This application is a 371 US nationalization of PCT Patent Application No. PCT/CN2020/105798, filed Jul. 30, 2020, which claims the benefit of and priority to Chinese Patent Application No. 202010530549.7, filed Jun. 11, 2020. The entire content of the aforementioned patent applications is incorporated herein by reference.
The disclosure relates to a speed measurement system, and further relates to a multi-geomagnetic sensor speed measurement system and a speed measurement method using the same.
With the increase in car ownership, traffic accidents and traffic jams are frequent and intelligent management of traffic is imperative. Intelligent traffic systems are the main means of intelligent management of traffic, and information collection technology is widely used in intelligent traffic systems. The vehicle speed measurement system is an indispensable part of the intelligent traffic system, as it measures the speed of vehicles on the road and provides traffic data for the intelligent traffic system. The intelligent traffic system can identify speeding vehicles and give warnings to speeding vehicles after obtaining speed information, thus avoiding traffic accidents caused by speeding vehicles and thus improving traffic safety.
Conventional vehicle speed measurement systems currently in use at home and abroad use optical, microwave radar, inductive coil and geomagnetic sensors to collect traffic data, and the controller analyses the data to obtain the speed of the vehicle. However, optical sensors have high environmental requirements and can affect speed measurement in bad weather such as haze; inductive coil sensors have a short life span; when there are multiple vehicles driving side by side in the same direction, or when there are large vehicles passing in adjacent lanes, speed measurement systems using microwave radar and traditional geomagnetic sensors are prone to not detecting vehicles or incorrectly detecting vehicles, resulting in speed measurement errors. Conventional vehicle speed measurement systems lack practicality, reliability, safety and are too limited to meet the requirements of large-scale deployment.
The purpose of the disclosure is to propose a multi-geomagnetic sensor speed measurement system and a speed measurement method thereof in order to improve the accuracy of speed measurement and promote the intelligent development of highways, in view of the above-mentioned shortcomings of the prior art.
To achieve the above purpose, the disclosure discloses a multi-geomagnetic sensors speed measurement system comprising a geomagnetic vehicle detection module, a data transmission module, a data reception module and a backend data processing module, the geomagnetic vehicle detection module being wired to the data transmission module, the data transmission module being wirelessly connected to the data reception module, and the data reception module being wired to the backend data processing module.
The multi-geomagnetic sensor speed measurement system comprises number M of geomagnetic vehicle detection modules, and the geomagnetic vehicle detection modules are deployed in groups along the roadside, wherein every two or more geomagnetic vehicle detection modules are grouped together. Each geomagnetic vehicle detection module comprises a group of geomagnetic sensors and a controller. The geomagnetic sensors are used to collect magnetic field data from the road surface. Adjacent geomagnetic sensors are spaced by d meters. The controller is used to receive data collected by the geomagnetic sensors, to analyze the temporal data used by the vehicles passing the geomagnetic vehicle detection module and to transmit the temporal data to the data transmission module at intervals which can be set to x seconds or y minutes, depending on actual requirements.
The data transmission module receives the temporal data using a wireless transmitter and sends it to the data reception module by wireless communication.
The data reception module receives the temporal data reported by the data transmission module using a wireless transmitter and transmits it to the backend data processing module.
The backend data processing module is used for processing the temporal data. The processing comprises aligning the acquired data, matching the temporal data with the corresponding vehicle to each other and calculating the speed of the vehicle as it passes the group of geomagnetic sensors based on the aligned data.
The speed measurement method of the disclosure using a multi-geomagnetic sensor speed measurement system comprises the steps of:
The disclosure has the following advantages over the prior art.
Firstly, it can effectively avoid the problem of incorrect vehicle speed measurement caused by not detecting a vehicle or detecting a vehicle as multiple vehicles.
Conventional sensor speed measurement schemes generally have disadvantages that make it difficult to meet the reliability and safety requirements in scenarios with complex and changing traffic conditions. The disclosure can effectively avoid the problem of vehicle speed measurement errors caused by vehicles not being detected or by detecting one vehicle as multiple vehicles due to data cleaning and data alignment operations.
Secondly, the disclosure uses multi-geomagnetic sensors to collect road data, and makes full use of the advantages of multiple sensors to co-ordinate the results of each sensor for speed estimation using the minimum variance method to improve accuracy, which is more advantageous and practical for vehicle speed measurement.
Thirdly, the disclosure uses geomagnetic sensors which are low cost and easy to deploy on a large scale, and the geomagnetic sensors do not react to non-ferromagnetic objects, so they can be effective with less interference.
Fourthly, the inventive system is less affected by environmental factors and can still work normally in rainy or foggy weather.
Embodiments of the disclosure are further described below in conjunction with the accompanying drawings.
Referring to
Referring to
Step 1, collecting the geomagnetic data of the vehicle passing for threshold detection processing using the geomagnetic vehicle detection module 1 to obtain temporal data which comprises data on the time spent for the vehicle to approach and leave the geomagnetic sensor 11. The step of collecting the geomagnetic data of the vehicle passing for threshold detection processing using the geomagnetic vehicle detection module 1 comprises the following steps:
When a vehicle passes the detection area of the geomagnetic sensor 11, the magnetic flux in the detection area of the geomagnetic sensor 11 changes dramatically and the change in magnetic flux is reflected in a corresponding increase or decrease in the output data of the geomagnetic sensor 11. By deploying the geomagnetic sensor module 1 alongside the road, the changes in the output data of the geomagnetic sensor 11 can be used to detect the passage of vehicles in real time. The geomagnetic sensor 11 transmits the output data to the controller 12 of the geomagnetic vehicle detection module 1;
If the geomagnetic data from sensor 11 is above the high geomagnetic data threshold Th1, then it is continuously determined whether the incoming data is above the high geomagnetic data threshold for a period of time Δt; if yes, it is recorded by a timer and then step 1.4) is performed, if not, it is determined to be interference from an adjacent reverse lane and no recording is performed; and
If the geomagnetic data from geomagnetic sensor 11 is below the high geomagnetic data threshold Th1, then it is determined that the vehicle is not close to the geomagnetic sensor 11 and no processing is performed;
The values of the high geomagnetic threshold Th1 and the time thresholds Δt are based on the actual waveform results obtained from the field test;
If the geomagnetic data from geomagnetic sensor 11 is below the low geomagnetic data threshold Th2, then continue to determine if the incoming data is below the low geomagnetic data threshold for a period of time Δt; if yes, it is recorded by a timer, if not, it is determined that the vehicle has not left the detection area of the geomagnetic sensor 11 and no recording is performed; and
If the geomagnetic data from geomagnetic sensor 11 is higher than the low geomagnetic data threshold Th2, the vehicle is considered to not having left the geomagnetic sensor 11 and continues to wait until the geomagnetic data from the geomagnetic sensor 11 is below the low geomagnetic data threshold Th2;
The value of the low geomagnetic threshold Th2 is based on the waveform results obtained from actual tests in the field.
Step 2, merging the temporal data into a group of data using the geomagnetic vehicle detection module 1. The merged temporal data is sent by the data transmission module 2 to the data reception module 3 which sends the temporal data to the backend processing module 4.
The geomagnetic vehicle detection module 1 combines temporal data into a group of data, meaning that the temporal data over a period of time is merged into a group of data, which can be set to x seconds or y minutes.
Step 3, performing a data cleaning process on the received temporal data using the backend processing module 4. The step of performing a data cleaning process on the received temporal data using the backend processing module 4 comprises the following steps:
Step 4, regrouping the temporal data after data cleaning using the backend processing module 4.
The temporal data after data cleaning is regrouped using the backend processing module 4 so that the value of the a-th group of data is in turn the a-th temporal data in each group of temporal data.
Step 5, selecting a reference sensor for the same group of temporal data using the backend processing module 4 and creating individual time windows. The step of selecting a reference sensor for the same group of temporal data using the backend processing module 4 and creating individual time windows comprises the following steps:
milliseconds and d is the interval between adjacent geomagnetic sensors 11, and v is the road speed limit value, where {circumflex over (t)}i, 1 is the measurement time of the i-th geomagnetic sensor 11 in each group the corresponding to the time when the first vehicle passes, where the i-th geomagnetic sensor 11 is the reference sensor for the j-th geomagnetic sensor 11.
Step 6, performing the processing accordingly based on the number of temporal data in the time window using the backend processing module 4.
Step 7, setting a measurement threshold δ when there is a plurality of temporal data corresponding in the time window and merging the temporal data based on the measurement threshold δ. The step of setting the measurement threshold δ and merging the temporal data based on the measurement threshold δ comprises the following steps:
If the measurement threshold δ has not been obtained, the geomagnetic sensor 11 is placed beside the road to record the output waveform generated by the geomagnetic sensor 11 when the vehicle passes the geomagnetic sensor 11 in the case of a vehicle being detected as multiple vehicles. The difference data of adjacent detection times is obtained by waveform analysis. The operation is repeated several times. A Gaussian distribution model
is established based on the difference data, where σ is the standard deviation, μ is the mean value, and the measurement threshold δ is taken as f(x=μ−3σ); and
If the difference between adjacent temporal data is less than the measurement threshold δ, the temporal data with the smallest value is retained and the other temporal data are deleted;
If the difference between the adjacent temporal data is not less than the measurement threshold δ, the temporal data closest in value to the temporal data of the reference sensor is retained and the other temporal data is deleted.
Step 8, confirming that a mis-detection has occurred is when there is no temporal data corresponding in the time window, i.e. the vehicle passes but is not detected, and the mis-detection data is compensated by interpolation. The step of compensating the mis-detection data by interpolation comprises the following steps:
Performing different interpolations at a position in the convoy using the backend processing module 4 based on the temporal data {circumflex over (t)}j, k;
If {circumflex over (t)}j, k is the temporal data for the middle of the convoy, the compensation formula is:
If {circumflex over (t)}j, k is the temporal data at the end of the convoy, the compensation formula is:
If {circumflex over (t)}j, k is the temporal data at the head of the convoy, the compensation formula is:
where {circumflex over (t)}i, k is the measurement time of the k-th vehicle in each group passing the i-th geomagnetic sensor 11 in each group, and {circumflex over (t)}j, k is the measurement time of the k-th vehicle in each group passing the j-th geomagnetic sensor 11 in each group, and {circumflex over (t)}j, 1 is the measurement time of the first vehicle in each group passing the j-th geomagnetic sensor 11 in each group, and similarly {circumflex over (t)}j, k−1 is the measurement time of the k−1-th vehicle in each group passing the j-th geomagnetic sensor 11 in each group, and {circumflex over (t)}i, 1 is the measurement time of the first vehicle in each group passing the i-th geomagnetic sensor 11 in each group, and {circumflex over (t)}j, k+1, {circumflex over (t)}j, k−2, {circumflex over (t)}i, k−1, {circumflex over (t)}i, k−2, {circumflex over (t)}i, 2, {circumflex over (t)}i, 3, {circumflex over (t)}j, 2, {circumflex over (t)}j, 3 and so on.
Step 9, determining that the data is correct at this time when there is a temporal data correspondence in the time window. Determining whether each group of data has been data aligned after getting the data alignment result according to step 5 to step 8, if yes, then perform step 10, if not, then perform step 5.
Step 10, estimating the speed of the vehicle using the minimum variance method based on the alignment results, and calculating the speed of the vehicle.
The vehicle speed is estimated from the alignment results using the minimum variance method, i.e. the speed is calculated using the following equation:
where vk is the speed of the k-th vehicle, and xk0 is the position of the k-th vehicle at moment 0. Setting the position of the first geomagnetic sensor 11 in each group of geomagnetic sensors 11 as the origin. {circumflex over (t)}i, k is the measurement time when the i-th vehicle corresponding to the k-th geomagnetic sensor 11 in each group of geomagnetic sensors 11 passes, and Li is the distance from the i-th geomagnetic sensor 11 to the origin.
The foregoing is only a preferred embodiment of The disclosure and is not intended to limit The disclosure. It is clear that any professional in the field, after understanding the content and principles of The disclosure, may make various modifications and changes in form and detail without departing from the principles and structure of The disclosure, but these modifications and changes based on the ideas of The disclosure are still within the scope of protection of the claims of The disclosure.
Number | Date | Country | Kind |
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202010530549.7 | Jun 2020 | CN | national |
Filing Document | Filing Date | Country | Kind |
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PCT/CN2020/105798 | 7/30/2020 | WO |
Publishing Document | Publishing Date | Country | Kind |
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WO2021/248655 | 12/16/2021 | WO | A |
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