Location method using LTE Received Signal Strength Indicator in tunnel environment

Abstract

This invention proposes a positioning method using Long Term Evolution (LTE) Received Signal Strength Indicators (RSIs) in tunnel environments, relating to the field of autonomous vehicle positioning technology. Considering that GNSS signals are blocked or even interrupted in long tunnel environments, leading to inaccurate positioning results, this invention uses LTE RSIs to replace GNSS signals. A database of LTE RSIs is measured in the tunnel, and LTE RSIs are continuously measured during vehicle movement to form user data. The database is compared with the user data, and a matching algorithm for LTE RSIs is designed to minimize the difference between the two sets of data, thus completing the matching between the database and user data. The location in the database where this match occurs is taken as the vehicle's position, completing the positioning method using LTE RSIs in tunnel environments.

Description

Technical Field

[0001] This invention relates to the field of autonomous vehicle positioning technology, and in particular to a positioning method using Long Term Evolution Received Signal Strength Indicator (LTSI) in tunnel environments. Background Technology

[0002] Autonomous driving is a mainstream application in the field of artificial intelligence and one of the most promising technologies. It can prevent numerous traffic accidents, improve urban traffic efficiency, and thus bring significant economic benefits. Furthermore, since electrification is the optimal way to achieve autonomous vehicles, autonomous driving can indirectly improve the environment and air quality. In addition, autonomous driving technology offers advantages such as saving time, providing convenience for special groups, and alleviating urban parking problems. Therefore, autonomous driving technology is receiving increasing attention.

[0003] Vehicle positioning is crucial for the safe and effective operation of autonomous driving. Accurate vehicle positioning is a key technology and function of autonomous driving, and also the foundation for advanced functions such as obstacle avoidance and parking. Traditional positioning technologies mainly rely on Global Navigation Satellite Systems (GNSS), especially Real-Time Kinematic (RTK) based on carrier phase differential technology, which can provide centimeter-level positioning accuracy when the signal is stable and continuous. Globally, there are systems such as the US GPS, China's BeiDou Navigation Satellite System, and the EU's Galileo Navigation Satellite System. However, due to poor connectivity between satellites and terminal equipment, GNSS signals are easily affected by congestion and multipath effects in urban canyons, building complexes, and indoor environments, leading to unstable positioning results. Especially in tunnel environments, GNSS signals are completely blocked and unusable, making vehicle positioning impossible within tunnels using GNSS signals.

[0004] Numerous studies have been conducted to estimate the location of mobile terminals indoors where GPS signals are unavailable. However, applying existing indoor positioning technologies to tunnel environments is not straightforward. Most existing indoor positioning technologies utilize already installed, dense infrastructure. Examples include Wi-Fi, Bluetooth, ultra-wideband (UWB), LEDs, and radio-frequency identification (RFID) to estimate the target's current location. Because these technologies lack widespread transmitter coverage, dense infrastructure installation is necessary. Installing new infrastructure in tunnels is not only extremely costly but also difficult to manage stably.

[0005] Long-Term Evolution (LTE) signals can be measured using mobile phones in tunnel environments. The advantages of LTE signals include the antenna network being installed within the tunnel, eliminating shadow areas; and LTE is managed by telecommunications service providers, ensuring stable and high-quality signals. Because the antennas are distributed longitudinally along the tunnel, the Received Signal Strength Indicator (RSSI) of LTE signals forms a unique pattern with several peaks within the tunnel, providing a basis for vehicle location using the RSSI.

[0006] Therefore, a technique is needed to accurately locate vehicles in long tunnel environments using non-GNSS signals, by using the received Long Term Evolution (LTE) signal strength indicator to estimate the vehicle position in the tunnel. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a positioning method using Long Term Evolution (LTE) Received Signal Strength Indicators (RSIs) in tunnel environments. This method uses LTIs instead of GNSS signals. A database of LTIs is measured within the tunnel, and LTIs are continuously measured during vehicle movement to form user data. The database is compared with the user data, and a matching algorithm for LTIs is designed to minimize the difference between the two datasets. The location where this match occurs in the database is considered the vehicle's position. This method completes the positioning process using LTIs in tunnel environments, solving the problem of GNSS signal obstruction or even unavailability in long tunnels.

[0008] The technical solution of this invention is as follows:

[0009] A positioning method using the Long Term Evolution (LTE) Received Signal Strength Indicator (RSI) in a tunnel environment includes the following steps:

[0010] Step 1: Construct a database of received signal strength indicators (RSIs) for Long Term Evolution (LTE) signals and preprocess the RSI data in the database to obtain a database vector.

[0011] Step 1.1 Divide the tunnel into reference points at x-meter intervals to obtain N reference points;

[0012] The number of reference points N is:

[0013]

[0014] Among them, L tunneldenoted as the tunnel length; x represents the interval between reference points; N represents the number of reference points.

[0015] Step 1.2 Receive the Long Term Evolution (LTE) signals emitted by K roadside units distributed in the tunnel at the reference point, measure the received signal strength indicator (RSI) value of the LTE signal at the reference point in the tunnel and calculate the average value to obtain the average RSI value of the LTE signal at each reference point.

[0016] The average received signal strength indicator value of the LTE signal received by the nth reference point from the kth roadside unit is:

[0017]

[0018] Where, φ n,k φ represents the average received signal strength indicator value of the LTE signal transmitted by the k-th roadside unit and received at the n-th reference point, where n is the reference point number and k is the roadside unit number; n,k,i This represents the measured value of the received signal strength indicator of the i-th LTE signal transmitted by the k-th roadside unit at the n-th reference point, where i is the sequence number of the LTE signal transmitted by the roadside unit, and G is the number of times the roadside unit transmits the LTE signal.

[0019] Step 1.3 Normalize the average received signal strength indicator value of the Long Term Evolution (LTE) signal for each reference point and combine the normalized average received signal strength indicator value with its corresponding reference point coordinates into a matrix form to obtain a database of received signal strength indicators for the Long Term Evolution (LTE) signal in long tunnels.

[0020] The method for normalizing the average received signal strength indicator value is as follows:

[0021]

[0022] Where, μ k and σ k These are the mean and variance of the average received signal strength indicator value of the kth roadside unit, respectively; This is the normalized average received signal strength indicator value for the LTE signal transmitted by the k-th roadside unit and received at the n-th reference point.

[0023] The database of received signal strength indicators for the long tunnel long-term evolution signal is as follows:

[0024]

[0025] Where D is the database of received signal strength indicators for long tunnel LTE signals; R is the coordinate vector of reference points in the database, where r nLet be the coordinates of the nth reference point; Φ is the normalized average received signal strength indicator matrix, where each element... The normalized average received signal strength indicator value is the Long Term Evolution signal received from the kth roadside unit at the nth reference point.

[0026] Step 1.4 Divide the database of received signal strength indicators for long tunnel long-term evolution signals into database vectors corresponding to different reference points;

[0027] Since there are N reference points, and each reference point contains the normalized average received signal strength indicator (RSSSI) measurement value for K roadside units, the normalized average RSSSI matrix in step 1.3 has a dimension of N×K. This matrix is ​​divided into N column vectors, with the nth column vector being Φ. n Φ represents the normalized average received signal strength indicator measurement of the K roadside units corresponding to the nth reference point, and therefore has a length of K. The nth database vector is Φ. n Specifically:

[0028]

[0029] Where, Φ n The nth database vector corresponds to the reference point coordinates r. n ;

[0030] Step 2: When the user is driving a vehicle in the tunnel, measure the received signal strength indicator of the Long Term Evolution (LTE) signal at the current location of the vehicle in the tunnel and construct the user data vector.

[0031] Step 2.1 Measure the received signal strength indicator (RSI) of the Long Term Evolution (LTE) signal transmitted by the roadside unit multiple times at the current location of the vehicle and save it as a user data matrix;

[0032] The user data matrix can be represented as:

[0033]

[0034] Where B is the user data matrix; ξ i,k N represents the measured value of the received signal strength indicator obtained from the k-th roadside unit for the i-th time. B This indicates the length of the user data, which is the total number of received signal strength indicator measurements obtained from the roadside unit;

[0035] Step 2.2 Normalize the measured values ​​of the received signal strength indicator in the user data matrix and calculate the average value to obtain the user data vector;

[0036] The method for normalizing the measured values ​​of the received signal strength indicator in the user data matrix is ​​as follows:

[0037]

[0038] Where, μ' k and σ' k These are the mean and variance of the received signal strength indicator value emitted by the k-th roadside unit, respectively. The i-th normalized received signal strength indicator measurement obtained by the user from the k-th roadside unit;

[0039] Then, the N obtained by the user from the kth roadside unit B Calculate the average of the normalized received signal strength indicator measurements:

[0040]

[0041] in, This is the average value of the normalized received signal strength indicator measurement obtained by the user from the kth roadside unit;

[0042] The user data vector is:

[0043]

[0044] Among them, B z Represents a user data vector;

[0045] Step 3 uses Euclidean distance to compare the differences between the database vector and the user data vector, and takes the coordinates of the reference point corresponding to the minimum Euclidean distance as the vehicle position.

[0046] Step 3.1 Iterate through N database vectors using the current user data vector, use Euclidean distance to measure the difference between the database vector and the user data vector to obtain the Euclidean distance vector, and find the minimum Euclidean distance value min(d) in the Euclidean distance vector. t,n The coordinates of the reference point r corresponding to ) t This refers to the vehicle's current position.

[0047] For database vectors and the user data vector at the current location in the tunnel. Use Euclidean distance to compare the differences between two vectors:

[0048]

[0049] Where d n (Φ n B z ) represents the user data vector B z and database vector Φ n The Euclidean distance between them;

[0050] When there is a location requirement, the user data vector at time t is traversed through N database vectors to obtain N Euclidean distances, resulting in the Euclidean distance vector:

[0051] d t =[d t,1 d t,2 K d t,N (11)

[0052] Where, d t Let d represent the Euclidean distance vector at time t. t,n This represents the Euclidean distance between the user data vector and the nth database vector at time t.

[0053] Step 3.2 Obtain the user data vector for the next time step t+1 using the method described in Step 2, and iterate through the coordinates r of the reference point located in Step 3.1 using the user data vector for the next time step t+1. t The following Nn t Given n database vectors, the coordinates of the reference point corresponding to the minimum Euclidean distance value are used as the vehicle position at the next moment. t Let r be the coordinates of the reference point. t The index in the coordinate vector R of the reference point;

[0054] Iterate through the remaining Nn user data vectors that need to be located at the next time t+1. t For each database vector, Nn is obtained using the method described in step 3.1. t Given Euclidean distances, we obtain the Euclidean distance vector for the next time step:

[0055]

[0056] Where, d t+1 d represents the Euclidean distance vector corresponding to the user data at time t+1. t+1,n This represents the Euclidean distance between the user data vector at time t+1 and the nth database vector, and the minimum Euclidean distance value min(d) is calculated. t+1,n The coordinates of the reference point r corresponding to ) t+1 This refers to the vehicle's current position.

[0057] The positioning method using LTE received signal strength indicator in a tunnel environment proposed in this invention has the following advantages compared with the prior art:

[0058] Considering that GNSS signals are often blocked or even interrupted in long tunnel environments, leading to inaccurate positioning results, this invention uses the Long Term Evolution (LTE) Received Signal Strength Indicator (RSI) to replace the GNSS signal. The LTI database vector in long tunnel environments is compared with the user data vector, and the user data with the smallest discrepancy is considered the best match. The location where this user data is generated is the estimated vehicle position. The positioning method proposed in this invention overcomes the drawback of GNSS signal blockage or interruption in long tunnel environments, and can estimate the vehicle's position in a long tunnel based on the LTI. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of a positioning method using the Long Term Evolution Received Signal Strength Indicator (LTSSI) in a tunnel environment, as described in an embodiment of the present invention.

[0060] Figure 2 This is a schematic diagram of the database and user data vector constructed in an embodiment of the present invention. Detailed Implementation

[0061] To make the technical solutions and advantages of the present invention clearer, the technical solutions in this application will be described below with reference to the accompanying drawings. The specific examples described herein are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0062] Location methods using LTE received signal strength indicators in tunnel environments, such as... Figure 1 As shown, the method includes the following steps:

[0063] Step 1: Construct a database of received signal strength indicators (RSIs) for Long Term Evolution (LTE) signals and preprocess the RSI data in the database to obtain a database vector.

[0064] Step 1.1 Divide the tunnel into reference points at intervals of x meters to obtain N reference points; the interval x of the reference points depends on the requirements for accuracy and efficiency and is given by engineering experience.

[0065] If higher accuracy is preferred, a smaller reference point interval is preferable; if higher efficiency is preferred, a larger reference point interval is preferable. Generally, the reference point interval is chosen as a trade-off between accuracy and efficiency requirements. To construct a database in a tunnel environment, reference points are set at intervals of x meters within the tunnel, and the number of reference points N is:

[0066]

[0067] Among them, L tunnel denoted as the tunnel length; x represents the interval between reference points; N represents the number of reference points.

[0068] Step 1.2 Receive the Long Term Evolution (LTE) signals emitted by K roadside units distributed in the tunnel at the reference point, measure the received signal strength indicator (RSI) value of the LTE signal at the reference point in the tunnel and calculate the average value to obtain the average RSI value of the LTE signal at each reference point.

[0069] Assuming the number of LTE signals received by a reference point from a roadside unit is G, then the average received signal strength indicator value of the LTE signal received by the nth reference point from the kth roadside unit is:

[0070]

[0071] Where, φ n,k φ represents the average received signal strength indicator value of the LTE signal transmitted by the k-th roadside unit and received at the n-th reference point, where n is the reference point number and k is the roadside unit number; n,k,i This represents the measured value of the received signal strength indicator of the i-th LTE signal transmitted by the k-th roadside unit at the n-th reference point, where i is the sequence number of the LTE signal transmitted by the roadside unit, and G is the number of times the roadside unit transmits the LTE signal.

[0072] Step 1.3 Normalize the average received signal strength indicator value of the Long Term Evolution (LTE) signal for each reference point and combine the normalized average received signal strength indicator value with its corresponding reference point coordinates into a matrix form to obtain a database of received signal strength indicators for the Long Term Evolution (LTE) signal in long tunnels.

[0073] The method for normalizing the average received signal strength indicator value is as follows:

[0074]

[0075] Where, μ k and σ k These are the mean and variance of the average received signal strength indicator value of the kth roadside unit, respectively; This is the normalized average received signal strength indicator value of the LTE signal received from the kth roadside unit at the nth reference point. The purpose of normalization is to adjust the received LTE signal strength to a relatively fixed value to prevent large differences in measurement values ​​between different devices due to differences in signal sensitivity of the devices receiving the LTE signal strength indicator.

[0076] The normalized average received signal strength indicator values ​​and their corresponding reference point coordinates are combined into a matrix to obtain a database of received signal strength indicators for long-term evolution signals in long tunnels:

[0077]

[0078] Where D is the database of received signal strength indicators for long tunnel LTE signals; R is the coordinate vector of reference points in the database, where r n Let be the coordinates of the nth reference point; Φ is the normalized average received signal strength indicator matrix, where each element... The normalized average received signal strength indicator value is the Long Term Evolution signal received from the kth roadside unit at the nth reference point.

[0079] Step 1.4 Divide the database of received signal strength indicators for long tunnel long-term evolution signals into database vectors corresponding to different reference points;

[0080] Since there are N reference points, and each reference point contains the normalized average received signal strength indicator (RSSSI) measurement value for K roadside units, the normalized average RSSSI matrix in step 1.3 has a dimension of N×K. This matrix is ​​divided into N column vectors, with the nth column vector being Φ. n Φ represents the normalized average received signal strength indicator measurement of the K roadside units corresponding to the nth reference point, and therefore has a length of K. The nth database vector is Φ. n Specifically:

[0081]

[0082] Where, Φ n The nth database vector corresponds to the reference point coordinates r. n ;

[0083] Step 2: When the user is driving a vehicle in the tunnel, measure the received signal strength indicator of the Long Term Evolution (LTE) signal at the current location of the vehicle in the tunnel and construct the user data vector.

[0084] Step 2.1 Measure the received signal strength indicator (RSI) of the Long Term Evolution (LTE) signal transmitted by the roadside unit multiple times at the current location of the vehicle and save it as a user data matrix;

[0085] The user data matrix can be represented as:

[0086]

[0087] Where B is the user data matrix; ξ i,k N represents the measured value of the received signal strength indicator obtained from the k-th roadside unit for the i-th time. B This indicates the length of the user data, which is the total number of received signal strength indicator measurements obtained from the roadside unit;

[0088] Step 2.2 Normalize the measured values ​​of the received signal strength indicator in the user data matrix and calculate the average value to obtain the user data vector;

[0089] Similar to the normalization method for received signal strength indicators in the database, the measured values ​​of received signal strength indicators in the user matrix are also normalized:

[0090]

[0091] Where, μ' k and σ' k These are the mean and variance of the received signal strength indicator value emitted by the k-th roadside unit, respectively. This is the i-th normalized received signal strength indicator measurement obtained by the user from the k-th roadside unit; the purpose of normalization here is the same as that described in step 1.3.

[0092] Then, the N obtained by the user from the kth roadside unit B Calculate the average of the normalized received signal strength indicator measurements:

[0093]

[0094] in, This is the average value of the normalized received signal strength indicator measurement obtained by the user from the kth roadside unit;

[0095] N obtained from K roadside units B The user data vector is composed of normalized received signal strength indicator measurements:

[0096]

[0097] Among them, B z Represents a user data vector;

[0098] Step 3 uses Euclidean distance to compare the differences between the database vector and the user data vector, and takes the coordinates of the reference point corresponding to the minimum Euclidean distance as the vehicle position.

[0099] Step 3.1 as follows Figure 2 As shown, the user data vector is iterated through N database vectors. Euclidean distance is used to measure the difference between the database vectors and the user data vectors to obtain an Euclidean distance vector. The minimum Euclidean distance value (min(d)) in the Euclidean distance vector is then selected. t,n The coordinates of the reference point r corresponding to ) t This refers to the vehicle's current position.

[0100] For database vectors and the user data vector at the current location in the tunnel. Use Euclidean distance to compare the differences between two vectors:

[0101]

[0102] Where d n (Φ n B z ) represents the user data vector B z and database vector Φ n The Euclidean distance between them;

[0103] When there is a location requirement, the user data vector at time t is traversed through N database vectors to obtain N Euclidean distances, resulting in the Euclidean distance vector:

[0104] d t =[d t,1 d t,2 K d t,N (11)

[0105] Where, d t Let d represent the Euclidean distance vector at time t. t,n This represents the Euclidean distance between the user data vector and the nth database vector at time t, and the minimum Euclidean distance value min(d) is calculated. t,n The coordinates of the reference point r corresponding to ) t As the vehicle's current position, r t Let r represent the coordinates of the minimum element in the Euclidean distance vector corresponding to the user data at time t, and use it as the vehicle localization result. t The coordinate vector R of the reference point in all databases is the nth... t indivual;

[0106] Step 3.2 Obtain the user data vector for the next time step t+1 using the method described in Step 2, and iterate through the coordinates r of the reference point located in Step 3.1 using the user data vector for the next time step t+1. t The following Nn t A database vector is used to determine the coordinates of the reference point corresponding to the minimum Euclidean distance value, which will be used as the vehicle's position at the next moment.

[0107] Assuming the vehicle is constantly moving forward in the tunnel, the positioning result at the next moment must be after the positioning result at this moment. That is, the reference point coordinate index representing the vehicle's position output at the next moment is greater than the reference point coordinate index representing the vehicle's position output at this moment.

[0108] Iterate through the remaining Nn user data vectors that need to be located at the next time t+1. t For each database vector, Nn is obtained using the method described in step 3.1. tGiven Euclidean distances, we obtain the Euclidean distance vector for the next time step:

[0109]

[0110] Where, d t+1 d represents the Euclidean distance vector corresponding to the user data at time t+1. t+1,n This represents the Euclidean distance between the user data vector at time t+1 and the nth database vector, and the minimum Euclidean distance value min(d) is calculated. t+1,n The coordinates of the reference point r corresponding to ) t+1 As the vehicle's current position, r t+1 This represents the coordinates of the smallest element in the Euclidean distance vector corresponding to the user data at time t+1, and is used as the vehicle localization result. Let r be an integer. t+1 The coordinate vector R of the reference point in all databases is the nth... t+1 indivual.

Claims

1. A positioning method using Long Term Evolution (LTE) Received Signal Strength Indicator (RSI) in a tunnel environment, characterized in that, Includes the following steps: Step 1: Construct a database of received signal strength indicators (RSIs) for Long Term Evolution (LTE) signals and preprocess the RSI data in the database to obtain a database vector. Step 1 specifically includes: Step 1.1 Divide the tunnel into reference points at x-meter intervals to obtain... One reference point; Step 1.2 Receive signals distributed in the tunnel at the reference point. The Long Term Evolution (LTE) signal emitted by each roadside unit is measured, and the received signal strength indicator (RSI) value of the LTE at a reference point in the tunnel is calculated and averaged to obtain the average RSI value of the LTE at each reference point. No. The reference point received the first The average received signal strength indicator value of the LTE signals transmitted by each roadside unit is: （1） in, Indicates the first The reference point received the first The average received signal strength indicator value of the LTE signal transmitted by each roadside unit. The reference point number, This refers to the serial number of the roadside unit; Indicates the first The reference point receives the first... The first roadside unit sent the first The measured value of the received signal strength indicator for the second long term evolution signal. The sequence number for sending Long Term Evolution (LTE) signals to roadside units; The number of times a Long Term Evolution (LTE) signal is sent to a roadside unit; Step 1.3 Normalize the average received signal strength indicator value of the Long Term Evolution (LTE) signal for each reference point and combine the normalized average received signal strength indicator value with its corresponding reference point coordinates into a matrix form to obtain a database of received signal strength indicators for the Long Term Evolution (LTE) signal in long tunnels. The method for normalizing the average received signal strength indicator value is as follows: （2） in, and They are the first The mean and variance of the average received signal strength indicator values ​​of each roadside unit; For the first The reference point received the first The normalized average received signal strength indicator value of the LTE signals transmitted by each roadside unit; The database of received signal strength indicators for the long tunnel long-term evolution signal is as follows: （3） in, A database of received signal strength indicators for long-term evolution signals in long tunnels; It is the coordinate vector of the reference point in the database, where For the first The coordinates of the reference points; This is a normalized average received signal strength indicator matrix, where each element... For the first The reference point received the first The normalized average received signal strength indicator value of the LTE signals transmitted by each roadside unit; Step 1.4 Divide the database of received signal strength indicators for long tunnel long-term evolution signals into database vectors corresponding to different reference points; Since there are N reference points, and each reference point contains the normalized average received signal strength indicator (RSSSI) measurement value for K roadside units, i.e., the normalized average RSSSI matrix in step 1.3 has a dimension of N×K, this matrix is ​​divided into N column vectors, the first of which is... The column vectors are , indicating the first The normalized average received signal strength indicator measurement of K roadside units corresponding to K reference points, therefore the length is K, the first... The database vectors are Specifically: （4） in, For the first Each database vector corresponds to a reference point coordinate. ; Step 2: When the user is driving a vehicle in the tunnel, measure the received signal strength indicator of the long-term evolution signal at the current location of the vehicle in the tunnel and construct the user data vector. Step 2 specifically includes: Step 2.1 Measure the received signal strength indicator (RSI) values ​​of the Long Term Evolution (LTE) signals transmitted by the roadside unit multiple times at the current vehicle location and save them as a user data matrix; The user data matrix is ​​represented as follows: （5） in, User data matrix; Indicates from the first The first roadside unit obtained the first The measured value of the received signal strength indicator. This indicates the length of the user data, which is the total number of received signal strength indicator measurements obtained from the roadside unit; Step 2.2 Normalize the measured values ​​of the received signal strength indicator in the user data matrix and calculate the average value to obtain the user data vector; The method for normalizing the measured values ​​of the received signal strength indicator in the user data matrix is ​​as follows: （6） in, and They are the first The mean and variance of the received signal strength indicator values ​​emitted by each roadside unit; For users from the first The first roadside unit obtained the first Subnormalized received signal strength indicator measurement; Then move the user from the first The roadside unit obtained Calculate the average of the normalized received signal strength indicator measurements: （7） in, For users from the first The average of the normalized received signal strength indicator measurements obtained from each roadside unit; The user data vector is: （8） in, Represents a user data vector; Step 3: Use Euclidean distance to compare the differences between the database vector and the user data vector, and take the coordinates of the reference point corresponding to the minimum Euclidean distance as the vehicle position.

2. The positioning method using LTE received signal strength indicator in a tunnel environment according to claim 1, characterized in that, Step 3 specifically includes: Step 3.1 Traverse the user data vector at this point. Given a database vector, use Euclidean distance to measure the difference between the database vector and the user data vector to obtain an Euclidean distance vector, and then select the minimum Euclidean distance value among the Euclidean distance vectors. The corresponding reference point coordinates This refers to the vehicle's current position. For database vectors and the user data vector at the current location in the tunnel. The Euclidean distance is used to compare the differences between two vectors: （9） in Represents user data vector and database vector The Euclidean distance between them; When there is a location requirement, the user data vector at time t is traversed. Given a database vector, obtain From the Euclidean distances, we obtain the Euclidean distance vector: （10） in, Let represent the Euclidean distance vector at time t. This represents the Euclidean distance between the user data vector and the nth database vector at time t. Step 3.2 Obtain the next time step using the method described in Step 2. The user data vector, and the next moment The coordinates of the reference point located in step 3.1 of the user data vector traversal. After Given a database vector, the coordinates of the reference point corresponding to the smallest Euclidean distance value are used as the vehicle's position at the next moment. Reference point coordinates coordinate vector at the reference point The serial number in; The next moment The remaining user data vectors to be located The database vectors are still obtained using the method in step 3.

1. Given Euclidean distances, we obtain the Euclidean distance vector for the next time step: （11） in, express The Euclidean distance vector corresponding to the user data at any given time. express The Euclidean distance between the user data vector at time step n and the nth database vector is calculated, and the minimum Euclidean distance value is recorded. The corresponding reference point coordinates This refers to the vehicle's current position.

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