CN102779411A - Method for automatically acquiring road grade - Google Patents

Abstract

The invention discloses a method for automatically acquiring road slopes, which belongs to the technical field of intelligent transportation. The method includes: collecting vehicle track information through on-board equipment sensors, processing the track information to obtain slope information at a specific latitude and longitude position, and outputting the slope information to the position of the vehicle on the road through map matching. The invention collects vehicle pitch angle information through a vehicle-mounted device sensor, and obtains an urban road gradient value through data processing and map matching. The obtained road slope information data is an important basis for establishing an energy consumption model, and it is also an important factor of the vehicle's driving environment, which can provide data support for the calculation of other traffic parameters.

Description

The Method of Obtaining Road Slope Automatically

technical field

The invention relates to the technical field of intelligent transportation, in particular to a method for automatically acquiring road gradients.

Background technique

As energy conservation and emission reduction become the theme of transportation development, the need to establish a real-time micro-monitoring model of urban road energy consumption is becoming more and more urgent. Represented by CMEM and MOVES models, the model development method based on motor vehicle power demand variables is currently the mainstream method. In particular, the vehicle specific power (VSP) variable, which is independent of vehicle weight, not only retains the advantages of the physical model in the field of automotive engineering, but also reduces the complexity of the model's in-depth parameters. It is suitable for the connection of traffic parameters and is the key to fuel consumption and emission models. Research and application direction.

The physical meaning of vehicle specific power (Vehicle Specific Power, VSP) is the power required to move the unit mass of the vehicle, which is equal to the sum of the power required for four aspects of kinetic energy change, potential energy change, overcoming road friction, and overcoming air resistance and the total mass of the vehicle. Compare. After simplification, VSP can be transformed into a function of driving speed, acceleration and road gradient. As an important parameter, road slope is difficult to be directly measured by portable devices or vehicle-mounted devices.

Contents of the invention

In view of this, the object of the present invention is to provide a method for automatically acquiring road gradients, so as to realize automatic acquisition of road gradients.

The invention provides a method for automatically obtaining road gradient, comprising:

The track information of the vehicle is collected by the on-board equipment sensor, and the track information is processed to obtain the slope information of the specific latitude and longitude position, and the slope information is output to the position of the vehicle on the road through map matching.

The invention collects vehicle pitch angle information through a vehicle-mounted device sensor, and obtains an urban road gradient value through data processing and map matching. The obtained road slope information data is an important basis for establishing an energy consumption model, and it is also an important factor of the vehicle's driving environment, which can provide data support for the calculation of other traffic parameters.

Description of drawings

Fig. 1 is the schematic diagram of longitudinal slope in the embodiment of the present invention;

Fig. 2 is the schematic diagram of minimum longitudinal slope in the embodiment of the present invention;

Fig. 3 is the flow chart of the method for automatically obtaining road gradient provided by the embodiment of the present invention;

Fig. 4 is a flowchart of a method for processing driving track information in an embodiment of the present invention;

Fig. 5 is the schematic diagram that selects sliding average window in the embodiment of the present invention;

FIG. 6 is a flowchart of a method for map matching in an embodiment of the present invention;

Fig. 7 is a schematic diagram of comparing the processed data with the Google database elevation map based on the method of the embodiment of the present invention.

Detailed ways

In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings.

In the embodiment of the present invention, the vehicle pitch angle information is collected by the vehicle-mounted device sensor, and the urban road slope value is obtained through data processing and map matching.

In order to facilitate the understanding of the embodiments of the present invention, several concepts in the real-time road condition information release system are first introduced:

Longitudinal slope: refers to the ratio of the height difference between two points on the same slope section on the longitudinal section of the route to its horizontal distance, expressed as a percentage. As shown in Figure 1, longitudinal slope=a/b*100%=tan(Θ)*100%.

Maximum longitudinal slope: It is the maximum slope value allowed by the highway. Factors determining the maximum longitudinal slope include the vehicle’s dynamic characteristics, road grade, and natural factors such as terrain, climate, and altitude. Its value should meet the requirements in Table 1.

Table 1

At the same time, when expressways with design speeds of 120km/h, 100km/h, and 80km/h are restricted by terrain conditions or other special circumstances, the maximum longitudinal slope value can be increased by 1% after technical and economic demonstration; the design speed in highway reconstruction is 40km /h, 30km/h, and 20km/h sections using the original highway, the maximum longitudinal slope value can be increased by 1% after technical and economic demonstration; when the cross-ridge route is continuously uphill or downhill, the relative height difference is 200-500m , the average longitudinal slope should not be greater than 5.5%, the average longitudinal slope should not be greater than 5% when the relative height difference is greater than 500m, and the average longitudinal slope of any continuous 3km section should not be greater than 5.5%.

Minimum vertical slope: It is the minimum slope value allowed by the road. When the subgrade surface of the laid track or road surface is lower than the natural opposite side, the subgrade is formed by excavation, and this kind of subgrade is a road cutting, as shown in Figure 2. Longitudinal cut sections of highways at all levels and other sections with poor lateral drainage shall adopt a longitudinal slope of not less than 0.3%, otherwise longitudinal drainage shall be designed for the side ditches. In arid areas and road sections with good lateral drainage, the minimum longitudinal slope may not be subject to the above restrictions.

Fig. 3 is the flow chart of the method for automatically obtaining road slope provided by the embodiment of the present invention, comprising the following steps:

Step 301 , collecting the driving track information of the vehicle through the vehicle-mounted device sensor. Including: vehicle longitude and latitude coordinates, pitch angle, elevation, speed and other information. The sampling data is explained in Table 2 below:

Table 2

Data Code Notes latitude The spatial coordinates of the collection point, the coordinates in the latitude direction under the wgs84 coordinates, unit: degree longitude The spatial coordinates of the collection point, the coordinates in the longitude direction under wgs84 coordinates, unit: degree altitude The spatial coordinates of the collection point, the coordinates of the elevation direction under wgs84 coordinates, unit: meter speed Acquisition vehicle speed unit; m/s roc Vehicle pitch angle, unit - degree, relative to the calculation of the horizontal attitude of the vehicle body

Step 302, process the driving track information to obtain the slope information of the specific latitude and longitude position.

As shown in Figure 4, the following steps are included:

Step 3021, transform the collected pitch angle information into the standard format longitudinal slope value in "Technical Standards for Highway Engineering". As shown in Table 3, the formula tan(RADIANS(roc)) is used. In the formula, roc refers to the pitch angle of the vehicle, in units of degrees, calculated relative to the horizontal attitude of the vehicle body; RADIANS is a function that takes a value or parameter representing the angle Convert to radians to convert pitch angle information into longitudinal slope values.

table 3

Step 3022: Filter the obtained longitudinal slope values according to the maximum longitudinal slope value and the minimum longitudinal slope value in the "Technical Standards for Highway Engineering", and clean out the data whose longitudinal slope value exceeds 9%. It can be seen from Table 1 that the maximum longitudinal wave value of the fourth-grade highway is 9%, so the longitudinal slope value data exceeding 9% should be cleaned.

Step 3023, use the moving average to process the cleaned longitudinal slope value. The moving average formula is as follows:

${\mathrm{<span\; class="notranslate">\; MA</span>}}_{<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ]</span>}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; N</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{<span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; ]</span>}$

Among them, MA _[i] is the sample set after sliding average, N is the sliding window, and s _[i+j] is the sample set that needs to be averaged.

The basic principle of moving average is to eliminate the irregular changes in the sequence by moving the window, so as to reflect the trend. The moving average has a smoothing effect on the original sequence, which weakens the up and down fluctuations of the original sequence, and the larger the window, the stronger the smoothing effect on the sequence. The moving average can smooth out the influence of abnormal fluctuations on the data. However, there are also problems in the application of the sliding average. Increasing the window of the sliding average (that is, N) has a better smoothing effect on fluctuations, but it will make the results insensitive to the actual changes in the data.

According to Figure 5, the sliding average window is selected, and the window of 100 can not only reflect the changing trend of the data well, but also retain the details.

Step 303 , output the slope information to the position of the vehicle on the road through the map matching algorithm. After obtaining the longitudinal slope value information, it is necessary to use the map matching algorithm to map the GPS data to the position of the vehicle on the road, so as to obtain the road gradient distribution of the road network. In the actual vehicle navigation system, due to various factors such as GPS positioning error, coordinate system conversion error and road electronic map accuracy error, the vehicle trajectory curve often deviates from the actual driving road on the navigation electronic map. The basic idea of map matching is to link the vehicle trajectory with the road network information in the digital map, and thus determine the exact position of the vehicle in the map road network, so that the longitudinal slope information can be corresponding to the accurate latitude and longitude points.

Map matching is a positioning correction method based on software technology. Its basic idea is to link the vehicle positioning trajectory with the road network information in the digital map, thereby determining the exact position of the vehicle in the map road network. The embodiment of the present invention uses the nearest neighbor method, and uses the vertical distance from the vehicle track point detected by GPS to a certain road link as the basis for judging the matching degree. The closer the link is, the more likely it is that the two will match.

As shown in Figure 6, the specific execution steps of the map matching algorithm are as follows:

Step 3031, obtaining the latitude and longitude coordinate information of the track data points detected by the GPS.

Step 3032: Collect all the links in the adjacent area (within a radius of 50 meters) as candidate links and put them into the set of candidate links.

Step 3033: Traversing the set of candidate links, judging the degree of matching between the current link and the track data point according to the nearest neighbor criterion: calculate the vertical distance from the track data point to the current link, and the shorter the distance, the higher the matching degree.

Step 3034 , check the set of candidate links, and exclude the links whose track data points are projected on the extension line of the links from the set of candidates. If the track data point is on the extension line of the link, then the track data point (that is, the corresponding latitude and longitude coordinate point) is far away from the link, and it is impossible to fall on the link. This link needs to be excluded. .

Step 3035: Select the link with the highest matching degree (ie the shortest distance) from the remaining candidate link set, and determine it as the matching link of the track data point.

Step 3036: Obtain the projection coordinates of the track data points on the matching road links, and use the coordinates to correct the longitude and latitude coordinates of the track data points. Use the projected coordinates on the matching road link as the correct latitude and longitude values to replace the original latitude and longitude coordinates.

The embodiments of the present invention describe the realization of slope recognition from three aspects: data collection, data processing, and map matching: first, the pitch angle information of the vehicle in the driving track is collected through the on-board device sensor; then the collected data (longitude and latitude , elevation, speed, pitch angle information, etc.) for data cleaning and data processing, to obtain the slope information of the specific latitude and longitude position; finally, for the processed data, through the designed map matching algorithm, the GPS data is output to the vehicle on the road. position, so as to obtain the road slope distribution of the road network. The obtained road slope information data is an important basis for establishing an energy consumption model, and it is also an important factor of the vehicle's driving environment, which can provide data support for the calculation of other traffic parameters.

It can be seen from Figure 7 that the collected information is basically consistent with the actual geographical information trend, and at the same time, through the on-site photos, it can be seen that the inflection point of the slope fluctuation is also accurate.

In a word, the above descriptions are only preferred embodiments of the present invention, and are not intended to limit the 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:

${\mathrm{MA}}_{\left[i\right]}=\frac{1}{N}\underset{j=0}{\overset{N-1}{\mathrm{\&Sigma;}}}{s}_{[i+j]}$

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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