CN1737502A - Quasi dynamic route optimization method of vehicle-mounted guiding system for evading delaying risk - Google Patents
Quasi dynamic route optimization method of vehicle-mounted guiding system for evading delaying risk Download PDFInfo
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Abstract
This invention relates to one auto loading guiding system route optimization method, which comprises the following steps: determining road unit even passing time, smooth reliability, invalidation relativity data; applying the above data with restrained A* route searching formula or improving the formula triggering function route researching formula; then executing the real time traffic information A* route researching method in the limited time; otherwise stops.
Description
Technical field
The present invention relates to onboard navigation system route optimization field, based on the unblocked reliability analysis, design and realized a kind ofly not having under real-time information or the limited real-time information considers to block the possibility minimum and the shortest binocular target of transit time is incured loss through delay the efficient algorithm of the quasi dynamic route optimizing of risk averse.
Background technology
Onboard navigation system (VIS) is as one of application of intelligent transportation system ITS, and it not only provides better routing information service to the user, can also help to reduce traffic jam, shortens running time and saves the energy, has therefore obtained in recent years using widely.Best route is important gordian technique in the vehicle automated navigation system preferably.China's research in this respect still is in the starting stage.According to route optimization based on information source, the vehicle automated navigation system can be divided into dynamic navigation and static navigation again, it is preferred that dynamic navigation is carried out route according to dynamic real-time information, it is preferred that static navigation is carried out route according to historical static information.Performance element difference according to path computing can be divided into the vehicle automated navigation system center control type and decentralised control formula onboard navigation system again in addition.Center control type path computing is finished by the computing machine of information center, and computing power is stronger, and decentralised control formula path computing is finished by truck-mounted computer, and computing power has limitation.The onboard navigation system that the present invention is directed to the decentralised control formula is carried out the route optimization design.
In blocking the normal urban transportation system of sending out, traffic flow has strong randomness, often has more greatly based on the routing of static analysis and real-time optimal path and departs from.But in the route of present dynamic route inducible system was preferred, have the problem of following several respects: 1) real-time information obtained and low-cost transmission problem.The whether accurate accurate prediction of depending on the road time of path decision, and in China, real-time information obtain and low-cost transmission problem is difficult to be solved at short notice.China is because fund is limit on the one hand, and the hardware of real-time information collection and transmission also fails to purchase on a large scale and install; On the other hand, also prematurity of real-time information forecasting techniques both at home and abroad, therefore be difficult to obtain all roadway elements in real time and information of forecasting; In addition, the message exchange of vehicle-mounted middle-end and information center need rely on wireless transmission, and is subjected to the restriction of channel capacity, is difficult to the low-cost of the information of accomplishing at present and transmits in real time.2) path computing real-time problem.Adopt legacy paths algorithm such as Dijkstra and standard A
*Algorithm carries out path computing, and its computing time, the increase with road network scale was index or non-linear increase.And the computing power of onboard navigation system is limited, and traditional algorithm is difficult to ensure the navigation real-time.3) user's multiple goal requires problem.At the crowded normal urban road network of sending out, it is very big that the randomness blocking and incur loss through delay takes place, so the user considers that not only the transit time under the normal condition is the shortest when carrying out routing, wishes also that the transit time reliability is maximum or run into the possibility minimum of obstruction.The multiple goal route planning generally can be by being that main target and other conditions are that restrictive condition is realized with a target.Limited critical path problem that Here it is.Yet this modification makes calculated amount increase greatly.And it is too subjective unavoidably to transfer multiple goal to single goal planning by linear weighted function; 4) coordination problem of user's optimum and system optimal.When derivative vehicle proportion is higher, can occur inducing vehicle to accumulate in same circuit, cause predisposition to lead the new obstruction of formation, cause system benefit to reduce.And it is consuming time long because of a large amount of iteration of need to take into account optimum optimum path search algorithm such as the point of fixity method (fixpoint) with system optimal of user when usually adopting, and is difficult to use in real-time navigation.
In view of above problem, incomplete and optimizing is consuming time because of real-time information longly can't be applied to reality in present stage based on the multiple goal path optimization algorithm of multidate information.Therefore existing China navigational system path optimization algorithm is based on static analysis more.But have hourage highly uncertainly owing to block the normal city road network of sending out, often have more greatly based on the routing of static analysis and actual optimal path and to depart from.Therefore,, meet the requirement of user's multiple goal, and path optimization's algorithm of taking into account the system optimization target is a problem of needing solution badly how not having to provide efficiently and accurately under comprehensive real-time information give-and-take conditions.
In fact, to road network topology structure and the metastable roadnet of each sub-district economic development, traffic flow has clear regularity.Under the condition that real time data can't gather comprehensively and accurately predict and low cost is transmitted, utilize historical traffic flow statistics data, analyze the probability of happening of road network unblocked reliability or obstruction or destructive insident, can provide more near actual conditions and the routing of effectively evading the satisfaction of incuring loss through delay risk.By these processing,, can obtain satisfactory solution with less time and space cost though not necessarily obtain optimum solution.Can be the decision maker simultaneously several reasonable paths (comprising optimal path) are provided,, reduce the clustering phenomenon so that traveler is selected according to self-demand.
Summary of the invention
Based on above analysis, the present invention is by fail-safe analysis, and by historical information is refined, having designed with average stroke time and unblocked reliability is the demarcation of biparametric roadway element right of way.Do not having under real-time information or only limited real-time information (as broadcasting, the electronic information plate information) condition, designed a kind of at distributed onboard navigation system the consideration transit time and block the efficient algorithm of the heuristic quasi dynamic route optimizing of risk binocular target.When not having real-time information, by designing constrained A
*Algorithm, and in the optimum path search process, carry out heuristic evading to blocking roadway element occurred frequently, be implemented in the quick search of effectively evading the trusted path of incuring loss through delay risk in the tolerance band that detours; When incident generations such as limited real-time information represents that accident is arranged, serious obstructions, by the actual effect correlation analysis and improve A
*The heuristic function of algorithm can realize inducing the real-time adjustment in path.The characteristics of this algorithm are that real time reaction speed is fast, can rely on multidate information completely, reduce trip and incur loss through delay risk, and can make real time reaction to emergency.By multipath planning and information issue, help realizing the coordination of system optimal and user's optimum simultaneously.
This invention has improved the accuracy based on the navigation of historical information owing to considered to block the possibility that takes place, and accuracy is higher than static navigation.
Technical thought of the present invention is characterized as:
1. the demarcation of biparametric roadway element right of way
2. design constrained A
*Path search algorithm is to improve the efficient of route searching.
3. utilize failure correlation analysis and risk averse A
*Path after algorithm solution right of way changes is planning problem again
Below be the detailed description of technical thought feature of the present invention and concrete scheme, as shown in Figure 1:
1. demarcate biparametric roadway element property file
In our technology, before the running route planning algorithm, to determine three kinds of data of serving algorithm earlier: the one, the average transit time of the roadway element of each typical period of time, the one, the possibility of obstruction takes place in each typical period of time roadway element, be the unblocked reliability of roadway element, the one, the failure correlation between the roadway element of each typical period of time.These three kinds of information are stored on the vehicle-mounted CD-ROM by the database form, and are upgraded in the cycle with certain hour (being generally half a year).During navigation with the average transit time of the roadway element of each typical period of time as right of way, and possibility occurrence and the uncertainty of travel time are blocked in consideration in the optimum path search process, by evading to improve navigation accuracy, improve the reliability of travel time based on static historical information to blocking roadway element occurred frequently.
Utilize this technical thought, in our risk averse autonomous navigation system, the average running time and the roadway element fiduciary level of (accident free or unusual congestion condition under) typical period of time under the roadway element normal condition, promptly the probability of roadway element running status normal (unimpeded) can exist in the vehicle optical disk in the navigation vehicle.We are referred to as roadway element default (acquiescence) property file.Among the present invention, each turns to a virtual segment and represents with the road network crossing to take the extension of network technology, thereby weighs network (promptly have only the limit that weight is arranged, node does not have weight) Yi Bian whole road network is converted into.Below for the method for building up of risk averse autonomous navigation system default file.
Determine that wherein the roadway element unblocked reliability will be through two processes:
A. typical period of time determines and the binary condition hypothesis
According to urban transportation time distribution character, one day can be divided into n (n＞=3) the individual period, our suggestion is calculated average running time of each roadway element and operational reliability respectively with being divided into early flat peak of flat peak, morning peak, noon, evening peak, five typical period of time in flat peak at night in one day.
Usually, the driver is not very sensitive to the change of normal running time, and when running time changed in an acceptable scope, they were ready to travel along the path of the minimum average B configuration running time of guiding.When traffic hazard takes place, because of running time fluctuation is bigger, so need upgrade and search out a new optimization path to the roadway element running time.
Therefore, roadway element is done the binary condition hypothesis, the state that is about to roadway element is divided into two kinds: normal and unusual; Roadway element comprises roadway element and crossing two parts, distinguishes the normal and unusual boundary of roadway element and be the roadway element unit of setting the in advance threshold speed that travels, and then is considered as acting normally greater than this value, then is considered as showing unusually less than this value; Distinguishing the normal and unusual boundary in crossing then is the average intersection delay threshold value of setting in advance; Then be considered as acting normally less than this value, then be considered as unusually greater than this value.
B. set up the default fiduciary level file of roadway element
According to binary condition hypothesis, the fiduciary level of roadway element can be defined as the probability that unusual delay (or travel speed is lower than certain boundary) do not take place in official hour section roadway element.
When having certain period of history the traffic flow data of (usually greater than three months), adopt the approximate value of following formula computing unit unblocked reliability;
Roadway element i unblocked reliability r
iBe expressed as:
When judging that whether unimpeded roadway element is, it is criterion that roadway element adopts the speed of a motor vehicle, and it is criterion that stop delay is adopted in the crossing, can be referring to the document of related fields as for criterion;
Usually, the unusual probability of incuring loss through delay takes place in the path to be increased along with the increase of the magnitude of traffic flow, therefore, when lacking historical traffic flow data, recommends to adopt the unblocked reliability of following functional form approximate estimation roadway element:
r
i＝￠(v
i/c
i)
3+β(v
i/c
i)
2+γ(v
i/c
i)+c (2)
In the formula,
r
i---the unblocked reliability of roadway element i;
v
i/ c
i---be defined as the saturation degree of roadway element i, wherein v
iBe flow, can obtain c by traffic flow data in a short time by roadway element i
iBe the traffic capacity of unit i, different with grade and different according to road type, be a definite value, can check in by pertinent literature;
￠, beta, gamma---return undetermined coefficient; C---constant term.
Set up the default running time file of roadway element
For the roadway element with traffic flow data more than month, at the average running time that calculates under the roadway element i normal condition in a certain amount of time, this average running time is exactly the weight w of roadway element i with statistical method
i
During for the traffic flow data of those neither ones more than the moon, for roadway element according to historical origin and destination information, O-D information just, utilize conventional traffic distribution method in the traffic programme theory that the O-D matrixes of different periods in one day is distributed, according to the volume of traffic that distributes on the resulting roadway element i, thereby calculate its travel speed according to the relation of the volume of traffic in the traffic flow theory and speed, use the travel speed of the length of roadway element i then divided by this roadway element, and then obtain the transit time of each roadway element, this average running time is exactly the weight w of roadway element i
iFor the crossing,, suppose that its mean delay time approximate same has more than one month the similar crossing of traffic flow data identical according to the crossing type;
The failure correlation of wherein setting up between roadway element adopts following method:
When traffic hazard occurred on certain roadway element, ANOMALOUS VARIATIONS also can take place because of being affected in other roadway elements that are adjacent, and we are called failure correlation between roadway element with this phenomenon; Determine the two kinds of means of passing through between roadway element: the one, analyze failure correlation between each roadway element according to historical traffic information; The one, utilize existing traffic simulation technology, make a certain roadway element produce and block, thereby analyze the travelling speed of other roadway elements and the relation between the unit of blocking the road; At last with the failure correlation data storage between roadway element on vehicle-mounted CD-ROM.
2. improved A
*Path search algorithm
The present invention's risk minimum the shortest with the following travel time of normal condition and that occur blocking is the double goal of path optimization, by designing the A of constrained obstruction risk averse
*Heuritic approach, and improve A
*The heuristic function of algorithm effectively improves the search efficiency of best route, reduces search time.
A good route is meant in the present invention, although not necessarily best (the fastest), be one reliable for acceptable and travel time of driver.If the expense (length or time) of the route of suggestion is unlike under normal operation optimization path showed increased, it is an acceptable so, if it is lower to run into the likelihood ratio of blocking or incuring loss through delay under steam, the path that is proposed so is reliably, determine the most reliable and shortest path is that a binocular is marked a route planning problem.The present invention reliably reaches the shortest Optimization Model of setting up dual optimization aim of path transit time with the path.
As mentioned above, binocular mark route planning problem can be converted into constrained single goal problem and finds the solution.And the traditional mathematics planning algorithm is found the solution overlong time.Therefore, we take constrained heuritic approach to solve this problem.Our algorithm thinking is based on the following fact: in shortest path algorithm, if roadway element i has bigger weight w
i, then it will have big possibility not to be included in shortest path P from node s to node t
StIn, if we set w
i=∞, roadway element i will appear at P never so
StIn, research in the past such as Rouphail (1995) once utilized this true a kind of paths planning method before travel that proposes, promptly by increasing shortest path P
0In the weight of every roadway element be original 20%, 50%, 100%, offer the some shorter alternative paths of application person.But this method does not consider to detour constraint, and Pu (2001) has expanded the algorithm of Rouphail, by Dijkstra shortest path algorithm and the exploratory increase method of roadway element weight, searched out under the constraint condition that detours with the shared some limits of shortest path than short path.But this algorithm can't be accomplished the optimization of sharing the limit is chosen.
The driver is relatively more responsive to unusual delay usually, and a good path should be avoided through running into the big or lower roadway element of fiduciary level of unusual delay possibility under the constraint condition that detours as much as possible.Therefore, the fact above utilizing, we have invented a kind of heuritic approach, utilize the method to the weighting of height obstruction risk unit to reduce the possibility that the excessive risk unit occurs in best road.This algorithm at first to the weight of excessive risk road add one very big on the occasion of, and then calculating shortest path, when gained shortest path road length retrains above detouring, gradually reduce the weight of increase, thereby under the constraint condition that detours, effectively search and avoid the high trusted path of incuring loss through delay risk (low fiduciary level) unit as far as possible.This algorithm belongs to heuritic approach, though not necessarily obtain optimum solution, this algorithm is consistent with experienced drivers ' behavior, and therefore the driver who is easy to be guided accepts.In this algorithm, in view of A
*Algorithm is the optimum path search algorithm (A of present comparatively effective single place monohapto point
*The 3rd the thinking feature description that see below described and improved to algorithm principle), we use A
*Algorithm is as basic shortest path searching method.
Algorithm comprises two parts: the one, and utilization A
*Algorithm calculates trusted path in conjunction with the weight increment method, and the 2nd, check whether the path satisfies length (or time) restriction.When finding the highly reliable path of satisfying length (or time) restriction, algorithm stops.Concrete scheme process flow diagram is seen accompanying drawing 2.
Wherein constrained existing A
*Path search algorithm is as follows:
1) in some typical period of time, makes iterations k=0, with w
iBe the weight of roadway element i, by existing A
*Algorithm finds the path P with minimal weight
S, 0, calculate P
S, 0Journey time is L
S, 0
2) by fiduciary level r to roadway element i
iAnalyze, the roadway element i that the online fiduciary level of satisfying the need is lower, r is got in suggestion
i＜0.5 roadway element increases a weight increment Delta w
i
Increase back weight w
i'=w
i+ Δ w
i=w
i+ α
k(1-r
i)
qW
0(3)
α is that weight increases coefficient 0＜α＜1.r
iBe the fiduciary level of roadway element i, W is got in suggestion
0=1.5L
S, 0～3L
S, 0
When k=0, discriminant index q=0, k＞=1 o'clock, discriminant index q=1;
3) calculate trusted path:
Make new round iterations k '=k+1, with w
i' be the new weight of roadway element i, with existing A
*The path P of algorithm computation weight minimum
S, k ', the weight of the roadway element i above it is reverted to w
i, calculate L
S, k ', path P just
S, k 'On each roadway element right of way w
iSummation;
4) check the path constraint condition:
If time restriction L is satisfied in the gained path
S, k '＜β L
S, 0, then forward 5 to), otherwise get back to 2); β is for allowing coefficient, and 1.0-1.5 is got in suggestion;
5) constrained existing A
*Path search algorithm finishes;
At this algorithm, in first time iteration, k=0, the weight that has each roadway element of high risk on the road network begins all to increase W
0Thereby, avoided these appearance of excessive risk roadway element in path planning.If violated the restrictive condition of the length that detours, just need planning again.This means to being met the path of the restriction of detouring, once the part excessive risk roadway element of being avoided needs by the path process of new planning, for this reason, and in iteration subsequently, the weight that the high risk roadway element has increased is progressively reduced, and shortest path is recomputated under new weight.Function alpha
k(1-r
i)
qGuarantee Δ w
iReduce along with the increase of iterations.In order to avoid the high-risk roadway element to appear on the recommendation paths as far as possible, the weight of high-risk roadway element is than lacking that relatively low red route unit reduces simultaneously.In order to obtain better path, when reducing Δ w
iAfter the optimal path that obtains when not violating restrictive condition, can suitably between circulation last time and current cycle values, raise Δ w
iAgain carry out the road through planning, because may exist one to avoid more high-risk roadway elements but also satisfy simultaneously the optimal path of length restriction.Yet this method will cause a large amount of iterative computation, is not suitable for the real-time route search, so we adopt Δ w in this article
iDull minimizing method, although this method may can not get optimal path, but it can obtain acceptable result quickly.
Allow factor beta different along with driver's difference, the driver is unwilling to take a risk more, and β is big more, may be will be cost with the long path of detouring because avoid dangerous roadway element.
Because of single point is the aforementioned rudimentary algorithm that need repeatedly call in the constrained path optimizing heuritic approach that has to the calculating of a shortest path, its search speed directly has influence on the high efficiency of above-mentioned algorithm.In the Shortest Path Searching Algorithm of point-to-point transmission, more effectively representing algorithm is exactly A at present
*Algorithm (Hart et a1., 1968).With the searching algorithm such as the dijkstra's algorithm difference of breadth First, A
*Whether algorithm only calculates with its adjacent node, and decide this node may be on optimal route with each node to the estimated distance of point of destination.In the algorithm search process, each node n is endowed weight f (n)=g (n)+h (n), here g (n) refer to from starting point long to the shortest path of node n, h (n)) dactylus point n estimates to the destination minimal path is long.Therefore f (n) estimates that through the shortest path from the starting point to the point of destination of node n is long we also are called A to all
*The heuristic function of algorithm.Heuristic function h (n) can control A
*The search behavior of algorithm.In the search procedure each node with minimum f value with selected as next extension point.If the actual minimal path that h (n) is less than or equal to from node n to the destination is long, A
*Algorithm will find optimum solution.When h (n) replaces with 0, algorithm will be simplified as dijkstra's algorithm (Dijkstra, 1959).H (n) validity near the actual value route searching more is good more.When h (n) was long greater than the actual shortest path from node n to the destination, search speed will improve, but can't guarantee optimal case.
A commonly used at present
*Algorithm h (n) estimates generally based on the Euclidean geometry distance estimations, when with stroke distances during as the road weight, generally arrive the long estimated value h (n) of shortest path of destination as node n with the Euclidean geometry distance, when being the road weight, then use the Euclidean geometry distance to estimate as h (n) divided by the road network maximal rate with the road time.But in actual road network, based on the h (n) of Euclidean geometry distance though estimate can guarantee to obtain optimum solution that because of h (n) estimation and actual shortest path length based on the Euclidean geometry distance have than large deviation, the search efficiency of algorithm is difficult to be protected.
The present invention is promptly according to the geometrical property and the traffic characteristics of actual road network, ingeniously utilizes constrained A
*The results of intermediate calculations of path search algorithm is improved h (n) and is estimated, make its as much as possible near but be less than or equal to the reality the shortest transit time of n point to terminal point, thereby improve constrained A
*The efficient of path search algorithm.
At A
*In the algorithm, two tables be use, table (open list) and open list (open list) just closed.Be placed in the node of checking as calculated and close in the table, calculated and the node that was not examined is placed in the open list.Close in the table when node n is placed to, g (n) is exactly the expense of the shortest path from the starting point to the node, and for not closing the node n of table, g (n) is then more than or equal to the shortest path expense from starting point to node n.
Wherein improved A
*The path search algorithm of heuristic function is as follows in the algorithm:
(1) in some typical period of time, makes iterations k=0, with w
iBe the weight of roadway element i, at the existing A of utilization
*During the algorithm computation shortest path, calculate transit time shortest path between terminus by search order from the terminal point to the starting point, to each the roadway element i right of way in the search procedure with its reverse right of way w
jFor being placed on the node n that closes in the table in the search procedure, storing its node n is g (n) ' to the shortest transit time value of terminal point, obtains having from origin-to-destination the path P of minimal weight simultaneously
S, 0, and then calculate P
S, 0Journey time is L
S, 0, promptly form P
S, 0Each roadway element weight and;
(2) by fiduciary level r to roadway element i
iAnalyze, for the low roadway element i of fiduciary level, r is got in suggestion
i＜0.5, increase a weight increment Delta w
i
Increase back weight w
i'=w
i+ Δ w
i=w
i+ α
k(1-r
i)
qW
0(4)
α is that weight increases coefficient 0＜α＜1.r
iBe the fiduciary level of road i, W is got in suggestion
0=1.5L
S, 0～3L
S, 0When k=0, discriminant index q=0; K＞=1 o'clock, discriminant index q=1;
(3) make new round iterations k '=k+1, with w
i' be the new weight of road i, with existing A
*Algorithm is by the search order from origin-to-destination, and the path of carrying out after right of way changes is recomputated; For in the computation process for being put into the node of closing in the table, utilize existing A in (1)
*The g of reverse search (n) ' makes it replace h (n) value; , use from the Euclidean distance of origin-to-destination divided by the design rate of roadway element as h (n) not at the node of closing in the table for those, the design rate of roadway element can be referring to the traffic engineering books, thereby calculate the path P of weight minimum
S, k ', the weight of the road i above it is reverted to w
i, calculate L
S, k ', path P just
S, k 'On each roadway element right of way w
iSummation;
(4) check the path constraint condition:
If time restriction L is satisfied in the gained path
S, k '＜β L
S, 0,, then forward (5) to, otherwise get back to (2); β is for allowing coefficient, and 1.0-1.5 is got in suggestion;
(5) improved A
*The path search algorithm of heuristic function finishes in the algorithm; Its algorithm flow is seen accompanying drawing 3.
This correction can significantly reduce the route searching scope, thereby effectively improves the efficient of algorithm.The validity of this method is: at actual road network, for the constraint heuristic A is being arranged
*Be put into the node of closing in the table in the step 1) of algorithm, g (n) is the reality the shortest transit time of node n to terminal point, and it is inevitable more than or equal to the estimation based on Euclidean distance and road network maximal rate.But still less than at subsequently iteration weighting posterior nodal point n the shortest transit time to terminal point.That is to say that these once were placed in the node of closing in the table in step 1), in iteration subsequently, can have and be better than estimating, be i.e. further actual shortest time of convergence and less than the actual shortest time based on shortest time of Euclidean distance and road network maximal rate.And in step 1) in the hunting zone most of nodes be placed in and closed in the table, estimate to the shortest transit time of the reality of the improvement of terminal point thereby in iteration subsequently, can obtain most of nodes involved in the hunting zone.
3, when transport information such as accident, obstruction, construction account for road etc. and occur on the path planning, carry out the A that has limited Real-time Traffic Information
*Path search algorithm: otherwise finish;
When traffic hazard occurs on the minimal path of having planned, the roadway element right of way of accident place roadway element and involved area will change, so vehicle needs be recomputated to the optimal path of destination.Occur on the introduction route or driver when departing from the route of suggestion as other unusual delays, optimal path also needs be recomputated.Current qualitativeization of incident roadway element (the language description of degree of congestion is only arranged) blockage information can be distributed to the driver by means such as broadcasting.Our invention emphasis concentrates on the route planning algorithm when the limited multidate information of incident roadway element is only arranged.
For autonomous navigation system, the accuracy of route planning is decided by when limited multidate information announcement has abnormal conditions to take place, to the estimation accuracy of accident roadway element and other relevant roadway element running times.In fact, when traffic hazard occurred on certain roadway element, ANOMALOUS VARIATIONS also can take place in other roadway elements that are adjacent because of being affected, and we are called the obstruction correlativity with this phenomenon.
We consider three kinds of failure correlations:
Class1: inefficacy positive correlation
Definition: when road unit i owing to incidents such as traffic hazard take place took place unusual the obstruction, roadway element j also blocked thereupon.
Type 2: inefficacy negative correlation.
Definition: when road unit i owing to incidents such as traffic hazard take place took place unusual the obstruction, the running status of roadway element j was improved on the contrary.
Type 3: it is independent to lose efficacy
Definition: when road unit i owing to incidents such as traffic hazard take place took place unusual the obstruction, the running status of roadway element j was not influenced by it.
The algorithm that route was planned again after right of way changed in the past is primarily aimed at the robot field, and the distance restriction of the unit of right of way variation far from terminus taken place algorithm validity.The present invention by to the accident roadway element, block the positive correlation roadway element and block danger, peak roadway element and rationally evade realization accident or unusual planning again of blocking path when taking place etc., the adjustment of realizing route; And utilize the store information of previous calculation to improve A
*Heuristic function in the algorithm improves the search efficiency of best route, reduces search time, guarantees the real-time of path planning.
If dynamic information is disclosed in when having accident to take place on the selected route, utilize risk averse A of the present invention
*Algorithm, the driver can reselect route fast, and algorithm mainly comprises three parts: weight increases, trusted path calculates and the constraint condition inspection.
This algorithm and described before constraint risk averse A arranged
*The difference of algorithm maximum is that weight increases process, except increasing the weight of blocking the excessive risk roadway element, the weight of our also increase accident roadway element and the weight of the positively related roadway element in unit, old course road of working together, effectively to evade excessive risk roadway element, the positively related roadway element of accident roadway element and colleague unit, old course road, its process flow diagram is seen accompanying drawing 4.
The A that has limited Real-time Traffic Information
*Path search algorithm is as follows:
[1] initialization:
Make iterations k=0, being presented at when dynamic information has unusual obstruction on the route of cooking up, and when needing again programme path, the estimation running time that makes roadway element i is the weight w of roadway element
i
[2] roadway element weight changes
For the lower roadway element of fiduciary level, r is got in suggestion
i＜0.5, and the relevant roadway element with it of accident roadway element, with their weight increase weight increment Delta w,
For roadway element i, increase the back weight
w
i’＝w
i+Δw
i＝w
i+α
k(1-r
i)
qW
0 (5)
α is for weighing to such an extent that increase coefficient 0＜α＜1.r
iBe the fiduciary level of roadway element i, W is got in suggestion
0=1.5L
S, 0～3L
S, 0When iterations k=0, q=0; K＞=1 o'clock, q=1;
For accident roadway element i, make the fiduciary level r of roadway element i
i=0, so w
i'=w
i+ α
kW
0, 0＜α＜1;
When unusual the obstruction takes place owing to roadway element i in road unit j, also block thereupon, make r
j=0, so w
i'=w
i+ α
kW
0, 0＜α＜1;
When road unit j owing to roadway element i took place unusual the obstruction, running status was improved on the contrary, makes r
j=1, so w
j'=w
j
When the running status of road unit j was not subjected to roadway element i that influencing of unusual obstruction taken place, its weight was constant;
[3] new round iterations k '=k+1 is with the existing A of the weight after changing
*Algorithm recomputates weight minimal path P
S, k ', the estimated value w of accident roadway element running time before the roadway element that reduces then arrives
i, and calculate L
S, k '
[4] route inspection
If P
S, k 'Satisfy restrictive condition, just L
S, k '＜β L
S, 0, turn to [5], otherwise, return [2];
[5] algorithm finishes.
P
S, k 'Satisfy the trusted path of length restriction condition exactly.
In order to save computing time, the length restriction condition can relax even cancel by proper method.This invention is particularly useful for the situation that following digital broadcasting is applied to the transport information issue.
Description of drawings
Fig. 1 algorithm is implemented overall procedure
The constrained optimum path search heuristic A of Fig. 2
*Algorithm flow chart
The constrained optimum path search heuristic A of Fig. 3 correction
*Algorithm flow chart
Heuristic A is planned in Fig. 4 path again
*Algorithm flow chart
The path of the shortest cruising time of Fig. 5 coexists under the length restriction condition trusted path relatively
Fig. 6 does not utilize the A of planning again of reverse search information
*The algorithm search scope
Fig. 7 utilizes the A of planning again of reverse search information
*The algorithm search scope
Embodiment
We are with the road network of having built of computer virtual, and at random to the assignment of carrying out of the average transit time of roadway element and unblocked reliability, with the feasibility and the validity of verification algorithm.Algorithm is tested under the network of different random and condition, at first, there is the little network of 36 nodes and 60 roadway elements under three kinds of conditions, to carry out the trusted path search that having of beginning-of-line detoured and retrained to one, utilize this experimental result can show the rationality of invention, utilization has the test findings of the big road network of 2800 nodes to show the search efficiency of this invention.
Little network as shown in Figure 5, node is represented with circle, node number is marked in the circle, roadway element is represented with thin grey lines.Average velocity under the normal condition (kilometer/hour) be marked on the next door of relevant roadway element with fiduciary level.Normal average velocity is between 30-60, and fiduciary level is between 0-1.Starting point and terminal point represent that with the rectangle of black the starting point number is 24, and the terminal point number is 35.Fiduciary level is lower than 0.9 roadway element and is regarded as blocking the excessive risk roadway element, and it is 1.1 that the length that detours allows factor beta.
Under the separate hypothesis in the back of losing efficacy between the roadway element, the fiduciary level in path is exactly the amassing of fiduciary level of the roadway element in all these paths, this long-pending degree of reliability that can be used to estimate a path.
As shown in Figure 5, represent with the black line of a broad according to the shortest path of the Time Calculation of normally on average travelling, expense be 38 (minute), the path fiduciary level is 0.45.The reliable road of the length restriction that do not detour (promptly avoiding all excessive risk roadway elements) represents with wide grey lines, its expense be 38.6 (minute), fiduciary level is 0.71.The shortest path that has length restriction represents with a wide dotted line, its expense be 35 (minute), fiduciary level is 0.56.Clearly, the fiduciary level in path is improved by avoiding the excessive risk roadway element, for example, on nothing detours the trusted path of length restriction, avoided at roadway element between node 18 and 19 (the roadway element fiduciary level is 0.81) and the roadway element between node 10 and 19 (the roadway element fiduciary level is 0.73).Yet, in having the shortest path of length restriction, some excessive risk roadway elements, for example roadway element between the node 10 and 19 (the roadway element fiduciary level is 0.73), satisfying length restriction, but fiduciary level still is higher than the shortest path of at all not considering the roadway element fiduciary level in being included in.
Accompanying drawing 6 and accompanying drawing 7 are big road network Test Drawing, in the drawings, the average cruising speed of roadway element by at random specify in 30-60 (kilometer/hour) between.Start node is 790, and terminal point is 2008, and trusted path is represented with wide black line, when on the trusted path of suggestion, having an accident, and the planning request is at node 939 again, and the accident roadway element is represented with a wide black line, loses efficacy relevant roadway element (comprising positive correlation and negative correlation) in circle.
In order more clearly to demonstrate A
*Again the planning algorithm of algorithm, we think that programme does not have length restriction again, therefore, the accident roadway element is added to a sizable value with running time with its actively relevant roadway element, and roadway element relevant with its passiveness then reduces to 1/2 of original value.As shown in Figure 6, begin again programme in trip and do not consider A
*The information of shortest path, originally Jian Yi path is represented with wide gray line, the path planning again of suggestion represents that with thick black line the node of using represents that with thick black circle the nodal point number of using is 392.
Accompanying drawing 7 is A before utilizing
*Searching for, canned data is carrying out A
*Search.Originally Jian Yi path is represented with the cinder line, and the path planning again of suggestion represents with thick black line, and the node of using represents that with thick black circle the nodal point number of using is 53, shows that search efficiency is greatly improved when having considered before travel information.
According to different scales grid road network at the interior 64M that saves as, carry out 1000 times stochastic calculation analysis on the notebook of CPU800M respectively, compare the uncorrected constraint A that has total computing time
*Total shortening computing time of algorithm is average shortens 66%.
Following table is the numerical result of detailed calculated time.
| Road network scale (nodal point number) | The path average search time (second) | Compare uncorrected A
*Total shortening computing time of |
| 30×30 | 1.2 | 51％ |
| 50×50 | 3.2 | 58％ |
| 80×80 | 4.8 | 72％ |
| 100×100 | 5.4 | 85％ |
Claims (2)
1, a kind of onboard navigation system quasi dynamic route optimization method of incuring loss through delay risk averse is characterized in that, may further comprise the steps:
1. demarcate biparametric roadway element property file
N, n 〉=3 typical period of time will be divided in one day; Below operation carry out at any one typical period of time wherein, the method for operating of other period is identical;
Determine three kinds of data of serving navigation algorithm: the one, the average transit time of the roadway element of each typical period of time; The one, the possibility of obstruction, the i.e. unblocked reliability of roadway element take place in each typical period of time roadway element; The one, the failure correlation between the roadway element of each typical period of time;
Determine that wherein the roadway element unblocked reliability will be through two processes:
A. roadway element is done the binary condition hypothesis: the state that is about to roadway element is divided into two kinds: normal and unusual; Roadway element comprises highway section and crossing two parts, distinguishes the normal and unusual boundary in highway section and be the unit of setting in advance, the highway section threshold speed that travels, and then is considered as acting normally greater than this value, then is considered as showing unusually less than this value; Distinguishing the normal and unusual boundary in crossing then is the average intersection delay threshold value of setting in advance; Then be considered as acting normally less than this value, then be considered as unusually greater than this value;
B. determine the unblocked reliability of roadway element, the unblocked reliability of roadway element can be defined as that unusual delay does not take place in the highway section in the official hour section, or travel speed is lower than the probability of certain boundary;
When the traffic flow data that has more than 3 months, adopt the approximate value of following formula computing unit unblocked reliability;
Roadway element i unblocked reliability r
iBe expressed as:
When judging that whether unimpeded roadway element is, it is criterion that the speed of a motor vehicle is adopted in the highway section, and it is criterion that stop delay is adopted in the crossing, can be referring to the document of related fields as for criterion;
When the traffic flow data that do not have more than 3 months, can pass through function f (v
i/ c
i) approximate estimation, the concrete form of function can determine that by returning method is: at first, and with v
i/ c
iBe independent variable, fiduciary level is that dependent variable is done scatter diagram, and the shape according to scatter diagram carries out curve fitting then, and last in the curve that simulates, selecting the most rational is concrete function expression;
v
i/ c
i---be defined as the saturation degree of roadway element i, wherein v
iBe flow, can obtain c by traffic flow data in a short time by roadway element i
iBe the traffic capacity of unit i, different with grade and different according to road type, be a definite value, can check in by pertinent literature;
Wherein set up the average transit time of roadway element, adopt following method:
For the roadway element with traffic flow data more than month, at the average running time that calculates under the roadway element i normal condition in a certain amount of time, this average running time is exactly the weight w of roadway element i with statistical method
i
During for the traffic flow data of those neither ones more than the moon, for the highway section according to historical origin and destination information, O-D information just, utilize conventional traffic distribution method in the traffic programme theory that the O-D matrixes of different periods in one day is distributed, according to the volume of traffic that distributes on the resulting highway section i, thereby calculate its travel speed according to the relation of the volume of traffic in the traffic flow theory and speed, use the travel speed of the length of highway section i then divided by this highway section, and then obtain the transit time in each highway section, this average running time is exactly the weight w of unit, highway section i
iFor the crossing,, suppose that approximate same of its average running time has more than one month the similar crossing of traffic flow data identical according to the crossing type;
Determine that wherein the failure correlation method between roadway element is as follows:
When traffic hazard occurred on certain roadway element, ANOMALOUS VARIATIONS also can take place because of being affected in other roadway elements that are adjacent, and this phenomenon is called failure correlation between roadway element; Determine that failure correlation between roadway element is by two kinds of means: the one, analyze failure correlation between each roadway element according to historical traffic information, the one, utilize existing traffic simulation technology, make a certain highway section produce and block, thereby analyze the travelling speed in other highway sections and the relation between the congested link; Then with the failure correlation data storage between roadway element on vehicle optical disk;
2. improved A* path search algorithm
Improved A* path search algorithm is divided into two kinds: a kind of is constrained A* path search algorithm, and a kind of is the path search algorithm that has improved heuristic function in the A* algorithm;
Wherein constrained existing A* path search algorithm is as follows:
1) in some typical period of time, makes iterations k=0, with w
iBe the weight of roadway element i, find path P with minimal weight by existing A* algorithm
S, 0, calculate P
S, 0Journey time is L
S, 0
2) by fiduciary level r to roadway element i
iAnalyze, the roadway element i that the online fiduciary level of satisfying the need is lower, r is got in suggestion
i＜0.5 roadway element increases a weight increment Delta w
i
Increase back weight w
i'=w
i+ Δ w
i=w
i+ α
k(1-r
i)
qW
0(2)
α is that weight increases coefficient 0＜α＜1.r
iBe the fiduciary level of roadway element i, W is got in suggestion
0=1.5L
S, 0~ 3L
S, 0When k=0, discriminant index q=0, k＞=1 o'clock, discriminant index q=1;
3) calculate trusted path:
Make new round iterations k '=k+1, with w
i' be the new weight of roadway element i, with the path P of existing A* algorithm computation weight minimum
S, k ', the weight of the roadway element i above it is reverted to w
i, calculate L
S, k ', path P just
S, k 'On each roadway element right of way w
iSummation;
4) check the path constraint condition:
If time restriction L is satisfied in the gained path
S, k '＜β L
S, 0, then forward 5 to), otherwise get back to 2); β is for allowing coefficient, and 1.0-1.5 is got in suggestion;
5) constrained existing A* path search algorithm finishes;
The path search algorithm that has wherein improved heuristic function in the A* algorithm is as follows:
When utilization A* algorithm, each node n in the road network, its weight f (n)=g (n)+h (n), g (n) refers to from starting point longly to the shortest path of node n here, h (n) dactylus point n arrives the estimation function that the destination shortest path is grown; Thereby g (n) refers to from starting point to the long estimation function of destination shortest path.In existing A* algorithm, also to use two tables, just close table (close list) and open list (open list); Be placed in the node of checking as calculated and close in the table, calculated and the node that was not examined is placed in the open list;
(1) in some typical period of time, makes iterations k=0, with w
iBe the weight of roadway element i, when the existing A* algorithm computation shortest path of utilization, calculate transit time shortest path between terminus by the search order from the terminal point to the starting point, to each the roadway element i right of way in the search procedure with its reverse right of way w
jFor being placed on the node n that closes in the table in the search procedure, storing its node n is g (n) ' to the shortest transit time value of terminal point, finally searches for the gained shortest path and is actually the path P that has minimal weight from origin-to-destination
S, 0, and then calculate P
S, 0Journey time is L
S, 0, promptly form P
S, 0Each roadway element weight and;
(2) by fiduciary level r to roadway element i
iAnalyze, for the low roadway element i of fiduciary level, r is got in suggestion
i＜0.5, increase a weight increment Delta w
i
Increase back weight w
i'=w
i+ Δ w
i=w
i+ α
k(1-r
i)
qW
0(3)
α is that weight increases coefficient 0＜α＜1.r
iBe the fiduciary level of road i, W is got in suggestion
0=1.5L
S, 0~ 3L
S, 0When k=0, discriminant index q=0; K＞=1 o'clock, discriminant index q=1;
(3) make new round iterations k '=k+1, with w
i' be the new weight of road i, by the search order from origin-to-destination, the path of carrying out after right of way changes is recomputated with existing A* algorithm; For being put into the node of closing in the table in the computation process, utilize the g (n) ' of existing A* reverse search in (1), make it replace h (n) value; , use from the Euclidean distance of origin-to-destination divided by the design rate of roadway element as h (n) not at the node of closing in the table for those, the design rate of roadway element can be referring to the traffic engineering books, thereby calculate the path P of weight minimum
S, k ', the weight of the road i above it is reverted to w
i, calculate L
S, k ', path P just
S, k ', on each roadway element right of way w
iSummation;
(4) check the path constraint condition:
If time restriction L is satisfied in the gained path
S, k '＜β L
S, 0,, then forward (5) to, otherwise get back to (2); β allows coefficient, and 1.0-1.5 is got in suggestion;
(5) path search algorithm that has improved heuristic function in the A* algorithm finishes;
3, when transport information such as accident, obstruction, construction account for road etc. and occur on the path planning, carry out the A* path search algorithm that has limited Real-time Traffic Information: otherwise finish;
Exist the A* path search algorithm of limited Real-time Traffic Information as follows:
[1] initialization:
Make iterations k=0, being presented at when dynamic information has unusual obstruction on the route of cooking up, and when needing again programme path, the estimation running time that makes roadway element i is the weight w of roadway element
i
[2] roadway element weight changes
For the lower roadway element of fiduciary level, r is got in suggestion
i＜0.5, and the relevant roadway element with it of accident roadway element, with their weight increase weight increment Delta w,
For roadway element i, increase the back weight
w
i’＝w
i+Δw
i＝w
i+α
k(1-r
i)
qw
0 (4)
α is for weighing to such an extent that increase coefficient 0＜α＜1.r
iBe the fiduciary level of roadway element i, W is got in suggestion
0=1.5L
S, 0~ 3L
S, 0When iterations k=0, q=0; K＞=1 o'clock, q=1;
For accident roadway element i, make the fiduciary level r of roadway element i
i=0, so w
i'=w
i+ α
kW
0, 0＜α＜1; Search for failure correlation data between the roadway element that is stored on the vehicle optical disk this moment, finds and the relevant roadway element of unit i that blocks the road;
If roadway element j when also taking place to block, is called positive correlation because roadway element i takes place by unusual the obstruction thereupon, make the fiduciary level r of roadway element j
i=0, so w
i'=w
i+ α
kW
0, 0＜α＜1;
If roadway element j when running status is improved on the contrary, is called negative correlation because roadway element i takes place by unusual the obstruction, make the fiduciary level r of roadway element j
j=1, so w
j'=w
j
When if the running status of roadway element j is not subjected to roadway element i that unusual influencing of blocking taken place, be called uncorrelatedly, its weight is constant;
[3] new round iterations k '=k+1 recomputates weight minimal path P with the weight after changing with existing A* algorithm
S, k ', the estimated value w of accident roadway element running time before the roadway element that reduces then arrives
i, and calculate L
S, k '
[4] route inspection
If P
S, k 'Satisfy restrictive condition, just L
S, k '＜β L
S, 0, turn to [5], otherwise, return [2];
[5] algorithm finishes.
2, the onboard navigation system quasi dynamic route optimization method of delay risk averse according to claim 1 is characterized in that, the step b in the step 1 determines the unblocked reliability of roadway element:
When the traffic flow data that do not have more than 3 months, recommend to adopt the unblocked reliability of following functional form approximate estimation roadway element:
r
i=￠ (v
i/ c
i)
3+ β (v
i/ c
i)
2+ γ (v
i/ c
iIn)+c (5) formula, r
i---the unblocked reliability of roadway element i; v
i/ c
i---be defined as the saturation degree of roadway element i, wherein v
iBe flow, can obtain c by traffic flow data in a short time by roadway element i
iBe the traffic capacity of unit i, different with grade and different according to road type, be a definite value, can check in by pertinent literature; ￠, beta, gamma---return undetermined coefficient; C---constant term obtains by returning.
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