CN103838846B - Emergency guiding method and emergency guiding system for individual on basis of big data - Google Patents

Abstract

The invention relates to an emergency guiding method and an emergency guiding system for an individual on the basis of big data. When an emergency event occurs, a user transmits GPS (global positioning system) information of a location and an emergency rescue request by using a client side. A server side searches arterial streets with high carrying capacity in a certain range surrounding a scene and provides information of places corresponding to emergency rescue service, the required time of the user heading for an arterial street, the time of the user waiting for a vehicle on the arterial street and the time of the user going to an emergency service point from the arterial street are comprehensively considered, and the global optimum path for the user who departs from the scene, passes through a certain arterial street and heads for an objective emergency service providing point is selected. Real-time tracking guiding on the client side is performed according to the optimum path returned from the server side. A big data statistic analysis processing technology is used, the advancing condition of the user can be tracked in real time and can be dynamically regulated, global optimization is carried out under the condition that the time and the cost for the whole process are comprehensively considered, and the emergency guiding method and the emergency guiding system provide maximum assistance for the individual in an emergency condition.

Description

A kind of based on big data towards personal emergent bootstrap technique and system

Technical field

The present invention relates to floating vehicle data analysis, location dependant services, optimum path search, the field such as mobile computing, it is related to A kind of save oneself bootstrap technique and system towards under personal case of emergency.When emergency event occurs, can be selected according to user Emergency management and rescue scene, based on magnanimity floating vehicle data build road carrying capacity model select optimum to answer first aid for user Help arterial highway, the user's real-time position information arriving in conjunction with mobile device tracking, user's travel path is done with optimum guide, using succinct Text prompt and voice auxiliary help user to reach appointed place as early as possible, obtain rescue service.

Background technology

With the development of modern economy society, emergent safety is increasingly subject to people's attention.This kind of event has burst Property and urgency, and often endanger huge.Emergent security fields, are all subject to national and correlational study persons for a long time Pay high attention to, many achievements in research in this field also output.Existing emergent security study, main study population , above occurred events of public safety.As faced escape during the occurred events of public safeties such as fire, earthquake, the research evacuated, it is related to build All many-sides such as design, urban planning, scheduling of resource, the behavioral pattern of people, Psychological Model.

In fact, in the middle of daily life, individual also can run into some emergency events, sometimes may require that some answer first aid Help service.Such as individual feels uncomfortable, needs to go to hospital to be given treatment to as early as possible；On the way run into someone for another example to be subject to Wound, needs to obtain as early as possible medical services.Still it is not directed to emergent class, security classes service or the research of individual at present.But If it is possible to effectively be guided to individual under case of emergency, them are helped to obtain the emergency management and rescue service of needs as early as possible, right Personally for be also very valuable.

With the citing of individual demand emergency medical services, may be required to this when get effective traffic handss as early as possible Section, goes to hospital.But user is in current location, may nearby there are some arterial streets, but should where beat actually Car, user is actually unclear.People are always experimental, fuzzy for the perception of road conditions, especially traffic shape Condition or dynamic change, thus under emergency conditions, people is difficult to make the decision-making of science.Personal emergency designed by the present invention Guide service is it is simply that be devoted to meeting personal this needs.

Content of the invention

For the demand of the emergency self-saving of public safety class, the present invention propose a kind of towards personal emergency self-saving guiding The implementation method of service, can carry out user's emergency self-saving guiding of real-time perception, support mobile whole towards city road network system The rapid requests response service at end.

For achieving the above object, the technical solution used in the present invention is as follows:

A kind of based on big data towards personal emergent bootstrap technique, its step includes:

1) user sends emergency management and rescue request when meeting with emergency event by user end to server, and passes through client Gps positioning service the gps coordinate of user location (being designated as p) is sent to server；

2) server is with user's on-site gps coordinate points as the center of circle, in search certain radius r qualified arterial highway and In radius r, qualified emergency service provides point, wherein: radius r and r(r > r) allow in the interval of a setting dynamically Float, to guarantee to search arterial highway and emergency service offer point as much as possible；Arterial highway refers to have higher attribute ratings and relatively The urban road of strong carrying capacity；Emergency service provides point to refer to public service facility (predominantly hospital, public security bureau, oiling Stand)；

3) for each arterial highway mroad=<e, v searching>, search walks to the shortest path of mroad from incident point p Footpath, wherein: e is section (edge) set constituting major trunk roads；V is the Extreme points set in the section constituting major trunk roads；P to mroad Shortest path refer to the shortest paths of connection section Road journey of all end points in p to Extreme points set v；For each Emergency service provides point, and the walking point of arrival from every mroad for the search is called a taxi and gone to the shortest path of emergency service offer point；

4) calculating each emergency service provides point for the arrival cost cost of p_p(spot), then choose and reach this Little emergency service provides point to recommend user, returns the optimal path reaching this emergency service offer point to client；Described Reach cost and comprise t₁、t₂、t₃, wherein: t₁It is that user proceeds on foot the time required for arterial highway along the shortest path planned；t₂It is User waits the time used by car on arterial highway；t₃It is that user drives to emergency service point institute along the shortest path planned from arterial highway The time needing；

5) the evacuation path that client the reception server returns, passes through, according to this evacuation path, the side that word and language guide Formula persistently guides user to reach emergency service and provides point.

A kind of employing said method based on big data towards personal emergent guiding system, comprising:

Client is for sending emergency management and rescue request to server and by gps positioning service, user is on-site Gps coordinate sends to server, and the evacuation path that the reception server returns carries out guiding in real time；

Server, sets up communication connection with client, for responding emergency management and rescue request, calculates optimal evacuation path simultaneously Send to client, comprising:

Arterial highway and emergency service provide point search module, for user's on-site gps coordinate points as the center of circle, searching for one Determining qualified emergency service in qualified arterial highway and radius r in radius r provides point, wherein: radius r and r allows to exist Dynamically float in the interval of one setting, to guarantee to search arterial highway and emergency service offer point as much as possible；Arterial highway refers to Have higher attribute ratings and the urban road of stronger carrying capacity；Emergency service provides point to refer to public service facility；

Shortest Path Searching module, connects arterial highway and emergency service provides point search module, for every for search Article one, arterial highway mroad=<e, v>, search walks to the shortest path of mroad from incident point p, wherein: e is the road constituting major trunk roads Section (edge) set；V is the Extreme points set in the section constituting major trunk roads；The shortest path of p to mroad refers to p to end point set Close the connection section Road journey of all end points in v paths the shortest；There is provided point for each emergency service, search is from every The walking point of arrival on mroad is called a taxi and is gone to the shortest path of emergency service offer point；

Reach cost calculation module, connect Shortest Path Searching module, provide point for p for calculating each emergency service Arrival cost cost_p(spot), then choose and reach the emergency service of cost minimization and provide point to recommend user, return and reach This emergency service provides the optimal path of point to client；Described arrival cost comprises t₁、t₂、t₃, wherein: t₁It is user along rule The shortest path drawn proceeds on foot the time required for arterial highway；t₂It is the time that user waits used by car on arterial highway；t₃It is user edge The shortest path of planning drives to the time required for emergency service point from arterial highway；

Optimal path returns module, is connected to and reaches this computing module, for according to reaching cost calculation result, choosing The emergency service reaching cost minimization provides point to recommend user, and returns the optimal path reaching this emergency service offer point to visitor Family end.

4 parts are divided to be specifically described the main contents of the present invention below:

1. the history operation record based on passenger carrying vehicle, sets up the statistical model of road carrying capacity to traffic route network ccm-rns

Traffic route network data is exactly an electronic chart, can carry out data conversion treatment by gis map and obtain, The nodal information connecting between every road information and road that it comprises in transportation network.The information of road includes the mark in section Knowledge, the species in section, the width in section, the length in section, the grade in section, the mark of start node, the mark of end node, The information of node includes the mark of node, longitude, latitude value.

We are by the history operation record of floating vehicle first, obtain whole road network scope flow of passengers record former Begin record.Original recorded data includes vehicles identifications, trigger event, operation state, the record time, longitude, latitude value, instantaneous The data item such as speed, travel direction.

Vehicle flowrate on road carrying capacity and this section has a very strong incidence relation, particularly with the becoming of no load discharge Gesture has direct relation.With reference to civic trip and work and rest rule, the present invention was processed to raw data set based on week, And investigated two dimension one kind and be divided into working day and two kinds of day off, another kind is divided into seven types of Monday to Sunday.

Provide some descriptive definitions first.One time of definition is t, the time of one day is divided into n decile, as base The n unit t in sequential statistical data_i, then t={ t₁,t₂,t₃,…,t_n}.Defining whole section is e, and whole road network can be by m The section edge of individual orientation_jConnect composition, then e={ edge₁,edge₂,edge₃,…,edge_m}；Definition node is v, each Section edge_jThere are two end points (node), use v_s(edge_j) and v_e(edge_j) represent section edge_jIn-degree and out-degree end Point, each end points is exactly a geographical coordinate v_i, geographical coordinate comprises longitude and two attributes of latitude, and we use lng respectively To represent with lat, then v_i=(lng_j,lat_k)；Define a section edge_jInside comprise u segmentation record seg_kIt is in series, So edge_j={seg₁,seg₂,seg₃,…,seg_u}.For different date types d_x, different time point t_i, different sections edge_jAnd section edge_jOn segmentation seg_kGenerate an experience carrier flow rate record, be designated as eflow (d_x,edge_j,t_i, seg_k).

On here basis, for specific section edge_jAnd the segmentation seg in section_kSky with certain time scope Current-carrying capacity record, establishes delivery flux calculation expression, is designated asShow that certain is specific Delivery flux magnitude in the concrete time range in place.

Aforesaid operations definition on the basis of, below we specifically give carrying capacity statistical computation step.

(1) by vehicle merger record and filter invalid record

Original gps record is not according to vehicles identifications separate records, and it is not quite identical to record time sequencing, needs Rearrange.Additionally need and filter some invalid gps records, as incorrect in gps recording status, record time-out or record spacing The situation such as excessive.

(2) vehicle travel record and road network, sets up vehicle travel track

Vehicle travel record is made up of one group of gps record, searches candidate roads by the longitude and latitude that gps records, uses Mapmatching algorithm and a-star algorithm calculate the vehicle travel track ry=recording best match with this group gps {edge₀,edge₁,edge₂,…,edge_z}.Have close because gps record has to dredge, same road can have multiple gps record Corresponding, and certain middle of the road line this gps record may not had to correspond to.Not only used in the concrete process calculating Mapmatching algorithm carries out path adaptation, or the polishing carrying out travel path with a-star algorithm.If there is cannot The one group of gps recorded segment joined, then be considered as the invalid gps record needing to filter.

(3) vehicle travel track burst screening, distinguishes the path segment of different operation states

There are different operation states in each car during operation, mainly include carrying, zero load, parking and stoppage in transit four The state of kind.The burst screening of vehicle travel track is exactly according to different operation state cutting labellings, is easy to subsequent statistical analysis.

(4) daily statistical vehicle flowrate

Stroke recording for the different vehicle to every day for each road merges, and calculates in each road one day Vehicle flowrate in Each point in time fragment.Vehicle flowrate mainly includes no load discharge value and driving (includes carrying and unloaded two The state of kind) flow value.

Added up according to the automobile's instant velocity in gps record average, calculate in Each point in time fragment in each road one day Average instantaneous velocity.The present invention goes out each road one always according to the path length joint account of each vehicle travel track burst Average speed in Each point in time fragment in it.

(5) by being nonworkdays statistical vehicle flowrate

On the basis of daily statistical vehicle flowrate, statistics merges further, and differentiation is two kinds of date types of nonworkdays, closes And calculate the statistical value that previous step draws, the basis calculating as road carrying capacity.

(6) press seven days Monday to Sundays statistical vehicle flowrate difference

It is the situation of nonworkdays vehicle flowrate that the present invention has not only investigated, and has also investigated one week seven days each vehicle flowrate Statistical value, and compare with previous step statistical result, draw Monday to Sunday and be between nonworkdays statistical result value Difference.Further refinement regulatory factor as different date types.

(7) set up file index for statistical data

In order to calculated off line result can be reused, need for statistic analysis result to store into data file.It is simultaneously The quick searching data and assessment of final carrying capacity value calculates it is achieved that a kind of file index of convenient and efficient.

The data volume very little of each statistic unit, if separate storage will generate scrappy file in a large number, affects file system The performance of system.The present invention allows data file to merge storage, simultaneously can be with fragmented storage, specific fragmented storage data volume size Can adjust.On the basis of fragmented storage data file, set up a file index data file, record each road markings With some start offset in certain specific segmented data files of the statistical result information Store under different date types Some side-play amount of value terminates.The corresponding statistical data of each indexing units, includes a concrete road and concrete day The statistic record of all time point slice unit under phase type one day.

(8) preparation carrying capacity computational methods are realized

In the case of obtaining target road section and a specific date-time, read related statistical data, using line Property smooth manner, sets up carrying carrying capacity smoothed curve using the sequential on the same day as coordinate axess, vertical coordinate is related to flow Passenger carrying capacity statistical value, the calculating of carrying capacity in a period of time is equivalent to the integrating meter to carrying capacity smoothed curve Calculate.

2. it is applied to the candidate arterial highway of emergency self-saving and emergency service provides point fast determination method gb-ess

The realization of the method mainly comprises 2 steps: 1) chooses by rasterizing index eo-grid and specifies around incident point All section edge that radius covers and emergency service provide point；2) use the edge from candidate for the pebmr-recovery algorithm Identify in set and recover arterial highway.Below the realization mechanism of each step is illustrated.

2.1 are selected based on the evacuation section Candidate Set of eo-grid

In the present invention we to road network construct rasterizing index.The definition of rasterizing index is given below.

Define 1 (for the rasterizing index eo-grid of section edge and emergent point): for section edge and emergency service The rasterizing index providing point can be defined as eo-grid=<lt, rb, set<cell>, hn, vn>, wherein lt, rb are index Road network scope, lt is the gps coordinate in the road network rectangle upper left corner, and rb is the gps coordinate in the road network rectangle lower right corner, set<cell>be Cell set after index, hn is the cell number that horizontal (East and West direction) divides, and vn is the cell number that longitudinally (north-south) divides Mesh.Index is shown to division such as Fig. 1 (a) of road network.

Define 2 (index grid cell): an eo-grid is cut into hn × vn cell, and a cell can define For cell=<lt, rb, id, set<edge>>, wherein lt, rb are respectively the upper left corner and the lower right corner gps coordinate of cell, and id is The numbering of cell, set<edge>it is the edge set falling under this cell.Shown in the expression of cell such as Fig. 1 (b).

A given gps point, rasterizing indexes specifies the edge in radius to wait for its quick return with it for the center of circle Selected works and emergency service provide point Candidate Set.To introduce how to determine the cells falling in specified range, Ran Houzai below Determine that edge candidate collection and emergency service provide point candidate collection.

Define 3 (emergency service provides point spot): an emergency service provides point can be defined as spot=< id, type, Gps, edge >, wherein id is the numbering of spot, and type provides the type of point (as hospital, police office, gas station for emergency service Deng), the gps coordinate that gps is located for spot, the section that edge is located for spot.

Fall into the determination process of the cells of hunting zone:

1. give incident point gps coordinate p (lat, lng), wherein lat is latitude, lng is longitude.Based on eo-grid rope Draw, in the case of using hash storage index, the cell at coordinate points place can be positioned in o (1) time complexity, be designated as x.

2. give the search radius r of arterial highway and emergency service provides the search radius r(r of point r), determine around x by radius All cell that r and r is inswept.We calculate beeline d of each cell to p using formula (1)_min(p, cell):

Wherein dis (gps1, gps2) is used for calculating the Euclidean distance between two gps points.We are by those d_min< r and d_min< cell of r is respectively as the candidate cell set determining arterial highway and emergency service offer point, and is registered on these cell Edge be used for candidate road section, emergency service provide point be candidate's emergency service provide point.The selection of cell and time Edge, emergency service is selected to provide the determination of point as shown in Figure 2.Centered on spot, in the range of radius r, we have found 4 { edge4, edge8, edge9 } on { edge3 } and major trunk roads 1 in bar candidate road section, respectively major trunk roads 2.With incident point Centered on, in the range of radius r, we have found 2 emergent destinatioies and (assume our application scenarios with hospital for emergent purpose Ground), it is spot1 and spot2 respectively.

2.2 major trunk roads based on candidate road section set identify restoration methods pebmr-recovery

Candidate road section (edge) the set not major trunk roads that previous step obtains.Major urban arterial highway is by some certain ranks Section connects and composes.During practical guide, the present invention will guide user to reach any one on certain major urban arterial highway Nearest position for current incident point.Propose major trunk roads identification restoration methods (partly-edge- for this Based main road recovery, abbreviation pebmr-recovery), the major trunk roads of candidate are known from candidate road section set Not out.

Define 4 (opening up based on the edge of section edge): a given section edge, be designated as ex, from this section, in head and the tail Search in both direction and meet the connected edge of constraints and extend successively, until can not find the connected edge of meet the constraint condition Till, extension terminates.The purpose extending in section is i.e. in order to recover the major trunk roads that initial edge ex is located.

Define 5 (major trunk roads mroad): major trunk roads can be defined as mroad=<e, v>, wherein e is to constitute major trunk roads Edge set, v is node vertice set (in actual road network be generally crossing) connecting section.Edge's and vertice Put in order and follow the direct of travel of major trunk roads.

Define 6 (section edge screening conditions): the rank in section determines the rank of the road of its expression, and we pay close attention to The stronger major urban arterial highway of emergency capability.According to the detailed section attribute being given in road net data, we can filter out satisfaction The candidate road section of level conditions.

Define 7 (section edge bias angle theta): in alignment based on the approximate connection of the adjacent segments edge on same major trunk roads It is assumed that edge bias angle theta define adjacent edge equidirectional on deflection angle.If θ < 5 ° then it is assumed that two neighboring edge is Edge on same major trunk roads, can continue down along opening up.

The discovery of candidate's major trunk roads and recovery process:

1. give section candidate collection, filter out eligibleSection;

2. give a section, register a major trunk roads mroad, be designated as mr.From the beginning of this section, to head and the tail both direction Expand, till can not find the new section meeting θ.Traversed section is registered to mr.

3. pair each candidate road section repeats 1.-2. operation, the section not repetitive operation on same major trunk roads, finally gives Candidate's major trunk roads set.

As shown in figure 3, using pebmr-recovery algorithm, we gather { edge from candidate edge₃,edge₄,edge₈, edge₉In have identified { arterial highway 1, arterial highway 2 }.Arterial highway 1 can be expressed as < e={ edge₂,edge₄,edge₈,edge₉},v= {v₁,v₃,v₆,v₇,v₈>, arterial highway 2 can be expressed as<e={ edge₁,edge₃,edge₄},v={v₂,v₃,v₄,v₅}>.

3. optimal emergency service provides the system of selection of point

For optimal emergency service provide point quick selection it is proposed that based on shortest path and arterial highway carrying capacity should Anxious service provision point reaches cost model (reaching cost model, abbreviation rcm).Arrival cost consideration 3 aspect factor: 1) the time t proceeding on foot required for arterial highway from incident point₁；2) the time t of car is waited on arterial highway₂；3) call a taxi to go to from arterial highway and answer Time t required for anxious service provision point₃.For this reason, be directed to 1) based on dijkstra by incident point to candidate arterial highway (by point and Line) undirected shortest path pathfinding algorithm (vertex-to-edge-oriented shortest path searching, letter Claim v2e-sps algorithm)；For 2) calculate user position on major trunk roads using road carrying capacity statistical model ccm-rns The longest Waiting time at place；3) search out arterial highway using dijkstra algorithm provides the shortest path of point to emergency service.Below Two parts are divided to be illustrated: to introduce the shortest pathfinding algorithm v2e-sps first, then provide the arrival providing point for emergency service Cost model, illustrates model is how to calculate emergency service using shortest path and major trunk roads carrying capacity to provide the arrival of point Cost.

3.1 (by point and line) undirected shortest path method for searching v2e-sps based on dijkstra

The method utilizes road net data, searches out the shortest path that spot reaches an arterial highway.Every arterial highway mroad It is made up of a section set mroad.e and an Extreme points set mroad.v.We define " arrival major trunk roads " is from incident point Set out, look for a communication path to reach any one end points in mroad.v.Spot is by subscription client gps equipment The gps coordinate submitted to, does not correspond to the end points in road net data.In order to carry out Shortest Path Searching based on road network, we are by thing The gps coordinate sending out point is mapped to respective stretch on road network (as shown in Fig. 2 incident point coordinates is mapped to section edge₁₁On).

Given major trunk roads mroad and incident point gps coordinate p, can from the shortest pathfinding process of incident o'clock to major trunk roads It is expressed as follows:

1. using road network technology, p is mapped on road network corresponding section e；

2., for the first node vs and se on the e of section, calculate respectively at 2 points to major trunk roads using dijkstra algorithm The shortest path of all nodes, obtains two set of minimal paths, is designated as { traj_s1,traj_s2,…,traj_sn},{traj_e1, traj_e2,…,traj_en, wherein n is the number of endpoint on arterial highway；

3. the path selecting shortest path in two set, is designated as to the optimal path of arterial highway mroad as from incident point p traj_mr.

Because service is towards the individual being under emergency management and rescue state, it reaches the mode of arterial highway and is generally walking, because This is without the concern for the direction in section.What v2e-sps executed is the Shortest Path Searching process on a non-directed graph.In order to improve The corresponding efficiency of background service, we are simplified to pathfinding process using the characteristic of dijkstra algorithm.Dijkstra is seeking Can determine during road all through node shortest path, using this point, when we find incident point p to arterial highway on certain Individual node v_mShortest path when, if just past another node v on major trunk roads during pathfinding_k, then pathfinding algorithm It is immediately finished.Because reaching node v_kMeet the definition of " arrival major trunk roads ".

As schemed shown in 3, using v2e-sps algorithm, we can find and evacuate to major trunk roads 1 and major trunk roads from incident point 2 shortest path is traj respectively_1min={edge₁₁,edge₁₂,edge₇And traj_2min={edge₁₁,edge₁₂,edge₁₆, edge₅}.

3.2 are applied to the emergent point arrival cost model rcm that individual saves oneself

One emergency service provides the arrival cost of point to be proceeded on foot arterial highway call a taxi from arterial highway from incident point with user Reaching emergency service provides characterizing total time of point consumption, is designated as t (spot).T (spot) comprises 3 part-times: 1) guiding is used Family walks through the time that shortest path reaches arterial highway, is designated as t₁；2) user gets to the waiting time required for car on arterial highway, It is designated as t₂；3) user goes to the time t required for emergent point by bus₃.

After the shortest path obtaining user's walking arrival arterial highway, the length in path can be obtained, be designated as l₁.According to warp Test it will be assumed that the average walking speed of people is s, then user walks through shortest path and reaches the duration that consumed of arterial highway:

$t_1=\frac{l_1}{s}---\left(2\right)$

Reach arterial highway after when empty wagons high latency with two factors about: a) user be located seg on fortune Loading capability, is designated as c (δ t)；B) the emergent number of request on the seg that user is located (waits empty with active user in same place The number of car), it is designated as n.C (δ t) represents as that time point t of user's arrival major trunk roads_qStart in the δ t time backward, Carrying capacity (being characterized with unloaded vehicle flowrate of hiring out) on the seg that user is located, according to ccm-rns model, c (δ t) can table It is shown as:

$c\left(\mathrm{\&delta;t}\right)={\&integral;}_{t_q}^{t_q+\mathrm{\&delta;t}}\mathrm{eflow}(d_x,{\mathrm{edge}}_j,t,{\mathrm{seg}}_k)={\mathrm{ef}}_{(d_x,{\mathrm{edge}}_j,{\mathrm{seg}}_k)}(t_q,t_{q+\mathrm{\&delta;t}})---\left(3\right)$

Emergent demand on known current seg is n, adds that the demand count value of active user is exactly n+1, on same road Section provides bearer service for n+1 user, then need more delivery time and carrying capacity,.With reference to the rule first rescued first Then carry out rescue to guide, active user needs to wait in line the (n+1)th train number it is contemplated that rescue of succeeding.Assume that active user needs Time to be waited is t₂, then t₂Meet:

c(t₂)=n+1+ζ(4)

Wherein ζ is relaxation factor, and this value is write from memory and is recognized as 0.In actual use, the value dynamic and configurable of this variable, can According to empirical scalar value α of history invalidation request record, calculate relaxation factor ζ=- α (n+1).

Obtain waiting time t on major trunk roads for the user using equation (4)₂.

Using dijkstra algorithm, we search out location point on arterial highway for the user and provide the shortest of point to emergency service Path, the running time on this paths depends on travel speed on each section for the Floating Car it is assumed that shortest path isThe length in each section is followed successively byAccording to magnanimity Floating Car historical data The average overall travel speed obtaining on each section isThen:

$t_3=\underset{i=1}{\overset{n}{\mathrm{\&sigma;}}}\frac{l_{\mathrm{ki}}}{s_{\mathrm{ki}}},$

Comprehensive t₁、t₂And t₃, emergency service provides point to be expressed as the arrival cost of incident point p:

cost_p(spot)=t(spot)=t₁+t₂+t₃(5)

(5) formula is emergency service and provides the arrival cost model (reaching cost model, abbreviation rcm) of point.

After the arterial highway taking candidate is gathered and emergency service provides point set, the present invention uses rcm to assess user's transfer Each bar major trunk roads reach the cost of each emergent point, choose the emergency service offer point reaching cost minimization and corresponding guiding road Footpath returns to user.

Determination with regard to n value.We are that each seg on every arterial highway arranges an enumerator, when client submits thing to Send out point coordinates to service end, service end calculates certain seg of arterial highway corresponding to the optimum path of navigation of determination and starts to guide When, active user is registered to the specified seg of this arterial highway, enumerator i.e.+1.When user reaches arterial highway, cancel the note of this user Volume, enumerator -1.

4. client returns optimum path of navigation according to service end and carries out user and saves oneself guides, and persistently tracking user gps Whether position is consistent with setting path, submits to and update guide task when occurring inconsistent

Need, in the mobile object saving oneself guide, gps location equipment and wireless telecommunications system are installed at each first, and join Standby emergency self-saving guides client-side program, can be described as " help me " emergent bootstrap.Client-side program is built-in to be led to server Cross traffic route road net data, FTP client FTP can calculate side between each road section length and each section exactly Tropism.

The identification of estimated direction determining is mainly drawn by Vector rotation angle calculation.It is primarily based on two adjacent sections Nearest section in segmentation seg, obtain two vectors be designated asWithVector direction is consistent with direction of keeping to the right, calculate to Amount is amassed and cosine angle.When vector product is for positive number, being rotated clockwise angle is θ, that is, turn right.When vector product is negative When, counterclockwise rotates angle is to turn left.When the vector product calculating be 0 and cosine angle be 0 degree when it may be possible to Straight forward is also likely to be reverse driving, and therefore special case also needs to check that whether consistent vector symbol is.

After mobile object initiates emergency self-saving service request, service end will return optimum guiding route to user, can With with ry={ edge₀,edge₁,edge₂,…,edge_zRepresenting, FTP client FTP will return a series of quick finger successively Draw, such as " 100 meters to the left ", " turning on the right side ", " waiting at 200 meters of front ".FTP client FTP needs persistently to follow the tracks of user Gps position, in good time renewal is guided message and is carried out voice broadcast, also needs to verify that moving direction and route are set with expected Whether route is consistent, if it find that inconsistent situation, then needs to initiate to update to server to guide task requests, obtains clothes again Business end responds and updates local key instruction.

Provide some descriptive definitions first.User's gps change in location is persistently followed the tracks of it is considered to two adjacent according to client Certain near two position coordinates, are designated as ν_ukAnd ν_uk+1, noteConceptual vector for track of passing through.According to two point coordinates positions Intermediate pointSearch the segmentation seg in the most close section_k, seg_kTwo ends coordinate be respectively ν_kAnd ν_k+1, noteFor guiding Vector.

The concrete method judging that user travel route deviates desired trajectory:

1) calculateWith seg_kBetween vertical dimension be d_uk, d_ukMeet and be less than maximum allowable offset d_max, beyond just for deviateing Predetermined guide route.

2) calculateWith guide route neighbouring main node v_iDistance whether be less than d'_min, if less than being considered as not Deviate the estimation of desired trajectory, if greater than carrying out next step calculating.

3) calculate anglec of rotation θ with respect to boot vector for the conceptual vector of track of passing through, if | θ | is more than given threshold Value λ, then judge that user deviate from predetermined track.The computational methods of θ value are with reference to as follows

$\mathrm{\&theta;}=\mathrm{sgn}(\stackrel{\&rightarrow;}{v_{\mathrm{uk}}{v}_{\mathrm{uk}+1}}\&times;\stackrel{\&rightarrow;}{v_k{v}_{k+1}})\arccos (\stackrel{\&rightarrow;}{v_{\mathrm{uk}}{v}_{\mathrm{uk}+1}}\&centerdot;\stackrel{\&rightarrow;}{v_k{v}_{k+1}})/\left(\right|\stackrel{\&rightarrow;}{v_{\mathrm{uk}}{v}_{\mathrm{uk}+1}}\left|\right|\stackrel{\&rightarrow;}{v_k{v}_{k+1}}\left|\right),$ θ represents that for positive number being rotated clockwise angle is | θ |, and θ is | θ | for negative number representation counterclockwise rotates angle.When θ is 0 Special case, haveDuring for negative, actual θ is to be rotated clockwise 180 degree.

What the present invention designed is the floating vehicle data structure road carrying capacity model based on magnanimity, can be in conjunction with user The environmental factorss of current position, the time of submission request and surrounding, are given to user and accurately recommend and foolproof Guiding, greatly alleviates user's decision-making burden in case of emergency, reduces user simultaneously and obtain rescue transportation service Uncertain.

The service that the present invention provides is different from commending system of calling a taxi, and commending system of calling a taxi only focuses on the recommendation in place of calling a taxi, And it is not concerned with how user goes to these places of calling a taxi.They are according to the current position of user, are that user recommends nearby to beat To car probability highest or Waiting time place the shortest.Designed system of the present invention, not only in conjunction with the probability getting to car and Waiting time screens to the emergency management and rescue arterial highway of candidate and recommends, and arrival is called a taxi from current location even more to have considered user The travel time of position, user reaches, after waiting time of position of calling a taxi and user get to car, the emergent clothes specifying classification Business provides the running time of point, and the process obtaining emergency service to whole user does full-range preferred plan.Simultaneously in user Go in the traveling process of emergency management and rescue arterial highway, real-time tracking is carried out according to the customer location that user's mobile device uploads, if Find that user deviates preset path, can automatically recalculate and screen emergency management and rescue arterial highway, and calculate optimal path, until user Reach optimum emergency management and rescue arterial highway.In addition, after the emergency service that the system provides is used by scale, all subscription service User can also receive the emergency management and rescue request of other users nearby, thus helping further need the use of rescue from probability Family acquisition as early as possible is corresponding to be serviced or rescues.In this sense, taxi commending system of calling a taxi is to expire completely The personal rescue demand under emergency scene of foot.

As seen through the above analysis, the present invention has filled up emergent field and has only focused on occurred events of public safety, and to individual An inadequate blank of emergent due care, does real-time rescue guiding, helps them as soon as possible to the individual under urgent environment Obtain corresponding transportation service.Meanwhile, it is different from commending system of calling a taxi, the present invention understands real-time tracking user's traveling situation and does dynamically Adjustment, considers full-range time cost and does global optimization, reach overall optimal effectiveness, to the individual in the case of meeting an urgent need Maximized help is provided.

Brief description

Fig. 1 a is the schematic diagram that road network is carried out with rasterizing division, and Fig. 1 b is the schematic diagram of cell structure in grid index.

Fig. 2 is to determine candidate edge set and the candidate's emergency service offer point set specified around incident point in radius The schematic diagram closing.

Fig. 3 is to recover arterial highway set from candidate edge set, and determines incident point to the shortest path of every major trunk roads Footpath and transfer each bar arterial highway reach accordingly the schematic diagram that emergency service recently provides the route of point.

Fig. 4 is to determine that the emergency service reaching cost minimization provides the schematic diagram of point.

Fig. 5 is the emergent boot flow figure of the present invention.

Specific embodiment

Below by specific embodiments and the drawings, the present invention will be further described.

The present invention carries out user's emergency self-saving guiding of real-time perception towards city road network system, supports the fast of mobile terminal Speed request response service, the emergent boot flow being adopted is as shown in figure 5, be described as follows to its main contents:

(1) the history operation record based on floating vehicle, sets up the statistics mould of road carrying capacity to traffic route network Type (carrying capacity model of road network system, abbreviation ccm-rns).We pass through to float first The history operation record of motor-car, obtains the protocol of the flow of passengers of whole road network scope.Then in conjunction with traffic road net Network data is processed to operation record, and counts carrying operation ability further, and then traffic route network is set up The empirical model of road carrying capacity.

(2) arterial highway closed on is searched according to the time place of emergency self-saving request and emergency service provides point (at this In bright, emergency service provides point to refer to hospital, police office, gas station etc. and provides the facility of public emergent service, according to application The different destination of the different choice of scene).In order to quickly determine possible arterial highway and emergent destination around incident point, propose Section based on rasterizing index and emergency service provide a point rapid screening algorithm (grid-based evacuation Spots selection, abbreviation gb-ess algorithm).Rasterizing index effectively can provide to section and emergency service and click through Row divides and positions, and the quick road determining around incident point and emergency service provide point.After determining the position of incident point, The section that comprised of all grids that certain radius scope covers using centered on incident point as the section of pre-selection, and comprise should Anxious point provides point as the emergency service of candidate.Every major trunk roads are all formed by connecting by some section head and the tail, our bases for this In road net model and section attribute it is proposed that (partly-edge-based is recovered based on the major trunk roads identification of pre-selection section set Main road recovery, abbreviation pebmr-recovery) algorithm.

(3) calculating incident point to each candidate's emergency service provides the optimum path of navigation of point, and calculates corresponding arrival Cost.Choose and reach the emergency service of cost minimization and point is provided and reaches the optimal path of this destination and return to user.Arrive Reach this and include three part-times: user goes to the time t of arterial highway from incident point₁, the time t of user's grade car on arterial highway₂, use Family goes to emergency service to provide the time t of point by bus₃.The quick selection of point is provided for the emergency service reaching cost minimization, Propose the arrival cost model (reaching cost model, abbreviation rcm) based on shortest path and arterial highway carrying capacity. Emergency service provides the selection of point to need to consider the factor of 3 aspects: 1) distance from incident point to arterial highway is short as far as possible, that is, Arterial highway can be gone to as soon as possible；2) emergency capability of arterial highway is strong as far as possible, will easily get to car as far as possible；3) from dry The distance of road to emergent destination is short as far as possible.For 1) we devise based on dijkstra by incident point to candidate Undirected shortest path first (the vertex-to-edge-oriented shortest path of arterial highway (by point and line) Searching, abbreviation v2e-sps algorithm).For 2) we are measured to the carrying capacity of arterial highway using ccm-rns.For 3) we utilize dijkstra algorithm search to provide the shortest path of point from arterial highway to candidate's emergency service.

(4) client carries out user's guiding according to the optimum path of navigation of service end return, and persistently follows the tracks of user gps position Whether consistent with setting path, submit to when occurring inconsistent, update to evacuate and guide request.

How to further illustrate the present invention below by the citing of actual emergency self-saving scene under concrete emergency scene Interact and play a role, but limit the scope of the present invention never in any form.

As Fig. 2 shows, the position that user indicates in flame runs into emergency, needs emergent guide service.User takes out handss Hold mobile device, open helpme client-side program, select to meet an urgent need accordingly in main interface guide service, such as medical aid clothes Business.Helpme Automatic Program starts the gps equipment in handheld device, starts user is positioned, and by positioning result and user The emergency service type selecting is uploaded to helpme service end, subsidiary request guiding mark.Helpme service end receives on user After the gps position with request guiding mark passing, centered on customer location, the satisfaction that radius r searches near user is empty The section of not busy carrying capacity condition, provides point with radius r search candidate's emergency service simultaneously, through screening, finds eligible Section { edge₃,edge₄,edge₈,edge₉, and qualified service offer place { spot1, spot2 }.

After determining the section of candidate, these sections are reduced into complete major trunk roads by system.As shown in figure 3, candidate Section has been restored to { arterial highway 1, arterial highway 2 }.This two arterial highways are the possible place getting rescue transportation service of user. Arterial highway 1 can be expressed as < e={ edge₂,edge₄,edge₈,edge₉},v={v₁,v₃,v₆,v₇,v₈>, arterial highway 2 can be expressed as< e={edge₁,edge₃,edge₄},v={v₂,v₃,v₄,v₅}>.Next step is it needs to be determined that incident point reaches the shortest of two major trunk roads Path, reaches the important evidence of two major trunk roads time costs as assessment.As shown in figure 3, system finds to be engaged in through searching element Sending out o'clock the shortest path of two major trunk roads is traj respectively_1min={edge₁₁,edge₁₂,edge₇And traj_2min={edge₁₁, edge₁₂,edge₁₆,edge₅}.

There is shortest path, system just can obtain the short line that user goes to candidate's major trunk roads, then according to distance just The travel time that user reaches candidate arterial highway from current location can be calculated, be designated as t₁.Additionally, system is using based on magnanimity traffic The road carrying capacity model that data is set up calculates the carrying capacity of candidate's major trunk roads, according to carrying capacity, just can calculate User reaches the estimated waiting time specifying arterial highway later, namely how long user can get to car later, be designated as t this period₂. Next, system can reach optimum emergency service for the search of each candidate's major trunk roads again provides the shortest path of point, and according to sea The historical data of amount Floating Car calculates the running time that each candidate's major trunk roads arrives at its optimum emergency service offer point, is designated as t₃.Consider these three factors, the integrated cost that user obtains emergency management and rescue service is t=t₁+t₂+t₃, system arranges to t Sequence, selects optimum emergency service to provide point for user, and then by user from current location, reaching optimum emergency service provides point Path return to client.As shown in figure 4, final result of calculation shows that the overall cost of spot2 is minimum, therefore path traj_1min={edge₁₁,edge₁₂,edge₁₆,edge₅,edge₄Return to user as optimum path of navigation.Helpme services The information that end returns to client includes guiding the gps position of destination, the crossing of all approach in title, and path of navigation The gps position of key point.

Helpme client receive the guiding gps position of destination, title and the key point gps sequence of service end return with Afterwards, start local navigation module, according to the order of key point gps sequence, start to carry out guiding in real time to user.First, draw Helical pitch sequence first informs that user guides the title of destination.And then start the traveling behavior of user is done guiding in real time, guiding bag Containing word and voice two aspect, the behavior of next step is shown on screen, and is broadcasted with voice module.As " please forwards 300 Rice, and turn right at crossing ".In user's traveling process, when often away from a path key point, the guiding module just row to user Enter direction to make a decision.If user does not advance according to default path of navigation, helpme client is by gps position up-to-date for user Put and be uploaded to service end, equally subsidiary request guiding mark, the screening of triggering service end and calculating process again.If user one Directly advance according to default path of navigation, reach the guiding destination specifying the most at last.Now, helpme client uploads again The gps position of user, and incidentally guide end of identification.

After helpme service end receives the gps position with guiding end of identification of user's upload, ask issuing one Rescue message, the subscriber of all message can receive the emergency message comprising positional information, obtained with helping user to shorten further The time of transportation service must be rescued.

Above by example, the present invention is described in detail, it will be understood by those of skill in the art that not surpassing Go out in the range of spirit and substance of the present invention, the present invention is made with certain modification and variation, such as number is returned to server According to concrete presentation format modify, or to index organizational form and search procedure carry out local change, still can be real The existing purpose of the present invention.Protection scope of the present invention is to be defined described in claims.

Claims (10)

1. a kind of based on big data towards personal emergent bootstrap technique, its step includes:

1) user sends emergency management and rescue request when meeting with emergency event by user end to server, and by client Gps positioning service sends on-site for user gps coordinate to server, and this user on-site gps coordinate is designated as p；

2) server connects with user's on-site gps coordinate points as the center of circle, qualified arterial highway and half in search certain radius r In the r of footpath, qualified emergency service provides point, wherein: radius r and r allows dynamically to float in the interval of a setting, with Guarantee to search arterial highway as far as possible and emergency service provides point；Arterial highway refers to have higher attribute ratings and stronger evacuation capacity Urban road；Emergency service provides point to refer to public service facility；

3) for each arterial highway mroad=<e, v searching>, search walks to the shortest path of mroad from incident point p, Wherein: e is the section set constituting major trunk roads；V is the Extreme points set in the section constituting major trunk roads；The shortest path of p to mroad Refer to the connection section Road journey of all end points in p to Extreme points set v paths the shortest；Each emergency service is carried For point, the walking point of arrival from every mroad for the search is called a taxi and is gone to the shortest path of emergency service offer point；

4) calculating each emergency service provides point for the arrival cost of p, then chooses and reaches the emergency service of cost minimization and carry Recommend user for point, return the optimal path that this emergency service offer point is provided to client；Described arrival cost comprises t₁、 t₂、t₃, wherein: t₁It is that user proceeds on foot the time required for arterial highway along the shortest path planned；t₂It is that user is first-class in arterial highway Time used by car；t₃It is that user drives to the time required for emergency service point along the shortest path planned from arterial highway；

5) client receives the evacuation path of server return, and reaching emergency service according to this evacuation Route guiding user provides Point.

2. method according to claim 1 is it is characterised in that step 2) eligible in described search certain radius r and r Arterial highway and emergency service provide point method be:

First road net data is set up with the rasterizing index for section, every section is registered to all index grid that it passes through On lattice, after obtaining user's on-site gps coordinate, with it as the center of circle, respectively by all index grids inswept for radius r and r In section and emergency service provide point to constitute candidate road section set and candidate's emergency service to provide point set；

Then according to section screening conditionsFilter out the section of major trunk roads rank, and recovered belonging to it using these sections Major trunk roads；The restoration methods of wherein major trunk roads are to open up algorithm based on the edge of adjacent segments equidirectional deflection angle θ, according to following step Rapid identification recovery major trunk roads:

A) give section candidate collection, filter out eligibleSection；

B) give a section, register a major trunk roads mroad, be designated as mr, from the beginning of this section, open up to head and the tail both direction Exhibition, till can not find the new section meeting θ, traversed section is registered to mr；

C) to each candidate road section repeat step a) and operation b), the section not repetitive operation on same major trunk roads.

3. method according to claim 1 is it is characterised in that step 2) described public service facility includes: hospital, public security Office, gas station.

4. method according to claim 1 is it is characterised in that step 3) described from incident point p to major trunk roads mroad The searching method of short path is:

First incident point p is matched a certain bar section on road network, then from the head and the tail end points difference in section, use Dijkstra algorithm searches the shortest communication path of all nodes of Extreme points set v；Then find out respectively and reach in both direction The shortest path of arterial highway, afterwards on the basis of considering p point to head and the tail end-point distances, selects p point to the shortest path of arterial highway；

Two end points in hypothesis p place section are vs, ve, and shortestpath (v1, v2) represents that on road network, v1 point walks to v2 The shortest path of point, pathfrom (vs) represents that vs points out and is dealt into the shortest path reaching arterial highway, pathfrom (ve) represents ve point Set out and reach the shortest path of arterial highway, dis (v1, v2) represents v1, the distance between v2 point, bestpath represents that p point reaches master The shortest path of arterial highway, then:

Pathfrom (vs)=min { shortestpath (vs, v) | v ∈ mroad.v },

Pathfrom (ve)=min { shortestpath (ve, v) | v ∈ mroad.v },

$bestpath=pathfrom\left(\underset{v\&element;\{vs,ve\}}{\arg \min }\right(\left|pathfrom\left(v\right)\right|+dis\left(p,v\right)\left)\right),$

In order to lift the efficiency of pathfinding, it is all that each end is reached with shortest path in search procedure using dijkstra algorithm Point characteristic, simplify pathfinding process: search from vs or ve to the shortest path of any v ∈ mroad.v during, if pass through Any one v_m∈ mroad.v, then search procedure terminate.

5. method according to claim 1 is it is characterised in that step 4) measure each emergency service and provide point to reach a cost Method be:

4-1) using user from incident point proceed on foot arterial highway and from arterial highway call a taxi reach emergency service provide point consume total when Between t (spot) come to characterize emergency service provide point arrival cost；T (spot) includes three part-times: guiding user's walking is led to Spend the time that shortest path reaches arterial highway, be designated as t₁；User gets to the waiting time required for car on arterial highway, is designated as t₂；User Go to the time t required for emergent point by bus₃；Wherein: the length that known users walking reaches the shortest path of certain arterial highway is l₁It is assumed that the general walking speed of user is s, then:

$t_1=\frac{l_1}{s};$

4-2)t₂Carrying capacity c of segmentation seg being located by user's point of arrival and determination wait emergency management and rescue on same seg Number of request n determines；Calculate the carrying capacity on this seg in the δ t time after user reaches arterial highway, be designated as c (δ t), Know that the total number of request being currently needed for rescuing is n+1 it is assumed that rescuing successively according to the priority reaching, user needs the time t waiting₂ Meet:

c(t₂)=n+1+ ζ,

Wherein, ζ is relaxation factor；Try to achieve waiting time t on major trunk roads for the user using above formula₂；

4-3) search out location point on arterial highway for the user using dijkstra algorithm provides the shortest path of point to emergency service, Running time on this paths depends on travel speed on each section for the Floating Car it is assumed that shortest path isThe length in each section is followed successively byAccording to magnanimity Floating Car history number According to obtaining the average overall travel speed on each section it isThen:

$t_3=\underset{i=1}{\overset{n}{\&sigma;}}\frac{l_{ki}}{s_{ki}},$

Comprehensive t₁、t₂And t₃, emergency service provides point to be expressed as the arrival cost of incident point p:

cost_p(spot)=t (spot)=t₁+t₂+t₃.

6. according to the method described in claim 5 it is characterised in that the method calculating arterial highway carrying capacity is: from the traffic of magnanimity The historical traffic feature in each section is extracted, when particularly the time dependent trend of no load discharge is to characterize certain in data Between section arterial highway carrying capacity；First statistical analysiss are carried out to traffic flow data it is considered to " ＆ nonworkdays on working day " and " week One to Sunday " two ways is come to date type d_xCarry out merger statistics, be divided within one day n isometric timeslice { t₁,…, t_n, road network is by a series of section { edge₁,edge₂... constitute, every section is made up of a series of connected segmentation seg；Right In given section edge_j、seg_kWith date type d_x, read related statistical data, using the mode of linear smoothing, calculate Go out each timeslice t_iOn no load discharge, be designated as eflow (d_x,edge_j,t_i,seg_k), seg is obtained with this_kIn date type d_x The time dependent smoothed curve of lower carrying capacity, then the carrying capacity in a period of time be equivalent to carrying capacity smoothed curve Integrate within this time period；For specific section edge_jAnd the segmentation seg in section_kSky with certain time scope Current-carrying capacity record, sets up delivery flux calculation expression, is designated asShow certain specifically Delivery flux magnitude in the concrete time range of point；Assume that the time point that user reaches major trunk roads is t_q, then the fortune in the δ t time Loading capability:

$c\left(\mathrm{\&delta;}t\right)={\&integral;}_{t_q}^{t_q+\mathrm{\&delta;}t}efow(d_x,{\mathrm{edge}}_j,t,{\mathrm{seg}}_k)={\mathrm{ef}}_{(d_x,{\mathrm{edge}}_j,{\mathrm{seg}}_k)}(t_q,t_{q+\mathrm{\&delta;}t}).$

7. method according to claim 1 it is characterised in that: step 5) in client use mobile device gps service, The gps coordinate of the new position of user once user deviates predetermined evacuation route, is then submitted to by real-time tracking user's conduct route Server, plans optimal evacuation egress route again.

8. method according to claim 7 is it is characterised in that step 5) judge that user travel route deviates desired trajectory Method is: the user's gps change in location persistently followed the tracks of according to client, it is considered to two certain adjoining two position coordinateses, is remembered For ν_ukAnd ν_uk+1, noteFor the conceptual vector of track of passing through, according to the intermediate point of two point coordinates positionsSearch the most close The segmentation seg in section_k, seg_kTwo ends coordinate be respectively ν_kAnd ν_k+1, noteFor boot vector,

1) calculateWith seg_kBetween vertical dimension be d_uk, d_ukMeet and be less than maximum allowable offset d_max, beyond just predetermined for deviateing Guide route；

2) calculateWith guide route neighbouring main node v_iDistance whether be less than d'_min, if less than be considered as without departing from The estimation of desired trajectory, if greater than carrying out next step calculating；

3) calculate anglec of rotation θ with respect to boot vector for the conceptual vector of track of passing through, if | θ | is more than given threshold value λ, Then judge that user deviate from predetermined track；The computational methods of θ value are:

θ represents that for positive number being rotated clockwise angle is | θ |, and θ is | θ | for negative number representation counterclockwise rotates angle, works as θ Special case for 0, hasDuring for negative, actual θ is to be rotated clockwise 180 degree.

9. method according to claim 1 it is characterised in that: step 5) in client according to this evacuation path pass through word Persistently guide user to reach with the mode of voice instruction and evacuate destination.

10. a kind of employing claim 1 methods described based on big data towards personal emergent guiding system, its feature exists In, comprising:

On-site for user gps for sending emergency management and rescue request to server, and is sat by client by gps positioning service Mark sends to server, and the evacuation path that the reception server returns；

Server, sets up communication connection with client, for responding emergency management and rescue request, calculates optimal evacuation path and sends To client, comprising:

Arterial highway and emergency service provide point search module, for user's on-site gps coordinate points as the center of circle, search is certain partly In qualified arterial highway and radius r in the r of footpath, qualified emergency service provides point, wherein: radius r and r allows at one Dynamically float in the interval setting, to guarantee to search arterial highway and emergency service offer point as much as possible；Arterial highway refers to have Higher attribute ratings and the urban road of stronger carrying capacity；Emergency service provides point to refer to public service facility；

Shortest Path Searching module, connects arterial highway and emergency service provides point search module, for for each searching Arterial highway mroad=<e, v>, search walks to the shortest path of mroad from incident point p, wherein: e is the section constituting major trunk roads (edge) gather；V is the Extreme points set in the section constituting major trunk roads；The shortest path of p to mroad refers to p to Extreme points set v In all end points the shortest paths of connection section Road journey；There is provided point for each emergency service, search is from every The walking point of arrival on mroad is called a taxi and is gone to the shortest path of emergency service offer point；

Reach cost calculation module, connect Shortest Path Searching module, provide point to arrive for p for calculating each emergency service Reach this, then choose and reach the emergency service of cost minimization and provide point to recommend user, return and reach this emergency service and provide The optimal path of point is to client；The described cost that reaches comprises t1, t2, t3, wherein: t1 is the shortest path step along planning for the user Row goes to the time required for arterial highway；T2 is the time that user waits used by car on arterial highway；T3 is the shortest path along planning for the user Footpath drives to the time required for emergency service point from arterial highway；

Optimal path returns module, is connected to and reaches this computing module, for according to reaching cost calculation result, choosing and reaching This minimum emergency service provides point to recommend user, and returns the optimal path reaching this emergency service offer point to client End.