WO2015051718A1 - Dynamic track navigation method and cloud platform - Google Patents

Dynamic track navigation method and cloud platform Download PDF

Info

Publication number
WO2015051718A1
WO2015051718A1 PCT/CN2014/087686 CN2014087686W WO2015051718A1 WO 2015051718 A1 WO2015051718 A1 WO 2015051718A1 CN 2014087686 W CN2014087686 W CN 2014087686W WO 2015051718 A1 WO2015051718 A1 WO 2015051718A1
Authority
WO
WIPO (PCT)
Prior art keywords
road
cloud platform
road segment
time
trajectory
Prior art date
Application number
PCT/CN2014/087686
Other languages
French (fr)
Chinese (zh)
Inventor
董路
Original Assignee
曹玮
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to CN201310466623.3 priority Critical
Priority to CN201310466623.3A priority patent/CN103557870B/en
Application filed by 曹玮 filed Critical 曹玮
Publication of WO2015051718A1 publication Critical patent/WO2015051718A1/en

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00Navigation; Navigational instruments not provided for in preceding groups G01C1/00-G01C19/00
    • G01C21/26Navigation; Navigational instruments not provided for in preceding groups G01C1/00-G01C19/00 specially adapted for navigation in a road network
    • G01C21/34Route searching; Route guidance
    • G01C21/3453Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical

Abstract

A dynamic navigation path planning method and a cloud platform, which are applicable to the field of navigation. The method comprises: receiving, by a cloud platform, multiple pieces of track information uploaded by a plurality of mobile terminals in real time and wirelessly or existing real-time path planning solutions of a plurality of terminals; then, using the multiple pieces of track information or the existing real-time path planning solutions of the plurality of terminals to update and improve a dynamic road section database inside the cloud platform (101); and when the cloud platform receives a certain path planning request with specific requirements proposed by the mobile terminals, according to data of the updated and improved dynamic road section database inside the cloud platform, figuring out, by the cloud platform, corresponding path planning, and then wirelessly sending same to the mobile terminals (102). The method has the advantages of using mobile terminals on a large scale to collect track information used as dynamic traffic information and conducting precise navigation, accurate prediction, reasonable avoidance of crowded roads, and accurate avoidance of roads closed to passage.

Description

Dynamic trajectory navigation method and cloud platform

This application claims priority from Japanese Patent Application No. 201310466623.3, filed on Jan.

Technical field

The invention belongs to the field of navigation, and in particular relates to a dynamic track navigation method and a cloud platform.

Background technique

With the development of mobile Internet, cloud computing, ITS intelligent transportation system, vehicle networking application technology and the construction of smart city, and the development of China's second generation Beidou satellite navigation system BD2, the in-depth study of dynamic navigation technology is becoming more and more The more important it is, the more urgent it is.

Road segments, nodes, definitions of shape points and static traffic restrictions. In the actual situation, in order to avoid excessive consideration of the topological relationship between roads, the road intersection in the road network map is generally extracted as the object of analysis, and the intersection is defined as one of the nodes, and the node may also include the end of the road. Or where the road property changes; at the same time, the road is segmented by nodes, and a section of the road between the two nearest nodes is defined as a road segment. In this way, the entire road network map will be composed of nodes and road segments. The intersection points are the nodes of the network, the road segments are the arcs of the network, and several interconnected road segments with the same name form a road. The road segment can be described by a broken line, and the apex at the turning point of the polyline is called a road shape value point. The shape value point exists on the road segment, and the portion between the two adjacent shape value points is called the sub-section of the road segment. Static traffic restriction information refers to fixed traffic restrictions that do not change over a long period of time in an actual transportation network: single-line, no turning, no U-turn. To process this information, it is first necessary to establish a model of the road topology relationship and to obtain a representation of the static traffic restriction information so that the information can be integrated into the traffic network model and can be easily identified and stored by the system.

Real-time traffic information collection. Previously, the acquisition of traffic information relied mostly on traffic flow detection equipment on the road, such as ring induction coils, radar, video photos, license plate recognition, infrared sensors and floating vehicles (FC). In the past one or two years, mobile terminals have been used to collect road condition information. For example, nowadays, a large number of taxi trajectories are used to enrich real-time traffic information, especially as a main source of information for real-time road conditions.

Forecast of road traffic conditions. Since the traffic condition information is changing, if the traveler selects the route according to the traffic information before his departure, perhaps when he arrives at an intersection, the road that should have been smooth has become overcrowded. Therefore, real-time prediction of the traffic conditions of the road in a certain period of time is crucial for precise navigation. At present, the research on this aspect is not effective.

In implementing the technical solutions of the prior art, the following problems are found:

Due to the limitations of previous wireless communication technologies, the lack of mobile Internet terminals and the lack of cloud platforms, it is technically impossible to achieve large-scale use of mobile terminals to collect track information for dynamic traffic information, resulting in a mature and effective one. Dynamic navigation method. The foreign countries closest to this technology are the US INRIX, the domestic high-tech, four-dimensional new, they can calculate the so-called optimal path based on real-time road condition information, but only rely on the road data and red and green on the original map. The qualitative congestion information on the yellow trunk road is used for calculation, and the path planning given is often very unreasonable. As an important aspect of dynamic navigation technology - the prediction of future road traffic conditions, so far, there is no ideal. Models and methods.

Summary of the invention

The object of the embodiments of the present invention is to provide a cloud platform central control type dynamic trajectory navigation method, which aims to solve the problem that the prior art cannot directly apply the trajectory information to the quantitative calculation of path planning, resulting in unreasonable path planning and reaction road conditions. The problem of change insensitivity; at the same time, it provides a new method for predicting congestion road conditions, and can calculate a path planning scheme with the shortest travel time based on the predicted result; and this prediction method is based on the upload of the relevant mobile terminal. The terminal has been derived from a real-time path planning scheme, so the prediction method is relatively reliable when the number of related mobile terminals is sufficient.

In one aspect, a dynamic navigation path planning method is provided, the method comprising:

The cloud platform receives multiple track information uploaded by multiple mobile terminals in real time or multiple real-time path planning schemes of multiple terminals, and then uses the multiple track information or multiple terminals to have a real-time path planning solution to update and improve the cloud platform. Internal dynamic road segment database;

When the cloud platform receives a specific path planning request from the mobile terminal, the cloud platform calculates a path plan with a specific requirement according to the dynamic road segment database data in the updated and improved cloud platform. Requesting a corresponding path plan, and then transmitting the corresponding path plan to the mobile terminal in a wireless manner;

The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo image and acquisition time, the code of the mobile terminal to which the trajectory belongs; the number of trajectories refers to consecutive two-dimensional or three-dimensional spatial position coordinate points uploaded by each mobile terminal within the statistical time range and spatial range Forming a trajectory in a chronological order from first to last, and then accumulating the number of the trajectories to obtain a quantity;

The real-time path planning scheme of the terminal refers to a driving plan that is already existing in the mobile terminal and is in use, from the location to the destination when the mobile terminal starts this uploading, which can tell the cloud platform Where does the mobile terminal start, which way to go, and where it will go; the main role is to predict the congestion of the road in the future, which is constantly changing as the mobile terminal continues to move; in fact, it It is also similar to a trajectory--a trajectory that may be formed in the future; it does not refer to the path plan that the cloud platform makes to the mobile terminal and will send to the mobile terminal.

If a vehicle numbered 1 is driven from the node V of one road segment VW to another node W, let t1v be the time when the vehicle No. 1 reaches the node V, and T1vw(t1v) is the vehicle No. 1 arrive at the node W. The time spent, ie time consuming, the time spent in a certain time zone T of n vehicles: T1vw (t1v), T2vw (t2v), ... Tnvw (tnv) weighted average, constitutes the average time consuming This average time-consuming defines Tpnvw, also known as the dynamic impedance of the segment vw from V to W in the T-time region. If the time zone T is the elapsed time corresponding to the existing trajectory information, it is the instantaneous dynamic impedance; if the time zone T is a specified future time zone, then the future time zone T and the terminal are used. The dynamic impedance calculated by the real-time path planning scheme and the historical data of the cloud platform is called the predicted dynamic impedance.

Within a cloud platform, real-time uploaded trajectory information of multiple mobile terminals and the terminal's existing real-time path planning scheme, generate and update new road segments, generate and update simulated traffic restriction information, generate and update instantaneous dynamic impedance, generate and Updating the predicted dynamic impedance, such a dynamic database of related segments is called a dynamic segment database.

The updating and perfecting the dynamic road segment database inside the cloud platform refers to generating and updating road segment data on an unknown road, generating and updating real-time dynamic impedance of all road segments according to the trajectory information including the number of trajectories and the acquisition time of the trajectory. , generation and Updating simulated traffic restriction information of all road segments, and generating and updating predicted dynamic impedances of all road segments according to the existing real-time path planning scheme and trajectory historical data of the plurality of terminals;

The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the acquisition time of the latitude and longitude constituting each point of the trajectory; The acquisition time of the latitude and longitude of the point refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.

In a second aspect, a cloud platform is provided, where the cloud platform includes multiple smart devices, and the smart device includes: a processor, a memory, a communication interface, and a bus;

The communication interface wirelessly receives multiple track information uploaded by multiple mobile terminals or multiple real-time path planning schemes of multiple terminals in real time, and the processor then uses the multiple track information or multiple terminals to have an existing real-time path planning scheme to update And perfecting the dynamic link database inside the cloud platform; when the communication interface receives a path planning request with specific requirements proposed by the mobile terminal, the processor calculates the dynamic road segment database data according to the updated and improved cloud platform. And corresponding a path planning request with a specific path planning request, and then transmitting the corresponding path planning to the mobile terminal in a wireless manner;

The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo image and acquisition time, the code of the mobile terminal to which the trajectory belongs; the number of trajectories refers to consecutive two-dimensional or three-dimensional spatial position coordinate points uploaded by each mobile terminal within the statistical time range and spatial range Forming a trajectory in a chronological order from first to last, and then accumulating the number of the trajectories to obtain a quantity;

The real-time path planning scheme of the terminal refers to a path planning scheme used by the mobile terminal to go from the place where the uploading starts to the destination;

The updating and perfecting the dynamic road segment database inside the cloud platform refers to generating and updating the road segment data on the unknown road, the instantaneous dynamic impedance of all the road segments, and all the road segments according to the trajectory information including the number of trajectories and the acquisition time of the trajectory. Simulating the traffic restriction information, and generating and updating the predicted dynamic impedance of all the road segments according to the existing real-time path planning scheme and the trajectory historical data of the plurality of terminals;

The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the acquisition time of the latitude and longitude constituting each point of the trajectory; The acquisition time of the latitude and longitude of the point refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.

In the embodiment of the present invention, the technical solution provided by the present invention has the advantages of realizing large-scale use of the mobile terminal to collect track information for dynamic traffic information and accurately and reasonably navigate.

DRAWINGS

1 is a flowchart of a dynamic navigation path planning method according to an embodiment of the present invention;

2 is a schematic structural diagram of a cloud platform according to an embodiment of the present invention.

detailed description

In order to make the objects, technical solutions and advantages of the present invention more comprehensible, the present invention will be described below with reference to the accompanying drawings and embodiments. Further details. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

One of the most significant inventive aspects of the present invention is to change the solid-state road segment database within the navigation system to a dynamic road segment database that changes as the trajectory information changes.

One of the most significant innovations of the present invention is that a real-time path planning scheme of a terminal of a plurality of mobile terminals is uploaded to the cloud platform center in real time, and is calculated according to the existing real-time path planning scheme of the terminal and historical data in the cloud platform. Predict dynamic impedance, used to predict future road congestion conditions and calculate path planning.

The invention can be said to be a product of cloud computing, big data, mobile internet, car networking, and Beidou navigation era. Because the number of uploaded pieces of trajectory information described in the present technology refers to the so-called massive, large data order of magnitude, that is to say, the plurality of trajectory information refers to a massive amount of tens of thousands or more Orderly, continuous, dense trajectory information flow, only in this case, the correlation calculation with the number of trajectories will have a good effect.

One of the most significant inventive aspects of the present invention is to transfer the main body of the path planning from the original mobile terminal to a control center, inside the cloud platform system, and change the usually solid state road segment database within the cloud platform system to the track information. Dynamic and dynamic segment database with changes; at the same time, this technology uses cloud computing technology, uses massive trajectory information, and calculates so-called big data according to statistical principles, using the number of trajectories and trajectory acquisition time as important parameters. Real-time, dynamic change of dynamic road segment database inside the cloud platform.

The embodiment of the present invention is implemented. Under the GPS or BD2 positioning system, a cloud computing platform wirelessly receives all mobile terminals loaded by the customer on the vehicle in real time, that is, a positioning device with communication function (such as taxi positioning). Tracking information sent by the monitoring device or navigation device (such as a smart phone), then processing and computing, dynamically updating the road segment database inside the cloud platform, generating real-time dynamic impedance weights and predicting dynamic impedance weights, or generating new road segments The new traffic restriction information is generated by the simulation. When receiving the path planning request from the mobile terminal, the cloud platform calculates a path plan according to the updated dynamic link database data, and then sends the path plan to the mobile terminal. The main technical principle of the specific implementation is as follows: the received trajectory information is discarded, and the Kalman filter processing is performed to remove the noise, and then the original road segment data in the GIS is projected. If successful, the trajectory information is included in the trajectory information. The time data changes the instantaneous dynamic impedance weight of the road segment; if it is unsuccessful, the temporary road segment is additionally generated and stored in the road segment database and generates an instantaneous dynamic impedance weight. When the customer proposes the shortest time path planning, the shortest path is first obtained according to the conventional shortest path algorithm (such as A * algorithm), and the newly generated road segments can be included in the n shortest paths, and then in the n path planning. According to the superposition of the instantaneous dynamic impedance weights of the included road segments, the path planning with the shortest overall time is selected, that is, the shortest time path planning. At the same time, according to the real-time path planning uploaded by multiple mobile terminals, the predicted dynamic impedance of a certain road segment at a certain time in the future can be calculated and applied to the calculation of some path planning.

The cloud platform is a cloud computing platform, which refers to a network-based, massive storage and computing resource with dynamic storage and computing capabilities, dynamically deployable on demand, dynamically optimized, and dynamically reclaimed. A series of computer clusters and data platforms that share resources in a virtualized manner. Because the plurality of mobile terminals in the present technology actually refers to a mass of tens of thousands or more than 100 million mobile terminals, where the track information uploaded by one mobile terminal is defined as one track information, and multiple tracks Information refers to massive, tens of thousands or more orders of magnitude and continuous dense trajectory information flow. It is only possible to complete such complicated computing tasks by using such a cloud platform with superior computing power. .

Compared with the prior art, the embodiment of the present invention has the beneficial effects that the data used in the present invention is comprehensive, continuous, and complicated. Massive trajectory information, because of the large sample size, so the credibility is high; its collection, storage and calculation, and path planning are carried out inside a cloud platform, with large amount of calculation and fast speed; and it has dynamic and can be used on the map. There is no new road to implement navigation, can use the trajectory information to update the traffic restriction information, can dynamically calculate the overall path planning time-consuming, real-time reaction to the change of road conditions; in addition, according to many related multiple movements The terminal that the terminal is using has a real-time path planning scheme to predict the congestion status of a certain road segment at a certain time in the future.

It should be noted that the above method for updating the dynamic road segment database including the generation of new road segments should be based on the premise of not complying with the laws and regulations concerning surveying and mapping in the relevant countries.

The specific embodiment of the present invention provides a dynamic navigation path planning method, which is shown in FIG. 1 and includes:

101. The cloud platform receives multiple track information uploaded by multiple mobile terminals or multiple real-time path planning schemes of multiple terminals in real time, and then uses the multiple track information or multiple terminals to have an existing real-time path planning solution, which is updated and improved. Dynamic road segment database inside the cloud platform;

102. When the cloud platform receives a path planning request with a specific requirement by the mobile terminal, the cloud platform calculates and selects a specific requirement according to the dynamic road segment database data in the updated and improved cloud platform. The path plan requests a corresponding path plan, and then the corresponding path plan is sent to the mobile terminal in a wireless manner;

The real-time path planning scheme of the foregoing terminal refers to a path planning scheme existing and in use within the mobile terminal from the location to the destination when the mobile terminal starts the current uploading;

The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo image and acquisition time, the code of the mobile terminal to which the track belongs;

The updating and perfecting the dynamic road segment database inside the cloud platform refers to generating and updating the road segment data on the unknown road, the instantaneous dynamic impedance of all the road segments, and all the road segments according to the trajectory information including the number of trajectories and the acquisition time of the trajectory. Simulating the traffic restriction information, and generating and updating the predicted dynamic impedance of all the road segments according to the existing real-time path planning scheme and the trajectory historical data of the plurality of terminals;

The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the acquisition time of the latitude and longitude constituting each point of the trajectory; The acquisition time of the latitude and longitude of the point refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.

The number of the trajectories refers to a continuous two-dimensional or three-dimensional spatial position coordinate point uploaded by each mobile terminal in a chronological time range and a spatial range, forming a trajectory in a chronological order from first to last. Then, the number of the track segments is accumulated, and the obtained number is obtained. The real-time path planning scheme of the terminal refers to a path planning scheme used by the mobile terminal to go from the place where the upload starts to the destination.

Optionally, the foregoing method for generating and updating road segment data on an unknown road includes: when a plurality of mobile terminals are traveling on an unknown road, and the uploaded track information cannot be matched to the original road segment data in the dynamic road segment database of the cloud platform. The cloud platform discards the trajectory information on the original road segment in the dynamic road segment database that cannot be matched to the cloud platform, discards the abnormal point, removes the noise, and merges and merges into a simulated road according to a certain method, and temporarily stores it into the dynamic road segment. In the database, the number of trajectories in the simulated road is simultaneously calculated; when the number of trajectories merged on this simulated road reaches a certain threshold within a certain time interval, the cloud platform will The simulated road is transformed into one or several new temporary or permanent newly generated road segment data, which is stored in the dynamic road segment database, and the cloud platform also continuously updates the newly generated road segment data according to the newly uploaded new track information; It is noted that the noise removal can be implemented by a Kalman filter algorithm.

The foregoing update and improvement of the dynamic link database in the cloud platform may specifically adopt any one or combination of the following manners:

Method A: The cloud platform calculates the average time consuming of the trajectory of a certain time zone on a certain road segment according to the number of trajectories uploaded by the mobile terminal in real time and the acquisition time of the trajectory, and uses the average time consuming as an instant The dynamic impedance is stored in a database, and the certain road segment is a road segment on the original road or a newly generated road segment on the unknown road;

When the mode A is adopted, when the path planning request of the specific requirement proposed by the mobile terminal is: the shortest time path planning request, the cloud platform is based on the dynamic road segment database data inside the updated and improved cloud platform. Calculating a path planning request with specific requirements The corresponding path planning specifically includes: the cloud platform uses the database data including these instantaneous dynamic impedances to calculate the path plan with the shortest overall time consumption.

In the mode B, the cloud platform stores the acquisition time of the trajectory uploaded by the plurality of mobile terminals that are driven on the original road and the unknown road into a dynamic database of the cloud platform, and the acquisition time of the trajectory corresponds to the acquisition time of the trajectory. The road segment is associated; when the mobile terminal sets a time zone, and makes a request: when some track acquisition time stored in the dynamic database falls into the time zone, find the trajectory corresponding to the acquisition time, and then Find the road segments where the corresponding trajectories are located, and then use these road segments to splicing out a path plan, and the cloud platform calculates the path plan according to the requirements of the mobile terminal using the qualified road segments.

Method C: The cloud platform stores the number of tracks on a certain road segment uploaded by a plurality of terminals in a database of the cloud platform, and is associated with the corresponding road segment; when the mobile terminal sets a threshold number, and proposes a track on some road segments When the quantity falls into the threshold of the quantity, the road sections are found out, and then the request of the path planning is spliced by the road sections, and the cloud platform splices out the path plan according to the request of the mobile terminal according to the conditional road section.

It is also possible to combine the mode B and the mode C, that is, select a road segment having a certain number of tracks within a certain period of time to splicing the path planning. One of the significance of this is that it can avoid some road sections that are closed due to maintenance or accidents, because in this case, the number of vehicle tracks in these closed time zones is obviously trending. At zero. The existing technology is not identifiable for this common situation.

Optionally, the foregoing method further includes between 101 and 102:

By checking the number of trajectories on a certain time zone and a certain road section of the unknown road and the original road, the simulation generates a prohibition of allowing turning, turning traffic restriction information, allowing U-turn, prohibiting U-turn traffic restriction information or one-way traffic restriction information.

Optionally, the simulation generation allows the turning or prohibiting the turning traffic restriction information includes: the cloud platform checks whether the two intersecting road sections have a continuous trajectory of a certain traveling direction formed by the same mobile terminal, and calculates in a set time zone. The number of such trajectories or the relative number of the trajectories compared with the relevant trajectories. When the calculation result is greater than a predetermined value, the simulated generation of the intersections between the two road segments according to the trajectory direction The traffic restriction information that can be turned is stored in a special database. Conversely, when the calculation result is less than a preset value, the simulated generation of the intersection between the two links is prohibited according to the direction of the trajectory. Turn traffic restrictions are stored in a special database.

Optionally, the foregoing simulation generation allows the U-turn or the U-turn traffic restriction information to include: the cloud platform checks whether a certain road segment has a forward and reverse trajectory continuously formed by the same mobile terminal with a shape point as a turning point, and calculates a set time zone The number of such trajectories in the domain, or the relative number of the trajectories compared with the relevant trajectories. When the calculation result is greater than a predetermined value, the simulation between the generated segments can be turned according to the trajectory at the turning point. The traffic restriction information of the direction U-turn is stored in a special database. Conversely, when the calculation result is less than a preset value, the simulation generates a prohibition between the road segments at the turning point according to the direction of the trajectory turning. Traffic restriction information is stored in a special database.

The above-mentioned simulation generates single-line traffic restriction information, including: the cloud platform checks the number of tracks formed by the mobile terminal in a certain direction of a certain road segment, and calculates the number of such tracks in a set time region, or the same direction The relative number of comparisons of other or related trajectories. When the result of the calculation is less than a predetermined value, the traffic restriction information of the prohibited passage in the direction of the road segment is simulated and stored in a special database. .

Optionally, the foregoing cloud platform calculates, according to the updated and improved data of the dynamic link database in the cloud platform, a corresponding path plan, including:

The cloud platform first uses the static conventional shortest path calculation method to calculate the path planning scheme with the shortest overall distance, and then selects the shortest path with the shortest time according to the instantaneous dynamic impedance on the road segment in the n shortest path planning scheme. Planning, the road section includes: original roads and road sections on unknown roads.

The above static conventional shortest path calculation method refers to a method called: A * heuristic search algorithm; the algorithm is used to calculate the dynamic road segment database data based on the updated and improved cloud platform. The A * heuristic search algorithm includes a special case of the A * heuristic search algorithm with a lower bound of 0: the dijkstra algorithm.

Optionally, the foregoing updating and perfecting the road segment database in the cloud platform by using the trajectory information means that the new road segment data generated by the trajectory information simulation is stored together with the original road segment data in a neighboring table manner. In the database.

Optionally, the cloud platform calculates the corresponding path plan according to the updated and improved road segment database data, and specifically includes:

The elevation and 2D or 3D motion direction information in the trajectory information are associated with the road segment and weighted and averaged, and then stored in the database together with the video and photo data to distinguish the approximate road segment; when the cloud platform includes the viaduct, the height is different. However, when some similar sections of the horizontal plane are similar or identical, or other similar heights but the horizontal positions are close to each other, the cloud platform checks the latitude and longitude coordinates of the approximate road segment nodes, and the longitude coordinates of the corresponding nodes of the two road sections. When the absolute value of the difference between the value difference and the latitude coordinate value is less than a set value at the same time, automatically reading the trajectory of the mobile terminal traveling on the two road segments may include the average elevation, the traveling direction, the video, and the photo. Information; it is also possible to simultaneously calculate the connection relationship between the two road segments and the respective adjacent road segments, and mark and prompt, and store them together in the dynamic road segment database, and the cloud platform is based on the trajectory stored in the dynamic road segment database. Information and articulation, computing path planning; then the mobile terminal can be The trajectory information including the average elevation, the driving direction, the video, the photo, and the connection relationship together with the mark and the prompt are sent to the mobile terminal together with the calculated path planning solution; the calculating the connection relationship refers to accumulating on a certain road segment The number of consecutive trajectories formed by each mobile terminal on a straight line or a turn, traveling across a node to an adjacent road segment, when the number falls within a set threshold time within a set time period, or when In a set time zone, when the ratio of the continuous trajectory is compared with the number of related trajectories and the ratio falls within a set threshold, it is confirmed that the two sections have the direction in which the trajectory runs. Cohesion.

Optionally, the foregoing uses the trajectory information and the existing real-time path planning scheme of the terminal to update and improve the dynamic path inside the cloud platform. The segment database refers to the real-time path planning scheme of the terminal that is dynamically uploaded by the cloud platform according to the dynamics of multiple mobile terminals, and the instantaneous dynamic impedance of the relevant segment of the road segment, and calculates a certain section of the road at a specified time in the future. a predicted quantity of the mobile terminal, and then finding a weighted average of the instantaneous dynamic impedance of the road segment corresponding to the quantity stored in the cloud platform according to the predicted quantity, as the predicted dynamics of the road segment The impedance is stored in a database of the cloud platform along with the corresponding time. When a mobile terminal proposes a specific path plan, the cloud platform predicts the traffic congestion of a specified time segment and a specified road segment according to the predicted dynamic impedance. The situation, and calculate a path planning scheme according to the requirements of the mobile terminal, and wirelessly transmit to the mobile terminal.

Optionally, the cloud platform calculates, according to the updated and improved road segment database data, the corresponding path plan specifically includes:

The method of updating and perfecting and calculating the path planning method can combine the technical solutions provided by the above methods as needed.

After the mobile terminal receives the path planning scheme for wireless transmission by the cloud platform, there are three cases:

a. The data of the link database in the cloud platform is exactly the same as that of the mobile terminal, and the mobile terminal directly splices the corresponding corresponding road segment according to the path planning scheme made by the cloud platform;

b. The map in the cloud platform and the map in the mobile terminal are different versions of the system, or although the data in the road segment database is different from the same version of the system, the main problem is that there are some segments on the cloud platform but the mobile terminal map is No, in order to solve this problem, the special database design and topology relationship should be established in advance, so as to make the two sections of the same system different versions of the database have high compatibility, so that the cloud platform can pass the detection and will jointly own The continuous road segment data information is sequentially arranged and sent to the terminal, and then the mobile terminal performs according to the method in a. above; for the part of the cloud platform that is not in the mobile terminal, the cloud platform will use the data in the part of the road segment. The latitude and longitude data of the location point is sent to the mobile terminal, and the mobile terminal further finds the corresponding location point according to the latitude and longitude data, and connects and displays it in the display screen, and prompts in the voice prompt: “Unknown road, please press the track Information is carefully driven."

C. For electronic maps of different systems, the road segment information will be converted into track information according to international or national relevant standards, that is, all path planning schemes will be sent to the mobile terminal in the form of track position point latitude and longitude data, and the mobile terminal is on the screen. According to this, draw a connection for the driver's reference, accompanied by a voice prompt: "Track navigation, please drive carefully according to the trajectory." This will help maximize the service to a variety of different customers.

It should be noted that the trajectory information described above may be trajectory information collected by a satellite positioning technology using a GPS/DR, BD2 (second generation Beidou navigation system)/DR mobile terminal positioning module, and a mobile communication base station positioning technology. It may also be an trajectory information acquired by using an electronic identification technology such as an RFID recognition technology, an infrared or a laser scanning technology to identify an electronic tag loaded on the vehicle, and may also include trajectory information acquired by video and image information, The way the track information is collected should not be limited by the acquisition method.

To protect the privacy of the user, the trajectory information and the collection of the real-time path planning scheme of the terminal may be acquired anonymously. The uploading of the trajectory information between the mobile terminal and the cloud platform or the reception of the path planning may also be performed in a variety of ways, including satellite communication, SMS communication of the Beidou satellite navigation system, WiFi, GPRS, 2G, 3G or 4G technologies. The specific embodiments of the present invention are not limited to any wireless communication method.

It should be noted that the trajectory information may include: longitude, latitude, elevation, two-dimensional or three-dimensional velocity, two-dimensional or three-dimensional motion direction, number of trajectories, code of the mobile terminal to which the trajectory belongs, video and image a parameter, and an acquisition time of the plurality of parameters; the updating and perfecting the dynamic road segment database inside the cloud platform refers to generating a plurality of parameters in the trajectory information including the number of trajectories and the acquisition time region of the trajectory And update road segment data on unknown roads, instantaneous dynamic impedance on all road segments, and simulated traffic restriction information on all road segments. One of the specific methods is: after receiving the trajectory information, the cloud platform first filters the trajectory to remove the clutter with abnormal or excessive deviation, and then according to a certain method, the position data in the trajectory information is the same as the original in the GIS database. Some road segments have data matching. If they succeed, they fall into the data of the road segment. The data of the point corresponding to the track and the link segment is changed to the data of the corresponding point of the link, and the instantaneous dynamic impedance weight of the segment is given according to the acquisition time of the track. If unsuccessful, store it in another database, and in this database, sort and merge the adjacent tracks to generate one or more simulated roads, when in a specified time zone, on the simulated road When the number of tracks reaches a certain value, a new road segment is divided and simulated according to a certain method.

In addition, the segment prediction dynamic impedance can be generated and updated according to the existing real-time path planning scheme of multiple terminals. The real-time path planning scheme of the terminal refers to a path planning scheme used by the mobile terminal from the location where the uploading starts to the destination; the instantaneous dynamic impedance refers to the received The trajectory information of the plurality of mobile terminals is used to calculate the weighted average time of a certain time zone of a certain road segment, and the result is the instantaneous dynamic impedance of a certain section of the certain time zone; the predicted dynamic impedance refers to uploading according to multiple mobile terminals. The multiple terminals have a real-time path planning scheme, and combine the historical data in the cloud platform to calculate the time consumption of a certain section of the future time zone, and the result is the predicted dynamic impedance of a certain section of the future time zone; All road segments are those that include newly generated road segments and original road segments.

It should be noted that the trajectory acquisition time described in the present application refers to a time set formed by the acquisition time of each location point constituting the trajectory, and the acquisition time of the location point refers to that the mobile terminal collects the When the latitude and longitude data is located, there may be an error in the time when the mobile terminal is located and the time at which the data is collected. Therefore, the acquisition time generally lags slightly behind the time at which the mobile terminal is actually located. However, in this technique, this time difference is generally ignored.

It should be noted that the traffic restriction information described in the present technology includes: prohibiting a turn to the left, prohibiting a turn to the right, prohibiting a U-turn, prohibiting a straight-line traffic prohibition sign information, turning left, turning right, allowing U-turn, one-way road only traffic signs information.

The cloud platform predicts the traffic congestion condition of a certain specified time and a certain road section according to the predicted dynamic impedance, and calculates a path planning scheme according to the requirements of the mobile terminal, and transmits the data to the mobile terminal wirelessly; the meaning is also: To predict and coordinate the traffic distribution of the vehicle. On the other hand, when the cloud platform and the mobile terminal collect the transmission speed of the trajectory information, the calculation speed of the path planning scheme and the wireless transmission speed are fast enough, and supplemented by the relevant vehicles. The direct communication of the trajectory information can also be used to prevent collisions between vehicles by means of automatic alarm and automatic evasion.

It should be noted that the calculating the connection relationship refers to accumulating the number of continuous trajectories formed when each mobile terminal on a certain road segment travels to the adjacent road segment during the straight or turning process. When the value of the quantity, or the relative value of the quantity compared with the number of other related trajectories, is greater than a set value within a set time zone, it is confirmed that the two road sections are spanned The node is a joint point, and there is a cohesive relationship in the direction in which the trajectory runs; when the value of the quantity, or the relative value of the quantity compared with the number of other related trajectories, is less than one in a set time zone When setting the value, it is true It is considered that the two sections are connected by the nodes they cross, and there is no connection relationship in the direction in which the trajectory runs. However, there is no connection relationship here, including the physical conditions such as the road of the upper and lower layers of the overpass. Limits on guardrails and gullies; also include restrictions on traffic rules that are not allowed to go straight and are not allowed to turn.

In summary, the implementation of this technology will play a certain role in promoting the development of ITS intelligent transportation system, vehicle networking application technology and the construction of smart cities in China.

The embodiment of the present invention further provides a cloud platform, which includes: a plurality of smart devices, the smart device may specifically be: a computer or a server, and the hardware structure diagram of the smart device is as shown in FIG. 2, including: a processor 201. Memory 202, communication interface 203, and bus 204.

The processor 201, the memory 202, and the communication interface 203 are connected to each other through a bus 204. The bus 204 may be an Industry Standard Architecture (ISA) bus or a Peripheral Component Interconnect (PCI) bus.

The above-mentioned processor 201 may be a general-purpose processor, including a central processing unit (English: central processing unit, CPU for short), a network processor (English: network processor, referred to as NP), and of course, may also be a digital signal processor (English: Digital Signal Processing, referred to as DSP).

The memory 202 is configured to store a program and a dynamic link database. In particular, the program can include program code, the program code including computer operating instructions for instructing the processor 201 to issue computer operating instructions. The memory 202 may include a high-speed random access memory (RAM) memory, and may also include a non-volatile memory such as at least one disk memory.

The communication interface 203 is configured to receive or send data. The data may be: a packet, a track information, or a path planning information. Specifically, the communication interface 203 may be a communication port, and the communication port includes but is not limited to a wireless communication port or a wired communication port.

The communication interface 203 wirelessly receives multiple track information uploaded by multiple mobile terminals in real time or has a real-time path planning scheme for multiple terminals, and the processor 201 then updates the existing track path plan by using the multiple track information or multiple terminals. And perfecting the dynamic link database inside the cloud platform; when the communication interface 203 receives a certain path planning request that is requested by the mobile terminal, the processor 201 is configured according to the dynamic segment database data inside the cloud platform that is updated and improved. Calculating a path plan corresponding to a path planning request with a specific requirement, and then transmitting the corresponding path plan to the mobile terminal in a wireless manner;

The real-time path planning scheme of the foregoing terminal refers to a path planning scheme existing and in use within the mobile terminal from the location to the destination when the mobile terminal starts the current uploading;

The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo image and acquisition time, the code of the mobile terminal to which the track belongs;

The updating and perfecting the dynamic road segment database inside the cloud platform refers to generating and updating the road segment data on the unknown road, the instantaneous dynamic impedance of all the road segments, and all the road segments according to the trajectory information including the number of trajectories and the acquisition time of the trajectory. Simulating traffic restriction information, and generating and updating all the roads according to the existing real-time path planning scheme and trajectory history data of the plurality of terminals The predicted dynamic impedance of the segment;

The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the acquisition time of the latitude and longitude constituting each point of the trajectory; The acquisition time of the latitude and longitude of the point refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.

Optionally, the processor 201 is configured to: when the track information uploaded by the multiple mobile terminals cannot match the original road segment data in the dynamic road segment database of the cloud platform, the processor 201 removes the track information that cannot match. Noise, according to a certain method, merged into one or more simulated roads, and temporarily stored in the dynamic road segment database, and accumulate the number of tracks in the simulated road; when in a certain time interval, a certain simulation When the number of tracks on the road is added to a certain threshold, the processor converts the simulated road into one or several new temporary or permanent newly generated road segment data, and stores the data in the dynamic road segment database, and the processor 201 The newly generated road segment data is also continuously updated according to the new track information uploaded in real time.

Optionally, the processor 201 is specifically configured to calculate, according to the number of trajectories uploaded by the mobile terminal in real time and the acquisition time of the trajectory, an average time consuming of the trajectory of a certain time zone on a certain road segment, and average the trajectory The time-consuming is stored as a real-time dynamic impedance in a database, and the certain road segment is a road segment on the original road or a newly generated road segment on the unknown road;

When the path planning request of a specific requirement proposed by the mobile terminal is: the shortest time path planning request, the processor calculates a certain specific according to the dynamic road segment database data inside the updated and improved cloud platform. The corresponding path planning request corresponding path planning specifically includes: the processor uses the database data including the instantaneous dynamic impedance to calculate the overall shortest path planning.

Optionally, the processor 201 is specifically configured to store, in a dynamic database of the cloud platform, an acquisition time of the trajectory uploaded by the plurality of mobile terminals that are used on the original road and the unknown road, and acquire the trajectory of the trajectory and the The acquisition time of the trajectory is associated with the road segment; when the mobile terminal sets a time zone, and makes a request: when some trajectory acquisition time stored in the dynamic database falls into the time zone, it is found that the acquisition time corresponds to The trajectory is further found out the path segment where the corresponding trajectory is located, and then a path plan is spliced by using the road segments, and the processor 201 calculates the path plan according to the request of the mobile terminal by using the qualified road segment.

Optionally, the processor 201 stores the number of tracks on a certain road segment uploaded by the plurality of terminals in a database of the cloud platform, and is associated with the corresponding road segment; when the mobile terminal sets a threshold number, and proposes to be on some road segments When the number of trajectories falls within the threshold of the number, the road segments are found, and then the request for path planning is spliced by the road segments, and the processor 201 splices out the path plan according to the request of the mobile terminal.

Optionally, the processor 201 is specifically configured to simulate to allow turning, prohibit turning traffic restriction information, allow U-turn, and prohibit U-turn traffic by checking the number of tracks on a certain time zone and a certain road section of the unknown road and the original road. Restrict information or one-way traffic restrictions.

Optionally, the processor 201 is specifically configured to check whether two intersecting road segments have a continuous trajectory of a certain traveling direction formed by the same mobile terminal, and calculate an absolute number of such trajectories in a set time region. Or the relative quantity compared with the relevant trajectory. When the calculation result is greater than a predetermined value, the simulation generates traffic restriction information between the two road sections that can be turned according to the trajectory direction of the intersecting node. Stored in a special database. Conversely, when the result of this calculation is less than a predetermined value, the simulated generation of the intersection between the two links is prohibited according to the direction of the trajectory. Turn traffic restrictions information to a special database.

Optionally, the processor 201 is specifically configured to check whether a certain road segment has a forward and reverse trajectory continuously formed by the same mobile terminal with a shape point as a turning point, and calculate the trajectory in a set time zone. The absolute number of the trajectories, or the relative number of the trajectories compared with the related trajectories, when the calculation result is greater than a predetermined value, the simulation between the generated segments can be turned around at the turning point according to the trajectory turning direction The traffic restriction information is stored in a special database. Conversely, when the calculation result is less than a preset value, the simulation generates a traffic restriction between the road segments that prohibits the U-turn in the turning direction of the turning point. Information is stored in a special database.

Optionally, the processor 201 is specifically configured to check the number of tracks formed by the mobile terminal in a certain direction of a certain road segment, and calculate the absolute number of such tracks in a set time region, or the same direction The relative number of comparisons of other or related trajectories. When the result of the calculation is less than a predetermined value, the traffic restriction information of the prohibited passage in the direction of the road segment is simulated and stored in a special database. .

Optionally, the processor 201 is specifically configured to calculate a path planning scheme with the shortest overall distance by using a static conventional shortest path calculation method, and then select, according to the instantaneous dynamic impedance on the road segment, the n shortest path planning schemes. A path plan with the shortest overall time consuming, the road segments include: original roads and road sections on unknown roads.

Optionally, the static conventional shortest path calculation method refers to an A * heuristic search algorithm; and the A * heuristic search algorithm is used to dynamically update the dynamic road segment database data according to the cloud platform. The path planning scheme with the shortest overall distance is calculated; the A * heuristic search algorithm includes a special case of the A * heuristic search algorithm with a lower bound of 0: the dijkstra algorithm.

Optionally, the updating and improving the dynamic link database in the cloud platform by using the plurality of trajectory information refers to: after the new link data generated by the trajectory information is simulated, the new link data is combined with the original link data. Stored in a database expressed in a contiguous table.

Optionally, the processor 201 is specifically configured to associate the elevation and the two-dimensional or three-dimensional motion direction information in the trajectory information with the road segment and weight the average, and store the information in the dynamic road segment database; when the cloud platform uses the upper and lower bridges including the viaduct When the height is different but the horizontal planes are similar or identical, or other similar sections with the same height but close horizontal position are used for path planning, the cloud platform first checks the latitude and longitude coordinates of the approximate road segment nodes, and the longitude coordinates of the corresponding nodes of the two road segments. When the absolute value of the difference between the value difference and the latitude coordinate value is less than a set threshold value at the same time, the average elevation and the traveling direction of the trajectory traveling thereon are automatically read, and the connection relationship with the adjacent road segments is calculated and marked. And prompting, and then sending the indication, the prompt indicating the elevation, the driving direction and the connection relationship, and the calculated path planning scheme to the mobile terminal; the calculating the connection relationship with the adjacent road segments refers to calculating the same mobile terminal The absolute number and relative number of consecutive trajectories spanning adjacent segments in the same direction, when The number and relative amount of the fall threshold number is set in a time region is set, it is confirmed for both engagement sections has a relationship in the direction of the running track.

Optionally, the using the trajectory information or the existing real-time path planning scheme of the terminal to update and improve the dynamic road segment database inside the cloud platform refers to the real-time path planning of the terminal that is dynamically uploaded by the cloud platform according to dynamics of multiple mobile terminals. The solution, and the instantaneous dynamic impedance within a certain period of time of the road segment involved, calculate a predicted number of mobile terminals on a certain road segment at a specified time in the future, and then find the stored and stored in the cloud platform according to the predicted quantity. The predicted quantity corresponds to a certain one of the road segments The weighted average of the instantaneous dynamic impedance during the segment time is used as the predicted dynamic impedance of the road segment, and the predicted dynamic impedance is stored together with the corresponding time in the dynamic road segment database of the cloud platform, when a mobile terminal proposes a specific path During the planning, the cloud platform predicts the traffic congestion condition of a specified time and a specified road section according to the predicted dynamic impedance, and calculates a path planning solution according to the requirement of the specific terminal planning of the mobile terminal, and sends the path planning plan to the mobile terminal. .

Those skilled in the art can understand that all or part of the technical solutions provided by the embodiments of the present invention can be completed by using related hardware of the program instructions. For example, it can be done by computer running. The program can be stored in a readable storage medium such as a random access memory, a magnetic disk, an optical disk, or the like.

The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention. All equivalent substitutions or improvements made within the specific embodiments of the present invention are included in the protection scope of the present invention. .

Claims (28)

  1. A dynamic navigation path planning method, the method comprising:
    The cloud platform receives multiple track information uploaded by multiple mobile terminals in real time or multiple real-time path planning schemes of multiple terminals, and then uses the multiple track information or multiple terminals to have a real-time path planning solution to update and improve the cloud platform. Internal dynamic road segment database;
    When the cloud platform receives a certain path planning request that is requested by the mobile terminal, the cloud platform calculates a corresponding path plan according to the updated and improved dynamic road segment database data of the cloud platform, and then the The corresponding path plan is sent to the mobile terminal in a wireless manner;
    The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo and acquisition time, the code of the mobile terminal to which the track belongs;
    The real-time path planning scheme of the terminal refers to a path planning scheme existing and in use within the mobile terminal from the location to the destination when the mobile terminal starts the current uploading;
    The updating and perfecting the dynamic road segment database inside the cloud platform includes: generating and updating road segment data on the unknown road according to the trajectory information including the number of trajectories and the acquisition time of the trajectory, and generating and updating the instant of all the road segments. Dynamic impedance, generating and updating simulated traffic restriction information of all road segments; in addition, generating and updating predicted dynamic impedances of all road segments according to the existing real-time path planning scheme and trajectory historical data of the plurality of terminals;
    The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the points formed by the acquisition time of the latitude and longitude constituting the points of the trajectory; The acquisition time of the latitude and longitude of each point of the trajectory refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.
  2. The method according to claim 1, wherein the generating and updating the link data on the unknown road comprises:
    When the mobile terminal travels on the unknown road and uploads the trajectory information, the cloud platform removes the abnormal point and noise from the position information in the trajectory information and combines them into one or more simulated roads according to a certain method, and temporarily stores them in the dynamic road section. In the database, the number of tracks in the simulated road is simultaneously accumulated; when the number of the accumulated tracks accumulated on a certain simulated road falls within a certain set time period, The cloud platform converts the certain simulated road into one or several new temporary or permanent newly generated road segment data, and stores the data in the dynamic road segment database, and then the cloud platform pairs the new track information according to the new track information uploaded in real time. Generate road segments and related data are continuously updated;
    The unknown road refers to a road in the original dynamic road segment database that does not have corresponding data.
  3. The method according to claim 1, wherein the calculating the corresponding path plan specifically comprises:
    The cloud platform calculates the average time consuming of the trajectory of a certain time zone on a certain road segment according to the number of trajectories uploaded by the mobile terminal in real time and the acquisition time of the trajectory, and uses the average time consumption as an instantaneous dynamic impedance. The time zones are stored together in a database, and the certain road segment refers to a road segment on the original road or a newly generated road segment on the unknown road;
    When the path planning request of the specific requirement proposed by the mobile terminal is: the shortest time path planning request, the cloud platform calculates the corresponding path according to the dynamic road segment database data inside the updated and improved cloud platform. The plan specifically includes: The cloud platform uses the database data that contains these instantaneous dynamic impedances to calculate the overall time-consuming path plan.
  4. The method according to claim 1, wherein the calculating the corresponding path plan specifically comprises:
    The cloud platform stores the acquisition time of the trajectory uploaded by the plurality of mobile terminals traveling on the original road and the unknown road into a dynamic database of the cloud platform, and associates the acquisition time of the trajectory with the road segment where the corresponding trajectory is located; The cloud platform or the mobile terminal sets a time zone, and makes a request: when some track acquisition time stored in the dynamic road segment database falls into the time zone, find the trajectory corresponding to the acquisition time, and then find out The road segments where the corresponding trajectories are located are then spliced out of the road plans by using the road segments; the cloud platform calculates the corresponding path plans according to the requirements of the cloud platform or the mobile terminal by using the qualified road segments.
  5. The method according to claim 1, wherein the calculating the corresponding path plan specifically comprises:
    The cloud platform calculates the number of tracks on a certain road segment uploaded by multiple mobile terminals, stores them in the database of the cloud platform, and associates them with the corresponding road segments; when the cloud platform or the mobile terminal sets a threshold number of tracks or a ratio of the number of tracks Threshold and request: when the number of trajectories on some road segments falls within the threshold of the number of trajectories, or when the ratio of the number of trajectories on some road segments to the number of related trajectories falls within the threshold of the number of trajectories And finding a part of the road segment, and then splicing a path plan with the some road segments; the cloud platform splicing out the corresponding path plan according to the request of the cloud platform or the mobile terminal by using the qualified road segments.
  6. The method according to claim 1, wherein the updating and improving the dynamic link database inside the cloud platform further comprises:
    By testing the number or relative quantity of continuous trajectories on a certain time zone or some specified road section on an unknown road or original road, simulating the generation of information that allows turning, prohibiting turning traffic restrictions, allowing U-turns, prohibiting U-turn traffic restrictions, or only One-way traffic restriction information.
  7. The method according to claim 6, wherein the simulating the generation of turning or prohibiting turning traffic restriction information comprises:
    The cloud platform checks whether two intersecting road segments share a continuous trajectory of a certain turning direction formed by the same mobile terminal, and calculates the number of such trajectories in a set time region, or the relative comparison with the related trajectories. Quantity, when the calculation result is greater than a preset value, the simulation generates traffic restriction information between the two road sections that is allowed to turn according to the turning direction at the intersecting node, and stores the information in a special database. Conversely, when the result of the calculation is less than a predetermined value, the simulation generates traffic restriction information between the two links that is prohibited from turning at the intersecting node according to the direction of the turn, and stores it in a special database. in.
  8. The method according to claim 6, wherein the simulation generation of the allowable U-turn or the U-turn traffic restriction information comprises:
    The cloud platform checks whether a certain road segment has forward and reverse trajectories continuously formed by the same mobile terminal with a shape point as a turning point, and calculates the number of such trajectories in a set time region, or The relative quantity compared with the relevant trajectory. When the calculation result is greater than a preset value, the simulation generates traffic restriction information between the road segments that allows the U-turn in the turning direction of the turning point to be stored in a special In the database; otherwise, when the result of the calculation is less than a predetermined value, the simulation generates a traffic between the road segments that is prohibited from turning around at the turning point according to the direction of the turning point. Restrict information and store it in a special database.
  9. The method according to claim 6, wherein the simulation generates only one-way traffic restriction information including:
    The cloud platform checks the number of tracks formed by a mobile terminal in a specified direction of a certain road segment, and calculates the number of such tracks in a set time region, or compares with the opposite direction or other related trajectories. The relative quantity, when the result of the calculation is less than a predetermined value, simulates the traffic restriction information of the prohibited passage of the road segment in the specified direction, and stores it in a special database.
  10. The method according to claim 1, wherein the cloud platform calculates a corresponding path plan according to the data of updating and perfecting the dynamic link database inside the cloud platform, including:
    The cloud platform first calculates a path planning scheme with the shortest overall distance by using a static conventional shortest path calculation method, and then calculates the instantaneous dynamic impedance on the included road segment in the path planning scheme with the shortest overall distance of the n. A path plan with the shortest overall time consumption, the road segments include: original roads and road sections on unknown roads.
  11. The method according to claim 10, wherein said static conventional shortest path calculation method refers to an A * heuristic search algorithm; and said A * heuristic search algorithm is used to update according to said And the dynamic road segment database data inside the perfect cloud platform calculates the path planning scheme with the shortest overall distance n; the A * heuristic search algorithm includes a special case of the A * heuristic search algorithm with a lower limit of 0: Dijkstra algorithm.
  12. The method according to claim 1, wherein the updating and improving the dynamic road segment database inside the cloud platform means storing the updated road segment data on the unknown road together with the original road segment data. In a database expressed in an adjacency list.
  13. The method according to claim 1, wherein the cloud platform calculates a path planning request corresponding to the specific requirement according to the dynamic road segment database data inside the updated and improved cloud platform. Path planning, including:
    The elevation weighted average value of each position point in the trajectory information or the weighted average of the two-dimensional, three-dimensional motion direction data, or the video photograph is stored in the database in association with the road segment to distinguish the approximate road segment; when the cloud platform retrieves When the upper and lower heights of the viaduct are different but the horizontal planes are similar or identical, or some of the similar sections are similar in height but close to the horizontal position, the latitude and longitude coordinates of the approximate road segment nodes are further quantitatively compared, and when the two road segments correspond to the nodes When the absolute value of the difference between the longitude coordinate value and the latitude coordinate value is less than a set value at the same time, the mobile terminal traveling on the two road segments is extracted including the average elevation, the average traveling direction, the video, and the photo. Trajectory information; or simultaneously calculate the connection relationship between the two road segments and their respective adjacent road segments, and mark and prompt, store in a special dynamic road segment database; when the mobile terminal proposes a specific path planning When requested, the cloud platform uses the inclusions stored in the special dynamic road segment database. The average elevation, the average driving direction, the video, the trajectory information of the photo or the connection relationship, calculate the corresponding path planning; then the average elevation, the average driving direction, the video, the trajectory information of the photo or the connection relationship Together with the marked and prompted, the calculated path planning scheme is sent to the mobile terminal; the calculating the connection relationship refers to accumulating each mobile terminal on a certain road segment to travel adjacent to the node in a straight line or a turn. The resulting number of consecutive trajectories formed when the road segment, when the value of the quantity, or the relative value of the quantity compared to the number of other related trajectories, is greater than a set value in a set time zone At the time, it is confirmed that the two sections are connected by the nodes that are crossed, and have a connection relationship in the direction in which the trajectory runs.
  14. The method according to claim 1, wherein the calculating the corresponding path plan comprises: the real-time path planning scheme of the terminal that is dynamically uploaded by the cloud platform according to the dynamics of the plurality of mobile terminals, and the related road segment Instant dynamic impedance, calculating a predicted number of mobile terminals on a specified road segment at a specified time in the future, and then finding out the segment on the road segment corresponding to the predicted number stored in the cloud platform according to the predicted quantity Some instantaneous dynamic impedance, the value obtained by weighting the instantaneous dynamic impedances is the predicted dynamic impedance of a specified road segment at a specified time in the future, and the predicted dynamic impedance and the specified time in the future. Stored together in a dynamic road segment database of the cloud platform; when a mobile terminal proposes a specific path plan, the cloud platform predicts a traffic congestion condition of a specified road segment at a specified time in the future according to the predicted dynamic impedance. And calculating the predicted dynamic impedance as one of the parameters to calculate a corresponding path planning scheme, Send to the mobile terminal.
  15. A cloud platform, the cloud platform includes a plurality of smart devices, the smart device includes: a processor, a memory, a communication interface, and a bus;
    The communication interface wirelessly receives multiple track information uploaded by multiple mobile terminals or multiple real-time path planning schemes of multiple terminals in real time, and the processor then uses the multiple track information or multiple terminals to have an existing real-time path planning scheme to update And perfecting the dynamic link database inside the cloud platform; when the communication interface receives a path planning request with specific requirements proposed by the mobile terminal, the processor calculates the dynamic road segment database data according to the updated and improved cloud platform. Corresponding path planning, and then transmitting the corresponding path plan to the mobile terminal in a wireless manner;
    The trajectory information includes: the number of trajectories and the acquisition time of the trajectory, the latitude and longitude of the trajectory and the acquisition time, the elevation and acquisition time, the two-dimensional or three-dimensional velocity and acquisition time, the two-dimensional or three-dimensional motion direction and the acquisition time, video or Photo image and acquisition time, the code of the mobile terminal to which the track belongs;
    The real-time path planning scheme of the terminal refers to a path planning scheme existing and in use within the mobile terminal from the location to the destination when the mobile terminal starts the current uploading;
    The updating and perfecting the dynamic road segment database inside the cloud platform refers to generating and updating road segment data on an unknown road, generating and updating real-time dynamic impedance of all road segments according to the trajectory information including the number of trajectories and the acquisition time of the trajectory. Generating and updating simulated traffic restriction information of all road segments, and generating and updating predicted dynamic impedances of all road segments according to the existing real-time path planning scheme and trajectory historical data of the plurality of terminals;
    The all the road segments are included in the newly generated road segment and the original road segment; the acquisition time of the trajectory refers to a time set corresponding to the acquisition time of the latitude and longitude constituting each point of the trajectory; The acquisition time of the latitude and longitude of the point refers to the time when the mobile terminal acquires the latitude and longitude coordinates of the points.
  16. A cloud platform according to claim 15, wherein
    The processor is specifically configured to: when the mobile terminal travels on an unknown road and uploads the track information, the processor removes the noise and the abnormal point from the position information in the track information, and merges and merges into one or a plurality of simulated roads, temporarily stored in the dynamic road segment database, and accumulating the number of tracks in the simulated road; and merging the accumulated tracks on a certain simulated road within a certain time zone When the quantity falls within a certain set threshold, the processor converts the certain simulated road into one or several new temporary or permanent newly generated road segment data, stores the data into a dynamic road segment database, and then the The processor continuously updates the newly generated road segment and related data according to the new trajectory information uploaded in real time;
    The unknown road refers to a road in the original dynamic road segment database that does not have corresponding data.
  17. A cloud platform according to claim 15, wherein
    The processor is specifically configured to calculate an average time consuming of a trajectory of a certain time zone on a certain road segment according to the number of trajectories uploaded by a plurality of mobile terminals in real time and the acquisition time of the trajectory, and use the average time consuming time as An instantaneous dynamic impedance is stored in a database, and the certain road segment refers to a road segment on the original road or a newly generated road segment on the unknown road;
    When the path planning request of a specific requirement proposed by the mobile terminal is: the shortest time path planning request, the processor calculates a corresponding path plan according to the dynamic road segment database data inside the updated and improved cloud platform. Specifically, the processor calculates the overall shortest path planning by using database data including these instantaneous dynamic impedances.
  18. A cloud platform according to claim 15, wherein
    The processor stores the acquisition time of the trajectory uploaded by the plurality of mobile terminals that are driven on the original road and the unknown road into a dynamic database of the cloud platform, and associates the acquisition time of the trajectory with the road segment where the corresponding trajectory is located When the cloud platform or the mobile terminal sets a time zone, and makes a request: when some track acquisition time stored in the dynamic database falls into the time zone, find the trajectory corresponding to the acquisition time, and then find The road segments where the corresponding trajectories are located are used, and then a path plan is spliced by using the road segments; the processor calculates the corresponding path plan according to the requirements of the cloud platform or the mobile terminal by using the qualified road segments.
  19. A cloud platform according to claim 15, wherein
    The processor calculates the number of tracks on a certain road segment uploaded by the plurality of mobile terminals, and stores them in a database of the cloud platform, and is associated with the road segment where the track is located; when the cloud platform or the mobile terminal sets one The number of trajectories threshold or the number of trajectory ratio thresholds, and requests: when the number of trajectories on some road segments falls within the threshold number of the trajectories, or when the ratio of the number of trajectories on some road segments to the number of related trajectories falls into this When the number of trajectory ratio thresholds is found, the some road segments are found, and then a path plan is spliced by using the road segments; and the processor splices the segments according to the requirements of the cloud platform or the mobile terminal. Corresponding path planning.
  20. A cloud platform according to claim 15, wherein
    The processor is specifically configured to simulate to generate turning and prohibiting turning traffic restriction information by verifying the number or relative number of continuous tracks on a certain time zone or a certain time zone on an unknown road or an original road, allowing for U-turn and prohibition U-turn traffic restriction information or only one-way traffic restriction information.
  21. The cloud platform of claim 20, wherein:
    The processor is specifically configured to check whether two intersecting road segments have a trajectory of a certain turning direction formed by consecutive same mobile terminals, and calculate the number, or the correlation, of the trajectories in a set time zone. The relative quantity of the trajectories compared, when the calculation result is greater than a predetermined value, the simulation generates traffic restriction information between the two road sections that is allowed to turn according to the certain turning direction at the intersecting node, and stores In a special database; otherwise, when the result of the calculation is less than a predetermined value, the simulation generates traffic restriction information between the two road segments at which the intersecting nodes prohibit turning according to the direction of the turn, and stores Go to a special database.
  22. The cloud platform of claim 20, wherein:
    The processor is specifically configured to check whether a certain road segment is continuously formed by the same mobile terminal with a shape point as a turning point. The forward and reverse trajectories, and calculate the number of such trajectories in a set time region, or the relative amount compared with the relevant trajectory, when the calculation result is greater than a predetermined value, Then, the simulation generates a traffic restriction information between the road segments that allows the U-turn in the turning direction of the turning point to be stored in a special database; otherwise, when the calculation result is less than a preset value, the simulation generates The traffic restriction information between the road sections that prohibits the U-turn at the turning point according to the direction of the turning of the track is stored in a special database.
  23. The cloud platform of claim 20, wherein:
    The processor is specifically configured to check the number of tracks formed by a mobile terminal in a specified direction of a certain road segment, and calculate the number of such tracks in a set time region, or the same direction or other The relative number of correlation trajectories is compared. When the calculation result is less than a preset value, the traffic restriction information of the prohibited passage of the road segment in the specified direction is generated and stored in a special database. .
  24. The cloud platform of claim 15 wherein:
    The processor is specifically configured to calculate a path planning scheme with the shortest overall distance by using a static conventional shortest path calculation method, and then calculate an overall size according to the instantaneous dynamic impedance on the included road segment in the n shortest path planning schemes. The shortest path planning, including the original road and the road section on the unknown road.
  25. A cloud platform according to claim 24, wherein:
    The static conventional shortest path calculation method refers to an A * heuristic search algorithm; and the A * heuristic search algorithm is used to calculate the dynamic link database data based on the updated and improved cloud platform. n The overall shortest path planning scheme; the A * heuristic search algorithm, including a special case of the A * heuristic search algorithm with a lower bound of 0: the dijkstra algorithm.
  26. The cloud platform of claim 15 wherein:
    The updating and perfecting the dynamic road segment database inside the cloud platform means that the road segment data on the unknown road generated and updated is stored together with the original road segment data in a database expressed in an adjacency list manner.
  27. A cloud platform according to claim 15 wherein:
    The processor is specifically configured to store an elevation weighted average value of each position point in the track information or a weighted average of the two-dimensional and three-dimensional motion direction data, or a video photo in a database in association with the road segment, to distinguish the approximation a road section; when the cloud platform retrieves some of the approximate road sections including the heights of the viaducts at different heights but the water level positions are similar or the same, or other heights are the same but the horizontal positions are close, the latitude and longitude coordinates of the approximate road section nodes are further quantitatively compared. When the absolute value of the difference between the longitude coordinate values of the corresponding nodes of the two road segments and the latitude coordinate values is simultaneously less than a set value, the average elevation and average of the mobile terminals traveling over the two road segments are extracted. Trajectory information of driving direction, video, and photo; or simultaneously calculating the connection relationship between the two road segments and their respective adjacent road segments, and marking and prompting, storing in a special dynamic road segment database; when the mobile terminal proposes a certain The cloud platform is stored in the special dynamic path when there is a specific path planning request The data in the database including the average elevation, the average driving direction, the video, the trajectory information of the photo or the connection relationship, and the corresponding path planning is calculated; then the average elevation, the average driving direction, the video, and the trajectory of the photo are calculated. The information or the connection relationship together with the mark and the prompt are sent to the mobile terminal together with the calculated path planning solution; the calculating the connection relationship means that each mobile terminal is accumulated in a certain direction on a certain road segment. The number of continuous trajectories formed when traveling across a node to an adjacent road segment during straight or cornering, when the value of the quantity, or the relative value of the quantity compared with the number of related trajectories falls within a setting Threshold When the value is obtained, it is confirmed that the two road segments have the junction point as the junction point and the connection direction in the direction in which the trajectory runs.
  28. The cloud platform of claim 15 wherein:
    The calculation of the corresponding path plan refers to the existing real-time path planning scheme of the terminal uploaded by the cloud platform according to the real-time upload of the mobile terminal, and the instantaneous dynamic impedance within a certain period of time of the involved road segment, and calculating a future designation. a predicted quantity of the mobile terminal on a specified road segment, and then, according to the predicted quantity, find some instantaneous dynamic impedance of the road segment stored in the cloud platform corresponding to the predicted quantity, and weight the some instantaneous dynamic impedance The average obtained value is the predicted dynamic impedance on a specified road segment at a specified time in the future, and then the predicted dynamic impedance is stored together with the corresponding time in the dynamic road segment database of the cloud platform; when a mobile terminal proposes a certain During a specific path planning, the cloud platform predicts a traffic congestion condition at a specified time and a specified road segment according to the predicted dynamic impedance, and uses the predicted dynamic impedance as one of the parameters, and according to other trajectory information in the cloud platform. Calculate a corresponding path plan.
PCT/CN2014/087686 2013-10-09 2014-09-28 Dynamic track navigation method and cloud platform WO2015051718A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201310466623.3 2013-10-09
CN201310466623.3A CN103557870B (en) 2013-10-09 2013-10-09 Dynamic trajectory navigation method and cloud platform

Publications (1)

Publication Number Publication Date
WO2015051718A1 true WO2015051718A1 (en) 2015-04-16

Family

ID=50012180

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2014/087686 WO2015051718A1 (en) 2013-10-09 2014-09-28 Dynamic track navigation method and cloud platform

Country Status (2)

Country Link
CN (1) CN103557870B (en)
WO (1) WO2015051718A1 (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109708654A (en) * 2018-12-29 2019-05-03 百度在线网络技术(北京)有限公司 A kind of paths planning method and path planning system

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103557870B (en) * 2013-10-09 2014-11-12 董路 Dynamic trajectory navigation method and cloud platform
IN2013MU03275A (en) * 2013-10-18 2015-07-03 Singh Puri Vikramjeet
CN103561070B (en) * 2013-10-25 2016-08-17 北京奇宝科技有限公司 Point out the carry-on location method and device that equipment arrives at the most on time, system
US9779606B2 (en) 2013-10-25 2017-10-03 Beijing Qihoo Technology Company Limited Methods, devices, and systems for prompting whether portable locator has arrived on time
CN104240500A (en) * 2014-08-25 2014-12-24 奇瑞汽车股份有限公司 Road condition information predicting method and system
CN104217109A (en) * 2014-09-01 2014-12-17 中国人民解放军国防科学技术大学 Method for realizing hybrid and active scheduling on quick satellites
CN104715628A (en) * 2014-12-23 2015-06-17 上海语镜汽车信息技术有限公司 Vehicle-mounted real-time road condition method and device based on positional relationship calculation
CN104501825B (en) * 2015-01-15 2017-07-25 刘畅 A kind of dynamic navigation method and equipment based on multidate information
CN104567908B (en) * 2015-01-22 2017-06-23 北京微车一族信息技术发展有限公司 It is a kind of can offline field driving digital map navigation method
CN105046983B (en) * 2015-08-14 2019-01-25 奇瑞汽车股份有限公司 A kind of traffic flow forecasting system and method based on bus or train route collaboration
CN105448088A (en) * 2015-11-20 2016-03-30 浪潮集团有限公司 Traffic condition monitoring method and system based big data
CN105547311A (en) * 2015-12-08 2016-05-04 深圳天珑无线科技有限公司 Route planning method, mobile terminal, and system
CN105446338B (en) * 2015-12-21 2017-04-05 福州华鹰重工机械有限公司 Cloud aids in automatic Pilot method and system
CN106023629B (en) * 2016-06-06 2018-12-25 西安电子科技大学昆山创新研究院 A kind of path recommended method and device
CN106840199B (en) * 2016-12-28 2019-07-09 北京市天元网络技术股份有限公司 A kind of calibration method and system of navigation of display data
CN106679685A (en) * 2016-12-29 2017-05-17 鄂尔多斯市普渡科技有限公司 Driving path planning method for vehicle navigation
CN107063281A (en) * 2017-04-12 2017-08-18 杨政超 Automobile navigation method, device and terminal
CN107221195B (en) * 2017-05-26 2020-03-17 重庆长安汽车股份有限公司 Automobile lane prediction method and lane level map
CN107192399B (en) * 2017-06-30 2020-02-18 Oppo广东移动通信有限公司 Navigation method, navigation device, storage medium and terminal
CN107146416B (en) * 2017-07-18 2020-01-21 深圳市锦粤达科技有限公司 Intelligent traffic management system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102385804A (en) * 2010-08-30 2012-03-21 谈宇清 Intelligent traffic system and navigation method thereof
WO2012094589A1 (en) * 2011-01-06 2012-07-12 Telenav, Inc. Navigation system with location adaptation and method of operation thereof
US20120303266A1 (en) * 2011-05-23 2012-11-29 Microsoft Corporation First waypoint distance
WO2012176973A1 (en) * 2011-06-22 2012-12-27 에스케이플래닛 주식회사 System and method for partially updating map data based on user's movement path, service apparatus and terminal apparatus thereof, and recording medium therefor
CN102853842A (en) * 2012-05-15 2013-01-02 董路 Navigation path planning method, apparatus, and system
CN103557870A (en) * 2013-10-09 2014-02-05 董路 Dynamic trajectory navigation method and cloud platform

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102735251B (en) * 2011-04-01 2014-12-17 深圳市赛格导航科技股份有限公司 Cloud computing based GPS navigation method and system
CN102436003A (en) * 2011-11-10 2012-05-02 浪潮电子信息产业股份有限公司 Cloud computing-based GPS (Global Positioning System) positioning method

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102385804A (en) * 2010-08-30 2012-03-21 谈宇清 Intelligent traffic system and navigation method thereof
WO2012094589A1 (en) * 2011-01-06 2012-07-12 Telenav, Inc. Navigation system with location adaptation and method of operation thereof
US20120303266A1 (en) * 2011-05-23 2012-11-29 Microsoft Corporation First waypoint distance
WO2012176973A1 (en) * 2011-06-22 2012-12-27 에스케이플래닛 주식회사 System and method for partially updating map data based on user's movement path, service apparatus and terminal apparatus thereof, and recording medium therefor
CN102853842A (en) * 2012-05-15 2013-01-02 董路 Navigation path planning method, apparatus, and system
CN103557870A (en) * 2013-10-09 2014-02-05 董路 Dynamic trajectory navigation method and cloud platform

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109708654A (en) * 2018-12-29 2019-05-03 百度在线网络技术(北京)有限公司 A kind of paths planning method and path planning system

Also Published As

Publication number Publication date
CN103557870B (en) 2014-11-12
CN103557870A (en) 2014-02-05

Similar Documents

Publication Publication Date Title
US10121366B2 (en) Method and system for modeling and processing vehicular traffic data and information and applying thereof
US10121382B2 (en) Data flow control order generating apparatus and sensor managing apparatus
US20180299290A1 (en) Lane-level vehicle navigation for vehicle routing and traffic management
US9983022B2 (en) Vehicle position estimation system, device, method, and camera device
US8731823B2 (en) Advanced map information delivery, processing and updating
Rahmani et al. Path inference from sparse floating car data for urban networks
CN102663887B (en) Implementation system and method for cloud calculation and cloud service of road traffic information based on technology of internet of things
US9672734B1 (en) Traffic aware lane determination for human driver and autonomous vehicle driving system
Davies et al. Scalable, distributed, real-time map generation
US20170069206A1 (en) Negative Image for Sign Placement Detection
Mathur et al. Parknet: drive-by sensing of road-side parking statistics
US9672735B2 (en) Traffic classification based on spatial neighbor model
He et al. Mapping to cells: a simple method to extract traffic dynamics from probe vehicle data
US9377313B2 (en) Methods and systems for creating digital street network database
CN105144259B (en) System is supervised and instructed in traffic
US9222786B2 (en) Methods and systems for creating digital transportation networks
US20160334236A1 (en) Context-based routing and access path selection
CN102147260B (en) Electronic map matching method and device
US10429201B2 (en) Collective vehicle traffic routing
US10223816B2 (en) Method and apparatus for generating map geometry based on a received image and probe data
CN107533800A (en) Cartographic information storage device, automatic Pilot control device, control method, program and storage medium
CN101964148B (en) Road traffic information recording server and GPS (Global Positioning System) user terminal
JP6094543B2 (en) Origin / Destination Extraction Device, Origin / Destination Extraction Method
US20120130625A1 (en) Systems and methods for determining traffic intensity using information obtained through crowdsourcing
CN100580735C (en) Real-time dynamic traffic information processing method based on car detecting technique

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14852596

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase in:

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 19/07/2016)

122 Ep: pct application non-entry in european phase

Ref document number: 14852596

Country of ref document: EP

Kind code of ref document: A1