutes. And d, judging that a parking lot is empty to be built when the vehicle arrives. Planning paths according to a formula (1) to obtain 2 (k) feasible paths among od in the whole city range 1 ＝11，12，6，7；k 2 =11, 13, 14, 15, 7), containing 7 road segments in total (road segment number: 11. 13, 14, 12,6, 16, 7), roadThe segment information is shown in Table 2. Wherein, from the information of Table 1Similarly available->According to the optimal principle of carbon emission of the road network, the carbon emission of paths K1 and K2 in a set K is calculated according to a formula 1 to obtain the carbon emission of each path in the set K, and MinZ (X) is solved to obtain Z (K) 1 )＝3.0388*10 7 ，Z(k 2 )＝7.2437*10 7 Thus, minZ (X) =z (k 2 ) Obtaining the optimal path with the minimum carbon emission as a path k 1 The vehicle follows the optimal path k 1 The (11, 12,6, 7) solution navigates to d-equipped parking lot, as in fig. 10.
TABLE 2 road segment information
Table 3 road speed data sample obtained by analyzing open source map
The parking lot built at the late 18:00 destination d has no available parking place, and the parking needs to be solved by a public parking lot with the destination within 300 meters. And (3) calculating a public parking lot combination scheme under the optimal condition of the carbon emission of the road network according to the formula (2), realizing optimal flow distribution of a research range partition and each road section, and obtaining an optimal path planning between od under the optimal condition.
Fig. 3 shows building information in this range, the lower left corner end point of the road network being defined as the origin of coordinates. Building information is acquired by taking a building centroid point as a characteristic point. Based on the origin of coordinates, each building centroid coordinate is labeled, and the parameters are shown in table 4.
Table 4 information of building and its affiliated parking space
TABLE 5 road information
Note that: in the "road type" column of Table 3, A, L and C represent main road, secondary main road and city branch, respectively; here, all roads listed here are two-way roads. )
Fig. 4 shows the regional distribution and public parking areas, and fig. 5 shows 7 candidate public parking areas of the region. By selecting the optimal combination mode of 7 parking lots, the road network traffic flow distribution mode is influenced, so that the optimal traffic performance in the road network, namely the optimal target with the minimum carbon emission, is realized. And under the optimal combination mode, obtaining an optimal path among the ods. The specific path planning calculation process is as follows:
in the present case study, 7 independent Thiessen polygons were created as parking analysis zones based on the available common parking lot centroid locations. The information of each polygon is represented by its centroid. Table 6 lists the road information shown in fig. 5.
TABLE 6 road endpoint information
Table 7 provides the basic information of these 7 public parks and their taisen polygonal analysis regions.
Table 7 public parking lot and road parameters
As shown in fig. 4, a link is created from the center of mass of the tawsen polygon analysis zone to the nearest road node, and all traffic generated by the buildings in the tawsen polygon analysis zone is distributed to the road network through the link. According to the generated connecting rod, the length, the Thiessen polygon centroid coordinates and the although road node coordinates are measured, and the parameters are shown in Table 7.
Table 8 centroid link parameters
In this example, 7 polygonal centroids are considered as feature points for traffic distribution and are connected to the road network by different links.
Programming a scheme based on an MATLAB platform, establishing dynamic division and flow distribution of a Thiessen polygon analysis area by using a public parking lot in a research range, and realizing optimal public parking lot site selection by using a uniqueness genetic algorithm (PGA).
Matlab simulation results
FIG. 6.1Matlab model calculation work interface, graph sources: programming screenshot
The Matlab calculates the proposal to obtain the result, 8 populations are inherited for 5 generations to obtain the optimal solution (minimum) of the whole carbon emission of the road network, and the combination number of the public parking lot of the optimal chromosome finally determined by the GA is as follows: 4,7,1,5,6. In the calculation process, the solving process of the road flow is as follows:
fig. 6.2 is a matrix result of a Matlab solving model modeling. In this example, since the optimal solution appears in the calculation result after the 5 generations of the genetic selection, there are a total of 5 sets of calculation results of the road segment flows, as shown in fig. 6.2 (a). Wherein, the optimal flow distribution of each generation of inherited road sections is as shown in fig. 6.2 (b):
in this example, there are 24 roads in total, which are bidirectional, so that 48 traffic data are generated in each generation of genetics, and the matrix structure is shown in fig. 6.3. Road segment flow calculation results of the first population inherited by the third generation:
fig. 6.2 iteratively generated 5 sets of road segment traffic matrices, picture sources: matlab programming screenshot
Fig. 6.3, 48 road segments in each matrix set distribute traffic, picture sources: matlab programming screenshot calculates the carbon emission of the whole road network by the flow of each road section, and the carbon emission calculation result after five generations of inheritance outputs emission amount historical data as shown in table 9;
table 9 the flow carbon emission values of each road section under the optimal solution set, unit: 1.0e+0.4 x (g)
Fig. 7 shows the optimization effect of the overall carbon emission of the road network during the PGA iteration scheme. In this simulation, the carbon emissions were slightly reduced after the first few rounds of optimization, and the optimum was reached after the fourth round of iteration, after which no further improvement was seen. As shown in fig. 6.1,4,5,6,7 is the best parking combination among a total of 1-7 available parking spaces. The traffic flow of the road network is divided by the Thiessen polygonal parking partitions divided by the 5 parking lots, and the travel path of the vehicle is calculated according to formula (2), as shown in FIG. 11.
Carbon emission accounting rationality explanation
1. Inspection of rationality of minimum carbon emission of road network
The total length of the road network of the research area is 4950 meters, the road is bidirectional, and the road length is 9900 meters. According to the matlab simulation result, the road network traffic and the road network traffic are summed up: 414742. CO obtained according to measurement and calculation of different vehicle types 2 Emission rate, table 10, estimated according to the vehicle carbon emission rate of about 200g/km, road network emission amount of about:
8.29×10 7 (g)。
TABLE 10 carbon emissions for different vehicle conditions
The calculated result is 3.5-3.7X10 7 (g) A. The invention relates to a method for producing a fibre-reinforced plastic composite Although simulation results and theoretical estimates existBut are of a consistent order of magnitude and the errors are all within reasonable limits. The possible causes of the calculation result errors are analyzed: firstly, the congestion status industry of the same road section at different moments is different, but the numerical values are in a reasonable range, the carbon emission calculation index in the reference is an empirical value of the automobile working condition in China, and the research fits the relation between the speed and the carbon emission according to the carbon emission of the U.S. traffic bureau and the experimental result. Second, since the carbon emissions are an integrated value, the vehicle base is large, and small differences in each vehicle will integrate to produce large differences in overall values.
2. Calculation of process scheme carbon emissions for genetic algorithm generation
The model generates a plurality of groups of parking lot combination schemes in the process of selecting the optimal solution by utilizing a genetic algorithm, and calculates the road network carbon emission according to the GA selected process scheme. And judging that the scheme obtained by the GA solution has the lowest carbon emission.
In summary, the calculation results verify the accuracy of the proposed carbon emission optimization model; and meanwhile, the feasibility of the parking site selection optimization model for controlling the emission of the jammed carbon and the rationality of model solving based on a genetic algorithm are verified.
The method is used as an important component of a low-carbon urban Intelligent Transportation System (ITS), and the path selection method based on parking decision can realize the beneficial effect of reducing the emission of the jammed carbon. The parking navigation and road condition optimization are combined through the dynamic parking partition, so that the dynamic parking guidance is realized, the dynamic and static traffic efficiency of a driver in a complex urban environment can be ensured, and the optimized and efficient overall path planning scheme with the lowest carbon and the optimized and efficient travelers is provided for the urban road network.
According to the invention, all public parking lots are public parking lots which can be parked in real time, the availability of the parking lots at the moment is firstly judged according to the running condition of vehicles, then genetic algorithm solution is carried out, the combination of reasonable organization schemes is obtained, parking areas are divided, and parking induction is carried out. According to a genetic algorithm, the unreasonable parking lot and the parking lot without the available parking spaces are deleted from the candidate s parking lots, the corresponding Thiessen polygonal mass centers are deleted, and road traffic flow is divided and calculated according to Thiessen polygonal grids formed by all the available parking lots finally, so that the planning navigation of the optimized carbon emission scheme path is realized.
The invention can fully plan the regulation and control effect of public parking lot resources on road traffic running conditions according to static traffic facilities, and reduce the carbon emission effect caused by urban road traffic jams. Besides real-time linkage of parking space information and road traffic condition planning, dynamic guidance of emergency road condition change is achieved, and meanwhile recommendation of vehicles entering a parking lot by a road network c emission optimization method is matched with a path-on-road module, so that a driver can travel more conveniently and efficiently, and beneficial effects are achieved on reduction of urban carbon emission. The system is a revolution for realizing the dynamic traffic regulation and control of static traffic and coping with road emergency and linkage technology.
Claims (3)
1. The navigation method based on the low-carbon target is carried out according to the following steps:
step 1: determining a starting point o and an end point d;
it is characterized in that the method comprises the steps of,
step 2: obtaining all feasible paths k among od in whole city 1 ，k 2 ，k 3 ，…，k m Is set K, k= { K 1 ，k 2 ，k 3 ，…，k m Defining a road sections in all feasible paths among the od to obtain a road section set A= {1,2,3 … a };
solving MinZ (X) according to the optimal principle of carbon emission of the road network, calculating the carbon emission of each path in the set K to obtain the carbon emission of each path in the set K, and obtaining an optimal path K with the minimum carbon emission ’ ，k ’ E, K, the vehicle follows the optimal path K ’ Navigating to a destination;
the optimal principle of the carbon emission of the road network is calculated according to the following formula:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
k represents the kth path in set K;
a is a road section number;
L a the unit is m, which is the length of the road section a;
the unit is s for the free flow time of the road section a;
c a the traffic capacity of the road section a is pcu/h;
alpha and beta are blocking coefficients, and 0.15 and 4 are taken respectively;
the unit is pcu for the flow on the kth path between od points with the starting point of o and the end point of d;
a road section-path variable, which is 0 or 1 variable; if the road section a belongs to the kth path between od points with the starting point of o and the end point of d, the road section a is +.>Otherwise->
f is a sixth order function subject to a speed-to-carbon emission rate conversion;
2. the parking lot navigation method based on the low-carbon target is carried out according to the following steps:
step (1): determining a starting point o and an end point d;
step (2): based on an open source map platform, acquiring real-time road condition information and parking facility use information at the current moment T, estimating the arrival time S according to the real-time road condition information, judging whether a matched parking lot has a free parking space when reaching a destination d, executing the step (3) if the matched parking lot has the free parking space when reaching the destination d, and executing the step (4) if the matched parking lot has no free parking space or the destination d has no matched parking space;
it is characterized in that the method comprises the steps of,
step (3): obtaining all feasible paths b among od in whole city 1 ，b 2 ，b 3 ，…，b m B= { B 1 ，b 2 ，b 3 ，…，b m Defining P road sections in all feasible paths among the od to obtain a road section set P= {1,2,3 … P };
solving MinZ (X) according to the optimal principle of carbon emission of the road network, and calculating the carbon emission of each path in the set B to obtain the carbon emission of each path in the set B, and obtaining an optimal path B with the minimum carbon emission ’ ，b ’ E P, the vehicle follows the optimal path b ’ Navigating to a destination;
the optimal principle of the carbon emission of the road network is calculated according to the following formula:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
b represents the B-th path in set B;
p is the road section number;
L p the unit is m, which is the length of the road section p;
the free flow time of the road section p is s;
c p the traffic capacity of the road section p is pcu/h；
Alpha and beta are blocking coefficients, and 0.15 and 4 are taken respectively;
the unit is pcu for the flow on the b-th path between od points with the starting point of o and the end point of d; />A road section-path variable, which is 0 or 1 variable; if the road section p belongs to the b-th path between od points with the starting point of o and the end point of d, the road section p is +.>Otherwise
f is a sixth order function subject to a speed-to-carbon emission rate conversion;
step (4): acquiring real-time road condition information and public parking lot use information at the current moment T, and pre-judging whether available public parking lots exist in 300 meters around the destination d;
if not, recommending the user to change the destination;
if so, N public parking lots with vacant parking spaces in the whole city range at the current moment are obtained, and the mass centers (N x ，N y ) Dividing Thiessen polygons for feature points to obtain a set O= {1,2, … i … j … N } of parking partitions, wherein i is more than or equal to 1 and less than or equal to N, j is more than or equal to 1 and less than or equal to N, and i is more than or equal to j, where i is (i) x ，i y ) Thiessen polygon partition starting at point, j is represented by (j x ，j y ) A Thiessen polygon partition for the endpoint;
n ', 2N' is less than or equal to N in N public parking lots, and the parking lots are formed Dividing an urban road network by the boundary of the alternative public parking lot combination alternative scheme to obtain a road section set R= {1,2,3 … R } and all feasible paths s among od 1 ，s 2 ，s 3 ，…，s m S = { S 1 ，s 2 ，s 3 ，…，s m }；
Solving MinZ (X) according to the principle of optimal road network carbon emission, and calculating the carbon emission of the urban road network divided by the combination alternative scheme of all public parking lots to obtain an optimal running path S' of the vehicle;
the vehicle navigates to the destination according to the optimal path S';
the specific formula is as follows:
x is the carbon emission of the road network;
z is the overall carbon emission level of the traffic road network;
r is the road section number;
ζ is the coefficient of the gravity model;
L r the unit is m, which is the length of the road section r;
f is the proportion of travel in a self-driving mode in the Thiessen polygon partition;
P i representing traffic volume generated by Thiessen polygon partition with i as a starting point;
B j representing the traffic attraction generated by the Thiessen polygonal partition with j as the endpoint;
t r (D r ) Traffic impedance for a Thiessen polygon partition starting at i to a Thiessen polygon partition starting at j;
D r the traffic flow on the road section r is pcu/h;
the unit is s, which is the free flow time of the road section r;
c r the traffic capacity of the road section r is pcu/h;
g is the number of ij pairs, G is the number of ij pairs;
s is the number of possible paths; h is the number of paths through r segments in the feasible paths;
μ is the desired value;
e is a natural logarithmic base;
θ is a traffic conversion parameter, θ=3 to 3.5;
is any one of the possible paths +.>Is set, the total travel time of (a);
α and β are blocking coefficients, and α=0.15 and β=4 are taken respectively;
D pr the number of the public parking lot positions of the r-section road is the number of the public parking lot positions of the r-section road;
D er the number of parking lots is set for the buildings with the exits on the r sections;
E pr the berth turnover rate is equal to the peak hour berth turnover rate of the public parking lot;
E er the method comprises the steps of establishing a parking lot peak hour berth turnover rate for a building;
U pr the utilization rate of berths is the peak hour of the public parking lot;
U er the method comprises the steps of building a parking lot peak hour berth utilization rate for a building;
f is a sixth order function subject to a speed-to-carbon emission rate conversion;
3. the low-carbon target-based parking lot navigation method according to claim 2, wherein an emergency situation is encountered during navigation:
if the traffic accident occurs along the optimal path b', returning to the step (2) to recalculate and judge;
if the destination d is provided with a spare parking space in the parking lot, planning a path according to a formula (2), and updating to obtain an optimal path until the navigation to the destination d is finished;
if no available vehicle position exists in the matched parking lot, executing the step (4) according to the road condition at the time of T+nt, wherein n=1, 2,3,4 and … to obtain the vehicle running path s 'under the condition of minimum carbon emission of the whole road network' T+nt Navigating to d; t is the current moment, and T is the time interval for acquiring the update of the open source map platform information;
if the public parking lot where the destination d is located is saturated, judging whether the current running position of the vehicle is within the range of the destination d300 meters or not;
if not, repartitioning the Thiessen polygon meshes according to the mass center of the public parking lot with the vacant parking spaces at the time of T+nt as the characteristic points, and recalculating the public parking lot positions and the optimal path s 'according to the formula (3)' T+nt ；
If yes, navigating to a public parking lot where a Thiessen polygon partition where a road section where the vehicle is located when T+nt;
and (5) until the navigation to the destination is finished.
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