CN104916155A - Real-time public transportation information service system - Google Patents
Real-time public transportation information service system Download PDFInfo
- Publication number
- CN104916155A CN104916155A CN201510263750.2A CN201510263750A CN104916155A CN 104916155 A CN104916155 A CN 104916155A CN 201510263750 A CN201510263750 A CN 201510263750A CN 104916155 A CN104916155 A CN 104916155A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- time
- real
- judgement
- data
- Prior art date
- Legal status (The legal status 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 status listed.)
- Granted
Links
Abstract
The invention discloses a real-time public transportation information service system, which comprises a service application programming interface, a data access interface, a vehicle arrival time prediction module, a vehicle arrival time prediction accuracy evaluation module, a real-time data processing module, an event statistics module and a vehicle real-time state monitoring module. Users query real-time public transportation information including the vehicle arrival time and the vehicle operating state through the service application programming interface. The real-time public transportation information service system disclosed by the invention processes abnormal conditions of vehicles in the public transportation service system, can carry out real-time processing on a great amount of public transportation information data quickly, and is high in efficiency. The abnormal conditions in real-time public transportation information are considered comprehensively, and queried vehicles and the operating states of all vehicles in the system are displayed in real time. Meanwhile, the real-time public transportation information service system has the advantages of accurate forecast for the arrival time of vehicles and quick query for the real-time public transportation information.
Description
Technical field
The present invention relates to intelligent transportation field, especially a kind of public communication information service system in real time.
Background technology
At intelligent transportation field, adopt real-time public communication information service system to significantly improve Level-of-Services of Public Transit, attract more passengers to adopt bus trip mode.Real-time public communication information service system is by processing in real time the geographic position data of bus timed sending, for the passenger waited in bus station provides real-time Bus information service, passenger can the relevant information of real-time query vehicle, as current location, distance is waited the distance of website, estimates the information such as the operation of vehicle is consuming time.
In the ground that bus sends in real time, position data has following features:
(1) data volume is large, and city bus quantity is many, and each car produced data every 20 seconds, and these data produced will be processed to provide information service in real time;
(2) data exception situation is many and complicated, vehicle-mounted positioning equipment is of a great variety, be subject to the multiple objective and unpredictable factor impact such as restriction, network signal of the precision of satnav, positioning equipment, cause the data that there are a large amount of abnormal conditions in data.
Existing real-time public communication information service system has the following disadvantages:
One is, cannot process in real time fast a large amount of position data;
Two are, consider comprehensive not for the abnormal problem in data.In real traffic circulation environment, can there are abnormal conditions in the traveling of bus, and as travelled not according to given line, or midway turns around to travel.Current existing real-time public communication information service system does not do too much design for the state of vehicle, the vehicle that this vehicle that some can be caused to be in abnormality is considered as normal operating condition is shown to user, cannot understand the overall state of all vehicles in whole system simultaneously.
Three are, the accuracy rate of the forecast of vehicle time of arrival should be appreciable, and the running status of system should be monitored, and system cloud gray model daily record should be analyzable, but existing real-time public communication information service system does not consider above problem comprehensively.
Summary of the invention
The technical problem to be solved in the present invention is the defect for existing in existing design, carries a kind of public communication information service system in real time.
For overcoming the defect existed in prior art; the technical scheme that the present invention takes is as follows: a kind of public communication information service system in real time, comprises attendant application DLL (dynamic link library), data access interface, vehicle prediction module time of arrival, vehicle predictablity rate time of arrival evaluation module, real time data processing module, event statistics module and vehicle real-time status monitoring module; Described attendant application DLL (dynamic link library) provides the passage of access system; described attendant application DLL (dynamic link library), vehicle prediction module time of arrival, vehicle predictablity rate time of arrival evaluation module, real time data processing module, event statistics module and vehicle real-time status monitoring module all interdepend with described data access interface and are connected, by this data access interface access system data storehouse; User is inquired about real-time Bus information by described attendant application DLL (dynamic link library); Wherein, described vehicle prediction module time of arrival, adopts several prediction algorithm, and runs in a distributed way, complete the prediction of vehicle time of arrival;
By described vehicle prediction module time of arrival, described vehicle predictablity rate time of arrival evaluation module, predicts that all the predicting the outcome produced is added up and verified in setting-up time, checking accuracy rate;
Described real time data processing module, receive uploaded by GPS by vehicle real time data, the every bar real time data uploaded carried out to the abnormal problem in pre-service, process real time data and be used in the state that the real time data after process upgrades vehicle;
Described event statistics module, records and adds up the various events that real-time public communication information service system occurs in operational process, and showing, in order to show the situation of described system cloud gray model with graphical interfaces;
Described vehicle real-time status monitoring module, monitors the real time data that vehicle is uploaded, and shows the real time status information of vehicle with graphical interfaces, in order to fully understand the real-time status of all vehicles;
The GPS real time data that described vehicle is uploaded comprises vehicle location coordinate, circuit number, car number, car status information; The extractible data of described system database comprise the car status information value of buffer memory, current time in system, car status information are updated the time, the position coordinates of the up and descending website of each circuit.
Further elaboration as to technique scheme:
In technique scheme, in described vehicle prediction module time of arrival, according to following formula predictions vehicle time of arrival:
Wherein, first website that described T (j|i) is current vehicle position front is i, and the prediction that vehicle arrives website j is consuming time; Described
for slave site i is to website i+1, the individual mean value consuming time of nearest m; Described
for slave site i is to website i+1, the kth reciprocal observed is individual consuming time; Described
for current vehicle position is to the distance of first website in front; If vehicle is just in time on certain website, this value is 0; Described
for website i is to the distance of website i+1; Described n is website sum.
In technique scheme, the real-time monitoring vehicle running status of described vehicle monitoring module, described travel condition of vehicle comprises off-line state, long-time stop same position state, determining target line state, determining target direction state and normal operating condition, vehicle original state is off-line state and is in the one in above-mentioned travel condition of vehicle all the time, the judgement of described vehicle off-line state is driven by user's inquiry request, described vehicle stops same position state for a long time, determining target line state, determining that the gps data that the judgement of target direction state and normal operating condition is uploaded by vehicle drives, and order judges as follows:
Step 1: receive the gps data that a vehicle is uploaded;
Step 2: judge whether vehicle-state is rest on same position for a long time;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 3: judge whether vehicle-state is determine target line;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 4: judge whether vehicle-state is determine target direction;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 5: judge whether vehicle-state is normal operation, after having judged, jumps to step 1, carries out the judgement of next gps data.
In technique scheme, the judgement of described vehicle off-line state is that vehicle does not upload gps data on the time span threshold values of setting.
In technique scheme, the judgement that described vehicle stops same position state for a long time comprises same position and the long-time judgement stopped, the judgement of described same position is that before and after vehicle, twice GPS elements of a fix error distance is less than or equal to twice GPS positioning error, described long-time stop judge the time span then having exceeded setting as stoppage of vehicle in the time of a certain position, and the judgement of described long-time stop carries out after the judgement of described same position.
In technique scheme, the target line of described vehicle is the circuit of the current operation of vehicle, described vehicle determining the judgement of target line state be position coordinates in the GPS data uploaded of vehicle not on the vehicle operating circuit of specifying, vehicle continues to upload continuous print gps data simultaneously.
In technique scheme; described vehicle target direction comprises the up of vehicle and down direction; described vehicle is determining that the judgement of target direction state is that the target line of vehicle is determined, up and down direction is uncertain and vehicle reports gps data continuously; The judgement of described vehicle normal operating condition is that the target line of vehicle has been determined and up and down direction in target line is also determined.
Compared with the existing technology, the invention has the beneficial effects as follows:
One is, processes in real time fast, high efficiency to large data;
Two are, consider the abnormal conditions in real-time Bus information comprehensively, and processing not according to given line traveling or the abnormal conditions such as traveling that turn around halfway the vehicle in traveling, shows the running status of all vehicles in enquiring vehicle and system in real time;
Three are, the accuracy rate of the forecast of vehicle time of arrival is high, and the running status of system is monitored in real time;
Four are, the inquiry of real-time Bus information fast, accurately.
Accompanying drawing explanation
Fig. 1 is system chart of the present invention.
Fig. 2 relies on annexation schematic diagram between each module of the present invention.
Fig. 3 is bus arrival time forecast model schematic diagram of the present invention.
Fig. 4 is travel condition of vehicle decision flow chart of the present invention.
Fig. 5 is vehicle off-line state decision flow chart in Fig. 4.
Fig. 6 is the process flow diagram that in Fig. 4, vehicle stops same position condition adjudgement for a long time.
Fig. 7 is the process flow diagram that in Fig. 4, target line condition adjudgement determined by vehicle.
Fig. 8 is the process flow diagram that in Fig. 4, target direction condition adjudgement determined by vehicle.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further detailed explanation.
Fig. 1-8 illustrates specific embodiments of the invention.
As Fig. 1, a kind of public communication information service system in real time, comprise attendant application DLL (dynamic link library) (AP services I) 1, data access interface 2, vehicle time of arrival (BAT:Bus Arrival Time) prediction module 3, vehicle time of arrival (BAT:Bus Arrival Time) predictablity rate evaluation module 6, real time data processing module 4, event statistics module 5 and vehicle real-time status monitoring module 7, described attendant application DLL (dynamic link library) (AP services I) 1 provides the passage of access system, as shown in Figure 2, described attendant application DLL (dynamic link library) 1, vehicle prediction module time of arrival 3, vehicle predictablity rate time of arrival evaluation module 6, real time data processing module 4, event statistics module 5 and vehicle real-time status monitoring module 7 all interdepend with described data access interface 2 and are connected, by this data access interface 2 access system data storehouse, and user inquires about real-time Bus information by described AP services I1.
Wherein: described vehicle time of arrival (BAT:Bus Arrival Time) prediction module 3; it comprises BAT and predicts that RPC (remote service interface) and BAT predicts nucleus module; adopt several prediction algorithm; and run in a distributed way; complete the prediction of vehicle time of arrival, its workflow is: a. user asks vehicle arrival time; B. vehicle location is obtained, to information such as waiting station distance, speed, real-time roads; C. information obtained in the previous step is brought into forecast model as parameter; D. will predict the outcome and return to user.
By described vehicle prediction module time of arrival 3, described vehicle predictablity rate time of arrival evaluation module 6, predicts that all predicting the outcome of generation is added up and verified in setting-up time, checking accuracy rate; This module work flow process is: a. analog subscriber request vehicle arrival time; B. the time of arrival obtaining corresponding requests predicts the outcome; C. time period when timing arrives to vehicle is actual from request is as true arrival time; D is after prediction after a while, and contrast predicts the outcome and legitimate reading, improves time prediction model.
Described real time data processing module 4, receive uploaded by GPS by vehicle real time data, the every bar real time data uploaded carried out to the abnormal problem in pre-service, process real time data and be used in the state that the real time data after process upgrades vehicle; Its concrete data handling procedure is: a. receiving real-time data stream; B. Data Analysis; C. data filtering; D. event monitoring (stop for a long time, and car etc.); E. circuit belonging to vehicle is calculated; F. up-downlink direction is calculated; G. vehicle site location is calculated.
Described event statistics module 5, records and adds up the various events that real-time public communication information service system occurs in operational process, and showing, in order to show the situation of described system cloud gray model with graphical interfaces.The various events occurred in real time data processing module all can send an event message to this module, and this module receives by event title, event description, event source after message, and generation time etc. are recorded.
Described vehicle real-time status monitoring module 7, monitors the real time data that vehicle is uploaded, and shows the real time status information of vehicle with graphical interfaces, and in order to fully understand the real-time status of all vehicles, and have trace playback, function got ready by map.
The GPS real time data that described vehicle is uploaded comprises vehicle location coordinate pos (it also comprised current position coordinates pos and position coordinates lastPos corresponding to a upper moment), circuit number lineID, car number BusID, car status information BusState; The extractible data of described system database comprise the car status information value BusState of buffer memory, current time in system curServerTime, car status information BusState are updated time updateTime, the position coordinates of the up and descending website of each circuit, and the form of expression of position coordinates is flex point sequence, it comprises up flex point sequence pointListUp and descending flex point sequence PointListDown.
Described attendant application DLL (dynamic link library) is suitable for most use scenes, be user's request is converted into corresponding http request, according to function and the parameter of request, call concrete service logic, in conjunction with the result calculated in real time and basic data, draw the result of needs.
Described data access interface, for have done one deck encapsulation on database, shields concrete Database details, provides the data access interface that general, shares between disparate modules.By this interface, can in advance by the Data import that needs to internal memory, improve access efficiency, reduction database access pressure.
Further elaboration as to above-described embodiment:
Model as shown in Figure 3, in the above-described embodiments, in described vehicle prediction module time of arrival 3, according to following formula predictions vehicle time of arrival:
Wherein, first website that described T (j|i) is current vehicle position front is i, and the prediction that vehicle arrives website j is consuming time; Described
for slave site i is to website i+1, the individual mean value consuming time of nearest m; Described
for slave site i is to website i+1, the kth reciprocal observed is individual consuming time; Described
for current vehicle position is to the distance of first website in front; If vehicle is just in time on certain website, this value is 0; Described
for website i is to the distance of website i+1; Described n is website sum.
In the above-described embodiments, described vehicle monitoring module 7 is monitoring vehicle running status in real time, native system defines following five kinds of travel condition of vehicle: off-line state, long-time stop same position state, determine target line state, determine target direction state and normal operating condition, the original state of each car is " off-line state ", and vehicle at any time all one of five kinds of shapes that can be in above-mentioned setting, and the state of vehicle can periodically upgrade.The judgement of described vehicle off-line state is driven by user's inquiry request, goes to detect vehicle and whether is in " off-line " state, often receive a gps data and will remove renewal vehicle-state when the status information of user's enquiring vehicle.As shown in Figure 4, described vehicle stops same position state for a long time, determines target line state, determines that the judgement of target direction state and normal operating condition is then that the gps data uploaded by vehicle drives, and judges by following sequencing step:
Step S101: receive the gps data that a vehicle is uploaded;
Step S102: judge whether vehicle-state is rest on same position for a long time;
If so, then jump to step S101, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step S103: judge whether vehicle-state is determine target line;
If so, then jump to step S101, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step S104: judge whether vehicle-state is determine target direction;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step S105: judge whether vehicle-state is normal operation, after having judged, jumps to step S101, carries out the judgement of next gps data.
It should be noted that, in the judgement of above-mentioned vehicle-state, except the judgement of off-line state, the judgement of the described travel condition of vehicle driven by gps data, the gps data that wherein in system, all vehicles are uploaded all comprises same data parameters, just in different decision processes, the parameter that system software is transferred is different, simultaneously, in the judgement of the above-mentioned travel condition of vehicle except off-line state, after a gps data uploaded by vehicle, system can carry out above-mentioned long-time stop same position state successively, determining target line state, determining the judgement of target direction state and normal operating condition, until determine the judgement that a kind of travel condition of vehicle just can carry out next travel condition of vehicle.
As Fig. 5, described vehicle off-line state is defined as: vehicle does not upload gps data on the time span threshold values of setting, and namely do not report gps data more than a time span threshold values (as 300 seconds), its decision method is as follows:
Step S201: the numbering (BusID) of user input query parameter vehicle;
Step S202: the car status information (BusState) extracting corresponding car number (BusID) from system database;
Step S203: judge whether car status information (BusState) is set to " off-line state ";
If so, step S207 is jumped to; Otherwise, jump to next step S204;
Step S204: obtain following 2 parameters from system database:
A, server current time curServerTime;
The time updatetime that b, car status information the last time is updated;
Step S205: the mistiming of two parameters in calculation procedure S204, and judge whether to meet a-b>300 second;
If so, step S206 is jumped to; Otherwise, jump to step S207;
Step S206: vehicle-state is set for " off-line state ", and the value revising car status information (BusState) is " off-line " state;
Step S207: the Query Result exporting car status information (BusState).
As shown in Figure 6; described vehicle stops in the judgement of same position state for a long time; the judging of described same position is defined as: GPS positioning error as A(unit as rice); distance d between the position coordinates pos that the vehicle location coordinate lastPos on vehicle in a real-time recorded data and current time extract from gps data is less than or equal to 2 times of GPS positioning errors; and 2 times of GPS positioning error statements judge the distance threshold values D of vehicle at same position; that is, D=2*A(unit is rice); Set a world length threshold values T, if vehicle has exceeded time threshold values T in the residence time of same position, then judged that vehicle is in and rest on same position for a long time; Represent that the judgement of described long-time stop is carried out after the judgement of described same position, the described concrete steps resting on the judgement of same position are for a long time as follows simultaneously:
Step S301: initialization 4 parameters: the time span threshold values T that the vehicle location coordinate lastPos on stoppage of vehicle start time tStart, vehicle in a real-time recorded data, judgement " rest on same position " for a long time, the distance threshold values D at same position is judged, initialization result is: tStart=Null, lastPos=NULL, T=300 second, D=20 meter, NULL represents empty;
Step S302: receive a gps data (these data record represents);
Step S303: obtain 2 parameters, the current time curServerTime of server and from record, extract position coordinates pos;
Step S304: judge whether to meet " tStart==NULL or lastPos==NULL ";
If so, step S310 is jumped to; Otherwise, carry out step S305;
Step S305: calculate the distance d between two position coordinates lastPos and pos;
Step S306: judge whether satisfy condition " d<=D ";
If so, step S307 is jumped to; Otherwise, carry out step S310;
Step S307: judge whether satisfy condition " curServerTime – tStart >=T ";
If so, step S308 is jumped to; Otherwise, carry out step S309;
Step S308: vehicle-state is set for " resting on same position for a long time "
Step S309: vehicle in " resting on same position for a long time " state, does not perform the judgement of other vehicle-states;
Step S310: to following two parameter assignment tStart=curServerTime, lastPos=pos, is set as next parameter judging vehicle-state by current location and present system time;
Step S311: judge whether satisfy condition " having judged that vehicle-state is rest on same position for a long time ";
If so, step S312 is jumped to; Otherwise, carry out step S309;
Step S312: receive next GPS data, carry out the judgement of vehicle-state.
As shown in Figure 7, the target line of described vehicle is the circuit of the current operation of vehicle, described vehicle is determining that the judgement of target line state is that position coordinates in the GPS data uploaded of vehicle is not on the vehicle operating circuit of specifying, vehicle continues to upload continuous print gps data simultaneously, and its concrete determining step is as follows:
Step S401: receive a gps data (these data record represents);
Step S402: extract 2 parameters from record, the circuit number lineId that the position coordinates pos of vehicle, vehicle report;
Step S403: take out 2 the flex point sequences (representing with coordinate in data) corresponding to corresponding line numbering lineId from system database: the flex point sequence pointListUp of vehicle up direction and the flex point sequence PointListDown of down direction;
Step S404: judging whether to satisfy condition coordinate pos can with the coordinate of flex point sequence on the circuit of one of pointListUp and pointListDown flex point sequence to mating;
If met, jump to step S405; Otherwise, carry out step S406;
Step S405: target line be can not determine by vehicle, arranges vehicle-state for " determining target line ", then performs step S407;
Step S406: vehicle is for being in " determining target line " state, and the target line arranging vehicle is numbered lineId, then performs step S408;
Step S407: receive next new GPS data, performs the judgement of vehicle-state;
Step S408: the judgement performing other vehicle-states.
As shown in Figure 8, described vehicle target direction comprises the up of vehicle and down direction, and described vehicle is determining that the judgement of target direction state is that the target line of vehicle is determined, up and down direction is uncertain and vehicle reports gps data continuously; The judgement of described vehicle normal operating condition is that the target line of vehicle has been determined and up and down direction in target line is also determined, the above-mentioned concrete steps judged as:
Step S501: the listing sequence poslist of initialization one vehicle location coordinate;
Step S502: receive a gps data (these data record represents);
Step S503: the position coordinates pos extracting vehicle from record, and pos is added to the afterbody of position coordinates list posList;
Step S504: judge whether the position coordinates number in position coordinates list posList is greater than 4;
If so, then step S505 is jumped to; Otherwise, then step S512 is jumped to;
Step S505: first position coordinates of delete position list of coordinates posList stem, and carry out step S507;
Step S506: take out following 3 parameters from system database, the flex point sequence pointListDown of the target line numbering targetLineId of vehicle, the flex point sequence pointListUp of target line up direction, target line down direction;
Step S507: judge whether to satisfy condition " in posList all coordinates can match circuit that pointListUp represents and direction is also mated ";
If met, then jump to step S508, otherwise jump to step S509;
Step S508: the target direction of vehicle is set for " up ", jumps to step S511 afterwards;
Step S509: judge whether to satisfy condition " in posList all coordinates can match circuit that pointListDown represents and direction is also mated ";
If met, then jump to step S510, otherwise jump to step S512;
Step S510: the target direction of vehicle is set for " descending ", jumps to step S511 afterwards;
Step S511: the state of vehicle is set for " normally running ", jumps to step S513 afterwards;
Step S512: target direction be can not determine by vehicle, arranges vehicle-state for " determining target direction ", jumps to step S513 afterwards;
Step S513: receive next gps data, judges the state of vehicle.
The above, it is only preferred embodiment of the present invention, the above not imposes any restrictions technical scope of the present invention, all above embodiment is done according to the technology of the present invention essence any amendment, equivalent variations and modification, all still belong in the scope of technical scheme of the present invention.
Claims (7)
1. a real-time public communication information service system, is characterized in that: comprise attendant application DLL (dynamic link library), data access interface, vehicle prediction module time of arrival, vehicle predictablity rate time of arrival evaluation module, real time data processing module, event statistics module and vehicle real-time status monitoring module; Described attendant application DLL (dynamic link library) provides the passage of access system; described attendant application DLL (dynamic link library), vehicle prediction module time of arrival, vehicle predictablity rate time of arrival evaluation module, real time data processing module, event statistics module and vehicle real-time status monitoring module all interdepend with described data access interface and are connected, and by this data access interface access system data storehouse; User is inquired about real-time Bus information by described attendant application DLL (dynamic link library);
Wherein, described vehicle prediction module time of arrival, adopts several prediction algorithm, and runs in a distributed way, complete the prediction of vehicle time of arrival;
By described vehicle prediction module time of arrival, described vehicle predictablity rate time of arrival evaluation module, predicts that all the predicting the outcome produced is added up and verified in setting-up time, checking accuracy rate;
Described real time data processing module, receive uploaded by GPS by vehicle real time data, the every bar real time data uploaded carried out to the abnormal problem in pre-service, process real time data and be used in the state that the real time data after process upgrades vehicle;
Described event statistics module, records and adds up the various events that real-time public communication information service system occurs in operational process, and showing, in order to show the situation of described system cloud gray model with graphical interfaces;
Described vehicle real-time status monitoring module, monitors the real time data that vehicle is uploaded, and shows the real time status information of vehicle with graphical interfaces, in order to fully understand the real-time status of all vehicles;
The GPS real time data that described vehicle is uploaded comprises vehicle location coordinate, circuit number, car number, car status information; The extractible data of described system database comprise the car status information value of buffer memory, current time in system, car status information are updated the time, the position coordinates of the up and descending website of each circuit.
2. the real-time public communication information service system of one according to claim 1, is characterized in that: in described vehicle prediction module time of arrival, according to following formula predictions vehicle time of arrival:
Wherein, first website that described T (j|i) is current vehicle position front is i, and the prediction that vehicle arrives website j is consuming time; Described
for slave site i is to website i+1, the individual mean value consuming time of nearest m; Described
for slave site i is to website i+1, the kth reciprocal observed is individual consuming time; Described
for current vehicle position is to the distance of first website in front, if vehicle is just in time on certain website, this value is 0; Described
for website i is to the distance of website i+1; Described n is website sum.
3. the real-time public communication information service system of one according to claim 1, it is characterized in that: the real-time monitoring vehicle running status of described vehicle monitoring module, described travel condition of vehicle comprises off-line state, long-time stop same position state, determining target line state, determining target direction state and normal operating condition, vehicle original state is off-line state and is in the one in above-mentioned travel condition of vehicle all the time, the judgement of described vehicle off-line state is driven by user's inquiry request, described vehicle stops same position state for a long time, determining target line state, determining that the gps data that the judgement of target direction state and normal operating condition is uploaded by vehicle drives, and order judges as follows:
Step 1: receive the gps data that a vehicle is uploaded;
Step 2: judge whether vehicle-state is rest on same position for a long time;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 3: judge whether vehicle-state is determine target line;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 4: judge whether vehicle-state is determine target direction;
If so, then jump to step 1, carry out the judgement of next gps data; Otherwise, just carry out the judgement of NextState;
Step 5: judge whether vehicle-state is normal operation, after having judged, jumps to step 1, carries out the judgement of next gps data.
4. the real-time public communication information service system of one according to claim 3, is characterized in that: the judgement of described vehicle off-line state is that vehicle does not upload gps data on the time span threshold values of setting.
5. the real-time public communication information service system of one according to claim 3, it is characterized in that: the judgement that described vehicle stops same position state for a long time comprises same position and the long-time judgement stopped, the judgement of described same position is that before and after vehicle, twice GPS elements of a fix error distance is less than or equal to twice GPS positioning error, described long-time stop judge the time span then having exceeded setting as stoppage of vehicle in the time of a certain position, and the judgement of described long-time stop is after the judgement of described same position.
6. the real-time public communication information service system of one according to claim 3, it is characterized in that: the target line of described vehicle is the circuit of the current operation of vehicle, described vehicle determining the judgement of target line state be position coordinates in the GPS data uploaded of vehicle not on the vehicle operating circuit of specifying, vehicle continues to upload continuous print gps data simultaneously.
7. the real-time public communication information service system of one according to claim 3, it is characterized in that: described vehicle target direction comprises the up of vehicle and down direction, described vehicle is determining that the judgement of target direction state is that the target line of vehicle is determined, up and down direction is uncertain and vehicle reports gps data continuously; The judgement of described vehicle normal operating condition is that the target line of vehicle has been determined and up and down direction in target line is also determined.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510263750.2A CN104916155B (en) | 2015-05-22 | 2015-05-22 | A kind of real-time public communication information service system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510263750.2A CN104916155B (en) | 2015-05-22 | 2015-05-22 | A kind of real-time public communication information service system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104916155A true CN104916155A (en) | 2015-09-16 |
| CN104916155B CN104916155B (en) | 2017-10-13 |
Family
ID=54085189
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510263750.2A Active CN104916155B (en) | 2015-05-22 | 2015-05-22 | A kind of real-time public communication information service system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104916155B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107945560A (en) * | 2017-12-21 | 2018-04-20 | 大连海事大学 | A kind of public transport smart electronics stop sign information display control method and system |
| CN108180922A (en) * | 2018-01-26 | 2018-06-19 | 百度在线网络技术（北京）有限公司 | A kind of navigation time assessment method, device, equipment and medium |
| CN108536438A (en) * | 2018-04-10 | 2018-09-14 | 武汉斗鱼网络科技有限公司 | Processing user behavior data gets module, method and computer-readable medium ready |
| CN109544947A (en) * | 2019-01-08 | 2019-03-29 | 重庆交通大学 | Calculation method of intersection delay based on track of vehicle reconstruct under monitoring scene |
| CN110796866A (en) * | 2019-11-09 | 2020-02-14 | 郑州天迈科技股份有限公司 | Communication kilometer data clearing method for bus intelligent regulation system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020069017A1 (en) * | 1995-08-14 | 2002-06-06 | Schmier Kenneth J. | Public transit vehicle arrival information system |
| CN1447128A (en) * | 2003-02-18 | 2003-10-08 | 何征 | Communication method for locating buses in real time and implemented system |
| JP2006079544A (en) * | 2004-09-13 | 2006-03-23 | Sumitomo Electric Ind Ltd | Travel time providing method, device, and program |
| CN1963847A (en) * | 2005-11-07 | 2007-05-16 | 同济大学 | Method for forecasting reaching station of bus |
| CN102708701A (en) * | 2012-05-18 | 2012-10-03 | 中国科学院信息工程研究所 | System and method for predicting arrival time of buses in real time |
| CN103106702A (en) * | 2012-12-20 | 2013-05-15 | 青岛海信网络科技股份有限公司 | Bus trip service system based on cloud computing |
| CN103680129A (en) * | 2013-12-06 | 2014-03-26 | 深圳先进技术研究院 | Method and system for monitoring operation of public transport vehicle |
| CN103778778A (en) * | 2013-12-19 | 2014-05-07 | 银江股份有限公司 | Rapid bus station service information system and rapid bus arrival information measuring and calculating method |
-
2015
- 2015-05-22 CN CN201510263750.2A patent/CN104916155B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020069017A1 (en) * | 1995-08-14 | 2002-06-06 | Schmier Kenneth J. | Public transit vehicle arrival information system |
| CN1447128A (en) * | 2003-02-18 | 2003-10-08 | 何征 | Communication method for locating buses in real time and implemented system |
| JP2006079544A (en) * | 2004-09-13 | 2006-03-23 | Sumitomo Electric Ind Ltd | Travel time providing method, device, and program |
| CN1963847A (en) * | 2005-11-07 | 2007-05-16 | 同济大学 | Method for forecasting reaching station of bus |
| CN102708701A (en) * | 2012-05-18 | 2012-10-03 | 中国科学院信息工程研究所 | System and method for predicting arrival time of buses in real time |
| CN103106702A (en) * | 2012-12-20 | 2013-05-15 | 青岛海信网络科技股份有限公司 | Bus trip service system based on cloud computing |
| CN103680129A (en) * | 2013-12-06 | 2014-03-26 | 深圳先进技术研究院 | Method and system for monitoring operation of public transport vehicle |
| CN103778778A (en) * | 2013-12-19 | 2014-05-07 | 银江股份有限公司 | Rapid bus station service information system and rapid bus arrival information measuring and calculating method |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107945560A (en) * | 2017-12-21 | 2018-04-20 | 大连海事大学 | A kind of public transport smart electronics stop sign information display control method and system |
| CN108180922A (en) * | 2018-01-26 | 2018-06-19 | 百度在线网络技术（北京）有限公司 | A kind of navigation time assessment method, device, equipment and medium |
| CN108180922B (en) * | 2018-01-26 | 2021-10-12 | 百度在线网络技术（北京）有限公司 | Navigation time evaluation method, device, equipment and medium |
| CN108536438A (en) * | 2018-04-10 | 2018-09-14 | 武汉斗鱼网络科技有限公司 | Processing user behavior data gets module, method and computer-readable medium ready |
| CN109544947A (en) * | 2019-01-08 | 2019-03-29 | 重庆交通大学 | Calculation method of intersection delay based on track of vehicle reconstruct under monitoring scene |
| CN110796866A (en) * | 2019-11-09 | 2020-02-14 | 郑州天迈科技股份有限公司 | Communication kilometer data clearing method for bus intelligent regulation system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104916155B (en) | 2017-10-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104916155A (en) | Real-time public transportation information service system | |
| Sun et al. | Predicting bus arrival time on the basis of global positioning system data | |
| JP5374067B2 (en) | Traffic condition simulation apparatus and program | |
| US9240124B2 (en) | Traffic-volume prediction device and method | |
| US8332084B1 (en) | Four-dimensional weather predictor based on aircraft trajectory | |
| CN104520912B (en) | Blocking prediction means, blocking prognoses system, blocking Forecasting Methodology and program | |
| Liu et al. | Dynamic shared autonomous taxi system considering on-time arrival reliability | |
| CN103699120B (en) | Fault diagnosis system for special vehicle | |
| CN107944797A (en) | The monitoring method of transport task, apparatus and system | |
| CN111462484A (en) | Congestion state determination method, device, equipment and computer readable storage medium | |
| WO2014125802A1 (en) | New road detection logic | |
| CN108074415A (en) | A kind of vehicle destination Forecasting Methodology and system based on user behavior | |
| CN113537584B (en) | Patrol task conflict processing method and device, electronic equipment and storage medium | |
| CN106228799A (en) | The method and apparatus monitoring illegal tampering vehicle positional information | |
| CN107195177A (en) | Based on Forecasting Methodology of the distributed memory Computational frame to city traffic road condition | |
| EP3450919A1 (en) | Route estimation apparatus and route estimation method | |
| CN103065466A (en) | Detection method of and detection device for abnormal traffic conditions | |
| CN105575155A (en) | Method and equipment for determining vehicle driving information | |
| CN112434260A (en) | Road traffic state detection method and device, storage medium and terminal | |
| Abidin et al. | Towards improved vehicle arrival time prediction in public transportation: integrating SUMO and Kalman filter models | |
| CN109945880B (en) | Path planning method, related equipment and readable storage medium | |
| US20190088116A1 (en) | Predicting vehicle travel times by modeling heterogeneous influences between arterial roads | |
| CN105489010A (en) | System and method for monitoring and analyzing fast road travel time reliability | |
| CN116758723B (en) | Vehicle transportation monitoring method, system and medium | |
| CN112799950A (en) | Background service load capacity test system and method, storage medium and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB03 | Change of inventor or designer information |
Inventor after: Zhou Yong Inventor after: Han Yunfei Inventor after: Peng Xianbin Inventor after: Lin Dong Inventor after: Bai Xue Inventor before: Zhou Yong Inventor before: Han Yunfei |
|
| COR | Change of bibliographic data | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |