Passenger management system for a travel vehicle using short-range communication technology and method therefor

Abstract

The present invention relates to a passenger management system and method for a travel vehicle, and more specifically, to a smart management system and method for a travel vehicle that improves the efficiency and safety of group travel operations by using near-field communication technology and server-based data processing logic to automatically identify in real time whether group travelers board or disembark from the vehicle, dynamically control resources according to the operating status of the system, and provide objective operation management information to the manager.

Description

Technology Field

[0001] The present invention relates to a passenger management system and method for a travel vehicle, and more specifically, to a smart management system and method for a travel vehicle that improves the efficiency and safety of group travel operations by using near-field communication technology and server-based data processing logic to automatically identify in real time whether group travelers board or disembark from the vehicle, dynamically control resources according to the operating status of the system, and provide objective operation management information to the manager. Background Technology

[0002] Recently, it has become common for large groups of people to travel in a single vehicle, such as a bus, for group tours, school trips, and corporate workshops. In such group travel, multiple stops are visited according to a fixed schedule, and it is essential to ensure that all members board the vehicle on time at each stop.

[0003] Conventional passenger management methods typically involved group leaders or managers manually verifying the number of passengers using lists or relying on voluntary reports from passengers. This approach not only increased the physical fatigue of managers but also frequently caused disruptions to the overall travel itinerary due to delays during the verification process. Furthermore, there was a constant risk of safety accidents caused by human error—specifically, the omission of passengers due to managerial mistakes or negligence.

[0004] Attempts were made to utilize short-range communication technologies such as RFID or beacons to address these issues, but the simplistic approach of merely recognizing everyone near the vehicle as "boarding" had technical limitations. For instance, frequent detection errors where non-boarders passing by or waiting briefly in front of the entrance were mistaken for passengers lowered the system's reliability. Furthermore, in crowded situations where a large number of people boarded simultaneously, data for some individuals was sometimes omitted due to the processing capacity limitations of the recognition equipment.

[0005] Therefore, there is a growing need for a systematic management system that goes beyond simply identifying personnel to clearly distinguish between actual boarding and non-boarding situations, actively responds to various changes in the operational environment to ensure data integrity, and provides administrators with reliable operational management information. The problem to be solved

[0006] The present invention has been devised to solve the problems of the prior art as described above, and the problem to be solved by the present invention is as follows.

[0007] The first task is to provide a multi-stage conditional judgment logic that comprehensively assesses the temporal continuity, spatial proximity, and duration of stay of near-field communication signals, thereby enhancing the accuracy and reliability of determining boarding status by clearly distinguishing non-boarding situations, such as loitering near or brushing past a vehicle, from actual boarding situations.

[0008] The second task is to diagnose situations where the system load fluctuates in real time, such as event surges caused by a large number of passengers boarding simultaneously, using objective indicators, and to dynamically control the scan intensity of the recognition device accordingly, thereby saving system resources in quiet situations and enabling stable recognition without data loss in crowded situations.

[0009] The third task is to support rapid and consistent decision-making by managers and improve operational efficiency by providing clear status information—such as 'early departure possible,' 'on-time departure possible,' or 'delayed departure'—based on objective criteria like passenger capacity and elapsed time, thereby replacing departure decisions that previously relied on the manager's subjective judgment.

[0010] The fourth task is to reduce managerial 'notification fatigue' and enable immediate response to critical and urgent situations by providing differentiated alerts based on the severity of the situation, through a comprehensive evaluation of the scale of the problem, temporal urgency, and managerial response efforts in the event of missing passengers.

[0011] The problems of the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0013] In a system for managing passengers of a travel vehicle according to an embodiment of the present invention for solving the above problem,

[0014] A server unit including a database for storing traveler information and on which multiple software modules are executed;

[0015] An administrator terminal unit connected to the above server unit via communication to display operation status information to the administrator and receive input from the administrator;

[0016] A traveler identification unit that transmits a signal identifying individual travelers; and

[0017] An in-vehicle recognition unit installed inside the travel vehicle that receives the signal from the traveler identification unit and transmits it to the server unit;

[0018] Includes,

[0019] The above server unit is,

[0020] Executes a boarding status management module that determines whether the traveler is on board based on a signal received from the in-vehicle recognition unit, and

[0021] It determines the real-time load status of the system and controls the operation of the in-vehicle recognition unit, and

[0022] The above-mentioned administrator terminal unit is,

[0023] It is characterized by executing a visualization notification module that visually displays the determination result received from the above-mentioned server unit and generates a notification according to the situation,

[0024] The above-mentioned boarding status management module is,

[0025] A first condition for determining whether a signal from a specific traveler identification unit is continuously detected more than a first set number of times within a first set time;

[0026] A second condition for determining whether the total detection time of the corresponding signal exceeds a preset second time when the first condition above is satisfied; and

[0027] A third condition for determining whether the average received signal strength measured during the second time period is greater than or equal to a preset first threshold when the second condition is satisfied;

[0028] Determine sequentially,

[0029] By determining the status of the traveler as 'boarding' only when all of the above first, second, and third conditions are satisfied,

[0030] It is characterized by preventing judgment errors that mistake non-passengers passing near the vehicle or staying near the entrance / exit for a short time as 'boarding', and

[0031] The above system is,

[0032] It further includes a calibration mode that collects a set of first signal strength values ​​measured inside the vehicle and a set of second signal strength values ​​measured outside the vehicle during the test phase,

[0033] The above first threshold is,

[0034] By being set by calculating the midpoint between the arithmetic mean of the first signal strength values ​​and the arithmetic mean of the second signal strength values,

[0035] It is characterized by providing objective judgment criteria optimized for signal strength distributions that differ depending on the installed vehicle environment, and

[0036] The above system is,

[0037] It further includes a calibration mode that collects a data set of dwell times for events classified as actual 'boarding' during the test phase, and

[0038] The above second time is,

[0039] By being set by calculating the value obtained by subtracting the value obtained by multiplying the standard deviation of the data set by a preset multiple from the arithmetic mean of the above dwell time data set,

[0040] It is characterized by ensuring the stability of the judgment by setting the minimum time required for a statistically significant normal boarding event as a threshold, and

[0041] The above server unit is,

[0042] It determines the system load status by monitoring the length of the event processing queue and the average processing latency collected in real time, and

[0043] The above load state,

[0044] If the length of the above queue exceeds a second threshold or the average processing delay time exceeds a third threshold, and is determined to be in a 'loaded state', the scan duty cycle of the in-vehicle recognition unit is increased to a predefined 'enhanced scan duty cycle', and

[0045] If the length of the queue and the average processing delay time are both determined to be in a 'normal state' below their respective thresholds, by controlling the scan duty cycle to be lowered to the 'default scan duty cycle',

[0046] It is characterized by preventing data loss during event surges caused by multiple travelers boarding simultaneously and saving system resources during idle periods,

[0047] The above second threshold and the above third threshold are,

[0048] Calculate the amount of change in the rate of change of average processing latency while gradually increasing virtual events in the system, and

[0049] By experimentally identifying and setting the point where the amount of change in the above rate of change increases rapidly above a preset threshold, that is, the inflection point of system performance degradation, through load testing,

[0050] It can be characterized by providing objective state transition criteria optimized for the hardware specifications of the system. Effects of the invention

[0052] According to the present invention for solving the above-mentioned problems, the following effects can be expected.

[0053] It has the effect of improving judgment accuracy and reliability. Through a multi-stage conditional judgment logic, this invention overcomes the limitations of conventional technology that made judgments based solely on the presence or absence of a simple signal, and selectively recognizes only the actual boarding situation. As a result, it significantly reduces judgment errors that mistake non-passengers around the vehicle for passengers, allowing administrators to trust the system's automatic judgment results and minimize the need for manual reconfirmation.

[0054] It has the effect of increasing system stability and resource efficiency. This invention dynamically controls scan intensity in conjunction with the real-time load status of the system. Through this, it actively increases data processing capacity during congestion situations where events surge, ensuring stable operation without recognition omissions, while conversely, it minimizes unnecessary system resource and power consumption during idle states, thereby maximizing operational efficiency.

[0055] The present invention provides the manager with data-based processed decision-making information, such as 'departure availability status.' By doing so, it reduces deviations caused by the manager's experience or subjectivity and supports the decision-making of departures based on consistent and objective criteria in all situations, thereby contributing to reducing unnecessary waiting times and increasing the on-time operation rate.

[0056] It has the effect of strengthening crisis management capabilities and increasing safety. By providing differential alert levels based on the severity of the situation, this invention encourages managers to immediately recognize and prioritize responses to emergency situations, such as multiple missing passengers or imminent departure times. This fundamentally prevents the risk of passenger omissions caused by human error on the part of managers, thereby significantly improving the safety of group travel.

[0057] The effects according to the present invention are not limited to those exemplified above, and a wider variety of effects are included within the present invention. Brief explanation of the drawing

[0059] Figure 1 illustrates an overall relationship diagram according to the present invention. Figure 2 illustrates a flowchart between all components according to the present invention. Figure 3 illustrates a flowchart of Process 1 according to the present invention. Figure 4 illustrates a flowchart of process 2 according to the present invention. Figure 5 illustrates a flowchart of process 3 according to the present invention. Figure 6 illustrates a flowchart of process 4 according to the present invention. Specific details for implementing the invention

[0060] Hereinafter, various embodiments are described in more detail with reference to the attached drawings. The embodiments described in this specification may be modified in various ways. Specific embodiments may be depicted in the drawings and described in detail in the detailed description. However, specific embodiments disclosed in the attached drawings are intended only to facilitate understanding of various embodiments. Accordingly, the technical concept is not limited by specific embodiments disclosed in the attached drawings, and it should be understood that it includes all equivalents or substitutions that fall within the spirit and scope of the invention.

[0061] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but these components are not limited by the aforementioned terms. The aforementioned terms are used solely for the purpose of distinguishing one component from another.

[0062] Functions related to artificial intelligence according to the present disclosure are operated through a processor and memory. The processor may be composed of one or more processors. In this case, the one or more processors may be general-purpose processors such as CPUs, APs, and DSPs (Digital Signal Processors), graphics-dedicated processors such as GPUs and VPUs (Vision Processing Units), or artificial intelligence-dedicated processors such as NPUs. The one or more processors control the processing of input data according to predefined operation rules or artificial intelligence models stored in memory. Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0063] The predefined rules of operation or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a basic artificial intelligence model is trained using a number of training data by a learning algorithm, thereby creating predefined rules of operation or artificial intelligence models configured to perform desired characteristics (or objectives). Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is executed, or it may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0064] An artificial intelligence model can be composed of multiple neural network layers. Each of the multiple neural network layers has multiple nodes and weight values, and performs neural network operations through calculations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, multiple weights can be updated so that the loss value or cost value obtained by the artificial intelligence model during the learning process is reduced or minimized. Additionally, to minimize the loss value or cost value, multiple weights can be updated in a direction that minimizes the gradient associated with the loss value or cost value. Artificial neural networks may include deep neural networks (DNNs), such as Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Restricted Boltzmann Machines (RBMs), Deep Belief Networks (DBNs), Bidirectional Recurrent Deep Neural Networks (BRDNNs), or Deep Q-Networks, but are not limited to the examples mentioned above.

[0065] A network is a network that serves as a transmission path for web pages; it may be a closed network such as a LAN (Local Area Network) or WAN (Wide Area Network), but it is desirable for it to be an open network such as the Internet. The Internet refers to a global open computer network structure that provides the TCP / IP protocol and various services existing at its upper layers, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), SNMP (Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service).

[0066] Terminals can be implemented in various forms. For example, the terminals described in this specification may include mobile terminals such as smartphones, tablet PCs, PDAs, portable multimedia players, and MP3 players, as well as fixed terminals such as smart TVs and desktop computers.

[0067] In this specification, terms such as “comprising” or “having” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. When a component is described as being “connected” or “connected” to another component, it should be understood that it may be directly connected to or connected to that other component, or that there may be other components in between. On the other hand, when a component is described as being “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

[0068] Meanwhile, a "module" or "part" for a component as used in this specification performs at least one function or operation. Furthermore, a "module" or "part" may perform a function or operation by hardware, software, or a combination of hardware and software. Additionally, a plurality of "modules" or a plurality of "parts," excluding a "module" or "part" that must be performed on specific hardware or on at least one processor, may be integrated into at least one module. A singular expression includes a plural expression unless the context clearly indicates otherwise.

[0069] In addition, power, power transmission, and control therefor for the following assembly configurations and embodiments, including "by control," follow conventional technology including terminals, applications, hardware control modules, etc., so they are omitted to avoid redundancy.

[0070] In addition, the operation embodiments and configurations described in a general manner without being explained in detail below follow the prior art and are omitted in order to focus on describing the purpose of the present invention and the resulting effects.

[0071] Furthermore, in describing the present invention, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the invention, such detailed description is abbreviated or omitted.

[0072] The travel vehicle passenger management system of the present invention is a system that checks and manages the status of passengers in a vehicle in real time based on designated travel information, and is configured to include a server unit (100), an administrator terminal unit (200), a traveler identification unit (300), and an in-vehicle recognition unit (400), wherein the server unit (100) and the administrator terminal unit (200) operate organically by executing a plurality of software modules.

[0073] The server unit (100) acts as the central processing unit of the entire system and is configured to include a database, synthesize all information, and perform operations for each module. The database includes a 'travel master table' containing travel information, a 'traveler table' containing information for each traveler, and an 'event log table' that records real-time boarding status and location information, and these maintain data consistency through cross-reference relationships. The server unit (100) receives an identification ID and a received signal strength indicator value from the in-vehicle recognition unit (400), transmits the analysis results to the administrator terminal unit (200) for visual display, and transmits a scan duty cycle control command to the in-vehicle recognition unit (400).

[0074] The travel information management module (110) executed in the above server unit (100) is a software module that stores and manages basic travel information, such as a travel itinerary and a list of travelers. The 'travel-related information' managed by the travel information management module (110) includes specific data fields that serve as criteria for subsequent logic judgment, such as 'total number of travelers', 'number of pre-allowed non-boarders', and 'allowed boarding time per stop'. The travel information management module (110) provides data so that the 'determination of departure availability' logic can directly query and use core criteria data, such as 'mandatory number of passengers' and 'allowed boarding time', and performs an important role in providing criteria essential to other judgment logics of the system beyond simple information storage.

[0075] The boarding status management module (120) executed in the server unit (100) is a software module that performs core logic for determining boarding status and updating status in real time. The boarding status management module (120) ensures specificity and reproducibility by executing a specific operation algorithm that includes a 'sequential AND combined filtering' method, three judgment criteria such as continuous detection, minimum stay, and signal strength, and a data-based threshold setting methodology. In addition, it complements the limitations of the automation system by including 'signal instability response logic' and 'manual processing functions by the manager'.

[0076] The above-mentioned administrator terminal unit (200) is a device such as a smartphone or tablet used by an administrator, and provides a user interface for information input and status monitoring. The monitoring screen of the above-mentioned administrator terminal unit (200) is configured in the form of a 'seat layout diagram,' where the seat changes from red, signifying 'non-boarding,' to green, signifying 'boarding,' the color and text of the departure button change according to the 'departure availability status,' and a warning banner of a specific color is displayed at the top according to the 'alarm level.' Additionally, the above-mentioned administrator terminal unit (200) performs active control functions that include a 'manual boarding processing' function, 'early departure' and 'forced departure' button functions, and a function to attempt to contact non-boarders, thereby enabling the administrator's input to change the state of the system or be utilized as judgment criteria data for the logic.

[0077] The visualization notification module (210) executed in the above-mentioned administrator terminal unit (200) is a software module that visualizes data received from the server unit (100) and generates situational notifications. The visualization notification module (210) provides 'situational notifications' in a differential manner in three stages: 'caution (yellow banner)', 'warning (orange banner and vibration)', and 'urgent (red flashing and warning sound)'. Furthermore, beyond simply displaying the raw data received from the server, it converts it into processed 'decision information', such as 'early departure possible' or 'departure delayed', and provides it to the administrator.

[0078] The above traveler identification unit (300) is a device for identifying individual travelers and may take the form of a smartphone's low-power Bluetooth (BLE) or radio frequency identification (RFID) card. The above traveler identification unit (300) transmits a signal capable of measuring a 'Received Signal Strength Indicator (RSSI)' along with an 'identification ID'. If the above traveler identification unit (300) is a smartphone, it is configured to periodically transmit low-power Bluetooth advertising packets even in a background state, so that the system can recognize them even without the user directly running the application.

[0079] The vehicle recognition unit (400) is a hardware device installed inside the vehicle to detect the traveler identification unit (300). The 'detection' operation of the vehicle recognition unit (400) is controlled by a specific parameter called the 'scan duty cycle,' and this value is variably controlled to 20%, 50%, 80%, etc., depending on the load state of the server unit (100). In addition, it includes a 'false detection surge response' logic that determines that an abnormal surge in data is a sensor malfunction and sends an alert to the administrator, thereby providing a mechanism for the system to recognize and respond to the possibility of malfunction caused by signal interference, etc.

[0080] Below, prior to describing in detail the core operation process of the travel vehicle passenger management system according to the present invention, the overall organic operation is briefly described.

[0081] The system according to the present invention first filters the continuity, persistence, and proximity of a signal received from an in-vehicle recognition unit (400) in multiple stages through a boarding confirmation conditional determination logic (process 1) to accurately identify only the actual passengers.

[0082] At the same time, the system executes a system load-linked scan control logic (process 2) to detect a surge in events in real time, such as multiple passengers boarding at the same time, and automatically increases the scan intensity of the in-vehicle recognition unit (400) to ensure stable recognition without data omission.

[0083] Real-time boarding status data accurately aggregated through the above processes is transmitted to the manager terminal unit (200), and the multi-condition-based departure availability determination logic (process 3) comprehensively analyzes the current number of passengers and the scheduled time to provide the manager with clear decision-making information such as 'early departure possible' or 'departure delayed'.

[0084] If there are missing passengers even though the departure time is imminent, the situational multi-stage alert generation logic (Process 4) automatically evaluates the severity of the problem (number of people, temporal urgency, etc.) and generates differential alerts such as 'Caution', 'Warning', and 'Urgent' to induce a quick and accurate response from the manager.

[0085] As such, each process of the present invention is organically interconnected to simultaneously achieve accurate recognition, stable operation, efficient decision support, and preemptive crisis management.

[0087] The boarding status management module (120) of the present invention defines multiple judgment criteria that are physically clear and mutually complementary and executes a command to comprehensively evaluate them in order to prevent judgment errors that may occur by relying on a single signal detection. The first criterion, the number of consecutive detections, is a criterion to prevent mistaking a non-passenger who happens to pass quickly near the vehicle or temporary signal interference as 'boarding.' Based on the technical fact that one-off or discontinuous signal detections are highly likely to indicate a situation where there is no actual intention to board, a condition is imposed that a signal must be received continuously at least a certain number of times within a preset time. The second criterion, the minimum dwell time, is a criterion to filter out situations that do not lead to actual boarding, such as staying briefly near the entrance door or waiting for a co-passenger. Based on empirical data that even if a signal is detected, if its duration is extremely short, it is difficult to regard it as an actual passenger, a condition is imposed that the detected signal must last for a meaningful minimum time. The third criterion, effective signal strength, is designed to prevent misidentifying individuals outside the vehicle as passengers inside. Since wireless signal strength has the physical characteristic of decreasing inversely proportional to distance, it utilizes the fact that the signal from the identification unit located inside the vehicle is received more clearly and strongly than when it is outside. Based on this, it is set to a minimum signal strength threshold that indicates a stable occupancy state.

[0088] The aforementioned three judgment criteria consist of a filtering procedure using a 'sequential AND combination method,' which ensures both computational efficiency and logical validity. This processing procedure first determines continuous detection, determines the minimum stay only for signals that pass this stage, and finally determines the signal strength only when both conditions are met. A command to finalize the 'boarding' status is executed only when all three criteria are satisfied. This sequential filtering method enhances the overall processing efficiency of the system by prioritizing the inspection of continuous detection conditions, which occur most frequently and have low computational costs, thereby minimizing unnecessary subsequent operations, such as calculating stay time and average signal strength. This significantly contributes to reducing the system load in real-world situations where a large number of travelers board intensively within a short period.

[0089] The data used for the above judgment criteria is obtained in real time from the in-vehicle recognition unit (400). For example, the in-vehicle recognition unit (400) scans the surrounding traveler identification unit (300) at 0.5-second intervals to collect identification IDs and signal strength values. Based on the collected data, the first criterion, the number of consecutive detections, counts whether a specific identification ID is included in the scan list four or more times consecutively within a preset time, for example, 3 seconds. The second criterion, the minimum dwell time, measures whether the time from the first time a specific identification ID is detected to the last time it is detected lasts for 2.0 seconds or more. The third criterion, the effective signal strength, calculates and compares whether the arithmetic mean of the signal strength values ​​collected during the 2.0 seconds is -75 decibel milliwatts or higher.

[0090] The result determined as 'boarding' by this logic is organically linked with various functions of the system to automatically transmit subsequent commands. A command is transmitted so that the status information of the traveler is updated from 'not boarding' to 'boarding', and this information is immediately recorded in the database of the server unit (100). In addition, the traveler's seat on the seat layout screen of the administrator terminal unit (200) is immediately changed from red, which signifies not boarding, to green, which signifies boarding, thereby providing intuitive status information to the administrator. Finally, the data is updated so that the total number of passengers increases by 1 and the number of passengers not boarding decreases by 1, which is reflected in the real-time occupancy rate calculation.

[0091] The processing procedure for a specific scenario, for example, when a traveler 'Hong Gil-dong' boards through the bus door, is described step-by-step as follows. In the initial signal detection step, at time reference 0.0 second, the recognition unit (400) inside the vehicle first detects the identification unit of 'Hong Gil-dong', and the system starts counting. Subsequently, in the continuous detection count determination step, the system checks for continuous detection within a 3-second time window, and if the signal is detected 4 times consecutively over 0.5 seconds, 1.0 seconds, and 1.5 seconds, it determines that the first criterion has been satisfied and executes a command to proceed to the next step. In the minimum dwell time determination step, even after the first criterion is satisfied, if the signal is continuously detected and 2.0 seconds have elapsed since the initial detection, it determines that the second criterion has been satisfied and proceeds to the next step. In the effective signal strength determination step, the system calculates the average of the 5 signal strength values ​​collected during the initial 2.0 seconds, and if the average value is -78.2 decibel milliwatts, which does not satisfy the third criterion of -75 decibel milliwatts, the determination is withheld. In the judgment deferral and re-evaluation stage, the average signal strength over the past 2.0 seconds is recalculated, including additional signals detected at the 2.5-second mark, and if the average value is -73.5 decibel milliwatts, which satisfies the third criterion, the system enters the final confirmation stage. In the final 'boarding' confirmation stage, since all three criteria are satisfied, the system transmits a command to finally confirm the status of 'Hong Gil-dong' as 'boarding' at the 2.5-second mark.

[0092] This logic enhances reliability through multiple conditions, but ensures system stability by including a supplementary device to prepare for exceptional situations that may occur in the actual field. To address signal instability, even if a signal is missed once during continuous detection, if it falls within a preset allowable number of missed detections, e.g., one time, it is considered to maintain continuity, thereby robustly responding to temporary signal instability. Additionally, to address equipment malfunction, an interface is provided to allow an administrator to manually process the traveler as 'boarding' from the administrator terminal unit (200) in case the system fails to recognize a specific traveler even though they have clearly boarded. This manual processing record is stored as a separate log and a command is transmitted to be used for future system inspection.

[0093] The effectiveness becomes clear when comparing the operation results of the prior art and the present invention by scenario. When a traveler quickly passes by a bus, the prior art using a single-signal detection method mistakes this for "boarding," whereas the present invention correctly maintains the "not boarding" state because the number of consecutive detections falls short of the threshold, thereby preventing false positives. Even when a traveler stays in front of the bus door for 1.5 seconds and then leaves, the prior art mistakes this for "boarding," but the present invention prevents false positives by maintaining the "not boarding" state because the minimum dwell time threshold is not met. On the other hand, in normal situations where an actual traveler boards and moves to a seat, both the prior art and the present invention correctly determine that the traveler has "boarded."

[0094] The results of 10 simulation examples assuming various situations demonstrate the consistency and accuracy of the logic of the present invention. For example, Examples 1, 5, 7, 9, and 10, which satisfy all conditions regarding the number of consecutive detections, dwell time, and average signal strength, are determined as 'boarding'. On the other hand, Examples 2 and 6, which lack the number of consecutive detections; Example 4, which lacks the dwell time; and Examples 3 and 8, which have weak signal strength, are all accurately determined as 'not boarding'.

[0095] The judgment rules of the present invention are clearly defined by a rule table. Rule 1 requires that the number of consecutive detections be greater than or equal to a first threshold and filters out transient signal detection. Rule 2 requires that the minimum dwell time be greater than or equal to a second threshold and filters out short-term dwell situations. Rule 3 requires that the average signal strength be greater than or equal to a first threshold and prevents misidentification of personnel outside the vehicle. The final judgment maximizes judgment reliability through triple filtering by combining all three of these rules using a logical AND operation.

[0096] The three judgment rules presented in this invention possess a technical necessity for resolving transient interference, short-term stays, and internal / external ambiguity, which are representative factors hindering accuracy in radio frequency-based location recognition systems. Since each rule is based on objective physical quantities such as count, time, and signal strength, the judgment logic of this invention is a concrete and rational configuration for solving technical problems.

[0097] By adopting the aforementioned multi-stage conditional judgment logic, the present invention achieves clear technical effects. Compared to a single-condition method, it improves judgment accuracy by effectively distinguishing non-boarding situations similar to actual boarding scenarios, thereby minimizing false positives. Furthermore, the increased reliability of automated judgment results significantly reduces the need for manual intervention by administrators, thereby enhancing management efficiency. The accurate real-time boarding status data thus obtained serves as the foundation for guaranteeing the accuracy and reliability of subsequent management functions, such as departure permission determination and non-boarder alerts, which will be described later.

[0098] The terms and threshold values ​​used in this invention have clear criteria. Continuous detection refers to a state in which a specific identification unit is continuously detected without omission within the scan cycle of the recognition unit (400) within the vehicle, and the minimum dwell time refers to the time from when the specific identification unit begins to be continuously detected until when detection ends. All threshold values ​​used in this invention are not fixed constants, but can be set or changed by the operator through a setting interface for the administrator, taking into account the size and internal structure of the vehicle to be operated, the type and performance of the recognition device used, and the expected maximum passenger density. Additionally, the system includes a function that automatically suggests recommended threshold values ​​based on test data through a calibration mode during initial system installation, which clarifies that the threshold values ​​have a reasonable basis for being optimized for the actual operating environment.

[0099] Calibration simulation and calculation for threshold setting

[0100] The calibration mode of the above system collects test data and applies statistical formulas to derive optimal threshold values ​​in specific vehicle and equipment environments. The following is data collected through 10 test boarding and non-boarding scenarios after installing an RFID reader on the door of a specific bus model (Hyundai Universe).

[0101] [Table 1-1]

[0102]

[0103] Based on the data in [Table 1-1] above, the system calculates the recommended threshold value through the following calculation formula.

[0104] Total sum of internal average RSSI = -455, Total sum of external average RSSI = -809

[0105] Number of internal measurements = 7, Number of external measurements = 10

[0106] Recommended threshold = ((-455 / 7) + (-809 / 10)) / 2 = (-65.0 + -80.9) / 2 -73.0 dBm

[0107] This aims to minimize the misclassification rate between the two groups by setting the statistical midpoint of the signal strength distribution inside and outside the vehicle as a threshold.

[0108] Average actual boarding time = (3.5+4.1+3.8+4.5+3.2+5.1+4.8) / 7 4.14 seconds

[0109] Standard deviation of actual boarding time 0.68 seconds

[0110] Recommended threshold = 4.14 - (1.5 × 0.68) = 4.14 - 1.02 3.12 seconds

[0111] This is intended to filter out non-boarding situations that happen to be measured as long by setting the minimum time required by most normal boarding events (about 93%) as a threshold, thereby ensuring the stability of the judgment.

[0112] The simulation results to verify how accurately the logic of the present invention operates when the calculated recommended threshold (t_dwell=3.12 seconds, S_RSSI_th=-73.0dBm) is applied are as follows.

[0113] [Table 1-2]

[0114]

[0115] As can be seen in [Table 1-2] above, prior art that uses only RSSI thresholds commits the error of mistaking external loitering or waiting in front of the door for 'boarding'. On the other hand, the present invention achieves the technical effect of effectively preventing false positives and increasing the reliability of the overall judgment by applying multiple thresholds set based on data, thereby accurately filtering these ambiguous situations as 'insufficient time' or 'insufficient RSSI'.

[0117] To solve the problems of resource waste and data loss caused by scanning at a fixed cycle, the server unit (100) of the present invention defines objective performance indicators that measure the real-time load status of the system as judgment criteria and executes commands to dynamically control scanning operations based on these criteria. The first criterion, the event processing queue length, is an indicator that directly represents the amount of data flowing into the system, i.e., the 'input load.' Since the queue length increases rapidly when recognition events surge due to multiple travelers boarding simultaneously, the increase in the queue length is considered a precursor symptom of potential data processing delay or loss, and is used as a key criterion for adjusting scan intensity. The second criterion, the average processing delay time, is an indicator that represents the time required to analyze received events and determine whether to 'board,' i.e., the 'processing performance.' Since this processing time increases if the central processing unit occupancy rate of the server is high or if a bottleneck occurs in database I / O, the increase in processing delay time is judged to mean an internal system overload, and is comprehensively considered together with the input load to accurately diagnose the overall state of the system.

[0118] The two judgment criteria mentioned above are combined according to a 'rule-based multi-stage state determination method' to determine the current state of the system, which ensures more stable and predictable operation than a simple proportional control method. In the above processing procedure, the server unit (100) compares the first criterion and the second criterion with a plurality of predefined threshold values ​​to determine the state of the system as one of a 'normal state', a 'caution stage', or a 'warning stage'. Each state is linked to a different scan duty cycle value, and a control command is automatically transmitted to the in-vehicle recognition unit (400) to operate at the corresponding duty cycle according to the state determination result. The method of controlling by dividing into discrete states and stages instead of controlling with continuous values ​​prevents the scan intensity from fluctuating continuously as the system reacts oversensitively to minor load variations, thereby providing technical advantages that increase the overall stability of the system and clarify the control logic to facilitate maintenance.

[0119] The data used for the above judgment criteria is measured and calculated in real time within the server unit (100). The event processing queue length counts in real time the number of events currently waiting and not being processed by the message queue module of the server unit (100). The average processing delay time is calculated by measuring the time difference between when each event enters the queue and when the final judgment is completed, and by taking the moving average of the delay times of events processed over the last minute. For example, the threshold for the first criterion is set to 50 for entering the caution phase and 150 for entering the warning phase, and the threshold for the second criterion is set to 150 milliseconds for entering the caution phase and 300 milliseconds for entering the warning phase.

[0120] The core operation parameters of the in-vehicle recognition unit (400) are changed in real time according to the determined system state. When determined to be a 'normal state', a control signal is transmitted to operate at a basic scan duty cycle, e.g. 20%, to minimize power consumption. When determined to be a 'caution stage', a command is transmitted to increase the scan duty cycle, e.g. 50%, to process increasing events without omission. When determined to be a 'warning stage', a maximum scan duty cycle, e.g. 80%, is increased to control the system to focus on ensuring the integrity of data processing even under system overload conditions.

[0121] The processing procedure for a specific scenario, for example, when 50 group tourists board a bus at once and the event surges, is described step-by-step as follows. In the initial stage, when the system is quiet with no passengers boarding, the queue length is 5 and the average processing delay time is 80 milliseconds, so the system maintains a 'normal state' and the in-vehicle recognition unit (400) operates with a basic scan duty cycle of 20%. Subsequently, when group tourists begin boarding and the event surges, increasing the queue length to 75, the system determines this as exceeding the threshold for entering the caution stage and changes the system state to the 'caution stage'. Upon the state change, the server unit (100) immediately sends a control command to the in-vehicle recognition unit (400) to increase the scan duty cycle to 50%. Afterwards, when the processing load on the server increases due to a surge in passengers and the average processing delay time increases to 320 milliseconds, the system determines this as exceeding the threshold for entering the warning stage and raises the system state to the 'warning stage'. Accordingly, the server unit (100) sends a control command again to maximize the scan duty cycle to 80% and prevent event loss. Finally, when the boarding of all passengers is completed and the system indicators stabilize, the system state returns to a 'normal state' and automatically sends a command to lower the scan duty cycle to 20%.

[0122] This logic applies a minimum maintenance time, e.g., 10 seconds, upon state change to prevent the state from repeatedly switching between 'Caution' and 'Normal' in short cycles. In other words, it controls the system so that when it enters the 'Caution' stage, it maintains that state for at least 10 seconds before returning to the 'Normal' state. Additionally, if the false detection rate increases abnormally rapidly and the queue length increases along with it, it determines this as a sensor malfunction and performs exception handling to issue a 'Sensor Inspection Required' alert to the administrator and lower the data processing priority of the corresponding recognition unit.

[0123] The effectiveness becomes clear when comparing the operational results of the prior art and the present invention by scenario. In quiet situations, such as prolonged stops, the prior art using a fixed-period scanning method consumes unnecessary resources; however, the present invention maximizes resource efficiency and saves energy by lowering the scan intensity. Conversely, in crowded situations, such as the simultaneous boarding of a group of passengers, the prior art carries a risk of data loss; whereas the present invention increases the scan intensity to reliably process all events and ensure data integrity.

[0124] The judgment rules of the present invention are defined by a table having clear conditions and control actions according to the system state. The 'normal state' is when both the queue length and the processing delay are below a default threshold and operates with a default duty cycle. The 'cautionary phase' is when either one exceeds the default threshold but is below the warning threshold and operates with an enhanced duty cycle. The 'warning phase' is when either one exceeds the warning threshold and operates with a maximum duty cycle.

[0125] The rules of the present invention are based on the technical necessity for stable system operation. Since all computer systems possess finite resources, dynamically allocating resources according to load conditions is an essential control logic to ensure system availability and stability; the validity of the present invention is clear as it utilizes the most universal and objective indicators in the field of information and communication for this purpose.

[0126] By adopting the load-linked scan control logic described above, the present invention achieves clear technical effects, including securing system stability and availability, increasing resource efficiency, and guaranteeing data integrity. It automatically increases system processing capacity during an event surge to prevent data loss or service delays, and minimizes unnecessary resource consumption by automatically reducing operating intensity when the system is idle.

[0127] The terms and threshold values ​​used in this invention have clear criteria. The scan duty cycle refers to the ratio of the time during which the actual scan operation is active within the total scan cycle. The threshold values ​​for each stage of queue length and processing delay time used in this invention are not arbitrary constants; rather, they are set by experimentally identifying the inflection point at which performance degradation begins under the corresponding hardware specifications through standardized load testing performed during the initial stages of system construction. Furthermore, the invention includes a function that allows the administrator to periodically tune the threshold values ​​or the system to automatically correct them by statistically analyzing long-term performance data collected during system operation, thereby ensuring that the threshold values ​​are based on objective grounds derived from the system's actual processing capabilities.

[0128] Load test simulation and computation for threshold setting

[0129] The above system measures the actual performance limits of the hardware through load testing and objectively sets the threshold values ​​of the scan control logic based on this. The following is load test data measured while increasing virtual events on specific server specifications.

[0130] [Table 2-1] Load test data for threshold setting

[0131]

[0132] Based on the data in [Table 2-1] above, the system finds the performance degradation inflection point and sets the threshold value through the following calculation formula.

[0133] It can be seen that when the load increases from 60 to 70, the change in the rate of change of delay time (Δ²T_L) increases rapidly from 0.7 to 1.5.

[0134] This corresponds to the inflection point where the processing delay graph changes from a linear increase to an exponential increase, and it is the point where the system begins to be unable to handle the load.

[0135] Recommended threshold = Average processing delay at the point where the inflection point begins = 170ms

[0136] Attention phase entry threshold = 170ms × 0.5 = 85ms

[0137] The simulation results for verifying the effect of the dynamic control logic of the present invention on system stability when the calculated recommended threshold (Caution: 85ms, Warning: 170ms) is applied are as follows.

[0138] [Table 2-2]

[0139]

[0140] Table 2-2 above shows that prior art using a fixed scan intensity can cause processing delays to exceed a critical threshold during a sudden surge in load, thereby inducing data loss. On the other hand, the present invention accurately determines the system state using objective thresholds based on load tests and achieves excellent technical effects by suppressing processing delays and ensuring data integrity and system stability even under extreme load conditions by dynamically increasing the scan intensity according to the load amount.

[0142] The visualization notification module (210) of the present invention executes commands that define key elements of operation management as judgment criteria and logically combine them to process, in order to convert departure decisions that relied on the manager's subjective judgment into a data-based, objective, and consistent process. The first criterion, the passenger requirement, is the most basic criterion for travel safety and customer satisfaction, and it checks whether all minimum passengers required for departure have boarded. Since departing without missing passengers is the top priority of operation management, this is set as the first key criterion for determining the state of being able to depart. The second criterion, the time elapsed requirement, is a criterion for compliance with the travel schedule, and it checks whether all the allowed stopping and boarding times allocated to the stop have elapsed. Since on-time operation must be observed to ensure the reliability of the entire travel schedule and prevent disruptions to subsequent schedules, this is set as an essential second criterion to be considered together with the passenger requirement.

[0143] The two judgment criteria mentioned above are processed according to a 'state branching method based on condition combinations,' which provides the most suitable decision-making information to the manager in response to various operation scenarios. In the above processing procedure, the server unit (100) cross-analyzes in real-time whether the first and second criteria are satisfied, and clearly determines the current operation status as one of three mutually exclusive states: 'early departure possible,' 'on-time departure possible,' or 'delayed departure.' The determined status information is immediately transmitted to the manager terminal unit (200) and a command is sent to display it visually. Instead of a single index or simple 'possible / impossible' binary information, by providing status information that directly matches the representative scenarios the operation manager encounters in the actual field, it supports increasing the manager's situational awareness speed and enabling rapid decision-making for follow-up actions.

[0144] The data used for the above judgment criteria is obtained in real time from the travel information management module (110) and the boarding status management module (120) of the server unit (100). To determine the passenger requirement, the current number of passengers is received in real time from the boarding status management module (120), and the total number of travelers and the number of pre-allowed non-boarders are queried from the travel information management module (110) to calculate the 'mandatory number of passengers'. To determine the time elapsed requirement, the 'boarding allowance time' of the corresponding stop stored in the travel information management module (110) is compared with the system's current time. For example, if the total number of travelers is 40 and the number of pre-allowed non-boarders is 2, the mandatory number of passengers is calculated as 38, and the boarding allowance time is set to 30 minutes.

[0145] The determined 'departure availability status' is intuitively conveyed through the user interface of the administrator terminal unit (200) to support rapid decision-making. When determined to be 'early departure available', the departure button is activated in green with the text 'early departure' to indicate that immediate departure is possible. When determined to be 'on time departure available', the departure button is activated in green with the text 'on time departure'. When determined to be 'delayed departure', the departure button remains in a deactivated state, and a warning banner reading 'Departure Delayed: N people not boarded' is displayed in red at the top of the screen. Additionally, as the boarding time approaches expiration, for example, the timer display on the administrator screen changes to yellow starting 5 minutes before the end, and flashes red starting 1 minute before, transmitting a signal that visually emphasizes the temporal urgency.

[0146] The processing procedure for a specific scenario, for example, preparing to depart from a rest area with a required passenger capacity of 38 and a boarding time limit of 30 minutes, is described step-by-step as follows. In the stop start stage, upon arrival at the rest area, the timer begins a 30-minute countdown, and since the current number of passengers is 0, it is displayed as 'Departure Delayed'. Subsequently, in the stage of meeting the passenger requirement and entering the 'Early Departure Available' state, if all passengers are confirmed to have boarded earlier than scheduled and the current number of passengers reaches 38, the system determines that the passenger requirement has been met, changes the status to 'Early Departure Available', and activates the departure button in green. When the manager confirms the 'Early Departure Available' display, decides to depart early, and presses the departure button, the system saves the departure record. As an alternative scenario, if the boarding time limit has expired but the current number of passengers is 37, the system maintains the 'Departure Delayed' state and displays a warning indicating '1 passenger missing'. Afterwards, when the last person boards and the current number of passengers reaches 38, the system changes the status to 'on-time departure possible' and sends a command to activate the departure button, as both the number of passengers and the time conditions are satisfied.

[0147] This logic includes exception handling measures to ensure reliability. If a passenger disembarks due to an emergency during the journey, the administrator can process the passenger as an 'emergency disembarkation.' This dynamically recalculates the 'mandatory passenger count' and automatically reflects it in the subsequent determination of the departure eligibility. Additionally, for exceptional situations where waiting for non-boarding passengers is no longer possible due to unavoidable reasons, a feature is provided that allows the departure button to be activated only after the administrator enters a reason for 'forced departure.' Furthermore, a command is executed to save this record separately so that it can be used as evidence in the event of a dispute.

[0148] The effectiveness of the prior art and the present invention becomes clear when comparing their operational results by scenario. In cases where all passengers board early, the prior art, which relies on the manager's subjective judgment, can cause unnecessary waiting times; however, the present invention automatically notifies the "early departure possible" status, thereby reducing travel time and increasing operational efficiency. In cases where passengers are missing as the departure time approaches, the prior art carries the risk of departure delays or passenger omissions due to managerial error; whereas the present invention automatically and clearly warns of "departure delays" and missing passengers, inducing a prompt response from the manager and preventing errors, thereby ensuring stability and reliability.

[0149] The judgment rule of the present invention is defined by a table having clear conditions and guidance content according to the final state. The 'Early Departure Possible' state is when the passenger requirement is met but the time requirement is not, and the green button is activated. The 'On-Time Departure Possible' state is when both the passenger and time requirements are met, and the green button is activated. The 'Delayed Departure' state is in all cases where the passenger requirement is not met, and a red warning is displayed.

[0150] The rules of this invention are based on 'number of people' and 'time,' the two most critical constraints in group travel operation management, and these are objective standards universally applicable to the operation management of all group transportation means. As they possess a technical necessity for safe and efficient operation, the state determination logic of this invention is rational and logical in its composition.

[0151] By adopting the above-described multi-condition-based departure capability determination logic, the present invention achieves clear technical effects such as ensuring objectivity and speed in decision-making, increasing operational efficiency, and preventing human error. By converting departure decisions, which previously relied on a manager's experience or intuition, into clear, data-based status information, it guarantees consistency in judgment and shortens decision-making time.

[0152] The terms and thresholds used in this invention have clear criteria. The mandatory number of passengers refers to the minimum number of passengers who must board at a given stop, excluding those exempted in advance from the total number of travel contractors. The permitted boarding time is the official stop time specified in the travel itinerary, which is set by the manager for each stop prior to the start of the trip. This value provides the flexibility for the manager to extend or shorten it in real-time depending on traffic conditions or local circumstances, meaning that the threshold is not fixed but can be reasonably changed to suit actual operational situations.

[0153] Historical data-based simulation and computation for threshold setting

[0154] In order to ensure the reasonableness of the 'allowed boarding time' set by the administrator in the above system, the system presents a recommended value through a statistical calculation formula based on past operation data. The following is data recorded during the past 10 operations at the same stop ('Cheonan Rest Area') on a specific route ('Seoul-Busan').

[0155] [Table 3-1] Historical driving data for threshold setting

[0156]

[0157] Based on the data in [Table 3-1] above, the recommended 'allowed boarding time' for the current trip (number of travelers: 43) is calculated using the following formula.

[0158] Past average actual stopping time = 250 minutes / 10 times = 25 minutes

[0159] Past average passengers per minute = 19.1 people / 10 trips 1.91 people / minute

[0160] Recommended time = (Historical average stop time) + (Current number of travelers / Average number of passengers per minute) - (Historical average time to complete boarding)

[0161] Addition of correction term: Correction based on actual time required, rather than simple summation.

[0162] Past average time to complete a ride = 210 minutes / 10 times = 21 minutes

[0163] Recommended time = 25 + (43 / 1.91) - 21 = 25 + 22.5 - 21 26.5 minutes

[0164] Therefore, the system suggests approximately 27 minutes to the administrator. This ensures the average break time from the past while preventing arbitrary time settings by predicting the time required to handle the current number of personnel based on data.

[0165] When the administrator adopts the system's recommended value (27 minutes), the simulation results for verifying the effect of the state determination logic of the present invention on operation efficiency are as follows.

[0166] [Table 3-2] (Currently in operation: 43 people)

[0167]

[0168] [Table 3-2] above shows that the prior art, which uses a fixed time (30 minutes) customarily set generously by the manager, causes unnecessary waiting time. On the other hand, the present invention provides an objective recommended time based on past operation data and current passenger count, and by quickly determining the 'early departure possible' status based on this, it achieves excellent technical effects that increase overall operation efficiency and minimize unnecessary delays.

[0170] The visualization notification module (210) of the present invention defines multidimensional judgment criteria that comprehensively evaluate the severity of a situation and executes a command to generate differential warnings accordingly, in order to solve the problems of 'notification fatigue' and 'failure to recognize important situations' that occur when the same warning is provided in all situations when a passenger does not board. The first criterion, the scale of the number of passengers not boarding, is an indicator representing the 'scale severity' of the problem. Since the manager's response priority and urgency are clearly different between a situation where one passenger does not board and a situation where five passengers do not board, the absolute number of passengers not boarding is set as the first criterion for determining the warning level based on the fact that the greater the number of passengers not boarding, the greater the impact on the operation. The second criterion, the temporal urgency, is an indicator representing the 'temporal severity' of the problem. Since the urgency of the situation is significantly different between a passenger not boarding when there are 30 minutes left until departure and a passenger not boarding when there are 1 minute left, even if the number is the same, the elapsed time of the boarding allowance is set as the second criterion considering that the available time for resolving the situation decreases as the scheduled departure time approaches. The third criterion, persistence of the situation and response efforts, serves as an indirect indicator of the problem's 'difficulty of resolution.' Since the continued non-boarding status despite multiple attempts by the manager to contact the individual suggests the possibility that an issue other than simple tardiness has occurred, the fact that the situation does not improve despite the manager's response efforts is established as the third criterion that amplifies the severity of the problem.

[0171] The three judgment criteria mentioned above are combined according to a 'priority-based rule nesting method' to determine the final alert level, which identifies the most urgent and critical situations without omission. In the processing procedure, the server unit (100) compares the first, second, and third criteria with multiple predefined threshold values ​​to calculate a preliminary alert level for each criterion. The final alert level is determined by selecting the highest level among these preliminary alert levels, i.e., the most serious situation. For example, if the situation corresponds to a 'caution' level based on personnel but a 'warning' level based on time, the command is executed to determine the final alert level as the higher 'warning' level. Unlike the weighted summation method, this method, which ensures that the alert level is immediately raised based on the single most serious factor, ensures that if even a single factor sends a serious danger signal, the system does not miss it and immediately generates the highest level alert to draw the manager's immediate attention, thereby minimizing potential risks in the operation management system directly related to safety.

[0172] The data used for the above judgment criteria is obtained in real time from the server unit (100) and the administrator terminal unit (200). The number of non-boarding passengers is received in real time from the boarding status management module (120) regarding the current number of non-boarding passengers. Temporal urgency calculates the elapsed time by comparing the boarding allowance time of the travel information management module (110) with the current elapsed time. Situation persistence counts the number of times the visualization notification module (210) of the administrator terminal unit (200) attempts to contact non-boarding passengers. For example, the alarm stages are divided into Stage 1 (Caution), Stage 2 (Warning), and Stage 3 (Urgent), and the threshold for the first criterion is set to enter Stage 1 as 1 or more passengers and enter Stage 2 as 3 or more passengers. The threshold for the second criterion is set to enter Stage 1 as an elapsed time exceeding 50% and enter Stage 2 as an elapsed time exceeding 80%. The threshold for the third criterion is set to enter Stage 2 as one or more contact attempts.

[0173] According to the determined alarm level, differential notifications are provided to the administrator terminal unit (200), and a signal is automatically transmitted to induce the administrator to intuitively recognize the severity of the situation and respond appropriately. In Level 1 (Caution), 'N people not on board' is quietly displayed as a yellow information banner at the top of the screen. In Level 2 (Warning), the information banner changes to orange, and a short vibration occurs once from the terminal. In Level 3 (Urgent), the information banner flashes red, and a warning sound is emitted along with a continuous vibration from the terminal.

[0174] The processing procedure for a specific scenario, for example, a situation with a required number of passengers of 38, a boarding time of 30 minutes, and a scheduled departure at 2:30 PM, is described step-by-step as follows. In the first step, if there are 2 missing passengers at 2:15 PM, the system issues a 'Level 1 (Caution)' alert and displays a yellow banner on the screen because the elapsed time has exceeded 50%. In the second step, if there are 3 missing passengers at 2:20 PM, the number of missing passengers has reached the Level 2 criterion, so the system upgrades the alert to 'Level 2 (Warning)' following the highest level, changes the screen banner to orange, and causes the terminal to vibrate. In the third step, even if the number of missing passengers decreases to 2 after the administrator attempts to contact the missing passengers, the system maintains 'Level 2 (Warning)' because the number of contact attempts satisfies the Level 2 criterion. In the fourth stage, if the scheduled departure time of 2:30 PM arrives but there are still 2 missing passengers, the system issues a 'Level 3 (Critical)' alert, flashes the screen red, and emits a warning sound to urge the manager to make an immediate final decision.

[0175] This logic includes exception handling measures to ensure reliability. If an alert of the same level persists, a strong alert is provided only the first time, and only visual notifications are maintained thereafter to reduce administrator fatigue. However, a command is sent to provide a strong alert again whenever the alert level is raised. Additionally, if an administrator attempts to contact a specific non-boarding passenger and receives a 'busy' or 'unreachable' status, this is recorded in the system as 'unreachable,' and the alert level is immediately raised by one step to allow the administrator to recognize potential risks more quickly.

[0176] The effectiveness becomes clear when comparing the operation results of the prior art and the present invention by scenario. In a minor situation where one passenger is missing 20 minutes before departure, the prior art immediately emits a warning sound, causing unnecessary stress to the manager, whereas the present invention improves the user experience by providing only quiet visual information at 'Level 1 (Caution)'. On the other hand, in a serious situation where five passengers are missing 1 minute before departure, the prior art provides only a warning of the same intensity as other situations, making it difficult to perceive the severity, whereas the present invention immediately issues a 'Level 3 (Urgent)' alert, inducing an immediate response from the manager and strengthening crisis management capabilities.

[0177] The judgment rule of the present invention is defined as a table having clear judgment rules according to the final alarm stage. 'Stage 1 (Caution)' is issued when there is one or more missing persons or when the elapsed time rate exceeds 50%. 'Stage 2 (Warning)' is issued when there are three or more missing persons, when the elapsed time rate exceeds 80%, or when there is one or more attempts to contact. 'Stage 3 (Urgent)' is issued when the elapsed time rate reaches 100%, and the system selects the highest stage among the stages calculated according to each condition as the final alarm stage.

[0178] The rules of this invention are based on the principles of situational severity assessment emphasized in crisis management theory, and utilize universal and objective criteria such as the scale of the problem, time pressure, and resolution effort. Therefore, the logic of this invention possesses a technical necessity to reduce the manager's cognitive load and induce an effective response.

[0179] By adopting the above-mentioned multi-stage alarm generation logic for each situation, the present invention achieves clear technical effects such as increased management efficiency, strengthened risk management, and improved user experience. Since the system primarily filters and notifies the severity of the situation, the manager can focus on the most urgent and important issues, prevent potential operational risks in advance, and reduce the manager's 'notification fatigue,' thereby increasing trust in the system.

[0180] The terms and thresholds used in this invention have clear criteria. The alert levels are discrete levels indicating the severity of the no-boarding issue, and each level is linked to a different notification method. The thresholds for each level used in this invention are provided so that an administrator can set them according to the specific travel agency's operation policy and service level agreement. Furthermore, the system includes a function that recommends an optimal threshold based on average delay patterns analyzed from past operation data, which implies that the thresholds are not arbitrary but have a rational basis based on operational data and policies.

[0181] Historical data-based simulation and computation for threshold setting

[0182] The alarm threshold of the above system can be set according to the operator's policy, but the system provides objective recommendations through statistical analysis of past operation data. The following is data on 20 'departure delay' events that occurred during past operations.

[0183] [Table 4-1]

[0184]

[0185] (Data example: The progression rate distribution exists between 101% and 130%)

[0186] Based on past delay data such as [Table 4-1] above, the system calculates a recommended alarm threshold rate through the following statistical calculation formula.

[0187] The statistical reference point for calculating the recommended threshold rate is defined as the 75th percentile value of the data set.

[0188] For example, the rank corresponding to 75% of 20 data points is 20 * 0.75 = 15th. Assuming the 15th value in the sorted data is 112%, this serves as a statistical reference point for the risk zone, implying that approximately 75% of delay events are concentrated after an elapsed rate of 112%. However, since a delay has already occurred after the scheduled departure time (the same point as 112%), in actual operation, this reference point is used to select the warning threshold rate from the range prior to the scheduled departure time (e.g., 80%–90%). This is to establish a critical threshold that allows an administrator to intervene before a severe delay occurs. For instance, if historical data analysis indicates that 75% of delays occurred after an elapsed rate of 85%, the system recommends setting the 'warning' stage time threshold rate to 85%.

[0189] 'Caution' stage time threshold = 85% * 0.6 50%

[0190] In this way, by setting warning and caution threshold rates based on objective risk breakpoints shown by historical data, it provides grounds for the claim that “exceeding this point is statistically highly likely to lead to a serious delay.”

[0191] The simulation results for verifying the effect of the multi-stage alarm logic of the present invention on the manager's crisis management capability when applying data-based recommended thresholds (Caution: 50%, Warning: 85%) are as follows.

[0192] [Table 4-2]

[0193]

[0194] Table 4-2 above illustrates the problem that prior art, which repeats the same alert for all non-boarding situations, causes 'notification fatigue' for managers and fails to distinguish the severity of the situation. In contrast, the present invention uses objective threshold values ​​set based on past data to gradually raise the level of the alert according to the urgency of the situation. Through this, the manager is not distracted by unnecessary initial alerts and receives the strongest alert at the truly critical moment, thereby achieving the technical effect of effectively responding to crisis situations.

[0196] The entire operation process of the travel vehicle passenger management system according to one embodiment of the present invention is described in detail step by step through a specific scenario. In the preset of this embodiment, information for a '2-night, 3-day group trip to Jeju Island' is registered in the travel information management module (110), and the total number of travelers is set to 40, with the number of pre-allowed non-boarders set to 0, so the required number of passengers is 40. The current stop is the 'Seongsan Ilchulbong Parking Lot,' the boarding allowance time is set to 20 minutes, and the scheduled departure time is set to 3:30 PM. In addition, the threshold value for each process of the system is set according to a pre-defined standard.

[0197] As the first step of the operation process, in a quiet state in terms of server load and initial boarding recognition situation at 3:20 PM, 10 minutes before departure, the system operates as follows. Since there are almost no passengers currently, the event processing queue length of the server unit (100) is 3 and the average processing delay is 70 milliseconds, so the server unit (100) determines this as a 'normal state' and sends a command to the in-vehicle recognition unit (400) to operate at a basic scan duty cycle of 20%. At this time, when traveler 'Kim Cheol-su' boards the vehicle, the in-vehicle recognition unit (400) continuously detects the traveler identification unit (300) of 'Kim Cheol-su'. The boarding status management module (120) of the server unit (100) analyzes the received data, confirms that all boarding confirmation conditions are satisfied as it was detected 7 times consecutively for 3.5 seconds and the average signal strength is measured at -68 decibel milliwatts, and executes a command to finally confirm the status of 'Kim Cheol-su' as 'boarding'. This judgment result is immediately transmitted to the administrator terminal unit (200), and the visualization notification module (210) changes the seat assigned to 'Kim Cheol-su' from red to green. At this time, the server load is in a normal state, but since the number of unboarded passengers is 39—significantly exceeding the 2nd stage entry threshold of 3 or more—even though only half of the boarding allowance time (50% elapsed) has passed, the multi-stage warning logic determines that the 'warning' stage criteria have been met based on the scale of unboarded passengers. Although the time criterion does not yet meet the 1st stage entry threshold (exceeding 50% elapsed), since the number of passengers satisfies the 2nd stage entry threshold first, the system determines the final warning stage as '2nd stage (warning)' and executes a command to display "39 unboarded passengers" as an orange banner on the administrator terminal screen and generate a short vibration. According to the departure availability determination logic, since the number of passengers condition is not met, the system displays a 'departure delayed' state.

[0198] As a second step, in the congestion situation at 3:25 PM, 5 minutes before departure, and in the situation of enhanced dynamic scanning, the system operates as follows. When a large number of travelers begin boarding at once and recognition events surge, the length of the event processing queue of the server unit (100) increases rapidly to 160. The server unit (100) immediately determines this as a 'warning state' and automatically sends a control command to the in-vehicle recognition unit (400) to increase the scan duty cycle to 80%, which is the maximum scan duty cycle. The in-vehicle recognition unit (400) increases the scan intensity to reliably collect the surge events without omission and transmits them to the server. Based on the enhanced scan performance, the boarding status management module (120) processes 35 additional travelers as 'boarding'. At this point, the total number of passengers is 36 and the number of non-boarders is 4, and the multi-stage warning logic maintains 'Stage 2 (Warning)' because the number of non-boarders still meets the warning criteria and updates the orange banner to “4 non-boarders”. The logic for determining departure eligibility still displays a 'departure delayed' status due to insufficient passenger capacity.

[0199] As a third step, in the situation of imminent departure and final status determination at 3:29 PM, one minute before departure, the system operates as follows. Three additional passengers board out of the four non-boarding passengers, bringing the total number of passengers to 39, leaving only one non-boarding passenger, 'Lee Mong-ryong'. When 'Lee Mong-ryong' boards at 3:29:30 PM and is confirmed as 'boarding', the total number of passengers becomes 40, satisfying all required passenger quotas. Since the passenger condition is satisfied even though it is not yet the scheduled departure time, the visualization notification module (210) changes the system status to 'Early Departure Possible' according to the departure possibility determination logic, activates the departure button in green, and displays the text "Early Departure". Since the number of non-boarding passengers has become 0, all alarm issuance conditions of the multi-stage alarm logic are released, and the orange banner on the administrator terminal disappears. Additionally, when the load on the server unit (100) is reduced after the boarding event processing is completed, the server sends a command to lower the scan duty cycle of the in-vehicle recognition unit (400) back to the default level of 20%.

[0200] As the final fourth step, at the final decision and departure situation at 3:29:45 PM, the manager checks the 'early departure possible' display on the manager terminal unit (200), obtains consent from the passengers in the vehicle, and presses the activated green 'early departure' button. The system records in the database of the server unit (100) that the vehicle departed at 3:29:45 PM and executes a command to start driving toward the next stop.

[0201] As such, the embodiment of the present invention implements an integrated system that efficiently and safely manages the operation of all travel vehicles by ensuring that each component and core process organically links and exchanges data in real time, thereby efficiently utilizing resources in quiet situations, ensuring stability in crowded situations, and providing managers with accurate data-based decision-making information.

[0202] Although preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above. Various modifications are possible by those skilled in the art without departing from the essence of the invention as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present invention. Explanation of the symbols

[0203] Server unit (100) Travel information management module (110) Boarding status management module (120) Manager terminal unit (200) Visualization notification module (210) Traveler identification unit (300) Vehicle in-vehicle recognition unit (400)

Claims

Claim 1 A passenger management system for a travel vehicle using short-range communication technology comprises: a server unit including a database for storing traveler information and executing a plurality of software modules; a manager terminal unit connected via communication to the server unit to display operation status information to a manager and receive input from the manager; and a traveler identification unit that transmits a signal for identifying individual travelers. The system includes an in-vehicle recognition unit installed inside the travel vehicle that receives a signal from the traveler identification unit and transmits it to the server unit; wherein the server unit executes a boarding status management module that determines whether the traveler is on board based on the signal received from the in-vehicle recognition unit, and controls the operation of the in-vehicle recognition unit by determining the real-time load status of the system; and wherein the administrator terminal unit executes a visualization notification module that visually displays the determination result received from the server unit and generates a notification according to the situation; and wherein the boarding status management module comprises: a first condition for determining whether a signal from a specific traveler identification unit is continuously detected more than a first number of times within a first time period set in advance; a second condition for determining whether the total detection time of the signal exceeds a second time period set in advance when the first condition is satisfied; and a third condition for determining whether the average received signal strength measured during the second time period is greater than or equal to a first threshold set in advance when the second condition is satisfied.The system is characterized by sequentially determining the status of the traveler as 'boarding' only when all of the first, second, and third conditions are satisfied, thereby preventing judgment errors that mistake non-boarders passing near the vehicle or staying near the entrance for a short time as 'boarding'; the system further includes a calibration mode that collects a set of first signal strength values ​​measured inside the vehicle and a set of second signal strength values ​​measured outside the vehicle during the test phase; the first threshold is set by calculating the median value of the arithmetic mean of the first signal strength values ​​and the arithmetic mean of the second signal strength values, thereby providing an objective judgment criterion optimized for signal strength distributions that differ depending on the installed vehicle environment; the system further includes a calibration mode that collects a set of dwell time data of events classified as actual 'boarding' during the test phase; and the second time is set by calculating the value obtained by subtracting a value obtained by multiplying the standard deviation of the data set by a preset multiplier from the arithmetic mean of the dwell time data set, thereby providing a statistically significant normal boarding A passenger management system for a travel vehicle using short-range communication technology, characterized by ensuring the stability of the judgment by setting the minimum time required by an event as a threshold. Claim 2 delete Claim 3 delete Claim 4 delete Claim 5 A passenger management system for a travel vehicle using short-range communication technology according to claim 1, wherein the server unit monitors the length of an event processing queue collected in real time and the average processing delay time to determine the load state of the system, and if the load state is determined to be a 'load state' where the length of the queue exceeds a second threshold or the average processing delay time exceeds a third threshold, the scan duty cycle of the in-vehicle recognition unit is adjusted upward to a predefined 'enhanced scan duty cycle,' and if the load state is determined to be a 'normal state' where both the length of the queue and the average processing delay time are below their respective thresholds, the scan duty cycle is adjusted downward to a 'basic scan duty cycle,' thereby preventing data loss during an event surge caused by multiple travelers boarding simultaneously and saving system resources during idle state. Claim 6 A passenger management system for a travel vehicle using short-range communication technology, characterized in that, in claim 5, the second threshold and the third threshold are set by gradually increasing virtual events in the system and calculating the amount of change in the rate of change of the average processing delay time, and experimentally finding and setting the point where the amount of change in the rate of change increases rapidly above a preset reference value, i.e., the inflection point of system performance degradation, through a load test, thereby providing an objective state transition criterion optimized for the hardware specifications of the system.

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