CN116311943B - Method and device for estimating average delay time of intersection - Google Patents
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
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- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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Abstract
The disclosure provides an estimation method and device of average delay time of an intersection, relates to the technical field of computers, and particularly relates to the technical field of intelligent traffic, road traffic management and navigation. The implementation scheme is as follows: for each entrance way of an intersection, acquiring a first number of vehicles entering the intersection through a stop line of the entrance way within a preset time range; acquiring a plurality of pieces of perception data of a first area of an entrance way based on a preset time interval within a preset time range; determining average actual passing time of the entrance way within a preset time range based on the number of vehicles, the preset time interval and the first number corresponding to each of the plurality of perception data; acquiring delay-free passing time of an entrance road; determining a first average delay time at the entrance based on the average actual transit time and the delay-free transit time; a second average delay time for the intersection is determined based on the plurality of first average delay times for the plurality of entrance lanes.
Description
Technical Field
The present disclosure relates to the field of computer technology, and in particular, to the field of intelligent traffic, road traffic management, and navigation technology, and more particularly, to a method, apparatus, electronic device, computer readable storage medium, and computer program product for estimating average delay time of an intersection.
Background
The average delay time of urban road intersections is a key component in advanced traffic information management systems, and an important index for evaluating the level of intersection traffic and the vehicle passing efficiency is evaluated. In the related art, when calculating average delay indication data of urban road intersections, the real-time position and the moving speed of a vehicle are generally obtained by adopting a three-dimensional coordinate mode based on real-time identification of a camera, and then the average delay time of the urban road intersections is calculated by utilizing the real-time position and the moving speed of the vehicle.
The approaches described in this section are not necessarily approaches that have been previously conceived or pursued. Unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, the problems mentioned in this section should not be considered as having been recognized in any prior art unless otherwise indicated.
Disclosure of Invention
The present disclosure provides a method, apparatus, electronic device, computer readable storage medium and computer program product for estimating average delay time of an intersection.
According to an aspect of the present disclosure, there is provided a method of estimating an average delay time of an intersection, wherein the intersection includes a plurality of entrance lanes, the method including: for each entrance way of the intersection, the following operations are performed: acquiring a first number of vehicles entering an intersection through a stop line of an entrance road within a preset time range; acquiring a plurality of pieces of perception data of a first area of an entrance way based on a preset time interval within a preset time range, wherein the first area comprises an area between a stop line in the entrance way and a detection starting position of data acquisition equipment, and each piece of perception data in the plurality of pieces of perception data comprises the number of vehicles in the first area; determining average actual passing time of the entrance way within a preset time range based on the number of vehicles, the preset time interval and the first number corresponding to each of the plurality of perception data; acquiring delay-free passing time of an entrance road; and determining a first average delay time at the entrance based on the average actual transit time and the delay-free transit time; and determining a second average delay time of the intersection based on the corresponding plurality of first average delay times of the plurality of entrance lanes.
According to another aspect of the present disclosure, there is provided an apparatus for estimating an average delay time of an intersection, wherein the intersection includes a plurality of entrance lanes, the apparatus comprising: an execution unit configured to execute operations of the following sub-units for each entrance lane of the intersection, the execution unit including: a first acquisition subunit configured to acquire a first number of vehicles entering the intersection through a stop line of the entrance road within a preset time range; a second acquisition subunit configured to acquire, within a preset time range, a plurality of pieces of perception data of a first area of the entrance lane based on a preset time interval, wherein the first area includes an area between a stop line within the entrance lane and a detection start position of the data acquisition device, and each of the plurality of pieces of perception data includes a number of vehicles within the first area; a first determining subunit configured to determine an average actual transit time of the entrance road within a preset time range based on the number of vehicles corresponding to each of the plurality of perception data, the preset time interval, and the first number; a third acquisition subunit configured to acquire a delay-free transit time of the entrance; and a second determining subunit configured to determine a first average delay time at the entrance based on the average actual transit time and the no delay transit time; and a first determination unit configured to determine a second average delay time of the intersection based on a plurality of first average delay times corresponding to the plurality of entrance lanes.
According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of estimating an average delay time of the intersection.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method of estimating the average delay time of an intersection described above.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program, wherein the computer program when executed by a processor implements the method of estimating an average delay time of an intersection as described above.
According to one or more embodiments of the present disclosure, an average actual traffic time of each entrance lane is obtained by counting a traffic flow (a first number) and a traffic space flow (a number of vehicles corresponding to each sensing data in a plurality of sensing data) of each entrance lane at an intersection within a preset time range, and then the average delay time of each entrance lane is calculated by combining the vehicle non-delay traffic time, so as to calculate the average delay time of the intersection. Therefore, the accuracy and timeliness of calculating the average delay time of the intersection are ensured, delay time statistics for each vehicle is not needed, and calculation resources are saved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The accompanying drawings illustrate exemplary embodiments and, together with the description, serve to explain exemplary implementations of the embodiments. The illustrated embodiments are for exemplary purposes only and do not limit the scope of the claims. Throughout the drawings, identical reference numerals designate similar, but not necessarily identical, elements.
FIG. 1 illustrates a schematic diagram of an exemplary system in which various methods described herein may be implemented, in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a method of estimating average delay time for an intersection according to an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of determining a second average delay time according to an embodiment of the present disclosure;
FIG. 4 is a block diagram showing the construction of an apparatus for estimating the average delay time of an intersection according to an embodiment of the present disclosure;
fig. 5 illustrates a block diagram of an exemplary electronic device that can be used to implement embodiments of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the present disclosure, the use of the terms "first," "second," and the like to describe various elements is not intended to limit the positional relationship, timing relationship, or importance relationship of the elements, unless otherwise indicated, and such terms are merely used to distinguish one element from another element. In some examples, a first element and a second element may refer to the same instance of the element, and in some cases, they may also refer to different instances based on the description of the context.
The terminology used in the description of the various illustrated examples in this disclosure is for the purpose of describing particular examples only and is not intended to be limiting. Unless the context clearly indicates otherwise, the elements may be one or more if the number of the elements is not specifically limited. Furthermore, the term "and/or" as used in this disclosure encompasses any and all possible combinations of the listed items.
Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.
Fig. 1 illustrates a schematic diagram of an exemplary system 100 in which various methods and apparatus described herein may be implemented, in accordance with an embodiment of the present disclosure. Referring to fig. 1, the system 100 includes a motor vehicle 110, a server 120, and one or more communication networks 130 coupling the motor vehicle 110 to the server 120.
In an embodiment of the present disclosure, motor vehicle 110 may include a computing device in accordance with an embodiment of the present disclosure and/or be configured to perform a method in accordance with an embodiment of the present disclosure.
The server 120 may run one or more services or software applications that enable a method of estimating the average delay time of an intersection. In some embodiments, server 120 may also provide other services or software applications, which may include non-virtual environments and virtual environments. In the configuration shown in fig. 1, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or a combination thereof that are executable by one or more processors. A user of motor vehicle 110 may in turn utilize one or more client applications to interact with server 120 to utilize the services provided by these components. It should be appreciated that a variety of different system configurations are possible, which may differ from system 100. Accordingly, FIG. 1 is one example of a system for implementing the various methods described herein and is not intended to be limiting.
The server 120 may include one or more general purpose computers, special purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-end servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and/or combination. The server 120 may include one or more virtual machines running a virtual operating system, or other computing architecture that involves virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain virtual storage devices of the server). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.
The computing units in server 120 may run one or more operating systems including any of the operating systems described above as well as any commercially available server operating systems. Server 120 may also run any of a variety of additional server applications and/or middle tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.
In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and/or event updates received from motor vehicle 110. Server 120 may also include one or more applications to display data feeds and/or real-time events via one or more display devices of motor vehicle 110.
Network 130 may be any type of network known to those skilled in the art that may support data communications using any of a number of available protocols, including but not limited to TCP/IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a satellite communications network, a Local Area Network (LAN), an ethernet-based network, a token ring, a Wide Area Network (WAN), the internet, a virtual network, a Virtual Private Network (VPN), an intranet, an extranet, a blockchain network, a Public Switched Telephone Network (PSTN), an infrared network, a wireless network (including, for example, bluetooth, wiFi), and/or any combination of these with other networks.
The system 100 may also include one or more databases 150. In some embodiments, these databases may be used to store data and other information. For example, one or more of databases 150 may be used to store information such as audio files and video files. The data store 150 may reside in various locations. For example, the data store used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The data store 150 may be of different types. In some embodiments, the data store used by server 120 may be a database, such as a relational database. One or more of these databases may store, update, and retrieve the databases and data from the databases in response to the commands.
In some embodiments, one or more of databases 150 may also be used by applications to store application data. The databases used by the application may be different types of databases, such as key value stores, object stores, or conventional stores supported by the file system.
Motor vehicle 110 may include a sensor 111 for sensing the surrounding environment. The sensors 111 may include one or more of the following: visual cameras, infrared cameras, ultrasonic sensors, millimeter wave radar, and laser radar (LiDAR). Different sensors may provide different detection accuracy and range. The camera may be mounted in front of, behind or other locations on the vehicle. The vision cameras can capture the conditions inside and outside the vehicle in real time and present them to the driver and/or passengers. In addition, by analyzing the captured images of the visual camera, information such as traffic light indication, intersection situation, other vehicle running state, etc. can be acquired. The infrared camera can capture objects under night vision. The ultrasonic sensor can be arranged around the vehicle and is used for measuring the distance between an object outside the vehicle and the vehicle by utilizing the characteristics of strong ultrasonic directivity and the like. The millimeter wave radar may be installed in front of, behind, or other locations of the vehicle for measuring the distance of an object outside the vehicle from the vehicle using the characteristics of electromagnetic waves. Lidar may be mounted in front of, behind, or other locations on the vehicle for detecting object edges, shape information for object identification and tracking. The radar apparatus may also measure a change in the speed of the vehicle and the moving object due to the doppler effect.
Motor vehicle 110 may also include a communication device 112. The communication device 112 may include a satellite positioning module capable of receiving satellite positioning signals (e.g., beidou, GPS, GLONASS, and GALILEO) from satellites 141 and generating coordinates based on these signals. The communication device 112 may also include a module for communicating with the mobile communication base station 142, and the mobile communication network may implement any suitable communication technology, such as the current or evolving wireless communication technology (e.g., 5G technology) such as GSM/GPRS, CDMA, LTE. The communication device 112 may also have a Vehicle-to-Everything (V2X) module configured to enable, for example, vehicle-to-Vehicle (V2V) communication with other vehicles 143 and Vehicle-to-Infrastructure (V2I) communication with Infrastructure 144. In addition, the communication device 112 may also have a module configured to communicate with a user terminal 145 (including but not limited to a smart phone, tablet computer, or wearable device such as a watch), for example, by using a wireless local area network or bluetooth of the IEEE802.11 standard. With the communication device 112, the motor vehicle 110 can also access the server 120 via the network 130.
Motor vehicle 110 may also include a control device 113. The control device 113 may include a processor, such as a Central Processing Unit (CPU) or a Graphics Processing Unit (GPU), or other special purpose processor, etc., in communication with various types of computer readable storage devices or mediums. The control device 113 may include an autopilot system for automatically controlling various actuators in the vehicle. The autopilot system is configured to control a powertrain, steering system, braking system, etc. of a motor vehicle 110 (not shown) via a plurality of actuators in response to inputs from a plurality of sensors 111 or other input devices to control acceleration, steering, and braking, respectively, without human intervention or limited human intervention. Part of the processing functions of the control device 113 may be implemented by cloud computing. For example, some of the processing may be performed using an onboard processor while other processing may be performed using cloud computing resources. The control device 113 may be configured to perform a method according to the present disclosure. Furthermore, the control means 113 may be implemented as one example of a computing device on the motor vehicle side (client) according to the present disclosure.
The system 100 of fig. 1 may be configured and operated in various ways to enable application of the various methods and apparatus described in accordance with the present disclosure.
According to some embodiments, as shown in fig. 2, there is provided a method for estimating an average delay time of an intersection, wherein the intersection includes a plurality of entrance lanes, the method comprising:
step S201, for each entrance road of the intersection, executing the following operations:
step S2011, acquiring a first number of vehicles entering an intersection through a stop line of an entrance road within a preset time range;
step 2012, acquiring a plurality of pieces of perception data of a first area of the entrance way based on a preset time interval within a preset time range, wherein the first area comprises an area between a stop line in the entrance way and a detection starting position of the data acquisition equipment, and each piece of perception data in the plurality of pieces of perception data comprises the number of vehicles in the first area;
step S2013, determining average actual passing time of the entrance way in a preset time range based on the number of vehicles corresponding to each sensing data in the sensing data, the preset time interval and the first number;
step S2014, obtaining delay-free passing time of an entrance way; and
step S2015, determining a first average delay time at an entrance way based on the average actual traffic time and the delay-free traffic time; and
Step S202, determining a second average delay time of the intersection based on a plurality of first average delay times corresponding to the plurality of entrance ways.
The average delay time is estimated based on the traffic flow data, the average actual traffic time of the entrance road is obtained by counting the traffic flow (first quantity) and the traffic space flow (namely the total quantity of vehicles contained in a plurality of first sensing data) of each entrance road at the intersection within a preset time range, and the vehicle delay time is calculated by combining the vehicle delay-free traffic time. Therefore, the accuracy and timeliness of the calculation of the delay time of the intersection vehicles are ensured, delay time statistics is not required to be carried out for each vehicle, and calculation resources are saved.
In some embodiments, the first quantity and the plurality of sensory data may be acquired by a data acquisition device.
In some embodiments, the data acquisition device may be a sensing device such as a camera device or a radar sensing device deployed at an intersection of an urban deployment. The data acquisition equipment can sample data according to a certain time interval to obtain the vehicle information of the entrance way. For video data obtained by the image pickup apparatus, image data may be acquired at time intervals (for example, 30 frames are acquired for 1 s). For radar data obtained by the radar sensing device, travel track data of the vehicle may be acquired at time intervals (for example, 30 times for 1 s).
In some embodiments, for the image data, the vehicle may be identified by an object detection algorithm to extract vehicle location information at the moment, so as to obtain the number of vehicles contained in the first area in each image data; for radar data, coordinate information of a vehicle track may be first acquired, thereby obtaining the number of vehicles in the first region at that time.
In some embodiments, the sensing device may perform data acquisition on the first area of the entrance track at a certain frequency (for example, 1s for 30 frames) to obtain a plurality of sampling data corresponding to each sampling time, and determine the number of vehicles corresponding to each sampling data; and then selecting the sampling data with the largest number of vehicles from the sampling data in each preset time interval according to the preset time interval (for example, 5 s), taking the sampling data as the sensing data corresponding to the preset time interval, and taking the number of vehicles corresponding to the sampling data as the number of vehicles corresponding to the sensing data (the space flow value in the preset time interval), thereby obtaining the sensing data in the preset time range.
In some embodiments, the detection of vehicles entering the intersection through the stop line of the entrance road in the preset time range may be performed simultaneously based on the above sampling data, so as to obtain the first number of vehicles passing through the stop line of the entrance road in the preset time range.
In some embodiments, the first number may be obtained by extracting the first number from the original perceived data at a certain time interval (e.g., 5 minutes), to obtain the number of passing vehicles in each second time interval (e.g., the number of passing traffic in the second time interval), and further obtain the first number.
In some embodiments, determining the average actual transit time of the entrance lane within the preset time range based on the number of vehicles, the preset time interval, and the first number corresponding to each of the plurality of sensory data comprises: determining the total waiting time of vehicles at the entrance way in a preset time range based on the number of vehicles corresponding to each sensing data in the sensing data and a preset time interval; and determining an average actual transit time based on the total vehicle waiting duration and the first number.
In some embodiments, it may be preferred to determine the total spatial flow of the first region over a predetermined time range (e.g., 30 minutes) based on the number of vehicles corresponding to each of the plurality of sensory data. That is, the number of vehicles corresponding to each sensing data corresponds to the number of vehicles being queued in the first area at the moment, and the average queuing time of the vehicles can be considered as the above-mentioned preset time interval (for example, 5 s), so that the total space flow of the first area in the preset time range can represent the total number of vehicles queued in the space (the first area) in the preset time range.
In some embodiments, the total waiting time of the vehicle in the first area within the preset time range may be further obtained based on the total space flow and the preset time interval.
In some embodiments, the average actual transit time of the transit vehicles may be determined further based on the total length of time the vehicles wait and the first number (the number of transit vehicles within the preset time range).
In some embodiments, the average actual transit time may be calculated by the following formula:
where τ represents a preset time range (the time interval of which may be represented as [ t, t+τ ]])，t q Representing a preset time interval (e.g. 5 s), t n Representing the second time interval described above (e.g. 5 minutes),the (t+i) th space flow value, n, of the inlet channel j of the intersection c in a preset time range t+i And the t+i th traffic flow value of the entrance road j of the intersection c in the preset time range is shown. Then (I)>Representing the number of space flow values in a preset time interval; />Representing the number of traffic flow data in a preset time interval; />Representing the total number of vehicles in line waiting on the first zone during a preset time interval,the total length of time the vehicle waits in the first zone is indicated for a preset time interval. / >Representing a preset time range ([ t, t+τ)]) The average actual transit time of the vehicles in the entrance way j of the inner intersection c.
Therefore, the total waiting time of the vehicles on the entrance way in the time period is obtained through the vehicle space flow (namely the number of the vehicles corresponding to each sensing data in the sensing data) and the preset time interval, and the average actual passing time of each passing vehicle (namely the average waiting time of each passing vehicle) is further determined, so that the estimation of the average actual passing time of the vehicles based on the flow is realized, the accuracy of the estimation is ensured, the statistical calculation is not needed for each vehicle, and the calculation resources are saved.
In some embodiments, the distance between the first stop line and the detection start position is a first distance, and acquiring the delay-free transit time of the first entrance way includes: acquiring the night passing speed at the first entrance; and determining a delay-free transit time based on the first distance and the night transit speed.
Therefore, the night passing speed corresponding to each entrance lane is obtained on the open platform, and the delay-free passing time is further determined, so that the accuracy of determining the delay-free passing time of each entrance lane is improved, and the calculation accuracy of the average delay time is further improved.
In some embodiments, the delay-free transit time may be calculated by the following formula:
wherein,first distance indicating entrance lane j at intersection c,/->Night traffic speed of entrance lane j representing intersection c, +.>Indicating the delay-free transit time of the entrance lane j of intersection c.
In some embodiments, the first average delay time at each entrance lane may be determined further based on the average actual transit time of the entrance lane and the no delay transit time.
In some embodiments, a time range ([ t, t+τ) is preset]) First average delay time of entrance lane j of inner intersection cThe calculation can be made by the following formula:
in some embodiments, an average value may be further calculated for a plurality of first average delay times corresponding to a plurality of entrance lanes of the intersection to obtain a second average delay time for the intersection.
In some embodiments, determining the second average delay time for the intersection based on the respective plurality of first average delay times for the plurality of entrance lanes may include: a second average delay time is determined based on the first number and the first average delay time corresponding to each of the plurality of lanes.
In practical situations, since there is a large difference in congestion levels of multiple entrance ways of an intersection, the second average delay time is determined directly based on the average value, and the overall average delay time of the intersection may not be truly reflected.
In some embodiments, the weight of each first average delay time may be determined based on the first number corresponding to each entrance, so as to perform weighted calculation on the first average delay time of each entrance, so that the excessively high weight of the entrance with a relatively smooth entrance can be avoided, and the accuracy of the overall average delay time is further improved.
In some embodiments, as shown in fig. 3, determining the second average delay time based on the first number and the first average delay time corresponding to each of the plurality of lanes may include:
step S301, determining the total traffic flow of the intersection within a preset time range based on the first number of each entrance way in the plurality of entrance ways;
step S302, determining a total delay time at each entrance way based on a first number of the entrance ways and a first average delay time for each entrance way in the plurality of entrance ways; and
step S303, determining a second average delay time based on the total vehicle flow and the total delay time of each of the plurality of entrance lanes.
In some embodiments, the total traffic flow at the intersection within the preset time frame may be first determined based on the first number of each of the plurality of lanes.
In some embodiments, the total traffic flow at the intersectionThe calculation can be performed by the following formula:
wherein,the traffic flow value of the entrance lane j of the intersection c in the time interval t to t+τ is represented.
In some embodiments, the second average delayTimeThe calculation can be based on the following formula:
wherein,the traffic flow value of the entrance way j of the intersection c in a preset time range is represented;representing the total delay time of the entrance way j; />Representing the total delay time of the multiple entrances.
Therefore, by carrying out weight calculation on each entrance, the excessively high weight of the smoother entrance can be avoided, and the accuracy of the overall average delay time is further improved.
In some embodiments, the first distance is greater than a preset distance threshold.
In some embodiments, the preset distance threshold may be 200 meters to 300 meters.
Therefore, statistics of all queuing vehicles of the entrance way can be guaranteed, and calculation accuracy of average delay time is further improved.
In some embodiments, as shown in fig. 4, there is provided an apparatus 400 for estimating an average delay time of an intersection, wherein the intersection includes a plurality of entrance lanes, and the apparatus 400 includes:
An execution unit 410 configured to execute operations of the following sub-units for each entrance lane of the intersection, the execution unit 410 including:
a first obtaining subunit 411 configured to obtain a first number of vehicles entering the intersection through the stop line of the entrance road within a preset time range;
a second obtaining subunit 412 configured to perform data collection on a first area of the entrance way at a preset time interval within a preset time range to obtain a plurality of sensing data, where the first area includes an area between a stop line within the entrance way and a detection start position of the data collection device, and each of the plurality of sensing data includes a number of vehicles within the first area;
a first determining subunit 413 configured to determine an average actual transit time of the entrance road within a preset time range based on the number of vehicles corresponding to each of the plurality of perception data, the preset time interval, and the first number;
a third acquisition subunit 414 configured to acquire a delay-free transit time of the entrance; and
a second determination subunit 415 configured to determine a first average delay time at the entrance based on the average actual transit time and the delay-free transit time; and
The first determining unit 420 is configured to determine a second average delay time of the intersection based on a plurality of first average delay times corresponding to the plurality of entrance lanes.
The operations performed by the units 410-420 and the sub-units 411-415 in the device 400 for estimating the average delay time of the intersection are similar to the operations performed by the steps S201-S202 and the steps S2011-S2015 in the main flow path extraction method, and are not described herein.
The average delay time is estimated based on the traffic flow data, the average actual traffic time of the entrance road is obtained by counting the traffic flow (first quantity) and the traffic space flow (namely the total quantity of vehicles contained in a plurality of first sensing data) of each entrance road at the intersection within a preset time range, and the vehicle delay time is calculated by combining the vehicle delay-free traffic time. Therefore, the accuracy and timeliness of the intersection vehicle delay time calculation are guaranteed, and meanwhile, the calculation of statistics for each vehicle is not needed, so that the calculation resources are saved.
In some embodiments, the first determining unit may include: the first determination subunit is further configured to: determining the total waiting time of vehicles at the entrance way in a preset time range based on the number of vehicles corresponding to each sensing data in the sensing data and a preset time interval; and determining an average actual transit time based on the total vehicle waiting duration and the first number.
In some embodiments, the first determining unit comprises: and a third determination subunit configured to determine a second average delay time based on the first number and the first average delay time corresponding to each of the plurality of lanes.
In some embodiments, the third determination subunit is further configured to: determining a total traffic flow at the intersection within a preset time range based on a first number of each of the plurality of entrance lanes; for each of a plurality of lanes, determining a total delay time at the lane based on a first number of lanes and a first average delay time; and determining a second average delay time based on the total vehicle flow and the total delay time for each of the plurality of lanes.
In some embodiments, the distance between the stop line and the detection start position is a first distance, and the third acquisition subunit is further configured to: acquiring the night passing speed at the entrance; and determining a delay-free transit time based on the first distance and the night transit speed.
In some embodiments, the first distance is greater than a preset distance threshold.
According to embodiments of the present disclosure, there is also provided an electronic device, a readable storage medium and a computer program product.
Referring to fig. 5, a block diagram of an electronic device 500 that may be a server or a client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the electronic device 500 includes a computing unit 501 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 may also be stored. The computing unit 501, ROM 502, and RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in electronic device 500 are connected to I/O interface 505, including: an input unit 506, an output unit 507, a storage unit 508, and a communication unit 509. The input unit 506 may be any type of device capable of inputting information to the electronic device 500, the input unit 506 may receive input numeric or character information and generate key signal inputs related to user settings and/or function control of the electronic device, and may include, but is not limited to, a mouse, a keyboard, a touch screen, a trackpad, a trackball, a joystick, a microphone, and/or a remote control. The output unit 507 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. Storage unit 508 may include, but is not limited to, magnetic disks, optical disks. The communication unit 509 allows the electronic device 500 to exchange information/data with other devices over a computer network such as the internet and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth devices, 802.11 devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.
The computing unit 501 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 501 performs the respective methods and processes described above, such as the method of estimating the average delay time of the intersection described above. For example, in some embodiments, the method of estimating the average delay time of an intersection described above may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the above-described method of estimating the average delay time of the intersection may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the above-described method of estimating the average delay time of the intersection in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
Although embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it is to be understood that the foregoing methods, systems, and apparatus are merely exemplary embodiments or examples, and that the scope of the present invention is not limited by these embodiments or examples but only by the claims following the grant and their equivalents. Various elements of the embodiments or examples may be omitted or replaced with equivalent elements thereof. Furthermore, the steps may be performed in a different order than described in the present disclosure. Further, various elements of the embodiments or examples may be combined in various ways. It is important that as technology evolves, many of the elements described herein may be replaced by equivalent elements that appear after the disclosure.
Claims (12)
1. A method of estimating an average delay time for an intersection, wherein the intersection includes a plurality of entrance lanes, the method comprising:
For each entrance way of the intersection, performing the following operations:
acquiring a first number of vehicles entering the intersection through a stop line of the entrance road within a preset time range;
acquiring a plurality of pieces of perception data of a first area of the entrance way based on a preset time interval within the preset time range, wherein the first area comprises an area between the stop line in the entrance way and a detection starting position of data acquisition equipment, and each piece of perception data in the plurality of pieces of perception data comprises the number of vehicles in the first area;
determining an average actual passing time of the entrance way within the preset time range based on the number of vehicles corresponding to each of the plurality of sensing data, the preset time interval and the first number, including:
determining the total waiting duration of the vehicles at the entrance way in the preset time range based on the number of vehicles corresponding to each piece of sensing data in the plurality of pieces of sensing data and the preset time interval; and
determining the average actual transit time based on the total vehicle waiting duration and the first number;
Acquiring delay-free passing time of the entrance way; and
determining a first average delay time at the entrance way based on the average actual transit time and the delay-free transit time; and
and determining a second average delay time of the intersection based on the corresponding first average delay times of the entrance tracks.
2. The method of claim 1, the determining a second average delay time for the intersection based on a corresponding plurality of first average delay times for the plurality of entrance lanes comprising:
the second average delay time is determined based on a first number and a first average delay time corresponding to each of the plurality of lanes.
3. The method of claim 2, wherein the determining the second average delay time based on the corresponding first number of each of the plurality of lanes and the first average delay time comprises:
determining a total traffic flow at the intersection within the preset time range based on a first number of each of the plurality of entrance lanes;
for each of the plurality of lanes, determining a total delay time at the lane based on a first number of lanes and a first average delay time; and
The second average delay time is determined based on the total vehicle flow and a total delay time for each of the plurality of lanes.
4. A method according to any one of claims 1 to 3, wherein the distance between the stop line and the detection start position is a first distance, the obtaining a delay-free transit time of the entrance way comprising:
acquiring the night passing speed at the entrance road; and
and determining the delay-free passing time based on the first distance and the night passing speed.
5. The method of claim 4, wherein the first distance is greater than a preset distance threshold.
6. An apparatus for estimating an average delay time of an intersection, wherein the intersection includes a plurality of entrance lanes, the apparatus comprising:
an execution unit configured to execute operations of the following sub-units for each entrance lane of the intersection, the execution unit comprising:
a first obtaining subunit configured to obtain a first number of vehicles entering the intersection through a stop line of the entrance road within a preset time range;
a second acquisition subunit configured to acquire, within the preset time range, a plurality of pieces of perception data of a first area of the entrance lane based on a preset time interval, wherein the first area includes an area between the stop line within the entrance lane and a detection start position of a data acquisition device, and each of the plurality of pieces of perception data includes a number of vehicles within the first area;
A first determining subunit configured to determine an average actual transit time of the entrance way within the preset time range based on the number of vehicles corresponding to each of the plurality of perception data, the preset time interval, and the first number, wherein the first determining subunit is further configured to:
determining the total waiting duration of the vehicles at the entrance way in the preset time range based on the number of vehicles corresponding to each piece of sensing data in the plurality of pieces of sensing data and the preset time interval; and
determining the average actual transit time based on the total vehicle waiting duration and the first number;
a third acquisition subunit configured to acquire a delay-free transit time of the entrance; and
a second determination subunit configured to determine a first average delay time at the entrance lane based on the average actual transit time and the delay-free transit time; and
and a first determination unit configured to determine a second average delay time of the intersection based on a plurality of first average delay times corresponding to the plurality of entrance lanes.
7. The apparatus of claim 6, the first determining unit comprising:
A third determination subunit configured to determine the second average delay time based on the first number and the first average delay time corresponding to each of the plurality of lanes.
8. The apparatus of claim 7, wherein the third determination subunit is further configured to:
determining a total traffic flow at the intersection within the preset time range based on a first number of each of the plurality of entrance lanes;
for each of the plurality of lanes, determining a total delay time at the lane based on a first number of lanes and a first average delay time; and
the second average delay time is determined based on the total vehicle flow and a total delay time for each of the plurality of lanes.
9. The apparatus of any of claims 6 to 8, wherein a distance between the stop line and the detection start position is a first distance, the third acquisition subunit being further configured to:
acquiring the night passing speed at the entrance road; and
and determining the delay-free passing time based on the first distance and the night passing speed.
10. The apparatus of claim 9, wherein the first distance is greater than a preset distance threshold.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the method comprises the steps of
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-5.
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