CN102779411A - Method for automatically acquiring road grade - Google Patents
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Abstract
The invention discloses a method for automatically acquiring a road grade and belongs to the technical field of the intelligent transportation. The method comprises the following steps of: acquiring running track information of a vehicle by a vehicle-mounted equipment sensor; processing the running track information to obtain grade information of a specific longitude and latitude position; and by map matching, outputting the grade information onto the position of the vehicle on a road. According to the invention, pitch angle information of the vehicle is acquired by the vehicle-mounted equipment sensor and the urban road grade value is obtained by data processing and map matching. The obtained road grade information data is important basis of establishing an energy consumption model, is also an important factor of the running environment of the vehicle and can provide data support for the calculation of other traffic parameters.
Description
Technical field
The present invention relates to the intelligent transport technology field, relate in particular to a kind of method of obtaining road grade automatically.
Background technology
Along with energy-saving and emission-reduction become the theme of transport development, the demand of setting up a real-time microcosmic monitoring urban road energy consumption model is more and more urgent.With CMEM, MOVES model is representative, is present main stream approach based on the model developing method of automotive power demand variable.Especially be independent of motor vehicle specific power (VSP) variable of car weight; The advantage that had both kept the physical model in automobile engineering field; Having reduced the complicacy that model gos deep into parameter again, be applicable to the linking of traffic parameter, is oil consumption discharging Study of model and application direction.
Motor vehicle specific power (Vehicle Specific Power; VSP) physical significance is a motor vehicle Moving Unit quality power demand, and it equals kinetic energy change, potential variation, overcome the road friction, overcome the ratio of air resistance four aspect power demand summations and vehicular gross combined weight.After simplifying, VSP can change into the function of travel speed, acceleration and road grade.Road grade is difficult to directly measure through portable set or mobile unit as an important parameters.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of method of obtaining road grade automatically, realize obtaining automatically of road grade.
The invention provides a kind of method of obtaining road grade automatically, comprising:
Through the driving trace information of mobile unit sensor acquisition vehicle, driving trace information is handled, obtain the grade information of concrete longitude and latitude position, through map match, said grade information is outputed to vehicle on the position of road.
The present invention comes collection vehicle angle of pitch information through the mobile unit sensor, and obtains the urban road value of slope through data processing and map match.The road grade information data that obtains is to set up the important foundation of energy consumption model, also is a key factor of the running environment of vehicle simultaneously, and the data support can be provided for the calculating of some other traffic parameter.
Description of drawings
Fig. 1 is the synoptic diagram of longitudinal gradient in the embodiment of the invention;
Fig. 2 is the synoptic diagram of minimum longitudinal gradient in the embodiment of the invention;
The method flow diagram that obtains road grade automatically that Fig. 3 provides for the embodiment of the invention;
The method flow diagram of Fig. 4 in the embodiment of the invention driving trace information being handled;
Fig. 5 is a synoptic diagram of selecting the running mean window in the embodiment of the invention;
Fig. 6 is the method flow diagram of map match in the embodiment of the invention;
Fig. 7 is the synoptic diagram based on the data after the processing of embodiment of the invention method and Google's database elevation map contrast.
Embodiment
For making the object of the invention, technical scheme and advantage clearer, the present invention is made further detailed description below in conjunction with accompanying drawing.
The embodiment of the invention is come collection vehicle angle of pitch information through the mobile unit sensor, and obtains the urban road value of slope through data processing and map match.
For the ease of understanding the embodiment of the invention, at first introduce the several notions in the real-time road condition information delivery system:
Longitudinal gradient: refer to the ratio of the discrepancy in elevation with its horizontal range of same slope section point-to-point transmission on the route vertical section, represent with percent.As shown in Figure 1, longitudinal gradient=a/b*100%=tan (Θ) * 100%.
Maximum longitudinal grade: be the ruling grade value that highway allow to adopt, the factor of confirming maximum longitudinal grade has natural causes such as kinematic behavior, road quality classification and landform, weather, the sea level elevation of automobile, and its value should meet table 1 regulation.
Table 1
Simultaneously, design rate is the highway of 120km/h, 100km/h, 80km/h, when receiving the restriction of topographic condition or other special circumstances, can increase by 1% through technical and economic proof maximum longitudinal grade value; Design rate is the highway section that utilizes original highway of 40km/h, 30km/h, 20km/h in the highway reconstruction, and through technical and economic proof, the maximum longitudinal grade value can increase by 1%; More the mountain range route goes up a slope or the descending highway section continuously, and when relative relief was 200-500m, average gradient should be greater than 5.5%, and average gradient should be greater than 5% during greater than 500m for relative relief, and the average gradient in 3km highway section should be not big by 5.5% continuously arbitrarily.
Minimum longitudinal gradient: be the minimum grade value that highway allows employing.When the road bed of laying track or road surface was lower than natural opposite, roadbed constituted with digging mode, and this roadbed is cutting, and is as shown in Figure 2.In the long cutting highway section of highways at different levels, and the not smooth highway section of other cross drainages, all should adopt to be not less than 0.3% longitudinal gradient, do the longitudinal drainage design otherwise tackle its gutter.The highway section that arid area and cross drainage are good, its minimum longitudinal gradient can not receive above-mentioned restriction.
Fig. 3 is the method flow diagram that obtains road grade automatically that the embodiment of the invention provides, and may further comprise the steps:
Table 2
| The data code name | Note |
| latitude | The volume coordinate of collection point, latitudinal coordinate under the wgs84 coordinate, unit: degree |
| longitude | The volume coordinate of collection point, the coordinate of longitudinal under the wgs84 coordinate, unit: degree |
| altitude | The volume coordinate of collection point, the coordinate of elevation direction under the wgs84 coordinate, unit: rice |
| speed | Gather vehicle speed unit; Meter per second |
| roc | The vehicle luffing angle, unit-Du, the car body horizontal attitude is calculated relatively |
As shown in Figure 4, may further comprise the steps:
Step 3021, the angle of pitch information that collects is changed into the standard format longitudinal gradient value in " highway technical standard ".As shown in table 3, use formula tan (RADIANS (roc)), in the formula, roc is meant the vehicle luffing angle, unit-Du, the car body horizontal attitude is calculated relatively; RADIANS is a function, is radian with a numerical value or a Parameters Transformation of representing angle, and angle of pitch information is converted into the longitudinal gradient value.
Table 3
Step 3022, the longitudinal gradient value that obtains is screened by the maximum longitudinal grade value and the minimum longitudinal gradient value of " highway technical standard " lining, wash the longitudinal gradient value and exceed 9% data.The maximum compressional wave value that from table 1, can find out Class IV highway is 9%, exceeds 9% longitudinal gradient Value Data so will clean.
Step 3023, use running mean are handled the longitudinal gradient value after cleaning.The running mean formula is following:
Wherein, MA
[i]Be the sample set after the running mean, N is a moving window, s
[i+j]It is the sample set that to do running mean.
The ultimate principle of running mean is to eliminate the irregular variation in the sequence through moving window, thereby reflects trend.Running mean has level and smooth effect to former sequence, make that the fluctuation up and down of former sequence has been weakened, and window is big more, and is strong more to the smoothing effect of ordered series of numbers.Running mean can smoothly be fallen the influence of unusual fluctuation to data.But running mean also has problems when utilization, and the smooth effect of window (the being N) fluctuation of increasing running mean is better, and logarithm becomes insensitive in the border factually but can make as a result.
Select the window of running mean according to Fig. 5,, kept details simultaneously again 100 to be the variation tendency that window can well reflect data.
Map match is a kind of location modification method based on software engineering, and its basic thought is with the road network informational linkage in vehicle location track and the numerical map, confirms the accurate position of vehicle in the map road network thus.The embodiment of the invention is used nearest neighbor method; The vertical range that the vehicle track points that GPS is detected arrives a certain road chain is as the foundation of judging matching degree; The shorter explanation of the vertical range track points that track points arrives a certain road chain is near more from this road chain, and the possibility of both couplings is just big more.
As shown in Figure 6, the concrete execution in step of map-matching algorithm is following:
The latitude and longitude coordinates information of the flight path data point that step 3031, acquisition GPS detect.
The embodiment of the invention is set forth gradient Realization of Identification from data acquisition, data processing, three aspects of map match: at first, and through the angle of pitch information of mobile unit sensor acquisition vehicle in driving trace; Subsequently the data (longitude and latitude, elevation, speed, angle of pitch information etc.) that collect are carried out data scrubbing and data processing, draw the grade information of concrete longitude and latitude position; At last, for the data of handling well, the map-matching algorithm through design outputs to vehicle on the position of road with gps data, thereby the road grade that obtains road network distributes.The road grade information data that obtains is to set up the important foundation of energy consumption model, also is a key factor of the running environment of vehicle simultaneously, and the data support can be provided for the calculating of some other traffic parameter.
Can find out that through Fig. 7 the information that collects conforms to actual geographical information trend basically,, can find out that the flex point that the gradient rises and falls also is accurately simultaneously through scene photograph.
In a word, the above is merely preferred embodiment of the present invention, is not to be used to limit protection scope of the present invention.
Claims (6)
1. a method of obtaining road grade automatically is characterized in that, comprising:
Through the driving trace information of mobile unit sensor acquisition vehicle, said driving trace information is handled, obtain the grade information of concrete longitude and latitude position, through map match, said grade information is outputed to vehicle on the position of road.
2. the method for obtaining road grade automatically according to claim 1 is characterized in that, said driving trace information comprises: the latitude and longitude coordinates of vehicle, angle of pitch information, elevation and speed.
3. the method for obtaining road grade automatically according to claim 2 is characterized in that, saidly driving trace information is carried out processed steps specifically comprises:
The angle of pitch information that collects is changed into standard format longitudinal gradient value;
The longitudinal gradient value that obtains is screened by maximum longitudinal grade value and minimum longitudinal gradient value, wash the longitudinal gradient value and exceed 9% data;
Use running mean that the longitudinal gradient value after cleaning is handled.
4. the method for obtaining road grade automatically according to claim 3 is characterized in that, saidly longitudinal gradient value after cleaning is carried out processed steps specifically comprises:
Wherein, MA
[i]Be the sample set after the running mean, N is a moving window, s
[i+j]It is the sample set that to do running mean.
5. according to claim 2, the 3 or 4 described methods of obtaining road grade automatically, it is characterized in that the step of said map match specifically comprises:
Obtain the latitude and longitude coordinates information of the flight path data point of driving trace;
Collect all interior road chains of said flight path data point close region as candidate road chain, and put into candidate road chain and concentrate;
Travel through said candidate road chain collection, judge the matching degree of current road chain and said flight path data point;
Inspection candidate road chain collection, the road chain that said flight path data point is projected on the chain elongation line of road excludes candidate road chain collection;
Choose residue candidate road chain and concentrate the highest road chain of matching degree, be set at the coupling road chain of said flight path data point;
Obtain the projection coordinate of said flight path data point on the chain of said coupling road, said projection coordinate is replaced the former latitude and longitude coordinates value of said flight path data point as correct latitude and longitude value.
6. the method for obtaining road grade automatically according to claim 5 is characterized in that, the step of the matching degree of said judgement current road chain and said flight path data point is specially:
Calculate the vertical range of said flight path data point, the matching degree height that distance is short to current road chain.
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Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104916133A (en) * | 2015-06-09 | 2015-09-16 | 福建工程学院 | Road altitude information extraction method and system based on traffic track data |
| CN105608985A (en) * | 2015-12-24 | 2016-05-25 | 东南大学 | Enhanced digital vector map production method with road longitudinal gradient |
| CN106548651A (en) * | 2017-01-17 | 2017-03-29 | 吉林大学 | A kind of On-line testing method of vehicle traveling road ahead fine information |
| CN106767883A (en) * | 2016-12-15 | 2017-05-31 | 清华大学苏州汽车研究院（吴江） | Map datum including road grade data generates system and method in real time |
| CN107560599A (en) * | 2017-09-04 | 2018-01-09 | 清华大学 | A kind of road grade data processing method of feature based point sampling and curve matching |
| CN107727045A (en) * | 2017-09-30 | 2018-02-23 | 福建农林大学 | Road radius of horizontal curve measuring method based on wheelpath |
| CN107990909A (en) * | 2016-10-27 | 2018-05-04 | 千寻位置网络有限公司 | A kind of test method and its system of simulated roadway position data |
| CN108803625A (en) * | 2018-08-09 | 2018-11-13 | 北京智行者科技有限公司 | A kind of running method |
| CN109118939A (en) * | 2017-06-23 | 2019-01-01 | 薛富盛 | Dimensional topography map and preparation method thereof |
| CN109910888A (en) * | 2019-03-04 | 2019-06-21 | 浙江吉利汽车研究院有限公司 | A kind of vehicle descending control method, device and equipment |
| CN111354100A (en) * | 2020-02-28 | 2020-06-30 | 西南交通大学 | Quantitative analysis method for key factors of truck oil consumption based on trajectory data |
| CN111831960A (en) * | 2020-07-10 | 2020-10-27 | 北京交通大学 | Dynamic load measuring and calculating method of internet wagon based on gradient disturbance identification and elimination |
| CN111882872A (en) * | 2020-07-17 | 2020-11-03 | 北京交通大学 | Road slope measuring and calculating method and device based on large-scale internet vehicle power distribution |
| CN112304281A (en) * | 2019-07-30 | 2021-02-02 | 厦门雅迅网络股份有限公司 | Road slope measuring method, terminal equipment and storage medium |
| CN112527930A (en) * | 2020-11-19 | 2021-03-19 | 深圳大学 | Pedestrian road gradient information extraction method based on smart phone |
| CN112945195A (en) * | 2021-01-26 | 2021-06-11 | 北京讯腾智慧科技股份有限公司 | Method and device for measuring gradient of track bridge during passing of train |
| CN113091708A (en) * | 2021-04-06 | 2021-07-09 | 中山大学 | Road subsection gradient estimation method and system based on multi-sample GPS quality control data |
| CN115331430A (en) * | 2022-07-14 | 2022-11-11 | 中通客车股份有限公司 | Intelligent network vehicle-connected road spectrum acquisition and analysis method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6009374A (en) * | 1995-10-24 | 1999-12-28 | Mitsubishi Denki Kabushiki Kaisha | Apparatus for and method of controlling vehicular systems while travelling |
| CN101349570A (en) * | 2007-07-20 | 2009-01-21 | 爱信艾达株式会社 | Navigation apparatus and program for navigation |
| JP2009236714A (en) * | 2008-03-27 | 2009-10-15 | Toyota Motor Corp | Gradient information calculation device, vehicle cruise controller, and navigation system |
| CN100578152C (en) * | 2006-08-25 | 2010-01-06 | 北京航空航天大学 | Heuristic path culculating method for treating large scale floating vehicle data |
| CN102622879A (en) * | 2011-01-26 | 2012-08-01 | 株式会社日立制作所 | Traffic information providing apparatus |
-
2012
- 2012-08-10 CN CN2012102855912A patent/CN102779411A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6009374A (en) * | 1995-10-24 | 1999-12-28 | Mitsubishi Denki Kabushiki Kaisha | Apparatus for and method of controlling vehicular systems while travelling |
| CN100578152C (en) * | 2006-08-25 | 2010-01-06 | 北京航空航天大学 | Heuristic path culculating method for treating large scale floating vehicle data |
| CN101349570A (en) * | 2007-07-20 | 2009-01-21 | 爱信艾达株式会社 | Navigation apparatus and program for navigation |
| JP2009236714A (en) * | 2008-03-27 | 2009-10-15 | Toyota Motor Corp | Gradient information calculation device, vehicle cruise controller, and navigation system |
| CN102622879A (en) * | 2011-01-26 | 2012-08-01 | 株式会社日立制作所 | Traffic information providing apparatus |
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| CN104916133A (en) * | 2015-06-09 | 2015-09-16 | 福建工程学院 | Road altitude information extraction method and system based on traffic track data |
| CN105608985A (en) * | 2015-12-24 | 2016-05-25 | 东南大学 | Enhanced digital vector map production method with road longitudinal gradient |
| CN107990909A (en) * | 2016-10-27 | 2018-05-04 | 千寻位置网络有限公司 | A kind of test method and its system of simulated roadway position data |
| CN107990909B (en) * | 2016-10-27 | 2021-05-25 | 千寻位置网络有限公司 | Test method and system for simulating road position data |
| CN106767883A (en) * | 2016-12-15 | 2017-05-31 | 清华大学苏州汽车研究院（吴江） | Map datum including road grade data generates system and method in real time |
| CN106548651A (en) * | 2017-01-17 | 2017-03-29 | 吉林大学 | A kind of On-line testing method of vehicle traveling road ahead fine information |
| CN109118939A (en) * | 2017-06-23 | 2019-01-01 | 薛富盛 | Dimensional topography map and preparation method thereof |
| CN109118939B (en) * | 2017-06-23 | 2022-02-18 | 薛富盛 | Three-dimensional topographic map and manufacturing method thereof |
| CN107560599B (en) * | 2017-09-04 | 2020-05-12 | 清华大学 | Road gradient data processing method based on feature point sampling and curve fitting |
| CN107560599A (en) * | 2017-09-04 | 2018-01-09 | 清华大学 | A kind of road grade data processing method of feature based point sampling and curve matching |
| CN107727045A (en) * | 2017-09-30 | 2018-02-23 | 福建农林大学 | Road radius of horizontal curve measuring method based on wheelpath |
| CN107727045B (en) * | 2017-09-30 | 2019-10-18 | 福建农林大学 | Road radius of horizontal curve measurement method based on wheelpath |
| CN108803625A (en) * | 2018-08-09 | 2018-11-13 | 北京智行者科技有限公司 | A kind of running method |
| CN108803625B (en) * | 2018-08-09 | 2021-07-23 | 北京智行者科技有限公司 | Driving method |
| CN109910888A (en) * | 2019-03-04 | 2019-06-21 | 浙江吉利汽车研究院有限公司 | A kind of vehicle descending control method, device and equipment |
| CN112304281A (en) * | 2019-07-30 | 2021-02-02 | 厦门雅迅网络股份有限公司 | Road slope measuring method, terminal equipment and storage medium |
| CN111354100A (en) * | 2020-02-28 | 2020-06-30 | 西南交通大学 | Quantitative analysis method for key factors of truck oil consumption based on trajectory data |
| CN111831960B (en) * | 2020-07-10 | 2021-11-16 | 北京交通大学 | Dynamic load measuring and calculating method of internet wagon based on gradient disturbance identification and elimination |
| CN111831960A (en) * | 2020-07-10 | 2020-10-27 | 北京交通大学 | Dynamic load measuring and calculating method of internet wagon based on gradient disturbance identification and elimination |
| CN111882872A (en) * | 2020-07-17 | 2020-11-03 | 北京交通大学 | Road slope measuring and calculating method and device based on large-scale internet vehicle power distribution |
| CN111882872B (en) * | 2020-07-17 | 2021-08-17 | 北京交通大学 | Road slope measuring and calculating method and device based on large-scale internet vehicle power distribution |
| CN112527930A (en) * | 2020-11-19 | 2021-03-19 | 深圳大学 | Pedestrian road gradient information extraction method based on smart phone |
| CN112527930B (en) * | 2020-11-19 | 2023-11-03 | 深圳大学 | Pedestrian road network road gradient information extraction method based on smart phone |
| CN112945195A (en) * | 2021-01-26 | 2021-06-11 | 北京讯腾智慧科技股份有限公司 | Method and device for measuring gradient of track bridge during passing of train |
| CN113091708A (en) * | 2021-04-06 | 2021-07-09 | 中山大学 | Road subsection gradient estimation method and system based on multi-sample GPS quality control data |
| CN115331430A (en) * | 2022-07-14 | 2022-11-11 | 中通客车股份有限公司 | Intelligent network vehicle-connected road spectrum acquisition and analysis method and system |
| CN115331430B (en) * | 2022-07-14 | 2024-03-08 | 中通客车股份有限公司 | Intelligent network-connected vehicle road spectrum acquisition and analysis method and system |
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Application publication date: 20121114 |