CN112668892B - Method, device, electronic equipment and storage medium for determining parking risk - Google Patents
Method, device, electronic equipment and storage medium for determining parking risk Download PDFInfo
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Abstract
The present disclosure relates to a method, an apparatus, an electronic device, and a storage medium for determining a parking risk. In one method, a plurality of historical tickets associated with a plurality of road segments, respectively, are obtained, the historical ticket in the plurality of historical tickets being a ticket generated by a vehicle parking within a road segment of the plurality of road segments. Based on the plurality of historical tickets, a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments are determined, respectively, the first parking risk and the second parking risk representing parking risks of the vehicle in the first road segment and the second road segment, respectively. The second parking risk is updated based on the positional relationship between the first road segment and the second road segment and the first parking risk. Further, a corresponding apparatus, electronic device and storage medium are provided. In this way, the parking risk may be determined in a more accurate and efficient manner.
Description
Technical Field
Implementations of the present disclosure relate to data processing, and more particularly, to a method, apparatus, electronic device, and storage medium for determining a parking risk of a vehicle.
Background
With the development of navigation technology and on-line vehicle scheduling technology, more and more driving assistance-related applications have been provided. These applications may provide navigation services to the driver and guide the vehicle to a desired location. However, in a real road environment, there may be areas where parking is prohibited and restricted. If the vehicle is parked in these areas, it may interfere with normal traffic order and produce a ticket. At this time, how to determine the parking risk at each position in the road in a more accurate manner becomes a research hotspot.
Disclosure of Invention
It is desirable to develop and implement a solution that determines the risk of stopping a vehicle in a more efficient manner. It is desirable that the solution be compatible with existing applications and guide the driver's parking behavior in a more efficient manner and maintain normal traffic order.
According to a first aspect of the present disclosure, a method for determining a parking risk of a vehicle is provided. In the method, a plurality of history tickets respectively associated with a plurality of road segments in a road are acquired, wherein the history ticket in the plurality of history tickets is a ticket generated when a vehicle parks in a road segment in the plurality of road segments. Based on the plurality of historical tickets, a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments are determined, respectively, the first parking risk and the second parking risk representing parking risks of the vehicle in the first road segment and the second road segment, respectively. The second parking risk is updated based on the positional relationship between the first road segment and the second road segment and the first parking risk.
According to a second aspect of the present disclosure, an apparatus for determining a parking risk of a vehicle is provided. The device comprises: an acquisition module configured to acquire a plurality of historical tickets respectively associated with a plurality of road segments in a road, the historical tickets in the plurality of historical tickets being tickets generated by parking a vehicle in a road segment in the plurality of road segments; a determining module configured to determine a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments, respectively, based on the plurality of historical tickets, the first parking risk and the second parking risk representing parking risks of the vehicle in the first road segment and the second road segment, respectively; and an updating module configured to update the second parking risk based on the first parking risk and the positional relationship between the first road segment and the second road segment.
According to a third aspect of the present disclosure, there is provided an electronic device comprising: a memory and a processor; wherein the memory is for storing one or more computer instructions, wherein the one or more computer instructions are executable by the processor to implement a method according to the first aspect of the present disclosure.
According to a fourth aspect of the present disclosure there is provided a computer readable storage medium having stored thereon one or more computer instructions, wherein the one or more computer instructions are executed by a processor to implement a method according to the first aspect of the present disclosure.
Drawings
Features, advantages, and other aspects of various implementations of the disclosure will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating by way of example, and not by way of limitation, several implementations of the disclosure. In the drawings:
FIG. 1 schematically illustrates a block diagram of a roadway environment in which a technique according to one exemplary implementation of the present disclosure may be used;
FIG. 2 schematically illustrates an example implementation according to this disclosure a block diagram of a process for determining a parking risk of a vehicle;
FIG. 3 schematically illustrates a flow chart of a method for determining a parking risk of a vehicle according to an exemplary implementation of the present disclosure;
FIG. 4 schematically illustrates a block diagram of a process of determining a parking risk associated with a road segment according to an exemplary implementation of the present disclosure;
FIG. 5 schematically illustrates a block diagram of time-varying parking risk according to an exemplary implementation of the present disclosure;
fig. 6 schematically illustrates a block diagram of parking risk for multiple road segments in a road according to an exemplary implementation of the present disclosure; and
Fig. 7 schematically illustrates a block diagram of a computing device/server for determining a parking risk of a vehicle according to an exemplary implementation of the present disclosure.
Detailed Description
Preferred implementations of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred implementations of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the implementations set forth herein. Rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The term "comprising" and variations thereof as used herein means open ended, i.e., "including but not limited to. The term "or" means "and/or" unless specifically stated otherwise. The term "based on" means "based at least in part on". The terms "one example implementation" and "one implementation" mean "at least one example implementation". The term "another implementation" means "at least one additional implementation". The terms "first," "second," and the like, may refer to different or the same object. Other explicit and implicit definitions are also possible below.
Hereinafter, an application environment according to an exemplary implementation of the present disclosure is described first with reference to fig. 1. Fig. 1 schematically illustrates a block diagram of a roadway environment 100 in which a technical solution according to one exemplary implementation of the present disclosure may be used. A real road environment may include a plurality of roads, and different roads may have different regulations regarding whether parking can be performed on both sides of the road. For example, both sides of the road 110 may be provided with a plurality of traffic signs. In particular, the traffic sign 120 may indicate that the vehicle is prohibited from stopping for a long period of time, and the traffic sign 122 may indicate that the vehicle is prohibited from stopping. Meanwhile, a camera 130 may be provided near the road, and different patterns may be drawn on the road surface of the road 110 for indicating various regulations regarding prohibition and limitation of parking. These traffic signs may sometimes be ignored when the driver drives the vehicle 140 over the road 110, resulting in the occurrence of a parking ticket.
Technical solutions have been proposed to alert drivers to access risk segments (e.g. stop-disabled segments and/or limit stop segments). However, these solutions determine a risk section based on traffic rules, traffic facilities, etc., and the accuracy is not satisfactory. Thus, it is desirable to be able to determine the parking risk in a more convenient and efficient manner.
To at least partially address the deficiencies in the above-described solutions, according to an exemplary implementation of the present disclosure, parking risk of each section of road may be determined separately. It will be appreciated that traffic may be blocked and even a traffic accident caused when the vehicle is parked in a restricted parking area and/or a restricted parking area. Thus, the driver should be alerted to the associated parking risk and guided to the area where the risk is low. Specifically, a concept of parking risk propagation is proposed, and parking risks of two road segments among a plurality of road segments may be updated based on a positional relationship between the two road segments. An overview of a solution according to one exemplary implementation of the present disclosure is provided first with reference to fig. 2.
In the context of the present disclosure, further details for determining a parking risk will be described taking an online vehicle allocation application as an example. Specifically, the passenger may call the vehicle using an online vehicle allocation application, specify an boarding point for boarding the passenger, and may specify a alighting point. For convenience of description, the entry point and the exit point may be collectively referred to as a riding point. If the riding spot is located on a prohibited parking or restricted parking road, it may disrupt normal traffic order, raise road hazards, and generate a ticket. According to one exemplary implementation of the present disclosure, parking risk at various locations in a road may be determined, thereby guiding a driver to park at a zero risk (or low risk) location.
Fig. 2 schematically illustrates a block diagram of a process 200 for determining a parking risk of a vehicle according to an exemplary implementation of the present disclosure. As shown in fig. 2, the road 110 may include a plurality of road segments 210, …, and 220. The first parking risk 212 for a first road segment 210 and the second parking risk 222 for a second road segment 220 of the plurality of road segments may be determined based on a plurality of historical fines associated with the plurality of road segments, respectively. Here, the first parking risk 212 and the second parking risk 222 represent parking risks of the vehicle parking in the first road section 210 and the second road section 220, respectively. It will be appreciated that since two road segments may be directly or indirectly adjacent, the parking risk of adjacent road segments may be propagated to other road segments (as indicated by arrow 230). At this time, the parking risk of each road segment may be updated based on the positional relationship between the first road segment 210 and the second road segment 220.
With exemplary implementations of the present disclosure, the parking risk for a given road segment may be updated based on the parking risk for other road segments in the vicinity of the given road segment. In this way, the risk distribution along the road 110 may be comprehensively considered, and thus the parking risk of each road segment may be determined in a more accurate manner and with finer granularity. Hereinafter, more details of one exemplary implementation according to the present disclosure will be described with reference to fig. 3.
Fig. 3 schematically illustrates a flowchart of a method 300 for determining a parking risk of a vehicle according to an exemplary implementation of the present disclosure. At block 310, a plurality of historical tickets associated with a plurality of road segments, respectively, of the road 110 are obtained, the historical ticket of the plurality of historical tickets being a ticket generated by a vehicle parking within a road segment of the plurality of road segments. It will be appreciated that the ticket is a direct proof that can be measured as to whether parking is allowed at a certain location. For providers of online vehicle distribution applications, a large number of vehicles may generate multiple tickets during operation. Thus determining the parking risk based on the collected plurality of historical tickets may quantify the parking risk in a simple and efficient manner.
It will be appreciated that the plurality of road segments herein may be divided by a predetermined length. According to one exemplary implementation of the present disclosure, the predetermined link length may be set in consideration of both the link granularity and the calculation amount. It will be appreciated that there may be an offset in the positioning data (e.g., on the order of about 10 meters), and thus the predetermined road segment length may be set to 20 meters or other values greater than the positioning offset.
It will be appreciated that for too short a road segment, it is difficult to collect input data from such a road segment for determining risk, and that such a road segment is difficult to accommodate multiple vehicle stops, so too short a road segment is not of much significance in determining risk of stopping. According to one exemplary implementation of the present disclosure, in order to avoid an excessively short-circuited section generated when dividing a road section (i.e., a "remainder" occurs when dividing the road 110), the predetermined road section length may be adjusted. For example, the road segment length may be adjusted within a range of plus or minus 4 meters (or other values).
Specifically, the road length of the road 110 may be determined, and the link length may be adjusted within a given range based on a ratio between the road length and a predetermined link length. Further, the road may be divided into a plurality of road segments based on a predetermined road segment length and an adjusted road segment length, thereby avoiding the occurrence of a "remainder" in the division process. Assuming a road length of 50 meters, the road may be divided into three road segments of 16 meters, 16 meters and 18 meters. With the exemplary implementation of the present disclosure, it is possible to avoid as much as possible the occurrence of an excessively short road section when dividing a road. In this way, it is possible to improve the efficiency of dividing road segments and to ensure that the length of each road segment is suitable for determining the parking risk.
It will be appreciated that the risk of parking on both sides of the road may vary due to the direction of travel of the road. According to one exemplary implementation of the present disclosure, a road may be divided into a plurality of road segments based on a driving direction of the road. Specifically, each of the road segments obtained above may be divided into two road segments in accordance with the vehicle traveling direction. With the exemplary implementations of the present disclosure, road segments may be divided at finer granularity, thereby making it possible to determine the parking risk of parking on both sides of a road in a more accurate manner.
At block 320, a first parking risk 212 for a first road segment 210 and a second parking risk 222 for a second road segment 220 of the plurality of road segments are determined based on the plurality of historical tickets, respectively. Here, the first parking risk 212 and the second parking risk 222 represent parking risks of the vehicle parking in the first road section 210 and the second road section 220, respectively. Hereinafter, how to determine the parking risk of each road section will be described with reference to fig. 4.
Fig. 4 schematically illustrates a block diagram of a process 400 of determining a parking risk associated with a road segment according to an exemplary implementation of the present disclosure. As shown in fig. 4, the first parking risk 212 may be determined based on a ticket 410 that occurs within the first road segment 210. According to one exemplary implementation of the present disclosure, the initial value of the first parking risk 212 may be set to zero and the first parking risk 212 updated based on the number of relevant tickets. The first parking risk 212 may be increased if it is determined that the place of occurrence of the historical ticket 410 of the plurality of historical tickets is located within the first road segment 210. An increase step size (e.g., increase step size=1) for updating the first parking risk 212 may be set, at which time each ticket occurring within the first road segment 210 may increase the first parking risk 212 by 1 unit. With the exemplary implementations of the present disclosure, the risk level may be quantified based on the number of fines, thereby determining the parking risk for each road segment in a convenient and efficient manner.
It will be appreciated that the number of call orders associated with a road segment may also affect risk assessment. In one example, 1 ticket is generated within a road segment and the number of orders associated with that road segment is 100. In another example, 1 ticket is generated within a road segment and the number of orders associated with the road segment is 2. It can be seen that the parking risk in the two examples is not the same. Thus, the first parking risk 210 may be determined based on the number of both the ticket 410 and the order 420.
According to one exemplary implementation of the present disclosure, the number of fines for a historical fine within the first segment 210 generated during a predetermined period of time (e.g., 1 month or other length of time) may be determined, and the number of orders for the historical order within the first segment 210 generated during the predetermined period of time may be determined. In turn, a first parking risk 212 may be set based on the number of fines and the number of orders. The order herein refers to an order for getting on and off in the first road segment 210.
According to one exemplary implementation of the present disclosure, the order and the type of ticket are the same. For example, if the ticket is a ticket due to boarding action, then the order here is that of boarding in the first segment 210; if the ticket is a ticket due to a drop-off behavior, then the order here is the order for a drop-off in the first segment 210. For example, the first parking risk 212 may be set based on the ratio of the number of fines to the number of orders. By using the exemplary implementation manner of the method, the parking risk of each road section can be determined in a normalized manner, and the accuracy of the risk determination process is further improved. It will be appreciated that the above description describes how the first parking risk 212 is determined, taking the first road segment 210 as an example only. Similar processing may be performed for other road segments to determine the parking risk of each road segment separately.
It will be appreciated that there may be differences in parking risk for the same road segment at different points in the day. For example, a road may be manually managed, and thus the risk of parking during the day may be high, and the risk of parking during the night may be low. At this time, the attribute of the parking risk related time may be set further based on the penalty time of the history ticket. According to one exemplary implementation of the present disclosure, the historical ticket may include a penalty time, at which time the portion of first parking risk 212 associated with the penalty time may be increased based on the penalty time.
According to one exemplary implementation of the present disclosure, a day may be divided into a plurality of time periods and a penalty time-dependent parking risk determined based on a ticket at the penalty time. Fig. 5 schematically illustrates a block diagram of a time-varying parking risk 500 according to an exemplary implementation of the present disclosure. As shown in fig. 5, assume that the majority of the ticket generated in the first segment 210 is concentrated at 7:00 to 19:00, then the parking risk is higher during the above period (as shown by risk curve 510), and at 19:00 to the next day 7: the risk of parking between 00 is low. With the exemplary implementations of the present disclosure, parking risk for a given road segment at various points in the day may be determined with finer granularity. In this way, the accuracy of the risk determination process can be further improved, thereby guiding the driver to stop on a zero-risk or low-risk road segment.
According to one exemplary implementation of the present disclosure, orders and tickets may be collected over a longer period of time and the parking risk for each road segment determined based on the time difference between the penalty date and the current time. In other words, the attenuation factor of the parking risk may be set based on the time difference. Specifically, orders and fines may be collected over the past 3 months. For orders and tickets within the last 1 month, the decay factor may be set to "1" (meaning no decay is performed). For orders and fines in the past month 2, the decay factor may be set to "0.7" to indicate that the parking risk due to these orders and fines only has a 70% effect on determining the parking risk. Further, for orders and fines in the past month 3, the decay factor may be set to "0.3" to indicate a lower impact.
Specifically, assume that the number of orders and fines in the past month 1 is 100 and 1, respectively, the number of orders and fines in the past month 2 is 100 and 2, respectively, and the number of orders and fines in the past month 3 is 100 and 5, respectively. The parking risk of the first road segment 210 may be determined based on the following equation 1:
Parking risk = 1/100 x 1+2/100 x 0.7+5/100 x 0.3 = 0.039 = 3.9% equation 1
By using the exemplary implementation manner of the present disclosure, data related to parking risk can be collected more comprehensively and effectively, so that accuracy of a risk determination process is improved.
The process of determining the parking risk for each of the plurality of road segments has been described above. After the parking risk of each road segment has been determined, the parking risk of a certain road segment(s) of the plurality of road segments may be updated based on the risk propagation rule. More details are described below, returning to fig. 3. At block 330 of fig. 3, the second parking risk 222 is updated based on the positional relationship between the first road segment 210 and the second road segment 220 and the first parking risk 212.
It will be appreciated that the parking risk herein may be propagated from high risk segments to low risk segments. Thus, the parking risk of other road segments in the vicinity of a given road segment may be updated when it is determined that the risk of the given road segment is high. It will be understood that risk propagation herein refers to the propagation of risk from a high risk segment to a low risk segment. Thus, when it is determined that the first parking risk 212 is higher than the second parking risk, the second parking risk is updated.
Specifically, assuming that the first parking risk 212 of the first road segment 210 is above a predetermined threshold, an update procedure is triggered. According to one exemplary implementation of the present disclosure, it may be specified, for example, that the update process is triggered when the first parking risk 212 is found to be non-zero. Alternatively and/or additionally, the predetermined threshold may be set to other values (e.g., 1%). According to one exemplary implementation of the present disclosure, a distance between the first road segment 210 and the second road segment 220 may be determined. For example, the distance may be defined in terms of the number of road segments between two road segments. At this time, the distance between two immediately adjacent road segments is 0.
According to one exemplary implementation of the present disclosure, the smaller the distance between two road segments, the greater the impact of the high risk road segments on the low risk road segments. In other words, risk spread is inversely proportional to distance. It will be appreciated that the higher the risk, the greater the impact of risk spread on other road segments in the vicinity. At this point, risk spread is proportional to the first parking risk 212. According to one exemplary implementation of the present disclosure, the second parking risk 222 may be updated based on the distance and the first parking risk 212. For example, the updated second parking risk may be determined based on the following equation 2:
where Risk' 2 represents the updated second parking Risk, risk 1 and Risk 2 represent the first parking Risk and the second parking Risk, respectively, and Disc represents the distance between the first road segment and the second road segment.
It will be appreciated that equation 2 only schematically shows one specific example for updating the parking risk. According to one exemplary implementation of the present disclosure, the updated parking risk may be determined based on other formulas. The upper limit of the influence range may be set, for example, the influence range may be designated as 2 (or other numerical value). In other words, the first parking risk can be propagated only within a range of not more than 2, and if the distance between the first road segment and the second road segment is more than 2, the first parking risk is not propagated to the second road segment. According to one exemplary implementation of the present disclosure, the impact range may be set based on the magnitude of the first parking risk. In other words, the greater the parking risk, the greater the impact range.
Continuing with the example above, the first parking risk 212 is 3.9% (non-zero), so the update process may be triggered. Assuming that the second parking risk 222 determined based on the ticket and the order is 0 and the distance between the first road segment 210 and the second road segment 220 is 0, the updated second parking risk can be expressed as formula 3:
More details about risk propagation are described below with reference to fig. 6. Fig. 6 schematically illustrates a block diagram of a parking risk 600 for a plurality of road segments in a road according to an exemplary implementation of the present disclosure. As shown, the road 110 is divided into a plurality of road segments 610, 620, 630, 640, 650, 660, and 670. Assuming that the parking risk of the link 640 is 3.9% and the influence range is 2, the updated parking risks of 3 links (distances 0 to 2, respectively) near the link 640 are expressed as 1.95%, 1.3% and 0.975%, respectively, in the order of distances from near to far.
Fig. 6 shows different risks in different gray scales, with legends 680, 682, 684, and 686 representing micro, low, medium, and high risks, respectively. In fig. 6, the parking risk for road segment 640 alone is initially determined to be non-zero based on the ticket and the order. After updating based on the risk propagation process described above, the segments 610 and 670 belong to a low risk segment, the segments 620 and 660 belong to a low risk segment, and the segments 630 and 650 belong to a medium risk segment. With the exemplary implementation of the disclosure, parking risks of a plurality of other road segments around the roadside can be comprehensively considered, and then the risks of each road segment can be determined in a more accurate manner.
It will be appreciated that the parking risk of each road segment may be affected by the traffic regulations of the area in which it is located. For example, a new no-parking area may be set along the road 110, or the no-parking area along the road 110 may be canceled. At this time, traffic rules associated with the road may also be acquired. Assuming that traffic regulations dictate that no parking areas are set along a certain road, the method 300 described above may be performed for that road. As another example, assuming that the traffic regulations prescribe cancellation of all prohibited parking areas along the road 110, the method 300 may no longer be performed for the road 110. According to one exemplary implementation of the present disclosure, related news dynamics may also be obtained, and the parking risk for each road segment may be increased accordingly, assuming that traffic news emphasizes the need for enhanced management of prohibited parking. For example, the step up step described above may be increased from 1 to 1.5.
With the exemplary implementations of the present disclosure, the parking risk for each road segment may be adjusted accordingly with the latest traffic rules and traffic news dynamics so that the obtained parking risk may more truly and accurately reflect the probability that parking within the road segment may result in a offending ticket.
According to one exemplary implementation of the present disclosure, a driver's parking behavior may be directed based on the determined parking risk. Assuming that the passenger selected riding spot is located on a high risk road segment, stopping in a road segment with a lower risk near the riding spot may be recommended. Specifically, if it is determined that the vehicle is about to park within a target road segment (e.g., the second road segment 220 described above) among the plurality of road segments, a target time associated with the parking action may be acquired. Further, a risk prediction for parking within the target road segment may be determined based on the target time (e.g., daytime) and the target parking risk of the target road segment. The parking risk at the target time may be determined based on a risk profile of the target road segment. If the risk of parking is high, the driver and passengers may be prompted to park at other less risky locations. If the risk of parking is low, parking can be performed at the desired home location.
It will be appreciated that the above describes a process of determining a parking risk in a vehicle distribution application by way of example only. The above-described solution may also be used in other applications according to one exemplary implementation of the present disclosure. For example, the above-described solution may be used in a vehicle navigation application. Assuming that the destination entered by the driver is located in a high risk road segment, the driver may be prompted for a parking risk and recommended a candidate low risk parking spot (e.g., a permitted parking road segment or a parking lot, etc.).
The procedure of the method for determining the parking risk has been described above with reference to fig. 2 to 6. According to an exemplary implementation of the present disclosure, an apparatus for determining a parking risk of a vehicle is provided. The device comprises: an acquisition module configured to acquire a plurality of historical tickets respectively associated with a plurality of road segments in a road, the historical tickets in the plurality of historical tickets being tickets generated by parking a vehicle in a road segment in the plurality of road segments; a determining module configured to determine a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments, respectively, based on the plurality of historical tickets, the first parking risk and the second parking risk representing parking risks of the vehicle in the first road segment and the second road segment, respectively; and an updating module configured to update the second parking risk based on the first parking risk and the positional relationship between the first road segment and the second road segment.
According to one exemplary implementation of the present disclosure, the update module includes: a distance determination module configured to determine a distance between the first road segment and the second road segment in response to determining that the first parking risk of the first road segment is above a predetermined threshold; and a risk updating module configured to update the second parking risk based on the distance and the first parking risk.
According to one exemplary implementation of the present disclosure, the risk updating module is further configured to update the second parking risk to be proportional to the first parking risk and inversely proportional to the distance.
According to one exemplary implementation of the present disclosure, the determining module includes: an improvement module is configured to improve the first parking risk in response to determining that a place of occurrence of a historical ticket of the plurality of historical tickets is located within the first road segment.
According to one exemplary implementation of the present disclosure, the historical ticket includes a penalty time, and the boost module includes: and a time module configured to increase a portion of the first parking risk associated with the penalty time.
According to one exemplary implementation of the present disclosure, the enhancement module includes: a ticket determination module configured to determine a ticket number of historical tickets within the first road segment generated during the predetermined period of time; an order determination module configured to determine an order quantity of historical orders within a first road segment generated during a predetermined period of time; and a setting module configured to set a first parking risk based on the number of fines and the number of orders.
According to one exemplary implementation of the present disclosure, the historical ticket includes a penalty date, and the boost module includes: a difference determination module configured to determine a time difference between the penalty date and the current date and time; and a decay module configured to set a first parking risk based on the time difference.
According to one exemplary implementation of the present disclosure, a plurality of road segments in a road are determined using the steps of: determining the road length of the road; adjusting a predetermined link length based on the road length; and dividing the road into a plurality of road segments based on the predetermined road segment length and the adjusted road segment length.
According to one exemplary implementation of the present disclosure, wherein the plurality of road segments in the road are determined using the steps of: the road is divided into a plurality of links based on the traveling direction of the road.
According to one exemplary implementation of the present disclosure, the apparatus further includes a media acquisition module configured to acquire traffic rules and news associated with the link; and the update module is further configured to update the plurality of parking risks based on traffic rules and news.
According to one exemplary implementation of the present disclosure, the update module is further configured to: in response to determining that the first parking risk is higher than the second parking risk, the second parking risk is updated.
According to one exemplary implementation of the present disclosure, further comprising: a time acquisition module configured to acquire a target time associated with a parking maneuver in response to determining that the vehicle is to park within a second road segment of the plurality of road segments; and a prediction module configured to determine a risk prediction for parking within the target road segment based on the target time and the second risk.
Fig. 7 schematically illustrates a block diagram of a computing device/server 700 for determining parking risk according to an exemplary implementation of the present disclosure. It should be understood that the computing device/server 700 illustrated in fig. 7 is merely exemplary and should not be taken as limiting the functionality and scope of the embodiments described herein.
As shown in fig. 7, computing device/server 700 is in the form of a general purpose computing device. Components of computing device/server 700 may include, but are not limited to, one or more processors or processing units 710, memory 720, storage 730, one or more communication units 740, one or more input devices 750, and one or more output devices 760. The processing unit 710 may be an actual or virtual processor and is capable of performing various processes according to programs stored in the memory 720. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to increase the parallel processing capabilities of computing device/server 700.
Computing device/server 700 typically includes a number of computer storage media. Such media may be any available media that is accessible by computing device/server 700 and includes, but is not limited to, volatile and non-volatile media, removable and non-removable media. The memory 720 may be volatile memory (e.g., registers, cache, random Access Memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 730 may be a removable or non-removable media and may include machine-readable media such as flash drives, magnetic disks, or any other media that may be capable of storing information and/or data (e.g., training data for training) and may be accessed within computing device/server 700.
Computing device/server 700 may further include additional removable/non-removable, volatile/nonvolatile storage media. Although not shown in fig. 7, a magnetic disk drive for reading from or writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk may be provided. In these cases, each drive may be connected to a bus (not shown) by one or more data medium interfaces. Memory 720 may include a computer program product 725 having one or more program modules configured to perform the various methods or acts of the various embodiments of the disclosure.
Communication unit 740 enables communication with other computing devices via a communication medium. Additionally, the functionality of the components of computing device/server 700 may be implemented in a single computing cluster or in multiple computing machines capable of communicating over a communication connection. Accordingly, computing device/server 700 may operate in a networked environment using logical connections to one or more other servers, a network Personal Computer (PC), or another network node.
The input device 750 may be one or more input devices such as a mouse, keyboard, trackball, etc. The output device 760 may be one or more output devices such as a display, speakers, printer, etc. Computing device/server 700 may also communicate with one or more external devices (not shown), such as storage devices, display devices, etc., as needed through communication unit 740, with one or more devices that enable users to interact with computing device/server 700, or with any device (e.g., network card, modem, etc.) that enables computing device/server 700 to communicate with one or more other computing devices. Such communication may be performed via an input/output (I/O) interface (not shown).
According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which one or more computer instructions are stored, wherein the one or more computer instructions are executed by a processor to implement the method described above.
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various implementations of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The foregoing description of implementations of the present disclosure has been provided for illustrative purposes, is not exhaustive, and is not limited to the implementations disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various implementations described. The terminology used herein was chosen in order to best explain the principles of each implementation, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand each implementation disclosed herein.
Claims (13)
1. A method for determining a parking risk of a vehicle, comprising:
acquiring a plurality of historical tickets respectively associated with a plurality of road segments in a road, wherein the historical tickets in the plurality of historical tickets are tickets generated when a vehicle parks in the road segments in the plurality of road segments;
Determining a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments, respectively, based on the plurality of historical tickets, the first parking risk and the second parking risk representing parking risks of a vehicle in the first road segment and the second road segment, respectively;
Responsive to determining that the first parking risk of the first road segment is above a predetermined threshold, and responsive to determining that the first parking risk is above the second parking risk, dividing the road into the plurality of road segments based on a predetermined road segment length and an adjusted road segment length;
determining a distance between the first road segment and the second road segment; and
Based on the distance and the first parking risk, the second parking risk is updated, and the second parking risk is updated to be proportional to the first parking risk and inversely proportional to the distance.
2. The method of claim 1, wherein determining the first parking risk comprises: and in response to determining that the place of occurrence of the historical ticket in the plurality of historical tickets is located within the first road segment, increasing the first parking risk.
3. The method of claim 2, wherein the historical ticket includes a penalty time, and increasing the first parking risk includes: the portion of the first parking risk associated with the penalty time is increased.
4. The method of claim 2, wherein increasing the first parking risk comprises:
determining a number of tickets to the historical ticket generated during the predetermined period of time within the first road segment;
determining an order quantity of historical orders within the first road segment generated during a predetermined period of time;
the first parking risk is set based on the number of fines and the number of orders.
5. The method of claim 2, wherein the historical ticket includes a penalty date, and increasing the first parking risk includes:
determining a time difference between the penalty date and a current date and time;
the first parking risk is set based on the time difference.
6. The method of claim 1, wherein the adjusted road segment length is determined using the steps of:
determining a road length of the road; and
The predetermined link length is adjusted based on the road length.
7. The method of claim 1, wherein the plurality of segments in the road are determined using the steps of: the road is divided into the plurality of road segments based on a traveling direction of the road.
8. The method of claim 1, further comprising:
Acquiring traffic rules and news associated with the road; and
The plurality of parking risks are updated based on the traffic rules and news.
9. The method of claim 1, further comprising:
responsive to determining that the vehicle is to be parked within the second road segment, obtaining a target time associated with a parking maneuver; and
And determining a risk prediction of parking in a target road segment based on the target time and the second parking risk.
10. An apparatus for determining a parking risk of a vehicle, comprising:
an acquisition module configured to acquire a plurality of historical tickets respectively associated with a plurality of road segments in a road, the historical ticket in the plurality of historical tickets being a ticket generated by a vehicle parking within a road segment in the plurality of road segments;
A determining module configured to determine a first parking risk of a first road segment and a second parking risk of a second road segment of the plurality of road segments, respectively, based on the plurality of historical tickets, the first parking risk and the second parking risk representing a parking risk of a vehicle parking within the first road segment and the second road segment, respectively; and
An update module configured to:
Responsive to determining that a first parking risk of the first road segment is above a predetermined threshold, and responsive to determining that the first parking risk is above the second parking risk, dividing the road into the plurality of road segments based on a predetermined road segment length and an adjusted road segment length;
determining a distance between the first road segment and the second road segment; and
Based on the distance and the first parking risk, the second parking risk is updated, and the second parking risk is updated to be proportional to the first parking risk and inversely proportional to the distance.
11. An electronic device, comprising:
a memory and a processor;
Wherein the memory is for storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method of any of claims 1 to 9.
12. A computer readable storage medium having stored thereon one or more computer instructions, wherein the one or more computer instructions are executed by a processor to implement the method of any of claims 1 to 9.
13. A computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the method according to claim 1.
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| CN105590461A (en) * | 2016-03-09 | 2016-05-18 | 余水平 | Method for prompting and guiding roadside parking by means of role-breaking big data |
| CN111179578A (en) * | 2018-11-09 | 2020-05-19 | 北京嘀嘀无限科技发展有限公司 | Method and system for determining parking place limitation |
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| US20140074402A1 (en) * | 2012-09-12 | 2014-03-13 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for determining risks associated with driving routes |
| CN111859173A (en) * | 2019-10-23 | 2020-10-30 | 北京嘀嘀无限科技发展有限公司 | Boarding point recommendation method and system |
| CN111814071B (en) * | 2019-12-25 | 2024-06-25 | 北京嘀嘀无限科技发展有限公司 | Get-on point recommendation method and device, storage medium and electronic equipment |
| CN111739325B (en) * | 2020-06-15 | 2021-08-03 | 腾讯科技（深圳）有限公司 | Method, apparatus, device and medium for determining abnormal parking probability and navigation control |
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| CN105590461A (en) * | 2016-03-09 | 2016-05-18 | 余水平 | Method for prompting and guiding roadside parking by means of role-breaking big data |
| CN111179578A (en) * | 2018-11-09 | 2020-05-19 | 北京嘀嘀无限科技发展有限公司 | Method and system for determining parking place limitation |
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