An integrated road assist transportation system adapted for cyclists

Abstract

This application discloses an integrated road assistive traffic facility system adapted to cyclists, relating to the field of intelligent transportation technology. It includes a basic support structure, multiple functional modules integrated into the basic support structure, a central control device, and an energy management device. The multiple functional modules include a safety protection module, an intelligent guidance module, and a functional supply module. The safety protection module includes: a roadside protection unit, including buffer barriers, lighting warning lights, and a road surface status sensor array; and an intersection conflict protection unit, configured in the intersection area, including retractable bollards and a target detection and early warning device. The central control device receives perception data from each functional module; generates collaborative control commands based on the perception data and distributes them to the corresponding functional modules to execute linked operations; the energy management device is used to coordinate and allocate power supply resources. This application possesses high robustness, supports rapid collaborative response, and can adapt to diverse cycling scenarios.

Description

Technical Field

[0001] This application relates to the field of intelligent transportation technology, and in particular to an integrated system of road assistive transportation facilities adapted to cyclists. Background Technology

[0002] With the rapid development of urban slow-traffic systems, roadside assistance facilities for cyclists have evolved from single-function physical guardrails or signs to intelligent and integrated systems. Existing technologies include some research attempts to monitor the cycling environment by deploying IoT sensors, such as using geomagnetic coils to detect vehicle traffic and employing video analytics to identify violations. However, such systems generally suffer from three major drawbacks: fragmented modules, slow response times, and unreliable data.

[0003] First, at the system architecture level, existing facilities mostly adopt a direct "sensing-display" connection mode, lacking a unified central coordination mechanism. Functions such as safety protection, information guidance, and service replenishment are implemented by independent subsystems, with no data sharing or control linkage between them, making it impossible to form a collaborative service loop covering the entire journey of cyclists.

[0004] Secondly, at the data processing level, existing systems lack standardized preprocessing procedures for accessing multi-source heterogeneous data (such as radar ranging, meteorological sensors, and user terminal reports). Due to the asynchronous clocks and inconsistent sampling frequencies of various acquisition devices, and the absence of integrity verification and anomaly removal mechanisms, the fused state information contains significant noise and timing misalignment.

[0005] Furthermore, although some literature mentions the concepts of "intelligent traffic poles" or "multi-functional light poles," their essence remains a physical stacking of devices, failing to address the logical coupling issue between the underlying data flow and control commands. The common practice among those skilled in the art is to use traditional traffic signal control logic or simply migrate vehicle-to-everything (V2X) technology to non-motorized vehicle scenarios, ignoring the unique characteristics of cyclists' behavior patterns, speed features, and interaction needs.

[0006] Therefore, how to build an integrated auxiliary facility system with a highly robust data foundation, support for rapid collaborative response, and adaptability to diverse cycling scenarios remains a long-standing technical challenge in this field. Summary of the Invention

[0007] To address the shortcomings of existing technologies and to construct an integrated auxiliary facility system with a highly robust data foundation, support for rapid collaborative response, and adaptability to diverse cycling scenarios, this application provides an integrated road auxiliary traffic facility system adapted to cyclists.

[0008] Firstly, the objective of this invention is achieved through the following technical solution: An integrated road assist traffic facility system adapted to cyclists includes: a basic support structure, multiple functional modules integrated on the basic support structure, a central control device, and an energy management device; The aforementioned multiple functional modules include at least a security protection module, an intelligent guidance module, and a function replenishment module; The security protection module includes: The protection unit along the route is configured on continuous sections of the cycling path and includes buffer guardrails, adaptive ambient light warning lights, and a road condition sensor array for real-time monitoring of road conditions. The intersection conflict prevention unit, configured in the intersection area, includes retractable bollards linked to traffic signals and a target detection and early warning device based on millimeter-wave radar; the target detection and early warning device acquires the relative distance and speed between motor vehicles and cyclists, and triggers an audible and visual warning when preset risk conditions are met; The central control device establishes communication connections with each functional module, receives sensing data from each functional module, generates collaborative control commands based on the sensing data, and distributes the collaborative control commands to the corresponding functional modules to execute linkage operations. The energy management device is electrically connected to the central control device and various functional modules, and is used to coordinate and allocate power supply resources.

[0009] By adopting the above technical solution, the safety protection module, intelligent guidance module, and functional supply module are uniformly integrated on the basic support structure and uniformly scheduled by the central control device, significantly improving the efficiency of road space utilization and achieving dual integration of physical space and functional logic. Furthermore, the safety protection module of this invention constructs an active safety protection system covering the entire road section and all scenarios: the roadside protection unit reduces collision damage and improves nighttime visibility through highly elastic buffer guardrails and adaptive lighting warning lights; the intersection conflict protection unit uses millimeter-wave radar to perceive the relative motion state of motor vehicles and cyclists in real time, and immediately triggers audible and visual warnings when preset risk conditions are met. Effectively prevents intersection collision accidents; the central control unit can receive sensing data from various functional modules in real time and generate collaborative control commands based on multi-source sensing data. For example, when the road surface condition sensor array detects a slippery condition, it can simultaneously trigger the anti-slip warning of the special scenario protection unit and the deceleration prompt of the intelligent guidance module to achieve rapid collaborative response across functional modules; then the energy management device is electrically connected to the central control unit and each functional module, and can dynamically allocate power supply resources according to the power consumption characteristics and operating status of each module, giving priority to ensuring the power supply of key safety functions such as collision warning and emergency lighting, thus ensuring the energy reliability and safety of the system during operation.

[0010] In a preferred embodiment of this application, the target detection and early warning device is configured to: confirm whether a cyclist has entered a conflict zone through an infrared beam sensor, and combine the relative distance and relative speed between the motor vehicle and the cyclist obtained by millimeter-wave radar, and make a multi-level risk judgment based on a preset distance and speed joint threshold. When a high-risk conflict is identified, it triggers audio-visual and text warnings for cyclists, vehicle-to-everything (V2X) avoidance reminders for motor vehicles, and dynamic warnings from retractable bollards.

[0011] By adopting the above technical solution, the data from infrared beam sensors and millimeter-wave radar are integrated to confirm the cyclist's entry into the conflict zone based on the duration of obstruction. Multi-level risk assessment is also performed by combining the relative distance and speed of motor vehicles, effectively suppressing false triggering caused by environmental interference. When the high-risk joint threshold is met, sound, light and text warnings, vehicle network avoidance reminders and dynamic warnings from bollards are triggered simultaneously, forming a three-way linkage intervention mechanism for cyclists, motor vehicles and roadside facilities.

[0012] In a preferred embodiment of this application: in the intelligent guidance module, the central control device performs data access verification and time synchronization processing, including: Perform integrity checks on various types of data accessed by the IoT platform, and trigger retransmission when the missing rate exceeds a preset threshold. Using the local high-precision clock as a reference, the time deviation between the timestamp of each data item and the local clock is calculated. When the time deviation is greater than the preset deviation threshold, the continuous data is corrected by linear interpolation, and the discrete data is discarded and waited for the next round of acquisition. The time synchronization formula is as follows: in, The data values ​​after calibration. The original data values, For local clock timestamps The original data timestamp For the timestamp of the next piece of raw data; This will be the next original data value.

[0013] By adopting the above technical solution, multi-source data from different sensors are strictly aligned in the time dimension. By implementing integrity verification and high-precision time synchronization for multi-source heterogeneous data, the system can identify communication packet loss and trigger retransmission. At the same time, timestamp deviation is calculated based on the local clock. Linear interpolation correction is used for continuous data, while discrete data is discarded and resampled, effectively eliminating timing misalignment caused by device clock drift or network jitter.

[0014] In a preferred embodiment of this application: the central control device performs data anomaly detection, including: The collected data items are judged to be within a reasonable range. When the congestion index of the cycling lane exceeds 0-10, the traffic flow exceeds 0-200 vehicles / minute, or the rainfall exceeds 0-200 mm / h, they are marked as abnormal. The rate of change R is calculated for time-series data collected in three consecutive rounds. If R exceeds a set threshold, it is considered abnormal. The formula for calculating the rate of change is as follows: ,in The current round of data values, The data should be from the previous round; for flow data, R ≤ 50%, and for meteorological data, R ≤ 30%. Compare the currently sensed or received data with the average of the three most recent valid data in the circular buffer. Compare the results and calculate the deviation D. When the deviation D exceeds twice the standard deviation... When an exception is detected, the expression is: .

[0015] By adopting the above technical solution and establishing a triple anomaly detection mechanism, including reasonable value range boundary determination, time series change rate threshold constraint, and statistical anomaly identification based on historical data of the circular buffer, erroneous data caused by sensor failure, communication interference, or extreme noise can be effectively eliminated.

[0016] In a preferred embodiment of this application: the central control device performs data preprocessing, including: The cycling speed data was cleaned to remove outliers exceeding 30 km / h or falling below 0.5 km / h, and normal noise was corrected using a moving average method. The moving average formula is as follows: in, denoted as the average cycling speed of the cleaned road section, and n is the number of sampling points; The velocity value is obtained from n consecutive data acquisitions. Data of different units were standardized, with traffic flow data standardized to "vehicles / 100 meters", speed data standardized to "km / h", and location data converted to WGS84 longitude and latitude format.

[0017] By adopting the above technical solutions, a speed threshold (0.5–30 km / h) that conforms to the characteristics of human cycling is set to eliminate invalid targets, and the moving average method is used to smooth out measurement noise, thereby improving the stability of the average speed of the road segment; at the same time, heterogeneous data such as flow rate, speed, and location are uniformly converted to eliminate differences in format and unit.

[0018] In a preferred embodiment of this application: the central control device performs scene type determination, specifically including: Match the time period label to the current time, which includes morning rush hour, evening rush hour, off-peak, and holidays; Based on the current cycling density ρ of the road segment and the maximum carrying capacity of the road segment Free riding speed Average cycling speed on the road The congestion index (CI) is calculated using the following formula: in, CI is a weighting coefficient. A value of CI ≥ 0.6 indicates congestion, 0.3 ≤ CI < 0.6 indicates mild congestion, and CI < 0.3 indicates smooth traffic.

[0019] By adopting the above technical solution, scenarios are initially divided based on time period labels and road types, and a weighted congestion index that integrates cycling density and average speed is introduced to objectively distinguish the level of road service.

[0020] In a preferred embodiment of this application: the central control device is configured to perform scenario type determination, including: If the current time period is labeled as morning or evening rush hour and the current road type is a main commuter road, it is determined to be a rush hour scenario. When the current road type is a leisure greenway or scenic road, or when the current time period is labeled as a holiday and there are no fewer than three scenic spots or rest areas within the preset surrounding area, it is determined to be a leisure greenway / scenic area scene; The remaining situations are classified as ordinary off-peak scenarios; The central control unit is also configured to perform user group determination, including: When the elderly mode trigger signal is received, it is determined to be an elderly person; When the vehicle type is identified as an electric bicycle, the rider is identified as an electric bicycle rider, and the remaining battery power data is collected. Otherwise, they are classified as ordinary members of the group.

[0021] By adopting the above technical solution, road type and the number of surrounding POIs (≥3 attractions) are introduced as supplementary conditions for scene determination, accurately distinguishing commuting and leisure cycling scenarios, and avoiding misjudgment caused by relying solely on time tags; at the same time, based on user-triggered signals or vehicle attribute identifiers, the group type is automatically identified to achieve refined classification of service objects, so as to achieve accurate perception of the current traffic status and user needs.

[0022] In a preferred embodiment of this application, the system further includes: For the elderly, the font size will be adjusted to the preset large font size, the color scheme will be switched to high contrast mode, and the voice broadcast speed will be adjusted to 80% of the speed of ordinary people; For electric bicycle riders, the full-charge range is matched based on the vehicle model. Calculate the distance that the remaining battery power can support based on the current remaining battery percentage (B) and the road condition correction factor (K). The calculation formula is: Where K=0.8 corresponds to congested road sections, and K=1.0 corresponds to uncongested road sections.

[0023] By adopting the above technical solutions, the high-contrast mode features black background and yellow text; for the elderly, the readability and cognitive efficiency of information are significantly improved by increasing the font size (≥24 points), using a black background and yellow text high-contrast color scheme, and reducing the speech speed to 80%; for electric bicycle riders, the range that can be supported is dynamically calculated based on the full-charge range of the model, the remaining power, and the road condition correction coefficient, providing users with accurate trip planning basis.

[0024] In a preferred embodiment of this application: the central control device dynamically configures the priority level and update frequency of information display based on the determined combination of scene type and user group, wherein: During peak commuting hours, regardless of user group type, the congestion index (when ≥0.6) and temporary road occupancy information are set to P1 level, the signal countdown and cycling speed are set to P2 level, and the surrounding basic supporting facilities are set to P3 level. The information update frequency is once every 0.5 seconds. In the context of leisure greenways / scenic areas, for the general public, the distance between scenic spots and rest areas is set to P1 level, the distribution of restrooms and road condition prompts are set to P2 level, historical scenic images are set to P3 level, the information is updated every 3 seconds, and image information is updated every 5 seconds. In ordinary off-peak scenarios, for the general public, the traffic condition prompts and signal countdowns are set to P1 level, the surrounding supporting facilities are set to P2 level, the weather information is set to P3 level, and the information is updated every 2 seconds. For the elderly, in any scenario, the core navigation guidance and safety warnings are set to P1 level, the signal countdown is set to P2 level, the simplified supporting information is set to P3 level, the information update frequency is once every 1 second, and the voice broadcast frequency is once every 2 seconds. For electric bicycle riders, in addition to the priority of the corresponding scenario, the remaining power range and the status of nearby charging points are set as P2 level information, and the power-related information is updated once every 1 second.

[0025] By adopting the above technical solution, the information priority and update frequency are dynamically configured based on the "scene-group" combination: during the commuting peak, the congestion and lane occupation information is updated at a high frequency of 0.5 seconds to ensure timeliness; in the leisure scene, the update frequency is reduced to save energy; for the elderly group, the core guidance is forcibly displayed and refreshed every 1 second; for electric bicycle users, the battery level prompt is superimposed. This mechanism enables the system to allocate computing and communication resources on demand, ensures the real-time availability of key information in high-risk scenarios, optimizes energy efficiency in low-demand scenarios, and achieves the collaborative optimum of user experience and system efficiency.

[0026] In a preferred example of this application: The conflict risk determination performed by the target detection and warning device includes the following steps: When the infrared opposed sensor detects that the occlusion state lasts for no less than 300 milliseconds, it is determined that the cyclist has entered the intersection conflict area; at the same time, when the millimeter-wave radar detects that the movement heading angle of the motor vehicle target is within the range of 30° to 60°, it is determined as a valid motor vehicle target turning right into the intersection; Based on the relative distance and relative speed between the valid motor vehicle target and the cyclist, the following joint threshold judgment is performed: When D≤4m and the relative speed≥3km / h are satisfied, it is determined as a high-risk conflict; When 4m<D≤8m and the relative speed≥5km / h are satisfied, it is determined as a medium-risk conflict, and the sampling frequency of the millimeter-wave radar is increased to enhance monitoring; Among them, the hierarchical early warning execution includes: When it is determined as a high-risk conflict, the following are triggered synchronously: The retractable isolation piles flash red light at a preset frequency, and the red light brightness is not less than 80cd / m²; Through the visual display unit, a text prompt is pushed to the cyclist according to the preset text prompt font, font size and preset continuous display time; Through the vehicle networking module, an avoidance reminder message is sent to the motor vehicle, and the voice broadcast duration is the preset avoidance prompt duration.

[0027] By adopting the above technical solution, it is confirmed that the cyclist enters when the infrared occlusion lasts for ≥300ms, and the right-turn conflict vehicle is identified by combining the radar heading angle of 30°-60°, effectively excluding instantaneous interference and non-related targets; a two-level distance-speed joint threshold is adopted, and the radar sampling rate is increased to 20Hz in the medium-risk case to enhance monitoring; in the high-risk case, the red light of the isolation pile flashes within ≤100ms. The full-process closed-loop control mechanism greatly shortens the time window from risk identification to intervention execution, and wins sufficient avoidance reaction time for both parties, fundamentally reducing the probability of intersection collision accidents.

[0028] To sum up, this application includes at least one of the following beneficial technical effects: 1. The safety protection, intelligent guidance and function replenishment modules are integrated into a unified basic support structure, and the central control device realizes the aggregation of sensing data, the generation and distribution of collaborative instructions, and builds an integrated architecture of physical integration and logical linkage, which overcomes the defects of traditional facility functions being fragmented and responses being isolated; the energy management device coordinates the power supply of the entire system to ensure the continuous operation of key modules under complex working conditions. 2. It not only improves space utilization efficiency, but also realizes a paradigm shift from "single-point passive protection" to "multi-modal proactive collaborative service", providing cyclists with continuous and consistent auxiliary support covering the entire journey. Attached Figure Description

[0029] Figure 1 This is an integrated facility architecture diagram of an integrated road auxiliary traffic facility system adapted to cyclists, according to one embodiment of this application; Figure 2 This is a flowchart of the collaborative control logic of an integrated road auxiliary traffic facility system adapted to cyclists, as described in one embodiment of this application. Figure 3 This is a schematic diagram of a multimodal information interaction interface of an integrated road auxiliary traffic facility system adapted to cyclists, according to one embodiment of this application; Figure 4 This is a flowchart illustrating the scenario-based adaptation and adjustment process in an integrated road assist traffic facility system adapted to cyclists, as described in one embodiment of this application. Detailed Implementation

[0030] The following is in conjunction with the appendix Figures 1 to 4 This application will be described in further detail.

[0031] In one embodiment, such as Figures 1 to 4 As shown, this application discloses an integrated road assistive traffic facility system adapted for cyclists, including: a basic support structure, multiple functional modules integrated on the basic support structure, a central control device, and an energy management device; the basic support structure is constructed with 6061-T6 high-strength aluminum alloy profiles to form the main frame. In one example, the frame is 1.2 meters high and 0.8 meters wide, with an internal honeycomb hollow structure, reserving multiple cable channels and standardized equipment installation cavities; the exterior is a 5cm radius curved surface to eliminate sharp edges. The bottom of the frame is fixed to the asphalt pavement by adjustable expansion bolts.

[0032] The system comprises multiple functional modules, including at least a safety protection module, an intelligent guidance module, and a function replenishment module. Each module connects to the basic support structure via a standardized RJ45 interface and a power interface. Specifically, the safety protection module includes a roadside protection unit configured along the continuous sections of the cycling path. This unit consists of a buffer guardrail made of an aluminum alloy frame and an inner 3cm thick EPDM high-elasticity buffer material, an adaptive ambient light intensity LED warning light embedded in the top of the guardrail, and a road surface condition sensor array installed at the bottom of the guardrail every 10 meters. The road surface condition sensor array includes temperature and humidity sensors and vibration sensors. The safety protection module also includes an intersection conflict prevention unit configured in the intersection area. This unit includes an electro-hydraulic driven retractable bollard linked to the intersection traffic signal controller, and a 24GHz millimeter-wave radar target detection and early warning device deployed 5 meters in front of the stop line of the right-turn lane for motor vehicles.

[0033] Specifically, the target detection and early warning device is configured to: confirm whether a cyclist has entered the conflict zone through an infrared beam sensor, and combine the relative distance and relative speed between the motor vehicle and the cyclist obtained by millimeter-wave radar, and make a multi-level risk judgment based on a preset distance and speed joint threshold; when a high-risk conflict is determined, it triggers an audio-visual and text warning for the cyclist, a vehicle-to-everything (V2X) avoidance reminder for the motor vehicle, and a dynamic warning from a retractable bollard.

[0034] This embodiment can be deployed at a typical T-junction where a main urban road intersects with a non-motorized vehicle lane. The hardware configuration of the intersection conflict prevention unit includes an infrared beam sensor, a millimeter-wave radar, and an execution unit. The infrared beam sensor is installed at the entrance of the non-motorized vehicle lane, with a pair of infrared beam sensors (transmitter and receiver) mounted on the roadside support structure. The beam height is 0.8 meters, horizontally covering the entire width of the non-motorized vehicle lane (2.5 meters). The output signal of the infrared beam sensor is connected to the digital input port of the central control unit. The millimeter-wave radar is installed on a roadside pole 5 meters in front of the stop line of the adjacent right-turn lane for motor vehicles. A 24GHz industrial-grade millimeter-wave radar, such as the TI IWR6843, is installed, with a detection angle of 120° and an effective detection range of 0.2-10 meters. The radar communicates with the central control unit via a CAN bus, reporting the detected target list in real time, including the distance, speed, azimuth, and heading angle of each target.

[0035] The execution unit includes retractable bollards, audio-visual warning units, and a vehicle-to-everything (V2X) communication module. The retractable bollards are located 1 meter behind the stop line of the non-motorized vehicle lane and feature built-in red LEDs and an electric push rod. The audio-visual warning units are integrated into the intelligent guidance module's LCD screen at the intersection. The V2X communication module is integrated into the central control unit and supports C-V2XPC5 direct communication.

[0036] Specifically, as Figure 2 shown, the steps for the target detection and warning device to perform conflict risk determination are as follows: Precondition confirmation: When the duration of the occlusion state detected by the infrared pair sensor is not less than 300 milliseconds, or when the time that the receiving end of the infrared pair sensor continuously fails to detect the light beam (i.e., the occlusion state = 1) reaches the set value, the central control device determines that the cyclist has entered the intersection conflict area; and immediately sends an instruction to the millimeter-wave radar to increase its sampling frequency from the default 10Hz to 20Hz to improve the monitoring accuracy.

[0037] Target validity screening: The central control device screens out targets with a moving heading angle within the range of 30° to 60° from the target list reported by the millimeter-wave radar: When the moving heading angle of the motor vehicle target detected by the millimeter-wave radar is within the range of 30° to 60°, it is determined as a valid motor vehicle target turning right into the intersection.

[0038] (c) Conflict determination: For each "valid right-turn motor vehicle target", the central control device performs the following joint threshold judgment based on the relative distance and relative speed between the valid motor vehicle target and the cyclist: When D ≤ 4m and the relative speed ≥ 3km / h, it is determined as a high-risk conflict; when 4m < D ≤ 8m and the relative speed ≥ 5km / h, it is determined as a medium-risk conflict, and the sampling frequency of the millimeter-wave radar is increased to enhance monitoring. At this time, the sampling frequency is 20Hz; Among them, the hierarchical early warning execution includes: When it is determined as a high-risk conflict, it synchronously triggers: (i) Send an instruction to the control motor of the isolation pile to raise it to a height of 30cm. At the same time, the internal red LED of the retractable isolation pile flashes red light at a preset frequency, and the red light brightness is not less than 80cd / m²; (ii) Through the visual display unit, push a text prompt to the cyclist according to the preset text prompt font, font size, and preset continuous display time. For example, drive the LCD screen at the intersection to display warning text such as "There is a motor vehicle turning right on the right, do not rush!" The font size is 28, black background and yellow characters, and start the directional speaker for voice broadcast for a duration of 5 seconds; (iii) Send an avoidance reminder message to the motor vehicle through the vehicle networking module, with the content of "Pay attention to avoiding the straight-going cyclist", and the voice broadcast duration is the preset avoidance reminder duration, such as 2 seconds.

[0039] The intelligent guidance module is integrated on the front of the basic support structure, as Figure 3As shown, it includes a 19-inch high-definition LCD touchscreen, a 15W directional speaker with a sound emission angle of ≤30°, and a Bluetooth 5.0 communication module. The functional supply module is located on the side of the basic support structure and includes two USB-A charging ports, two Type-C charging ports, an emergency supplies box controlled by an electromagnetic lock, and a designated shared bicycle parking area on the side.

[0040] Furthermore, in the intelligent guidance module, the central control device performs data access verification and time synchronization processing, including: The system performs integrity checks on various types of data accessed by the IoT platform, triggering retransmission when the missing data rate exceeds a preset threshold. For example, the central control device, via a 4G communication module, requests a data packet containing information such as road conditions, traffic light status, and weather from the city's IoT platform every second. Each data packet includes a standard JSON header with a field count identifier. The central control device's built-in verification program first parses this identifier and compares it with a preset list of complete fields, for example, a list of 20 core fields. If the number of missing fields exceeds 10% of the total number of fields (≥3 fields missing), the data packet is deemed incomplete, a retransmission request is immediately sent to the platform, and the previous valid data is temporarily stored as a replacement.

[0041] Using the local high-precision clock as a reference, the time deviation between the timestamp of each data item and the local clock is calculated. When the time deviation is greater than the preset deviation threshold, linear interpolation is used to correct continuous data, while discrete data is discarded and waits for the next round of acquisition. The preset deviation threshold is 500ms. The central control device has a built-in high-precision temperature-compensated crystal oscillator (TCXO) as the local clock reference.

[0042] The time synchronization formula is as follows: in, The data values ​​after calibration. The original data values, For local clock timestamps The original data timestamp For the timestamp of the next piece of raw data; This will be the next raw data value. For each successfully received data item, retrieve the original timestamp. and with the local clock A comparison is performed. If the time deviation is greater than 500ms, the device marks the data item as "needs calibration". Subsequently, the central control device queries the circular buffer and performs data correction processing. For such discontinuously changing data, if the time deviation is >500ms, the central device does not perform interpolation, but directly discards the data item, maintains the previous valid state, and starts the next round of acquisition and waits.

[0043] The central control device uses a domestic embedded controller based on the HarmonyOS operating system, such as the RK3588 chip, which is built inside the basic support structure. The central control device establishes communication connections with the above-mentioned safety protection module, intelligent guidance module, and functional supply module through an industrial-grade CAN bus. During system operation, the central control device continuously receives various sensing data from each functional module. The various sensing data includes road surface conditions, vehicle positions, charging status, etc. Based on these sensing data, the processor in the central control device executes a preset collaborative control logic to generate corresponding collaborative control instructions. For example, when receiving a signal of icy road surface, instructions such as "display warning information" and "start voice broadcast" are generated. Subsequently, the central control device distributes these instructions to the corresponding intelligent guidance module through the CAN bus to perform linkage operations.

[0044] Specifically, after completing the above time synchronization and verification, the central control device performs data anomaly detection. The central control device has a preset physical reasonable value range table built-in, including: the effective range of the congestion index (CI) is [0, 10]; the effective range of motor vehicle flow is [0, 200] vehicles / minute; the effective range of rainfall is [0, 200] mm / h. The data anomaly detection includes: Judging the reasonable value range of the collected data items. When the congestion index of the cycling lane exceeds the range of 0 - 10, the motor vehicle flow exceeds 0 - 200 vehicles / minute, and the rainfall exceeds 0 - 200 mm / h, it is marked as abnormal; first, check whether the current data value falls within the corresponding interval. If it is marked as "value range anomaly", it is directly excluded from the data stream.

[0045] For the data passing the value range verification, further perform the threshold determination of the time series change rate: calculate the data change rate R for the time series data collected in three consecutive rounds. If R exceeds the set threshold, it is determined as abnormal. The formula for calculating the data change rate is: , where is the current round data value, is the previous round data value; for flow data, R ≤ 50%, and for meteorological data, R ≤ 30%; for flow data such as motor vehicle flow and meteorological data such as rainfall, once it is judged as a change rate anomaly, the data item is excluded.

[0046] For the data passing the above two - fold verification, the central control device compares the currently sensed or received data with the mean value of the nearest three - round valid data in the circular buffer and the standard deviation of the three - round historical data to calculate the deviation D. When the deviation D exceeds twice the standard deviation .

[0047] Any data item deemed abnormal by any stage is removed from the current data stream and a log entry is triggered. Simultaneously, the system maintains its previous valid state and reacquires new data in the next data collection cycle.

[0048] Furthermore, after anomaly detection, the central control unit performs standardized preprocessing on the retained valid raw data. In this embodiment, cycling speed data is the core object, but it is extended to other heterogeneous data types. Specifically, the cycling speed data is cleaned to remove outliers exceeding 30 km / h or falling below 0.5 km / h, and a moving average method is used to correct for normal noise. The central control unit first processes the raw cycling speed data from the road condition sensor array or IoT platform. Range filtering is performed, and for the retained effective velocity sequences, a 5-point moving average method is used for smoothing to suppress random measurement noise. The specific calculation formula is as follows: The moving average formula is as follows: in, denoted as the average cycling speed of the cleaned road section, and n is the number of sampling points; The value represents the velocity value collected consecutively for n times; in this embodiment, n is 5.

[0049] In this embodiment, the central control device standardizes data of different dimensions, unifying flow data as "vehicles / 100 meters", speed data as "km / h", and location data as WGS84 longitude and latitude format.

[0050] In this embodiment, the central control device also performs scene type determination, specifically including: The system matches the current time to the corresponding time period label, which includes morning rush hour, evening rush hour, off-peak, and holidays. The current time is provided by the built-in RTC (Real-Time Clock) module in the central control unit. The road type is configured during system initialization via a configuration file or imported from the city's GIS platform; for example, the current road segment might be labeled "Commuter Main Road." The cycling density ρ is obtained from preprocessed traffic flow data. For example, if, after standardization, 15 bicycles are measured within a 100-meter stretch, then ρ = 15 bicycles / 100 meters. Maximum carrying capacity density. The maximum carrying capacity density value is set based on the road type. For example, if the road segment is a "commuter artery", then... =20 vehicles / 100 meters; if it is a "leisure greenway", then =10 vehicles / 100 meters. Free riding speed A preset constant is set for the system, with a value of 15 km / h.

[0051] Based on the current cycling density ρ of the road segment and the maximum carrying capacity of the road segment Free riding speed Average cycling speed on the road The congestion index (CI) is calculated using the following formula:

[0052] Where α is the weighting coefficient, with a value of 0.6; CI ≥ 0.6 is considered congested, 0.3 ≤ CI < 0.6 is considered mildly congested, and CI < 0.3 is considered unobstructed.

[0053] The central control unit is configured to perform scenario type determination, including: If the current time period is labeled as morning or evening rush hour and the current road type is a commuter main road, it is determined to be a rush hour scenario; if the current road type is a leisure greenway or scenic road, or if the current time period is labeled as a holiday and there are no fewer than three scenic spots or rest areas within the preset surrounding area, it is determined to be a leisure greenway / scenic area scenario; otherwise, it is determined to be a normal off-peak scenario; the preset surrounding area is within a radius of 500 meters.

[0054] The central control unit is also configured to perform user group determination, including: When an elderly mode trigger signal is received, the system identifies the user as elderly. Elderly mode trigger signals include structured messages sent proactively by a mobile app or NFC card to the central control device. For elderly users, the display font size is adjusted to a preset large font size, the color scheme is switched to high contrast mode, and the voice broadcast speed is adjusted to 80% of the normal speaking speed. For example, the LCD screen's UI rendering engine forces all text font sizes to 24 points or larger; the background color is switched to pure black, and the text color is switched to high-contrast yellow, i.e., "black background with yellow text"; during voice broadcast, the text-to-speech (TTS) module's speaking speed parameter is adjusted from the default 180 words / minute to 144 words / minute.

[0055] When a vehicle is identified as an electric bicycle, the user is identified as an electric bicycle rider, and remaining battery power data is collected. The user's built-in smart terminal (such as a vehicle infotainment system or battery management system module) broadcasts the vehicle's attributes via Bluetooth. Upon receiving this Bluetooth broadcast, the central control unit identifies the vehicle type and simultaneously retrieves the remaining battery power. For electric bicycle riders, the full-charge range is matched to the vehicle model. Calculate the distance that the remaining battery power can support based on the current remaining battery percentage (B) and the road condition correction factor (K). The calculation formula is: Where K=0.8 corresponds to congested road sections, and K=1.0 corresponds to uncongested road sections.

[0056] When neither of the above two types of signals is triggered, that is, during the interaction process, neither the elderly mode signal is received nor the electric bicycle icon is recognized, the user is determined to be a member of the general population. Finally, the device generates a structured context label, for example: {“scene”: “leisure”, “user_group”: “e-bike”}.

[0057] For example, the central control unit first matches the "morning rush hour" label based on the current time being 8:15 AM on a weekday. Combining this with the known "commuter main road" attribute, regardless of the calculated CI value, it is directly classified as a "commuter peak scenario". If the current time is 10:00 AM on a Saturday and the road type is "leisure greenway", then even if CI=0.7, it is classified as a "leisure greenway / scenic area scenario"; if it is a regular urban secondary road and not during peak hours, further judgment is made based on the CI value: if CI≥0.6, it is congested, but the scenario is still classified as a "regular off-peak scenario".

[0058] In this embodiment, as Figure 4 As shown, the central control device dynamically configures the priority level and update frequency of information display based on the determined combination of scene type and user group, wherein: (i) During peak commuting hours, regardless of user group type, the congestion index (≥0.6) and temporary road occupancy information are set to P1 level, the signal countdown and recommended cycling speed are set to P2 level, and surrounding basic supporting facilities are set to P3 level. The information update frequency is once every 0.5 seconds. For example, P1 level information: real-time acquisition of the congestion index (CI) and temporary road occupancy events pushed by the municipal platform. If CI ≥0.6, the "Severe Congestion" icon and text are highlighted in the permanent area at the top of the LCD screen; temporary road occupancy information is forcibly displayed in a red pop-up window. For P2 level information, such as the traffic light countdown (from the intersection signal controller interface) and the "recommended cycling speed" (e.g., "recommended ≤15km / h") based on the current speed are displayed scrolling in the middle of the screen. P3 level information: information on surrounding basic supporting facilities such as toilets and drinking fountains is collapsed to the secondary menu.

[0059] (ii) In leisure greenways / scenic areas, targeting the general public, the distance between scenic spots and rest areas is set to P1 level, the location of restrooms and road condition indicators are set to P2 level, and historical scenic images are set to P3 level. Information is updated every 3 seconds, and image-based information is updated every 5 seconds. For example, P1 level information such as "Lake Pavilion (300m ahead)" and "Rest Area (100m to the left)" are displayed at the top with large icons and distance indicators. P2 level information: The restroom distribution map and the "Road Condition" green indicator are located in the center. P3 level information: The historical scenic photo carousel is placed at the bottom.

[0060] (iii) In ordinary off-peak scenarios, for the general public, road condition prompts and signal countdowns are set to P1 level, surrounding supporting facilities are set to P2 level, and weather information is set to P3 level, with the information update frequency being once every 2 seconds; at this time, new P2 level information such as "remaining power can support: 31.2km" and "charging point A (2 available)" are added to the P2 information queue.

[0061] (iv) For the elderly population, in any scenario, core navigation guidance and safety warnings will be set to Level P1, signal countdown to Level P2, and simplified supporting information to Level P3. Information will be updated every 1 second, and voice announcements will be broadcast every 2 seconds. For example, Level P1 information will only display the most essential "direction arrow," "nearest rest area: 200m," and safety warnings such as "Vehicle ahead, please be careful!" Level P2 information will display the signal countdown in very large numbers. Level P3 information will only retain the "restroom" icon, hiding other supporting information.

[0062] For electric bicycle riders, in addition to the priority of the corresponding scenario, the remaining power range and the status of nearby charging points are set as P2 level information, and the power-related information is updated once every 1 second.

[0063] The energy management unit, also known as the energy supply unit, is electrically connected to the central control unit and various functional modules. It adopts a dual-mode architecture of "solar priority + municipal power backup," with a flexible monocrystalline silicon solar panel mounted on top, connected to a 12V / 100Ah lithium iron phosphate battery pack for energy storage; the photoelectric conversion efficiency of the flexible monocrystalline silicon solar panel is ≥22%. The photovoltaic charge / discharge controller and automatic transfer switch (ATS) inside the energy management unit work together to monitor battery power and load demand in real time, and coordinate the allocation of power resources from solar energy or the municipal power grid (AC 220V) to ensure a stable power supply for the system under any weather conditions.

[0064] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0065] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An integrated road auxiliary traffic facility system adapted for cyclists, characterized in that, include: The basic support structure, multiple functional modules integrated on the basic support structure, a central control device, and an energy management device; The aforementioned multiple functional modules include at least a security protection module, an intelligent guidance module, and a function replenishment module; The security protection module includes: The protection unit along the route is configured on continuous sections of the cycling path and includes buffer guardrails, adaptive ambient light warning lights, and a road condition sensor array for real-time monitoring of road conditions. The intersection conflict prevention unit, configured in the intersection area, includes retractable bollards linked to traffic signals and a target detection and early warning device based on millimeter-wave radar; the target detection and early warning device acquires the relative distance and speed between motor vehicles and cyclists, and triggers an audible and visual warning when preset risk conditions are met; The central control device establishes communication connections with each functional module, receives sensing data from each functional module, generates collaborative control commands based on the sensing data, and distributes the collaborative control commands to the corresponding functional modules to execute linkage operations. The energy management device is electrically connected to the central control device and various functional modules, and is used to coordinate and allocate power supply resources.

2. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 1, characterized in that, The target detection and early warning device is configured to: confirm whether a cyclist has entered the conflict zone through an infrared beam sensor, and combine the relative distance and relative speed between the motor vehicle and the cyclist obtained by millimeter-wave radar, and make multi-level risk judgments based on a preset distance and speed joint threshold. When a high-risk conflict is identified, it triggers audio-visual and text warnings for cyclists, vehicle-to-everything (V2X) avoidance reminders for motor vehicles, and dynamic warnings from retractable bollards.

3. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 1, characterized in that, In the intelligent guidance module, the central control device performs data access verification and time synchronization processing, including: Perform integrity checks on various types of data accessed by the IoT platform, and trigger retransmission when the missing rate exceeds a preset threshold. Using the local high-precision clock as a reference, the time deviation between the timestamp of each data item and the local clock is calculated. When the time deviation is greater than the preset deviation threshold, the continuous data is corrected by linear interpolation, and the discrete data is discarded and waited for the next round of acquisition. The time synchronization formula is as follows: in, The data values ​​after calibration. The original data values, For local clock timestamps, This is the original data timestamp. For the timestamp of the next piece of raw data; This will be the next original data value.

4. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 3, characterized in that, The central control device performs data anomaly detection, including: The collected data items are judged to be within a reasonable range. When the congestion index of the cycling lane exceeds 0-10, the traffic flow exceeds 0-200 vehicles / minute, or the rainfall exceeds 0-200 mm / h, they are marked as abnormal. The rate of change R is calculated for time-series data collected in three consecutive rounds. If R exceeds a set threshold, it is considered abnormal. The formula for calculating the rate of change is as follows: ,in The current round of data values, The data should be from the previous round; for flow data, R ≤ 50%, and for meteorological data, R ≤ 30%. Compare the currently sensed or received data with the average of the three most recent valid data in the circular buffer. Compare the results and calculate the deviation D. When the deviation D exceeds twice the standard deviation... When an exception is detected, the expression is: 。 5. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 3, characterized in that, The central control unit performs data preprocessing, including: The cycling speed data was cleaned to remove outliers exceeding 30 km / h or falling below 0.5 km / h, and normal noise was corrected using a moving average method. The moving average formula is as follows: in, denoted as the average cycling speed of the cleaned road section, and n is the number of sampling points; The velocity value is obtained from n consecutive data acquisitions. Data of different units were standardized, with traffic flow data standardized to "vehicles / 100 meters", speed data standardized to "km / h", and location data converted to WGS84 longitude and latitude format.

6. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 1, characterized in that, The central control device performs scenario type determination, specifically including: Match the time period label to the current time, which includes morning rush hour, evening rush hour, off-peak, and holidays; Based on the current cycling density ρ of the road segment and the maximum carrying capacity of the road segment Free riding speed Average cycling speed on the road The congestion index (CI) is calculated using the following formula: in, CI is a weighting coefficient. A value of CI ≥ 0.6 indicates congestion, 0.3 ≤ CI < 0.6 indicates mild congestion, and CI < 0.3 indicates smooth traffic.

7. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 6, characterized in that, The central control device is configured to perform scenario type determination, including: If the current time period is labeled as morning or evening rush hour and the current road type is a main commuter road, it is determined to be a rush hour scenario. When the current road type is a leisure greenway or scenic road, or when the current time period is labeled as a holiday and there are no fewer than three scenic spots or rest areas within the preset surrounding area, it is determined to be a leisure greenway / scenic area scene; The remaining situations are classified as ordinary off-peak scenarios; The central control unit is also configured to perform user group determination, including: When the elderly mode trigger signal is received, it is determined to be an elderly person; When the vehicle type is identified as an electric bicycle, the rider is identified as an electric bicycle rider, and the remaining battery power data is collected. Otherwise, they are classified as ordinary members of the group.

8. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 7, characterized in that, The system also includes: For the elderly, the font size will be adjusted to the preset large font size, the color scheme will be switched to high contrast mode, and the voice broadcast speed will be adjusted to 80% of the speed of ordinary people; For electric bicycle riders, the full-charge range is matched based on the vehicle model. Calculate the distance that the remaining battery power can support based on the current remaining battery percentage (B) and the road condition correction factor (K). The calculation formula is: Where K=0.8 corresponds to congested road sections, and K=1.0 corresponds to uncongested road sections.

9. An integrated road assist traffic facility system adapted to cyclists according to claim 7 or 8, characterized in that, The central control device dynamically configures the priority level and update frequency of information display based on the determined combination of scene type and user group, wherein: During peak commuting hours, regardless of user group type, the congestion index (when ≥0.6) and temporary road occupancy information are set to P1 level, the signal countdown and cycling speed are set to P2 level, and the surrounding basic supporting facilities are set to P3 level. The information update frequency is once every 0.5 seconds. In the context of leisure greenways / scenic areas, for the general public, the distance between scenic spots and rest areas is set to P1 level, the distribution of restrooms and road condition prompts are set to P2 level, historical scenic images are set to P3 level, the information is updated every 3 seconds, and image information is updated every 5 seconds. In ordinary off-peak scenarios, for the general public, the traffic condition prompts and signal countdowns are set to P1 level, the surrounding supporting facilities are set to P2 level, the weather information is set to P3 level, and the information is updated every 2 seconds. For the elderly, in any scenario, the core navigation guidance and safety warnings are set to P1 level, the signal countdown is set to P2 level, the simplified supporting information is set to P3 level, the information update frequency is once every 1 second, and the voice broadcast frequency is once every 2 seconds. For electric bicycle riders, in addition to the priority of the corresponding scenario, the remaining power range and the status of nearby charging points are set as P2 level information, and the power-related information is updated once every 1 second.

10. The integrated road auxiliary traffic facility system adapted to cyclists according to claim 2, characterized in that, The target detection and early warning device performs conflict risk assessment by including the following steps: When the infrared beam sensor detects that the obstruction lasts for no less than 300 milliseconds, it determines that the cyclist has entered the intersection conflict zone; at the same time, when the millimeter-wave radar detects that the heading angle of the motor vehicle target is within the range of 30° to 60°, it determines that it is a valid motor vehicle target turning right into the intersection. Based on the relative distance and relative speed between the valid motor vehicle target and the cyclist, the following joint threshold judgment is performed: When D≤4m and relative speed≥3km / h, it is judged as a high-risk conflict; When 4m < D ≤ 8m and the relative speed ≥ 5 km / h are satisfied, it is determined as a medium-risk conflict, and the sampling frequency of the millimeter-wave radar is increased to enhance monitoring; Among them, the implementation of hierarchical warning includes: When it is determined as a high-risk conflict, the following are triggered synchronously: The retractable isolation pile flashes red light at a preset frequency, and the brightness of the red light is not less than 80 cd / m²; Through the visual display unit, text prompts are pushed to the cyclists according to the preset text prompt font, font size, and preset continuous display time; Through the vehicle networking module, avoidance reminder information is sent to the motor vehicle, and the voice broadcast duration is the preset avoidance reminder duration.

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