CN113129603B - Parallel road overspeed determination method, device, terminal and storage medium - Google Patents
Parallel road overspeed determination method, device, terminal and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device, a terminal and a storage medium for judging overspeed of a parallel road, wherein the method comprises the following steps: s1, determining whether the road section where the target vehicle is located is a parallel road or not; s2, if the road is a parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road; and S3, when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road, calculating the running probability of the target vehicle on each road, and outputting an overspeed estimation result. Through the mode, the driving probability of the vehicle on each road in the parallel roads is calculated, the speed of the vehicle is compared with the speed limit of each road, and then the driving probability and the comparison result are output so as to judge the possibility of overspeed driving of the vehicle.
Description
Technical Field
The present application relates to the field of vehicle driving safety technologies, and in particular, to a method, an apparatus, a terminal, and a storage medium for determining an overspeed on a parallel road.
Background
With the increasing perfection of highway traffic, vehicles running on a highway are more and more, racing behavior happens occasionally, and the phenomenon of vehicle overspeed is rare. Meanwhile, various traffic cases related to vehicle speeding often occur. Therefore, the supervision and management of over-speed of road vehicles is becoming an increasingly important issue for traffic control departments.
At present, vehicle-mounted terminals on the market have an overspeed reminding function, however, in overspeed judgment, overspeed of a common single road is easy to judge, but for parallel roads with short distance or overhead roads which can be driven up and down, the problem of inaccurate positioning may occur to vehicle-mounted equipment, so that it is impossible to determine which road the vehicle is driven on, and the speed limit on the parallel roads may be different, so that the overspeed judgment result is not necessarily accurate, and finally a false alarm is generated.
Disclosure of Invention
The application provides a method, a device, a terminal and a storage medium for judging overspeed of a parallel road, which aim to solve the problem that the judgment of overspeed running of vehicles on the existing parallel road is not accurate enough
In order to solve the technical problem, the application adopts a technical scheme that: provided is a parallel road overspeed determination method, including: s1, determining whether the road section where the target vehicle is located is a parallel road or not; s2, if the road is a parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road; and S3, when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road, calculating the running probability of the target vehicle on each road, and outputting an overspeed estimation result.
As a further improvement of the present application, the calculating of the traveling probability of the target vehicle on each road includes: s31, acquiring a driving rating label value of a driver corresponding to the target vehicle; and S32, obtaining the driving probability by combining the driving rating label value, the speed of the target vehicle and the speed limit value of each road in the parallel roads.
As a further refinement of the present application, the driver driving rating label value is computationally generated based on analyzing historical driving behavior data of the driver including over-speed, hard-acceleration, hard-deceleration, and sharp-turn.
As a further improvement of the application, historical driving behavior data is continuously updated, and a driver driving rating label value is dynamically calculated and generated.
As a further improvement of the present application, before step S32, the method further includes: acquiring real-time traffic information of each road in parallel roads, and screening out the road in a congestion or slow running state and the real-time traffic speed of the road; and if the speed of the target vehicle is higher than the real-time traffic speed of the road in the congestion or slow traffic state, determining that the running probability of the target vehicle on the road is zero.
As a further improvement of the present application, step S1 is preceded by: extracting roads and road information in the road network data from a map search engine; and according to the road information, calibrating the roads with the same road passing direction, parallel relation and road spacing within the preset threshold range as the parallel roads.
As a further improvement of the present application, step S1 is preceded by: and acquiring track points of the target vehicle, and matching the road section with the shortest foot distance with the current driving direction of the track points as the road section where the target vehicle is located.
In order to solve the above technical problem, another technical solution adopted by the present application is: provided is a parallel road overspeed determination device comprising: the road section determining module is used for determining whether the road section where the target vehicle is located is a parallel road or not; the speed comparison module is used for comparing the speed of the target vehicle with the speed limit value of each road in the parallel roads when the road section where the target vehicle is located is the parallel road; and the judgment calculation module is used for calculating the running probability of the target vehicle on each road and outputting an overspeed estimation result when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a terminal comprising a processor, a memory coupled to the processor, the memory having stored therein program instructions that, when executed by the processor, cause the processor to perform the steps of the method for determining a speed limit of a parallel road according to any one of the above.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a storage medium storing a program file capable of implementing any one of the above-described parallel road overspeed determination methods.
The beneficial effect of this application is: the method for judging the overspeed of the parallel road comprises the steps of obtaining the speed of a target vehicle when the target vehicle is determined to run on the parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road, calculating the running probability of the target vehicle on each road when the speed of the target vehicle is determined to be between the minimum speed limit value and the maximum speed limit value of each road in the parallel road, confirming the overspeed condition of the target vehicle on each road according to the comparison result of the speed of the target vehicle and the speed limit values of each road, and finally outputting the running probability and the overspeed condition for a background manager to judge whether the target vehicle is overspeed or not, wherein the method effectively assists the background manager to judge the overspeed of the vehicle running in the parallel road area so that the background manager can timely and accurately judge the overspeed of the running vehicle no matter which road section the running vehicle is located, therefore, the reminding and the management and control can be performed in time under the condition of overspeed.
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Fig. 1 is a flowchart illustrating a method for determining a parallel road overspeed according to an embodiment of the present invention;
fig. 2 is a functional block diagram of a parallel road overspeed determining apparatus of an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a terminal according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a storage medium according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indications (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are only used to explain the relative positional relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Fig. 1 is a flowchart illustrating a method for determining a parallel road overspeed according to an embodiment of the present invention. It should be noted that the method of the present application is not limited to the flow sequence shown in fig. 1 if the results are substantially the same. As shown in fig. 1, the method comprises the steps of:
and step S1, determining whether the road section where the target vehicle is currently located is a parallel road.
It should be noted that the parallel roads in this embodiment include an upper and lower parallel road (such as a viaduct) and a left and right parallel road (such as a main road and a sub road belonging to one road), and when it is necessary to determine whether the target vehicle is overspeed, it is first necessary to determine whether the road segment where the target vehicle is currently located is the parallel road; if the speed limit value is not the parallel road, directly comparing the speed limit value of the current road with the speed of the target vehicle to determine whether the target vehicle is overspeed; if the road is a parallel road, step S2 is executed.
Further, before performing the overspeed determination on the parallel road, it is necessary to construct road network information in advance, and calibrate the parallel road, and therefore, in this embodiment, step S1 includes:
1. and extracting roads and road information in the road network data from a map search engine.
Specifically, the map search engine may be one or more of a Baidu map, a Google map, an Tencent map, and the like, and extracts road and road information from road network data of the map search engine, where the road information includes attribute information of roads, traffic directions, hierarchical relationships, distances between adjacent roads, and the like, it should be noted that the attribute information of roads includes attributes of overpasses, main roads, attributes of auxiliary roads, and the like, and the map search engine only sets attributes of a certain road, but who is a main relationship and an auxiliary relationship, and who is an overhead relationship, and is not calibrated.
2. And according to the road information, calibrating the roads with the same road passing direction, parallel relation and road spacing within the preset threshold range as the parallel roads.
Specifically, for roads in a left-right parallel relationship and an up-down parallel relationship, whether the roads are parallel roads is determined according to a traffic direction between the roads and a distance between the roads, and the roads with the same traffic direction, the left-right parallel relationship and the road distance within a preset threshold range are marked as the parallel roads, wherein the preset threshold is preset, for example, within a range of 10 meters, an existing a viaduct is provided, a distance between a road B below the a viaduct and the a viaduct is 5 meters, and the two roads are in the same driving direction, and then the a viaduct and the B road are marked as a group of parallel roads. It should be understood that, when parallel road calibration is performed, every time parallel road calibration is performed, two adjacent roads are determined based on adjacent roads, and therefore, a situation that one parallel road region includes multiple sets of two parallel roads may exist in a final calibration result.
Further, before the overspeed determination is performed on the target vehicle, it is necessary to confirm the road section area where the target vehicle is currently located, and therefore, in this embodiment, step S1 includes:
and acquiring a track point of the target vehicle, and matching the road section with the shortest foot distance as the current road section of the target vehicle, wherein the driving direction of the road section is consistent with the current driving direction of the track point.
Specifically, when the target vehicle needs to be subjected to overspeed judgment, the track point of the target vehicle is subjected to road grabbing processing, specifically: the method comprises the steps of carrying out spatial road network data search on track points, scanning all road section information in a certain range of the track points, matching according to the foot hanging distance and the driving direction of the track points from each road section, and taking the road section which is always in the driving direction of the track points and has the shortest distance with the foot hanging distance of the track points as the current road section where a target vehicle is located.
And step S2, if the road is a parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road.
Specifically, after the current road section of the target vehicle is confirmed, if the current road section does not include a parallel road, the road section only includes one road, and whether the target vehicle is overspeed can be judged by directly comparing the speed limit value of the road with the vehicle speed of the target vehicle.
If the current road section is a parallel road, the road section comprises two roads, and the speed limit value of each road is compared with the speed of the target vehicle, so that the relation between the speed of the target vehicle and the speed limit value of each road can be confirmed; if the speed of the target vehicle is lower than the minimum speed limit value in each road, the target vehicle is not overspeed when running on any road; if the speed of the target vehicle is higher than the maximum speed limit value in each road, the target vehicle is overspeed when running on any road; if the vehicle speed is between the minimum speed limit and the maximum speed limit on each road, step S3 is executed.
In this embodiment, the vehicle speed of the target vehicle may be calculated from the track points extracted during road holding.
And step S3, when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road, calculating the running probability of the target vehicle on each road, and outputting the overspeed estimation result.
Specifically, when the vehicle speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value in each road, it is described that the target vehicle may travel on the road with a higher speed limit value without overspeed or may travel on the road with a lower speed limit value with overspeed.
Further, the step S3 of calculating the driving probability of the target vehicle on each road specifically includes:
and step S31, acquiring the driving rating label value of the driver corresponding to the target vehicle.
It should be noted that the driving rating label value is a rating grading model established for reflecting the historical driving behavior of the driver, and is generated based on the historical driving behavior data of the analyzed driver including overspeed, sharp acceleration, sharp deceleration and sharp turning. For example, when the driving behavior of the driver such as speeding, rapid acceleration, rapid deceleration, and sharp turning occurs frequently, it is indicated that the driving behavior of the driver is aggressive, and the speeding behavior is easy to occur, and when the driving behavior of the driver such as speeding, rapid acceleration, rapid deceleration, and sharp turning occurs a small amount, it is indicated that the driving behavior of the driver is cautious, and the speeding behavior is not easy to occur, therefore, in this embodiment, the number of times the speeding behavior occurs in the driver's historical driving behavior within the preset time interval is analyzed, and then the driving behavior of the driver is subjected to stability rating and quantization, for example, the driving rating can be divided into: aggressive driving (overspeed prone), normal driving (occasional overspeed), cautious driving (minimal overspeed), conservative driving (no overspeed never), for each driving rating, it corresponds to a preset driving rating label value, for example: the driving rating label value corresponding to the aggressive driving type is 0.8, the driving rating label value corresponding to the ordinary driving type is 0.5, the driving rating label value corresponding to the cautious driving type is 0.3, and the driving rating label value corresponding to the conservative driving type is 0.1.
Further, in order to improve the accuracy of the driver driving rating, in the present embodiment, the historical driving behavior data is continuously updated, and the driver driving rating tag value is dynamically calculated and generated.
Specifically, overspeed, rapid acceleration, rapid deceleration and rapid turning times behavior data of the vehicle are collected and counted in real time, so that data in the grading model are updated, and the driving grading label value of the driver is dynamically calculated based on the model preset calculation logic. It should be noted that the preset calculation logic of the model includes positive and negative feedback mechanism adjustment of the driving rating of the driver, specifically, it is determined according to the update of the driving behavior data of the driver that the adjustment of upgrading or degrading the driving rating is performed when the preset condition is satisfied, for example, when the number of times of overspeed, rapid acceleration, rapid deceleration and rapid turning accumulated in the preset time interval exceeds the preset number, the driving rating of the driver is upgraded by one level until the driving rating is upgraded to the highest level, otherwise, the driving rating of the driver is downgraded by one level until the driving rating is upgraded to the lowest level.
The driving rating of the driver is dynamically updated according to the driving behavior of the driver, so that the driving rating of the driver is closest to the current truest driving state of the driver.
And step S32, obtaining the driving probability by combining the driving rating label value, the speed of the target vehicle and the speed limit value of each road in the parallel roads.
Generally, according to the risk aversion consideration, an aggressive driver is more apt to travel at a speed equal to or greater than the road speed limit value, and a cautious driver is more apt to travel at a speed equal to or less than the road speed limit value, so if the driving rating label of the driver of the target vehicle is an aggressive driving type, it is first assumed that the driver has a high possibility of speeding over while driving the vehicle, and if the driving rating label of the driver of the target vehicle is a normal driving type, a cautious driving type, a conservative driving type, it is first assumed that the driver has a low possibility of speeding over while driving the vehicle, and then the driving probability is calculated in combination of the driving rating label value, the target vehicle speed, and the speed limit value of each road in the parallel roads. In an alternative implementation, the driving probabilities of two roads in the parallel road are respectively calculated according to the following formulas:
the driving probability k (the absolute value of the difference between the vehicle speed and the other road speed limit)/(the absolute value of the difference between the two road speed limits); and when the driving probability of the road with the high speed limit value is calculated, k takes a 1-driving rating label value, and when the driving probability of the other road is calculated, k takes a driving rating label value.
Specifically, the following example is used to illustrate the process of obtaining the driving probability by combining the driving rating label value, the vehicle speed of the target vehicle, and the speed limit value of each road in the parallel roads:
assuming that the parallel roads where the target vehicle is currently located include A, B, the speed limit value of the road a is recorded as: vAThe speed limit value of the road B is recorded as: vB60 Km/h, the current vehicle speed of the target vehicle is VCWhen the driving rating of the driver driving the target vehicle is an aggressive driving type, which corresponds to a driving rating tag value of 0.8, 65 Km/h, then:
the running probability of the road A is (1-0.8) × (V)C-VB)/(VA-VB)＝0.05＝5％；
The driving probability of the vehicle on the road B is 0.8 (V)A-VC)/(VA-VB)＝0.6＝60％；
And finally obtaining an overspeed speculation result: the running probability of the target vehicle on the road A is 5% and the target vehicle does not run in an overspeed, and the running probability of the target vehicle on the road B is 60% and the target vehicle runs in an overspeed;
if the driving rating of the driver of the target vehicle is assumed to be a conservative driving type and the corresponding driving rating tag value is 0.1, the target vehicle is driven by the driver
The running probability of the road A is (1-0.1) × (V)C-VB)/(VA-VB)＝0.225＝22.5％；
The driving probability of the vehicle on the road B is 0.1 ═ V (V)A-VC)/(VA-VB)＝0.075＝7.5％；
And finally obtaining an overspeed speculation result: the target vehicle has a running probability of 22.5% on the a road and does not run at an overspeed, and has a running probability of 7.5% on the B road and runs at an overspeed.
Yet another example: assuming that the parallel roads where the target vehicle is currently located include A, B, the speed limit value of the road a is recorded as: vAThe speed limit value of the road B is recorded as: vB60 Km/h, current vehicle of target vehicleSpeed is VCWhen the driving rating of the driver driving the target vehicle is aggressive driving type, which corresponds to a driving rating tag value of 0.8, then:
the running probability of the road A is (1-0.8) × (V)C-VB)/(VA-VB)＝0.19＝19％；
The driving probability of the vehicle on the road B is 0.8 (V)A-VC)/(VA-VB)＝0.04＝4％；
And finally obtaining an overspeed speculation result: the target vehicle has a traveling probability of 19% on the a road and does not run at an overspeed, and has a traveling probability of 4% on the B road and runs at an overspeed.
Further, the real-time traffic condition of the road may also be used to assist in determining whether the vehicle is speeding, and therefore, in this embodiment, before step S32, the method further includes:
1. and acquiring real-time traffic information of each road in the parallel roads, and screening out the road in a congestion or slow running state and the real-time traffic speed of the road.
Specifically, after the parallel roads are confirmed, the real-time traffic information of each road can be acquired through a navigation tool or a map engine, whether the road of the current road section of the target vehicle is in a congestion or slow-moving state or not is confirmed, and the real-time traffic speed of the road is acquired.
2. And if the speed of the target vehicle is higher than the real-time traffic speed of the road in the congestion or slow traffic state, determining that the running probability of the target vehicle on the road is zero.
Specifically, the speed of the target vehicle is compared with the real-time traffic speed of the road in the congested or slow running state, and when the speed of the target vehicle is higher than the real-time traffic speed, it is indicated that the target vehicle is not possible to run on the road in the congested or slow running state, at this time, the running probability of the target vehicle on the road can be set to zero, and the running probability of the road does not need to be calculated through the driving rating label value, the speed of the target vehicle and the speed limit value of the road.
For example, if the parallel roads where the target vehicle is currently located include A, B two roads, the speed limit value of the a road is 80 Km/h, the speed limit value of the B road is 60 Km/h, and the vehicle speed of the target vehicle is 70 Km/h, if it can be known by acquiring the real-time traffic information of the A, B road, at this time, the a road is in a slow running state, the real-time running speed is 30 Km/h, and is much lower than the current vehicle speed of the target vehicle, it can be determined that the running probability of the target vehicle on the a road is zero, and the B road is in a clear state, it can be inferred that the target vehicle runs on the B road, and the vehicle speed is higher than the speed limit value of the B road, and it can be concluded that the target vehicle runs at an excessive speed on the B road.
The method for judging the overspeed of the parallel road comprises the steps of obtaining the speed of a target vehicle when the target vehicle is determined to run on the parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road, calculating the running probability of the target vehicle on each road when the speed of the target vehicle is determined to be between the minimum speed limit value and the maximum speed limit value of each road in the parallel road, confirming the overspeed condition of the target vehicle on each road according to the comparison result of the speed of the target vehicle and the speed limit value of each road, and finally outputting the running probability and the overspeed condition for a background manager to judge whether the target vehicle is overspeed or not, wherein the method effectively assists the background manager to judge the overspeed of the vehicle running in the parallel road area so that the background manager can timely and accurately judge the overspeed of the running vehicle no matter which road section the running vehicle is located, therefore, the reminding and the management and control can be performed in time under the condition of overspeed.
Fig. 2 is a functional block diagram of the parallel road overspeed determining apparatus according to the embodiment of the present application. As shown in fig. 2, the parallel road overspeed determining apparatus 2 includes a link determining module 21, a speed comparing module 22, and a determination calculating module 23.
The road section determining module 21 is configured to determine whether a road section where the target vehicle is currently located is a parallel road;
the speed comparison module 22 is used for comparing the speed of the target vehicle with the speed limit value of each road in the parallel roads when the road section where the target vehicle is located is the parallel road;
and the judgment calculation module 23 is used for calculating the running probability of the target vehicle on each road and outputting an overspeed estimation result when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road.
Alternatively, the operation of the determination calculating module 23 to calculate the traveling probability of the target vehicle on each road may be further: acquiring a driving rating label value of a driver corresponding to a target vehicle; and obtaining the driving probability by combining the driving rating label value, the speed of the target vehicle and the speed limit value of each road in the parallel roads.
Alternatively, the driver driving rating label value is calculated and generated based on analyzing historical driving behavior data of the driver including speeding, sharp acceleration, sharp deceleration, and sharp turns.
Alternatively, the historical driving behavior data is continuously updated and the driver driving rating label value is dynamically computed and generated.
Alternatively, the determination calculating module 23 is further configured to, before performing an operation of deriving the traveling probability in combination of the driving rating label value, the target vehicle speed, and the speed limit value of each of the parallel roads: acquiring real-time traffic information of each road in parallel roads, and screening out the road in a congestion or slow running state and the real-time traffic speed of the road; and if the speed of the target vehicle is higher than the real-time traffic speed of the road in the congestion or slow traffic state, determining that the running probability of the target vehicle on the road is zero.
Optionally, the road segment determining module 21 is further configured to, before performing the operation of determining whether the road segment where the target vehicle is currently located is a parallel road: extracting roads and road information in the road network data from a map search engine; and according to the road information, calibrating the roads with the same road passing direction, parallel relation and road spacing within the preset threshold range as the parallel roads.
Optionally, the road segment determining module 21 is further configured to, before performing the operation of determining whether the road segment where the target vehicle is currently located is a parallel road: and acquiring track points of the target vehicle, and matching the road section with the shortest foot distance with the current driving direction of the track points as the road section where the target vehicle is located.
For other details of the technical solutions implemented by the modules in the parallel road overspeed determination device in the above embodiment, reference may be made to the description of the parallel road overspeed determination method in the above embodiment, and details are not described here again.
It should be noted that, in this specification, each embodiment is described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same as and similar to each other in each embodiment may be referred to. For the device-like embodiments, since they are substantially similar to the method embodiments, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiments
Referring to fig. 3, fig. 3 is a schematic structural diagram of a terminal according to an embodiment of the present disclosure. As shown in fig. 3, the terminal 30 includes a processor 31 and a memory 32 coupled to the processor 31.
The memory 32 stores program instructions that, when executed by the processor 31, cause the processor 31 to perform the steps of the parallel road overspeed determination method in the above-described embodiment.
The processor 31 may also be referred to as a CPU (Central Processing Unit). The processor 31 may be an integrated circuit chip having signal processing capabilities. The processor 31 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a storage medium according to an embodiment of the present application. The storage medium of the embodiment of the present application stores a program file 41 capable of implementing all the methods described above, where the program file 41 may be stored in the storage medium in the form of a software product, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices, such as a computer, a server, a mobile phone, and a tablet.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The above embodiments are merely examples and are not intended to limit the scope of the present disclosure, and all modifications, equivalents, and flow charts using the contents of the specification and drawings of the present disclosure or those directly or indirectly applied to other related technical fields are intended to be included in the scope of the present disclosure.
Claims (9)
1. A parallel road overspeed determination method characterized by comprising: s1, determining whether the road section where the target vehicle is located is a parallel road or not; s2, if the road is a parallel road, comparing the speed of the target vehicle with the speed limit value of each road in the parallel road; s3, when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road, calculating the running probability of the target vehicle on each road, and outputting an overspeed estimation result; the calculating the driving probability of the target vehicle on each road comprises the following steps: s31, acquiring a driving rating label value of a driver corresponding to the target vehicle, wherein the driving rating label value is a grading model established for reflecting the historical driving behavior of the driver; and S32, obtaining the driving probability by combining the driving rating label value, the speed of the target vehicle and the speed limit value of each road in the parallel roads.
2. The parallel road overspeed determination method according to claim 1, wherein said driver driving rating label value is calculated and generated based on analyzing historical driving behavior data of the driver including overspeed, sharp acceleration, sharp deceleration, and sharp turn.
3. The parallel road speeding determination method as claimed in claim 2, wherein the historical driving behavior data is continuously updated, and a driver driving rating label value is dynamically calculated and generated.
4. The parallel road overspeed determination method according to claim 2, further comprising, before said step S32: acquiring real-time traffic information of each road in the parallel roads, and screening out the road in a congestion or slow running state and the real-time traffic speed of the road; and if the speed of the target vehicle is higher than the real-time traffic speed of the road in the congestion or slow traffic state, determining that the running probability of the target vehicle on the road is zero.
5. The parallel road overspeed determination method according to claim 1, further comprising, before step S1: extracting roads and road information in the road network data from a map search engine; and calibrating the roads with the same road passing direction, parallel relation and road distance within the preset threshold range as parallel roads according to the road information.
6. The parallel road overspeed determination method according to claim 1, further comprising, before said step S1: and acquiring a track point of the target vehicle, and matching the road section with the shortest foot distance with the road section with the current driving direction of the track point to obtain the road section where the target vehicle is located.
7. A parallel road overspeed determining apparatus characterized by comprising: the road section determining module is used for determining whether the road section where the target vehicle is located currently is a parallel road or not; the speed comparison module is used for comparing the speed of the target vehicle with the speed limit value of each road in the parallel roads when the road section where the target vehicle is located is the parallel road; the judgment and calculation module is used for calculating the running probability of the target vehicle on each road and outputting an overspeed estimation result when the speed of the target vehicle is between the minimum speed limit value and the maximum speed limit value of each road; the calculating the driving probability of the target vehicle on each road comprises the following steps: acquiring a driving rating label value of a driver corresponding to a target vehicle, wherein the driving rating label value is a grading model established for reflecting the historical driving behavior of the driver; and obtaining the driving probability by combining the driving rating label value, the speed of the target vehicle and the speed limit value of each road in the parallel roads.
8. A terminal, characterized in that the terminal comprises a processor, a memory coupled to the processor, in which memory program instructions are stored, which program instructions, when executed by the processor, cause the processor to carry out the steps of the method for determining a speed limit of a parallel road according to any of claims 1-6.
9. A storage medium storing a program file capable of implementing the parallel road overspeed determination method according to any one of claims 1 to 6.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105448108A (en) * | 2015-12-30 | 2016-03-30 | 上海经达信息科技股份有限公司 | Overspeed discrimination method based on hidden Markov road network matching |
| CN107093322A (en) * | 2017-05-22 | 2017-08-25 | 成都亿盟恒信科技有限公司 | A kind of overlapping region overspeed alarming method and system based on limiting vehicle speed |
| CN108292475A (en) * | 2015-11-30 | 2018-07-17 | 日产自动车株式会社 | The generation method and device of the prediction information of vehicles used in the traveling of road vehicle net |
| CN108961799A (en) * | 2018-07-24 | 2018-12-07 | 佛山市高明曦逻科技有限公司 | Driving information road auxiliary system |
| CN109448412A (en) * | 2018-11-01 | 2019-03-08 | 新疆凯力智慧电子科技有限公司 | The vehicle-mounted segmentation speed limiting system of one kind and application method |
| DE102018116600A1 (en) * | 2018-02-20 | 2019-08-22 | Hyundai Motor Company | Vehicle and tax procedure thereof |
| CN111554102A (en) * | 2020-04-24 | 2020-08-18 | 上海经达信息科技股份有限公司 | Vehicle overspeed judging method, system, storage medium and terminal |
| CN111710174A (en) * | 2020-07-27 | 2020-09-25 | 尹维 | Road traffic safety early warning command system and method based on Internet of things |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101847833B1 (en) * | 2015-10-27 | 2018-04-11 | 현대자동차주식회사 | A system for predicting a volume of traffic, a displaying apparatus for a vehicle, a vehicle and a method for predicting a volume of traffic |
| CN105869439B (en) * | 2016-04-13 | 2019-03-26 | 重庆邮电大学 | A kind of road river conjunction anti-collision early warning method, roadside device and anti-collision system |
| US10319221B2 (en) * | 2016-11-04 | 2019-06-11 | Ford Global Technologies, Llc | Systems and methods for vehicular application of detected traffic flow |
| JP6916433B2 (en) * | 2016-11-30 | 2021-08-11 | 富士通株式会社 | Road improvement part extraction program, road improvement part extraction device, and road improvement part extraction method |
| CN110097763B (en) * | 2018-01-30 | 2021-08-10 | 保定市天河电子技术有限公司 | Method and system for measuring speed of multilane vehicle |
| US11023749B2 (en) * | 2019-07-05 | 2021-06-01 | Zoox, Inc. | Prediction on top-down scenes based on action data |
| CN111898835B (en) * | 2020-08-11 | 2022-02-22 | 腾讯科技（深圳）有限公司 | Intelligent traffic management method, device, computer and readable storage medium |
-
2021
- 2021-03-26 CN CN202110327522.2A patent/CN113129603B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108292475A (en) * | 2015-11-30 | 2018-07-17 | 日产自动车株式会社 | The generation method and device of the prediction information of vehicles used in the traveling of road vehicle net |
| CN105448108A (en) * | 2015-12-30 | 2016-03-30 | 上海经达信息科技股份有限公司 | Overspeed discrimination method based on hidden Markov road network matching |
| CN107093322A (en) * | 2017-05-22 | 2017-08-25 | 成都亿盟恒信科技有限公司 | A kind of overlapping region overspeed alarming method and system based on limiting vehicle speed |
| DE102018116600A1 (en) * | 2018-02-20 | 2019-08-22 | Hyundai Motor Company | Vehicle and tax procedure thereof |
| CN108961799A (en) * | 2018-07-24 | 2018-12-07 | 佛山市高明曦逻科技有限公司 | Driving information road auxiliary system |
| CN109448412A (en) * | 2018-11-01 | 2019-03-08 | 新疆凯力智慧电子科技有限公司 | The vehicle-mounted segmentation speed limiting system of one kind and application method |
| CN111554102A (en) * | 2020-04-24 | 2020-08-18 | 上海经达信息科技股份有限公司 | Vehicle overspeed judging method, system, storage medium and terminal |
| CN111710174A (en) * | 2020-07-27 | 2020-09-25 | 尹维 | Road traffic safety early warning command system and method based on Internet of things |
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