UWB-based expressway traffic flow parameter monitoring method and system

Abstract

The invention discloses a UWB-based expressway traffic flow parameter monitoring method. The method comprises the following steps: establishing a road coordinate system model; acquiring position information P of a vehicle in the road coordinate system model; and calculating traffic flow parameters according to the position information. The invention also discloses a monitoring system of the method, and the system comprises the electronic tag which is installed on a vehicle and is used for transmitting a position signal; the plurality of base stations are installed on the roadside at intervals and are used for receiving the position signals sent by the electronic tags and generating position parameters; and the central system is in communication connection with each base station and is used for acquiring the position parameters generated by each base station and calculating traffic flow parameters according to the position parameters. Through obtaining vehicle position information at different moments, real-time detection of space average speed, traffic flow density and traffic volume of vehicles in a monitoring area can be realized, data support is provided for traffic management and planning, and road traffic efficiency and safety are improved. The method has the advantages of high precision, low cost, simple installation and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic flow parameter monitoring, and in particular to a method and system for monitoring traffic flow parameters on a UWB expressway. Background Art

[0002] With the rapid development of the economy, the number of cars in my country has increased year by year, and people have a strong demand for travel, which has led to increasing congestion on urban roads during peak hours in the morning and evening. In order to avoid or alleviate urban traffic congestion, it is necessary to effectively monitor the traffic flow parameters of roads to provide support for traffic management and planning.

[0003] Traditional traffic flow parameter monitoring methods have problems such as low accuracy, high cost, and complex installation. In view of the above technical problems, this application proposes a method and system for monitoring traffic flow parameters on expressways based on UWB. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for monitoring traffic flow parameters on a UWB-based expressway to solve the technical problems mentioned in the background technology. The purpose of the present invention is achieved through the following technical solutions:

[0005] A method for monitoring traffic flow parameters on expressways based on UWB includes the following steps:

[0006] Step S1, establishing a road coordinate system model;

[0007] The road coordinate system model includes a horizontal coordinate X and a vertical coordinate Y;

[0008] Step S2, obtaining the position information P of the vehicle in the road coordinate system model;

[0009] Step S3, calculating traffic flow parameters according to the location information obtained in step S2;

[0010] Traffic flow parameters include spatial average speed Traffic density K and traffic volume Q.

[0011] Furthermore, the average space velocity The calculation steps are:

[0012] Step S11: Set monitoring points P in sequence along the vehicle travel direction on the horizontal coordinate X. O and monitoring point P D ;

[0013] Step S12: Obtain the number of times the vehicle under test passes through the monitoring point P O Time T O And the vehicle under test passes through the monitoring point P D Time T D ;

[0014] Step S13: Calculate the number of times the vehicle under test passes through the monitoring point P O and monitoring point P D The time between the sections t i :

[0015] t i =T D -T O

[0016] Step S14: Calculate the number of monitoring points P O and monitoring point P D The spatial average speed of all tested vehicles on the road section

[0017]

[0018] Where l is the monitoring point P O and monitoring point P D The length of the road section between the monitoring points P O and monitoring point P D The total number of vehicles tested on the road section between them.

[0019] Furthermore, the vehicle under test passes through the monitoring point P O Time T O The method for determining includes the following steps:

[0020] Step S111: Obtain the position information P1 of the vehicle under test at time T1, and calculate the position information P1 and the monitoring point P o The distance between them is D1;

[0021] Step S112: When the position information P1 of the vehicle under test is consistent with the monitoring point P o If the distance D1 between them is within the permissible range, the vehicle under test is considered to be at the monitoring point P. o , then the corresponding T1 moment is T O ;

[0022] Step S113: When the position information P1 of the detected vehicle is consistent with the monitoring point P o If the distance D1 between the two is outside the permissible range, the vehicle under test will be o , then:

[0023] T O =T1+△t1

[0024] If the vehicle under test is at the monitoring point P o Downstream of , then:

[0025] T O =T1-△t1

[0026] in,

[0027]

[0028] V1=|P 1，T-△T P 1，T | / △T

[0029] Where: △T is the unit time; |P 1，T-△T P 1，T | is the distance moved by the measured vehicle in a unit time before time T1; V1 is the speed of the measured vehicle in a unit time before time T1, △t1 is the position information P1 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V1 o The distance between D1 and time.

[0030] Furthermore, the vehicle under test passes through the monitoring point P D Time T D The method for determining includes the following steps:

[0031] Step S111′, obtain the position information P2 of the vehicle under test at time T2, calculate the position information P2 and the monitoring point P D The distance between them is D2;

[0032] Step S112′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between them is within the permissible range, it is considered that the vehicle under test is at the monitoring point P. D , then the corresponding T2 time is T D ;

[0033] Step S113′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between the two is outside the permissible range, the vehicle under test will be D , then:

[0034] T D =T2+△t2

[0035] If the vehicle under test is at the monitoring point P D Downstream of , then:

[0036] T D =T2-△t2

[0037] in,

[0038]

[0039] V2=|P2, T-△T P2, T | / △T

[0040] Where: △T is the unit time; |P2,T-△T P2, T | is the distance moved by the measured vehicle in a unit time before time T2; V2 is the speed of the measured vehicle in a unit time before time T2, △t2 is the position information P2 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V2 D The distance between the time D2.

[0041] Furthermore, the calculation steps of the traffic density K are as follows:

[0042] Step S21, setting a monitoring interval with a length of L along the horizontal coordinate X direction of the road coordinate system model;

[0043] Step S22, extracting the position information of all vehicles in the road coordinate system model to obtain the number N of vehicles in the monitoring interval;

[0044] Step S23, calculate the traffic density K:

[0045] K = N / L.

[0046] Furthermore, the calculation steps of traffic volume Q are:

[0047] Step S31: Set monitoring point P on the horizontal axis X S ;

[0048] Step S32: Obtain the preset statistical time period U T Passing monitoring point P S The number of all vehicles;

[0049] Step S33, obtaining the vehicle type, and calculating the equivalent number of cars according to the vehicle conversion coefficient of the highway engineering technical standard;

[0050] Step S34: Add up the equivalent number of cars of all vehicles to obtain the traffic volume Q.

[0051] Further, step S32 specifically includes:

[0052] Step S321, setting the statistical time interval:

[0053] [tg T ,t+U T +g T ];

[0054] Among them, t is the starting time, U T is the preset statistical time period, g T The interval time for reading the vehicle position;

[0055] Step S322: Setting monitoring point P S Monitoring interval:

[0056] [P S -eg T V s ,P S +e+g T V s ];

[0057] Among them, e is the positioning accuracy, g T is the interval time for reading the vehicle position, V s is the vehicle speed;

[0058] Step S323, obtaining the number of all vehicles passing through the monitoring interval within the statistical time interval;

[0059] Step S324: Obtain the vehicle position information P closest to the monitoring interval near , calculate the vehicle from P near To P S Time t snear :

[0060]

[0061] in, P near To P S The distance, V s is the vehicle speed;

[0062] Step S325: If the vehicle position information P near At the monitoring point P S , then:

[0063] t s =t pnear +t snear

[0064] If the vehicle position information P near At the monitoring point P S Downstream of , then:

[0065] t s =t pnear -t snear

[0066] If t s ∈[t,t+U T ], then add the vehicle to the number of vehicles obtained in step S323;

[0067] Among them, t pnear The vehicle under test is at P near Time of location recording, t s The converted vehicle passes the monitoring point P S time.

[0068] A UWB-based expressway traffic flow parameter monitoring system, comprising:

[0069] Electronic tags, which are installed on vehicles and are used to transmit location signals;

[0070] Base stations, several of which are installed at intervals on the roadside, are connected to the electronic tags for communication, and are used to receive location signals sent by the electronic tags and generate location parameters;

[0071] The central system is connected to each base station in communication, and is used to obtain the location parameters generated by each base station and calculate the traffic flow parameters according to the location parameters.

[0072] The technical solution provided in the embodiments of the present application has at least the following technical effects or advantages:

[0073] By acquiring vehicle location information at different times, it is possible to achieve real-time detection of the spatial average speed, traffic density and traffic volume of vehicles in the monitoring area, provide data support for traffic management and planning, and improve road traffic efficiency and safety. Compared with existing video surveillance technology, it has the advantages of high accuracy, low cost and simple installation. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The drawings in the specification, which constitute a part of this application, are used to provide a further understanding of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0075] Figure 1 This is a flow chart of the monitoring method of the embodiment of the present application;

[0076] Figure 2 The spatial average speed of the embodiment of this application Algorithm flow chart;

[0077] Figure 3 This is a flow chart of the vehicle flow density K algorithm of the embodiment of the present application;

[0078] Figure 4 This is a flow chart of the traffic volume Q algorithm of the embodiment of the present application;

[0079] Figure 5 This is a schematic diagram of the monitoring system of an embodiment of the present application.

[0080] The attached figure shows: 1. electronic tag; 2. base station; 3. central system. DETAILED DESCRIPTION

[0081] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the drawings and specific implementation methods of the specification. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0082] Example 1

[0083] like Figure 1-4 A method for monitoring traffic flow parameters on a UWB-based expressway is shown, comprising the following steps:

[0084] Step S1, establishing a road coordinate system model;

[0085] The road coordinate system model is obtained through RTK mapping. The road coordinate system model uses the length direction of the road as the horizontal coordinate X and the width direction of the road as the vertical coordinate Y. The vertical coordinate Y direction is divided into several lanes.

[0086] Step S2, obtaining the position information P of the vehicle in the road coordinate system model;

[0087] Using UWB positioning technology, the position P(x, y) of the vehicle within the UWB monitoring range arranged on both sides of the expressway is obtained, where x is the position of the vehicle on the horizontal coordinate X of the road coordinate system model, and y is the position of the vehicle on the vertical coordinate of the road coordinate system model. By obtaining the position information of the vehicle at different times, the driving direction and lane of the vehicle can be identified.

[0088] Step S3, calculating traffic flow parameters according to the location information obtained in step S2;

[0089] Traffic flow parameters include spatial average speed Traffic density K and traffic volume Q.

[0090] In traffic flow theory, speed is usually the spatial average speed That is, the ratio of the length of a road section or lane to the average travel time of all vehicles passing through the section.

[0091] like Figure 2 As shown, the average space velocity The calculation steps are:

[0092] Step S11: Set monitoring points P in sequence along the vehicle travel direction on the horizontal coordinate X. O and monitoring point P D ;

[0093] Step S12: Obtain the number of times the vehicle under test passes through the monitoring point P O Time T O And the vehicle under test passes the monitoring point P D Time T D ;

[0094] Among them, the vehicle under test passes the monitoring point P O Time T O The method for determining includes the following steps:

[0095] Step S111: Obtain the position information P1 of the vehicle under test at time T1, and calculate the position information P1 and the monitoring point P o The distance between them is D1;

[0096] Step S112: When the position information P1 of the vehicle under test is consistent with the monitoring point P o If the distance D1 between them is within the permissible range, the vehicle under test is considered to be at the monitoring point P. o , then the corresponding T1 moment is T O ;

[0097] Step S113: When the position information P1 of the detected vehicle is consistent with the monitoring point P o If the distance D1 between the two is outside the permissible range, the vehicle under test will be o , then:

[0098] T O =T1+△t1

[0099] If the vehicle under test is at the monitoring point P o Downstream of , then:

[0100] T O =T1-△t1

[0101] in,

[0102]

[0103] V1=|P1, T-△T P1, T | / △T

[0104] Where: △T is the unit time; |P1, T-△T P1, T | is the distance moved by the measured vehicle in a unit time before time T1; V1 is the speed of the measured vehicle in a unit time before time T1, △t1 is the position information P1 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V1 o The distance between D1 and time.

[0105] The vehicle under test passes through the monitoring point P D Time TD The method for determining includes the following steps:

[0106] Step S111′, obtain the position information P2 of the vehicle under test at time T2, calculate the position information P2 and the monitoring point P D The distance between them is D2;

[0107] Step S112′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between them is within the permissible range, it is considered that the vehicle under test is at the monitoring point P. D , then the corresponding T2 time is T D ;

[0108] Step S113′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between the two is outside the permissible range, the vehicle under test will be D , then:

[0109] T D =T2+△t2

[0110] If the vehicle under test is at the monitoring point P D Downstream of , then:

[0111] T D =T2-△t2

[0112] in,

[0113]

[0114] V2=|P2, T-△T P2, T | / △T

[0115] Where: △T is the unit time; |P2, T-△T P2, T | is the distance moved by the measured vehicle in a unit time before time T2; V2 is the speed of the measured vehicle in a unit time before time T2, △t2 is the position information P2 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V2 D The distance between the time D2.

[0116] The above ΔT can be selected as the sampling interval time of the base station.

[0117] Step S13: Calculate the number of times the vehicle under test passes through the monitoring point P O and monitoring point P D The time between the sections t i :

[0118] t i =T D -TO

[0119] Step S14: Calculate the number of monitoring points P O and monitoring point P D The spatial average speed of all tested vehicles on the road section

[0120]

[0121] Where l is the monitoring point P O and monitoring point P D The length of the road section between the monitoring points P O and monitoring point P D The total number of vehicles tested on the road section between them.

[0122] According to the definition of traffic flow characteristics in traffic engineering: traffic density K refers to the number N of vehicles per unit length of road (lane) at a certain moment.

[0123] like Figure 3 As shown in Figure 2, the calculation steps of traffic density K are:

[0124] Step S21: set a monitoring interval with a length of L along the horizontal coordinate X direction of the road coordinate system model. The monitoring interval can be a single lane or the entire road.

[0125] Step S22: extract the position information of all vehicles in the road coordinate system model to obtain the number N of vehicles in the monitoring interval.

[0126] All vehicles in the road coordinate system model are traversed. If their position coordinates are within the monitoring interval of length L, the corresponding vehicle is placed in the traffic density queue. After all vehicles are traversed, the length of the traffic density queue is obtained, that is, the number of vehicles N in the monitoring interval.

[0127] Step S23, calculate the traffic density K:

[0128] K = N / L.

[0129] Traffic volume refers to the number of traffic entities passing through a certain section of the road during the statistical time period.

[0130] like Figure 4 As shown, the calculation steps of traffic volume Q are:

[0131] Step S31: Set monitoring point P on the horizontal axis X S ;

[0132] Step S32: Obtain the preset statistical time period U T Passing monitoring point P S The number of all vehicles;

[0133] Specifically include:

[0134] Step S321, set the statistical time interval: Since the base station obtains the vehicle position at a certain time interval g T Therefore, when determining the traffic volume statistics time interval, it is necessary to use g T Taking this into account, the statistical time interval is [tg T ,t+U T +g T ];

[0135] Among them, t is the starting time, U T is the preset statistical time period, g T The interval time for the base station to read the vehicle position;

[0136] Step S322: Setting monitoring point P S Monitoring interval: Due to the certain error in UWB positioning, and the time interval g at which the base station reads T The vehicle will generate a certain amount of displacement, and the monitoring interval is set as: [P S -eg T V s ,P S +e+g T V s ];

[0137] Among them, e is the positioning accuracy, g T is the interval time for reading the vehicle position, V s is the vehicle speed, V s It is obtained by dividing the vehicle displacement in the previous sampling interval by the sampling interval.

[0138] Step S323, obtaining the number of all vehicles passing through the monitoring interval within the statistical time interval;

[0139] Due to the problem of reading time interval, some vehicles pass through the monitoring point P S However, they are not recorded, so it is necessary to judge these vehicles through trajectory interpolation. The specific steps are as follows:

[0140] Step S324: Obtain the vehicle position information P closest to the monitoring interval near , calculate the vehicle from P near To P S Time t snear :

[0141]

[0142] in, P near To P S The distance, V sis the vehicle speed, V s It is obtained by dividing the displacement of the vehicle in the previous sampling interval by the sampling interval;

[0143] Step S325: If the vehicle position information P near At the monitoring point P S , then:

[0144] t s =t pnear +t snear

[0145] If the vehicle position information P near At the monitoring point P S Downstream of , then:

[0146] t s =t pnear -t snear

[0147] If t s ∈[t,t+U T ], then add the vehicle to the number of vehicles obtained in step S323;

[0148] Among them, t pnear The vehicle under test is at P near Time of location recording, t s The converted vehicle passes the monitoring point P S time.

[0149] Step S33: Obtain the vehicle type and calculate the equivalent number of cars according to the vehicle conversion coefficient of the highway engineering technical standard; obtain the vehicle type according to the information recorded on the electronic tag and convert different models into corresponding equivalent cars. The vehicle conversion coefficient standard is shown in the following table:

[0150] Vehicle Type Passenger car Large passenger car Large truck Articulated Truck Conversion factor 1.0 2.0 2.5 3.0

[0151] Step S34: The equivalent number of cars of all vehicles is accumulated to obtain the traffic volume Q. That is, all vehicles are multiplied by the corresponding conversion coefficient according to their vehicle types and then accumulated to obtain the traffic volume Q.

[0152] Example 2

[0153] like Figure 5 The UWB-based expressway traffic flow parameter monitoring system shown includes an electronic tag 1, a base station 2 and a central system 3.

[0154] The electronic tag 1 is used to transmit the vehicle's location signal. The electronic tag 1 is installed on the windshield on the upper right side of the co-pilot seat of the vehicle, so that the electronic tag 1 is out of the driver's sight to avoid interfering with the driver's observation of the road conditions. At the same time, this position is usually far away from the metal structure of the vehicle, reducing the shielding and interference of the wireless communication signal, ensuring the communication capability, and being able to transmit signals with the base station 2 as quickly as possible.

[0155] Several base stations 2 are installed at intervals on the roadside. The base stations 2 are connected to the electronic tags 1 for receiving the location signal sent by the electronic tags 1 and generating location parameters. The base stations 2 can receive the signal sent by the electronic tags 1 at the front of the vehicle at the first time, reducing the time error in the transmission signal. The installation height of the base stations 2 shall not be less than 2m. The spacing between the base stations 2 is determined according to the coverage range of the factory base stations. At the same time, in order to reduce the cost of setting up a separate pole, the base stations 2 can be installed using existing monitoring equipment poles, street light poles, or sign poles.

[0156] A wireless communication module is also installed at the base station 2. The central system 3 is connected to each base station 2 through the wireless communication module to obtain the location parameters generated by each base station 2, calculate the traffic flow parameters according to the above method, and evaluate the traffic flow through the traffic flow state recognition model to provide decision-making and control support to the traffic management department.

[0157] The technical solution provided in the embodiments of the present application has at least the following technical effects or advantages:

[0158] By acquiring vehicle location information at different times, it is possible to achieve real-time detection of the spatial average speed, traffic density and traffic volume of vehicles in the monitoring area, provide data support for traffic management and planning, and improve road traffic efficiency and safety. Compared with existing video surveillance technology, it has the advantages of high accuracy, low cost and simple installation.

[0159] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring traffic flow parameters on expressways based on UWB, characterized in that: The following steps are involved: Step S1, establishing a road coordinate system model; The road coordinate system model includes a horizontal coordinate X and a vertical coordinate Y; Step S2, obtaining the position information P of the vehicle in the road coordinate system model; Step S3, calculating traffic flow parameters according to the location information obtained in step S2; The traffic flow parameters include spatial average speed Traffic density K and traffic volume Q.

2. The method for monitoring traffic flow parameters of expressways based on UWB according to claim 1, characterized in that: The average space velocity The calculation steps are: Step S11: Set monitoring points P in sequence on the horizontal coordinate X along the vehicle's driving direction. O and monitoring point P D ; Step S12: Obtain the number of times the vehicle under test passes through the monitoring point P O Time T O And the vehicle under test passes through the monitoring point P D Time T D ; Step S13: Calculate the number of times the vehicle under test passes through the monitoring point P O and monitoring point P D The time between the sections t i : t=TD-To Step S14: Calculate the number of monitoring points P O and monitoring point P D The spatial average speed of all tested vehicles on the road section Where l is the monitoring point P O and monitoring point P D The length of the road section between the monitoring points P O and monitoring point P D The total number of vehicles tested on the road section between them.

3. The method for monitoring traffic flow parameters of a UWB-based expressway according to claim 2 is characterized in that: The vehicle under test passes through the monitoring point P O Time T O The method for determining includes the following steps: Step S111: Obtain the position information P1 of the vehicle under test at time T1, and calculate the position information P1 and the monitoring point P o The distance between them is D1; Step S112: When the position information P1 of the vehicle under test is consistent with the monitoring point P o If the distance D1 between the two is within the permissible range, it is considered that the vehicle under test is at the monitoring point P. o , then the corresponding T1 moment is T O ; Step S113: When the position information P1 of the detected vehicle is consistent with the monitoring point P o If the distance D1 between the two is outside the permissible range, the vehicle under test will be o , then: T O =T1+△t1 If the vehicle under test is at the monitoring point P o Downstream of , then: T O =T1-△t1 in, V1=|P1, T-△T P1, T | / △T Where: △T is the unit time; |P1, T-△T P1, T | is the distance moved by the measured vehicle in a unit time before time T1; V1 is the speed of the measured vehicle in a unit time before time T1, △t1 is the position information P1 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V1 o The distance between D1 and time.

4. The method for monitoring traffic flow parameters of expressways based on UWB according to claim 2 is characterized in that: The vehicle under test passes through the monitoring point P D Time T D The method for determining includes the following steps: Step S111′, obtain the position information P2 of the vehicle under test at time T2, and calculate the position information P2 and the monitoring point P D The distance between them is D2; Step S112′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between the two is within the permissible range, it is considered that the vehicle under test is at the monitoring point P. D , then the corresponding T2 time is T D ; Step S113′: When the position information P2 of the detected vehicle is consistent with the monitoring point P D If the distance D2 between the two is outside the permissible range, the vehicle under test will be D , then: T D =T2+△t2 If the vehicle under test is at the monitoring point P D Downstream of , then: T D =T2-△t2 in, <h2 style=";text-align:left;direction:ltr">V2=|P2,<h2 style=";text-align:left;direction:ltr"> T-△T <h2 style=";text-align:left;direction:ltr"> P2,<h2 style=";text-align:left;direction:ltr"> T <h2 style=";text-align:left;direction:ltr"> | / △T Where: △T is the unit time; |P2, T-△T P2, T | is the distance moved by the measured vehicle in a unit time before time T2; V2 is the speed of the measured vehicle in a unit time before time T2, △t2 is the position information P2 and the monitoring point P of the measured vehicle passing through the measured vehicle at a speed V2 D The distance between them is D2.

5. The method for monitoring traffic flow parameters of expressways based on UWB according to claim 1 is characterized in that: The calculation steps of the traffic density K are as follows: Step S21, setting a monitoring interval with a length of L along the horizontal coordinate X direction of the road coordinate system model; Step S22, extracting the position information of all vehicles in the road coordinate system model to obtain the number N of vehicles in the monitoring interval; Step S23, calculate the traffic density K: K = N / L.

6. The method for monitoring traffic flow parameters of expressways based on UWB according to claim 1, characterized in that: The calculation steps of the traffic volume Q are: Step S31: Set monitoring point P on the horizontal axis X S ; Step S32: Obtain the preset statistical time period U T Passing monitoring point P S The number of all vehicles; Step S33, obtaining the vehicle type, and calculating the equivalent number of cars according to the vehicle conversion coefficient of the highway engineering technical standard; Step S34: Add up the equivalent number of cars of all vehicles to obtain the traffic volume Q.

7. The method for monitoring traffic flow parameters of expressways based on UWB according to claim 6 is characterized in that: Step S32 specifically includes: Step S321, setting the statistical time interval: [t-g T ,t+U T +g T ]; Among them, t is the starting time, U T is the preset statistical time period, g T The interval time for reading the vehicle position; Step S322: Setting monitoring point P S Monitoring interval: [P S -eg T V s ,P S +e+g T V s ]; Among them, e is the positioning accuracy, g T is the interval time for reading the vehicle position, V s is the vehicle speed; Step S323, obtaining the number of all vehicles passing through the monitoring interval within the statistical time interval; Step S324: Obtain the vehicle position information P closest to the monitoring interval near , calculate the vehicle from P near To P S Time t snear : in, P near To P S The distance, V s is the vehicle speed; Step S325: If the vehicle position information P near At the monitoring point P S , then: t s =t pnear +t snear If the vehicle position information P near At the monitoring point P S Downstream of , then: t s =t pnear -t snear If t s ∈[t,t+U T ], then add the vehicle to the number of vehicles obtained in step S323; Among them, t pnear The vehicle under test is at P near Time of location recording, t s The converted vehicle passes the monitoring point P S time.

8. A UWB-based expressway traffic flow parameter monitoring system, characterized in that: include: An electronic tag installed on the vehicle and used to transmit a location signal; A base station, a plurality of the base stations are installed at intervals on the roadside, the base stations are in communication connection with the electronic tags, and are used to receive the location signal sent by the electronic tags and generate location parameters; The central system is respectively connected to the base stations for obtaining the location parameters generated by the base stations and calculating the traffic flow parameters according to the location parameters.

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