Urban road planning and designing system and method based on big data

Abstract

The invention discloses an urban road planning design system and method based on big data, and relates to the technical field of intelligent traffic engineering, and the method comprises the following steps: constructing a time window boundary tracing zone, synchronously collecting road traffic flow, vehicle track data and intersection signal data in the urban road planning data generation process, and obtaining a time window boundary tracing zone; and recording an acquisition time difference, an update time difference and a timestamp granularity difference of adjacent administrative regions in the same planning time period, determining a data fracture position and marking a fracture form, and forming a boundary tracing list. According to the invention, by constructing the time window boundary tracing zone and the cross-region continuous discrimination zone, synchronous association and fracture identification of cross-administrative-region data are realized, and the situation that data interruption is misjudged as traffic blocking is avoided; by establishing a communication contact sequence and a boundary undertaking channel and implementing pulse silence regulation and control, dynamic continuity and coordinated migration of cross-regional roads are kept, and the rationality and adaptability of planning and design are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation engineering technology, specifically to a big data-based urban road planning and design system and method. Background Technology

[0002] Big data-driven urban road planning and design refers to a planning approach that moves beyond relying solely on experience or static survey data in the planning and layout of urban roads. Instead, it utilizes big data processing as a core support, continuously collecting and utilizing multi-source data from traffic flow monitoring, vehicle trajectories, travel behavior, population distribution, land use, and environmental perception. Through data cleaning, correlation integration, and time-series analysis, it systematically analyzes road traffic characteristics and spatial demands. Based on this analysis, it scientifically designs road grade configurations, alignment arrangements, intersection settings, and capacity structures. This approach, through comprehensive analysis of massive historical and real-time data within a big data processing framework, reveals the spatiotemporal patterns and potential trends of urban traffic operations, enabling road planning schemes to better meet actual travel needs and adapt to urban development and traffic changes.

[0003] The existing technology has the following shortcomings: In existing technologies, when conducting urban road planning and design based on big data, traffic data from adjacent administrative regions are typically collected independently by different data entities and updated at different times. Due to inconsistencies in data collection cycles, time stamping methods, and synchronization mechanisms, data gaps or breaks can easily occur during the time window alignment and overlap processing phases for data from adjacent administrative regions. When dynamically analyzing the aforementioned data, existing planning systems often directly judge road traffic status based on data continuity, lacking the ability to identify the characteristics of cross-administrative region data boundaries. This leads to misjudging such data breaks as actual traffic disruption sources, resulting in unreasonable adjustments to the connectivity of cross-regional roads. Consequently, the road network structure is incorrectly fragmented at the planning level, affecting the overall rationality of the cross-administrative region road connectivity structure.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a big data-based urban road planning and design system and method to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a big data-based urban road planning and design method, comprising the following steps: Construct a time window boundary marking zone, and simultaneously collect road traffic flow, vehicle trajectory data and intersection signal data during the generation of urban road planning data. Record the time difference, update time difference and timestamp granularity difference between adjacent administrative regions in the same planning period, determine the data break location and mark the break shape, and form a boundary marking list. Based on the boundary description list, a cross-regional continuity discrimination zone is constructed, and the road traffic flow direction, vehicle trajectory density and road segment code before and after the break are mapped to a unified time baseline. The dynamic features of the break are extracted and the break type label is generated to form a suspected blockage index. Based on the suspected blocking index, the cross-regional road connectivity chain is traced back, the entry sequence, exit sequence and turning sequence of the corresponding interface road segment are extracted, the connectivity contact point sequence is constructed and the acceptable range of the contact point is marked. Based on the sequence of connected contact points, a boundary acceptance channel is constructed. The broken segments corresponding to the boundary description list are transformed into acceptable gaps and written into the channel threshold. The cross-regional road connectivity simulation is limited to continuous segment migration within the channel threshold range, and an acceptance threshold table is generated. Based on the threshold table, pulse silence interleaving control is performed within the time window of cross-administrative region boundaries. By injecting short-term silence segments and micro-delay segments in stages, the fracture edge gradually shifts along the channel threshold direction and maintains the migration rhythm of the cross-regional road connectivity chain, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships.

[0007] Preferably, the steps for generating the boundary description list are as follows: During the urban road planning data generation phase, data collection areas are set around the main roads, secondary roads and intersections of the city. Road traffic flow, vehicle trajectory data and intersection signal data are collected synchronously, and the time starting point of the collection terminals of each administrative region is unified during the synchronous collection process. After completing the synchronous collection, the collected data from different administrative regions are input into the time window boundary recording tape, the time difference of collection time, the time difference of update time and the time stamp granularity difference are recorded, and the spatial correlation information of road traffic flow, vehicle trajectory and intersection signal data is written into the recording tape; The fracture location is determined in the time window boundary tracing band based on the joint analysis results of the acquisition time difference, update time difference, and timestamp granularity difference, and the time interval and spatial coordinates corresponding to the fracture location are written into the tracing band. After determining the location of the fracture, the fracture morphology is marked according to the temporal pattern and spatial distribution characteristics of the fracture segment, and a boundary description list is generated.

[0008] Preferably, when marking the morphology of the fracture location, the temporal pattern and spatial distribution characteristics of the fracture segment are combined. The fracture segments are classified according to the degree of abrupt change in road traffic flow, the sudden drop in vehicle trajectory density, and the duration of intersection signal switching. Annotation fields are established in the time window boundary marking band to record the temporal range, spatial coordinates, and associated road information of the fracture.

[0009] Preferably, the steps for generating the suspected blocking index are as follows: Based on the boundary delineation list, the road traffic flow data, vehicle trajectory data and road segment coding information before and after the fracture are read, and the time distribution of the data is balanced according to the time difference of collection, update time difference and timestamp granularity difference, and the data before and after the fracture are mapped to the corresponding road nodes and intersections in the spatial dimension. After completing the data mapping, a unified time baseline is constructed based on the time window range in the boundary description list. The road traffic flow direction, vehicle trajectory density and road segment coding information before and after the break are aligned to the unified time axis, so that the data maintains structural continuity on the time baseline. After establishing a unified time baseline, the trend of road traffic flow changes, changes in vehicle trajectory density distribution, and road segment coding connection relationships before and after the fracture are extracted to form a fracture dynamic feature set. Based on the dynamic feature set of fractures, fracture type labels are generated and a suspected blockage index is formed to measure the impact of fractures on the continuity of traffic on roads across administrative regions.

[0010] Preferably, in the process of generating fracture type labels, fracture types are classified into traffic flow mutation type, trajectory sparse type, code break type and composite offset type according to the differences in road traffic flow direction before and after the fracture, the magnitude of vehicle trajectory density change and the continuity offset characteristics of road segment coding, and the time period, spatial range and affected road number are recorded in the fracture type label.

[0011] Preferably, the steps for constructing the connected contact sequence are as follows: Based on the suspected blocking index, backtracking analysis of cross-administrative region road data is performed. The road traffic flow, vehicle trajectory density and road segment coding information are tracked along the time period before and after the break, and the road boundary nodes at the break are determined and a road node linked list is formed. Based on the road node linked list, the entry sequence of the interface road segment is extracted. The time window is extended upstream along the time sequence with the break position as the center. Road nodes with vehicle trajectory density greater than the set threshold are recorded and the entry sequence is formed. After the entry sequence is extracted, the corresponding exit sequence is extracted. Starting from the break point, the time window is extended downstream along the time sequence, and the exit nodes are arranged in chronological order to form the exit sequence. Based on the entry and exit sequences, the turning sequence of the break position is extracted, the connected contact sequence is constructed, and the bearing range of the contact is calibrated.

[0012] Preferably, the steps for generating the acceptance threshold table are as follows: Spatial extraction of fracture segments is performed based on the connected contact sequence and boundary description list. The time interval of the fracture segments is matched with the time position of the connected contact to form the fracture receiving area. The road traffic flow, vehicle trajectory density and road geometric parameters are integrated to generate structured description units. After completing the spatial extraction of the fractured fragments, a boundary receiving channel is established with the connecting contact point as the core. A connection path is generated along the outer edge of the receiving range, so that the receiving channel connects the upstream and downstream boundaries of the fracture in space and maintains the continuity of the passage state in the time dimension. After the receiving channel is constructed, a channel threshold is set and the broken segments are transformed into receptive gaps, forming a channel boundary zone with the spatial path of the receiving channel as the axis; After the channel threshold is set, a receiving threshold table is generated, which records the channel number, contact number, threshold range, receiving gap coordinates, and time window range.

[0013] Preferably, the threshold setting of the passage is based on the acceptable range of the connecting contact point, and the width of the passage boundary zone is determined in combination with the road grade, number of lanes and traffic density. Different types of fractures correspond to different threshold constraints, so that the threshold range of the flow change type fracture keeps the direction of traffic consistent, and the threshold range of the coded chain break type fracture allows multiple paths to be accepted.

[0014] Preferably, based on the threshold table, pulse-silent interleaved control is performed within the cross-administrative region boundary time window, injecting short-term silent segments and micro-delay segments in stages to gradually shift the fracture edge along the channel threshold direction and maintain the migration rhythm of the cross-regional road connectivity chain. The steps are as follows: Based on the threshold table, the time window range of pulse silence control is determined, the start time and end time at the boundary are extracted and divided into multiple stages, so that the time window covers the complete passage cycle of the broken segment. After determining the time window, short-term silent segments are injected into the receiving channels that cross administrative boundaries. Injection positions are set at equal intervals on both sides of the channel centerline to make the traffic flow curve form a flexible transition zone on the time axis and weaken data abrupt changes. After the short-term silent segment takes effect, a small delay segment is injected along the threshold direction of the receiving channel, so that the fracture edge gradually shifts on the time axis and maintains the time continuity of the passage state. By combining short-duration silent segments and minimal delay segments, the traffic data within the boundary time window is controlled as a whole, so that the fracture edge can maintain coordinated migration in time and space and generate a dynamically stable rearranged connected dataset.

[0015] A big data-based urban road planning and design system includes a boundary marking module, a continuity discrimination module, a touchpoint analysis module, a connecting passage module, and a connectivity control module. The boundary marking module constructs a time window boundary marking zone, synchronously collecting road traffic flow, vehicle trajectory data, and intersection signal data during the generation of urban road planning data. It also records the time difference, update time difference, and timestamp granularity difference between adjacent administrative regions within the same planning period, determines the data break location, marks the break shape, and forms a boundary marking list. The continuous discrimination module constructs a cross-regional continuous discrimination zone based on the boundary description list, maps the road traffic flow direction, vehicle trajectory density and road segment code before and after the break to a unified time baseline, extracts the dynamic features of the break and generates a break type label, forming a suspected blockage index. The contact point analysis module traces the cross-regional road connectivity chain based on the suspected blocking index, extracts the entry sequence, exit sequence and turning sequence of the corresponding interface road segment, constructs the connectivity contact point sequence and marks the acceptable range of the contact point; The receiving channel module constructs boundary receiving channels based on the sequence of connected contact points, transforms the broken segments corresponding to the boundary description list into receiving gaps and writes them into the channel threshold, limits the migration of continuous segments in the cross-regional road connectivity simulation within the channel threshold range, and generates a receiving threshold table. The connectivity control module performs pulse-silent interleaved control within the cross-administrative region boundary time window based on the acceptance threshold table. By injecting short-term silent segments and micro-delay segments in stages, it gradually shifts the fracture edge along the channel threshold direction and maintains the migration rhythm of the cross-regional road connectivity chain, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention constructs a time window boundary marking zone and a cross-regional continuity discrimination zone during the urban road planning data generation stage. This enables synchronous correlation of data collected from different administrative regions in both time and space, allowing for the identification and labeling of break locations and morphologies caused by differences in data collection. Through this method, cross-regional traffic data possesses continuity recognition capabilities during alignment and fusion, effectively preventing data interruptions caused by temporal heterogeneity from being misjudged as traffic disruptions. This maintains a complete representation of road traffic conditions in planning analysis, making the cross-regional road network structure more consistent with actual traffic patterns in layout design.

[0017] This invention establishes a sequence of connected contact points and boundary acceptance channels, generates acceptable gaps at fracture points and applies channel threshold constraints, and combines pulse-silent interleaved regulation to achieve gradual translation of fracture edges, enabling cross-administrative region roads to maintain coordinated migration in time and space. Through this method, road connectivity chains can continuously and stably extend during dynamic planning, and cross-regional traffic structures maintain adaptive consistency in data updates and traffic changes, thereby improving the rationality and long-term applicability of road planning and design results. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0019] Figure 1 This is a flowchart of a big data-based urban road planning and design method according to the present invention.

[0020] Figure 2 This is a schematic diagram of a big data-based urban road planning and design system according to the present invention. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0022] This invention provides, for example Figure 1 The urban road planning and design method based on big data, as shown, includes the following steps: Construct a time window boundary marking zone, and simultaneously collect road traffic flow, vehicle trajectory data and intersection signal data during the generation of urban road planning data. Record the time difference, update time difference and timestamp granularity difference between adjacent administrative regions in the same planning period, determine the data break location and mark the break shape, and form a boundary marking list. To address the issue of discrepancies in time stamping methods and data collection cycles in urban road planning data generated across administrative regions, this paper describes the use of time window boundary marking strips to temporally organize and spatially correlate the data. This ensures that the foundational data for subsequent road connectivity analysis possesses complete temporal consistency and spatial continuity. The specific steps are as follows: During the urban road planning data generation phase, data collection areas are established around main roads, secondary roads, and intersections. Road traffic flow, vehicle trajectory data, and intersection signal data are collected synchronously. During the collection process, a unified time window is used as the sampling period. Within each time window, the rate of change in road traffic flow, the spatial distribution density of vehicle trajectories, and the state transition information of intersection signals are continuously recorded, ensuring the continuity of the collection results over time. To address inconsistencies in data collection frequencies between different administrative regions, a baseline is unified for the time starting point of each administrative region's collection end during synchronous collection, ensuring the comparability of the collected data when entering the time window boundary recording zone. This collection process lays the data foundation for subsequent recording of collection time differences, update time differences, and timestamp granularity differences.

[0023] After synchronous data collection, data from different administrative regions are input into the time window boundary marking tape, and the collected data is time-stamped according to the planned time period. For the time distribution of data collected from adjacent administrative regions within the same time period, the difference in collection times for each administrative region is calculated, and the specific value of the collection time difference is recorded. Simultaneously, the update time difference of the data in the system is also recorded, i.e., the time delay experienced from data generation to entry into the analysis channel. Furthermore, to reflect the differences in time stamp granularity among administrative regions, the timestamp granularity difference is extracted, which characterizes the differences in time annotation accuracy among different data subjects. While recording the above three types of time difference parameters, the spatial correlation information of road traffic flow, vehicle trajectory, and intersection signal data is also written into the marking tape, forming data entries corresponding to both time and space dimensions. This allows the boundary marking tape to accurately locate data anomalies caused by time differences in subsequent steps.

[0024] A data break identification mechanism is established within the time window boundary delineation band, jointly analyzing the differences in collection time, update time, and timestamp granularity. When any parameter within a continuous time window exceeds a set threshold, it is considered a time period where a data break may occur. At this point, the system spatially locates the suspected break location based on the trend of road traffic flow changes and the continuity of vehicle trajectories within that time period. During the location process, the time series of road traffic flow is compared with the spatial distribution trajectory of vehicle trajectories to determine the spatial coordinates of the break and the corresponding road node location. Simultaneously, the time window information before and after the break segment is written into the boundary delineation band, ensuring that each break record has a clear time interval identifier and spatial location description. In this way, the time window boundary delineation band not only records time difference parameters but also forms a break identification framework that corresponds one-to-one with the urban road spatial topology, providing a basis for subsequent break morphology annotation.

[0025] After determining the location of the fracture, the fracture segments are morphologically labeled. Morphological labeling is based on the occurrence pattern and spatial distribution characteristics of the fracture segments within a time window, comprehensively considering the abrupt changes in road traffic flow, sudden drops in vehicle trajectory density, and abnormal durations of intersection signal switching. Fracture morphologies are classified into several types, including time-delayed, sampling-missing, granularity-mismatched, and mixed fracture types. For each fracture type, a corresponding labeling field is established in the boundary delineation band to describe the fracture's temporal range, spatial coordinates, and affected road numbers. Subsequently, all fracture labeling results are integrated in chronological order to generate a boundary delineation list. This list includes the fracture's start and end times, fracture category, associated roads, adjacent administrative district numbers, and time difference parameters, which are directly used in subsequent cross-regional continuity determination stages. Through the generated boundary delineation list, the fracture characteristics of urban road planning data in both time and space are fully presented, enabling data from different sources to be uniformly mapped to the same time baseline in subsequent steps, thus providing a complete data foundation for the dynamic analysis of cross-administrative district road connectivity.

[0026] Based on the boundary description list, a cross-regional continuity discrimination zone is constructed, and the road traffic flow direction, vehicle trajectory density and road segment code before and after the break are mapped to a unified time baseline. The dynamic features of the break are extracted and the break type label is generated to form a suspected blockage index. To conduct cross-administrative-region continuity analysis on the break locations and their time difference characteristics recorded in the boundary delineation list, a cross-regional continuity discrimination band is constructed to ensure that cross-regional road data can be uniformly mapped and correlated in both time and space dimensions. By constructing the cross-regional continuity discrimination band, a coherent time baseline can be established before and after the data break, dynamic features reflecting changes in traffic conditions can be extracted, and different types of breaks can be identified and classified, thus providing a continuity judgment basis for subsequent road connectivity projections. The specific steps are as follows: Spatiotemporal mapping of road data before and after a data fracture is prepared based on a boundary delineation list. The list includes the start and end times, fracture morphology, road number, and adjacent administrative district numbers for each fracture. Based on this, traffic flow data, vehicle trajectory data, and road segment coding information before and after the fracture are selected and read according to the time stamp order in the list. During the reading process, the temporal distribution of the data is balanced based on the time difference, update time difference, and timestamp granularity difference recorded by the data collection terminals in each administrative district, ensuring that data collected from different areas can be compared in time series. Spatially, traffic flow and vehicle trajectory density before and after the fracture are mapped to corresponding road nodes and intersection locations, forming a multidimensional dataset containing both temporal and spatial coordinates, providing a data input foundation for establishing a unified time baseline.

[0027] After completing the spatiotemporal mapping preparation of the data, a unified time baseline is constructed based on the time window range in the boundary delineation list. The unified time baseline serves as a reference framework for time synchronization between different administrative regions, enabling road data before and after the rupture to be arranged and compared according to the same time scale. During construction, the road traffic flow direction, vehicle trajectory density, and road segment coding information before and after the rupture are sequentially aligned to the unified time axis according to the start and end times of the boundary delineation list. For regional data with shorter sampling periods, time-weighted interpolation is used to maintain continuity on the time baseline; for regional data with longer sampling periods, fine-tuning is performed based on the update time difference to eliminate uneven time distribution. In this way, data before and after the rupture can maintain structural alignment on the same time baseline, thus providing a complete temporal reference for dynamic feature extraction.

[0028] After establishing a unified time baseline, dynamic feature extraction is performed on road data before and after the fracture. Centered on the time baseline, dynamic feature extraction focuses on the changing trends of road traffic flow, the distribution changes in vehicle trajectory density, and the spatial continuity of road segment codes. For each fracture location, the magnitude and direction of changes in road traffic flow within two time windows before and after the fracture are extracted to reflect the temporal transformation of road traffic conditions; the density change range of vehicle trajectories at the fracture location is extracted to reflect the changing trends of road use intensity; and the connectivity of road segment codes on both sides of the fracture is extracted to reflect the continuity of the road topology at the fracture. During the extraction process, the three types of feature data are combined in chronological order to form a fracture dynamic feature set, giving each fracture an independent dynamic descriptive unit. This dynamic feature set includes not only changes in the temporal dimension but also connectivity in the spatial dimension, providing multi-dimensional feature support for fracture type identification.

[0029] Based on the extracted dynamic feature set of fractures, fracture type labels are generated, forming a potential blocking index. The process of generating fracture type labels includes feature pattern recognition and classification description of the fracture feature set. Based on the differences in traffic flow before and after the fracture, the magnitude of trajectory density changes, and the offset characteristics of road segment coding continuity, fracture types are classified into traffic abrupt change type, trajectory sparse type, coding chain break type, and composite offset type. For each fracture type, the corresponding time period, spatial range, and affected road number are recorded in the fracture type label. Subsequently, combining the fracture intensity, impact range, and duration recorded in the fracture type label, a comprehensive impact index of the fracture is calculated, serving as a core component of the potential blocking index. The potential blocking index measures the degree of impact of fractures on the continuity of cross-administrative region road traffic; a higher value indicates that the fracture is more likely to interfere with road connectivity. All potential blocking indices of fractures are organized and summarized in chronological order to form the core data structure of the cross-regional continuity discrimination band. This discrimination band can serve as input for subsequent cross-regional road connectivity chain backtracking, guiding subsequent steps to extract and analyze connectivity points in fracture areas.

[0030] Based on the suspected blocking index, the cross-regional road connectivity chain is traced back, the entry sequence, exit sequence and turning sequence of the corresponding interface road segment are extracted, the connectivity contact point sequence is constructed and the acceptable range of the contact point is marked. To restore the spatial connectivity of roads across administrative regions by blocking suspected indexes, it is necessary to perform serialization analysis on the road break locations and their adjacent areas. This involves extracting the entry, exit, and turning sequences of interface road segments by tracing back the cross-regional road connectivity chain, thereby constructing a connectivity contact sequence and defining the acceptable range of each contact. This process reorganizes the road structure at the cross-regional data break points in both time and space, creating a continuously mapping chain relationship between the break location and its upstream and downstream traffic conditions. This provides an operational contact basis for subsequent connectivity rearrangement. The specific steps are as follows: Backtracking analysis of cross-administrative region road data is performed based on a suspected blockage index. The suspected blockage index records the time interval, spatial coordinates, and impact on road traffic conditions of the break location. Starting from the suspected blockage index, road data is traced backward along the time periods before and after the break, extracting the upstream and downstream road segments adjacent to the break point. During the backtracking process, traffic flow, vehicle trajectory density, and road segment codes on both sides of the break point are synchronously matched according to a unified time baseline to determine the road boundary nodes at the break point. For each boundary node, the road number connected to it and its traffic distribution in the time series are extracted and arranged in chronological order to form a road node linked list. By parsing this linked list, the connection status and directional attributes of the road before and after the break can be clarified, providing path references for subsequent sequence extraction. At this point, the preliminary outline of the cross-regional road connectivity chain is reconstructed in both time and space dimensions, giving each blockage point a basis for tracing the preceding and following paths.

[0031] Based on the backtracked road connectivity chain, the entry sequence of the interface road segment is extracted. The entry sequence describes the path structure and traffic patterns of vehicles entering the fracture location from the upstream area. During the extraction process, a certain time window is extended upstream along the time series direction, centered on the fracture location. Road nodes with vehicle trajectory density greater than a set threshold within this window are selected, and their corresponding road numbers, traffic directions, and average traffic speeds are recorded. These nodes are then arranged in chronological order to form the entry sequence. When generating the entry sequence, the traffic flow direction information in the suspected blockage index is used to uniformly correct the traffic direction of each entry node, ensuring consistency in the flow direction of the entry sequence. By establishing the entry sequence, the traffic inflow pattern and vehicle convergence characteristics of the upstream area of ​​the fracture can be reflected, providing a reference for subsequent judgment of the downstream response of the fracture. The entry sequence not only records the spatial connection order of roads but also describes the dynamic evolution of traffic flow through time sequence, enabling a complete reconstruction of the traffic state of the upstream area of ​​the fracture.

[0032] After the entry sequence is extracted, its corresponding exit sequence is extracted. The exit sequence describes the travel path and diffusion direction of vehicles after leaving the fault location in the downstream area. During the extraction process, starting from the fault location, a time window of equal length is extended downstream along the time series direction. Nodes whose vehicle trajectory density and road traffic flow are both higher than the baseline average during this time period are selected, and their road numbers, travel directions, and node positions are recorded. Subsequently, these nodes are arranged in chronological order to form the exit sequence corresponding to the entry sequence. When generating the exit sequence, the time span of the exit sequence is corrected by combining the fault duration information recorded in the suspected blockage index to ensure that traffic changes within the fault-affected area are fully covered. The entry sequence and the exit sequence are connected on the time baseline through the fault location to form a continuous time chain spanning the areas before and after the fault. At this point, the distribution trend of vehicle flow at the fault location can be visually presented, and the transfer characteristics of cross-administrative region traffic flow at the fault boundary can be revealed.

[0033] Based on the entry and exit sequences, the turning sequence at the break point is extracted, and a connected contact point sequence is constructed. Simultaneously, the acceptable range of the contacts is calibrated. The turning sequence describes the potential directional changes of vehicles entering the downstream road from the upstream road at the break point. When constructing the turning sequence, the nodes closest in space and with a travel direction angle less than a preset range are paired based on the end node of the entry sequence and the beginning node of the exit sequence. The turning relationship between the paired nodes is recorded, including left turn, straight, or right turn types. Each pair of paired nodes is defined as a connected contact point. The temporal position of the connected contact point corresponds to the center moment of the break section, and its spatial position corresponds to the geometric midpoint between the paired nodes. Arranging all connected contacts in chronological order forms the connected contact point sequence. To ensure the accuracy of subsequent road connectivity rearrangement, the acceptable range is calibrated for each connected contact point. The acceptable range is determined comprehensively based on the road width before and after the break point, the number of lanes, traffic flow intensity, and spatial intersection angle, and is used to limit the matching boundary of the contact point in the subsequent construction of the connecting channel. After calibration, each contact point has clear spatial coordinates, time location, and coverage description, forming a set of directional and receptive connected information units.

[0034] Based on the sequence of connected contact points, a boundary acceptance channel is constructed. The broken segments corresponding to the boundary description list are transformed into acceptable gaps and written into the channel threshold. The cross-regional road connectivity simulation is limited to continuous segment migration within the channel threshold range, and an acceptance threshold table is generated. To restore the continuous connectivity of cross-administrative region roads within the fractured area based on the sequence of connecting points, the corresponding fracture segments in the boundary delineation list are structurally transformed and spatially constructed. This is achieved by establishing boundary connection channels to transform fracture segments into connectable gaps, and setting threshold conditions within these channels to constrain the migration range of the cross-regional road connectivity projection. This process not only reconstructs the connectable road space at the fracture points but also restricts the migration rhythm in the temporal dimension, thereby ensuring that the extension of cross-administrative region road connectivity occurs within a controllable space. The specific steps are as follows: Spatial extraction and transformation of fractured segments are prepared based on connected contact point sequences and boundary description lists. The connected contact point sequences record the spatial and temporal locations of the contact points at the fracture points, as well as their catchment areas. The boundary description lists record the time intervals, fracture types, and corresponding road numbers of the fractured segments. By matching these two sets of data, a correspondence can be established between fractured segments and contact points. Using each connected contact point as the center, road segment data overlapping with the contact point's time interval is extracted along the upstream and downstream directions of the fractured segment. The spatial range of these road segment data is defined as the fracture catchment area. Subsequently, road traffic flow, vehicle trajectory density, and road geometric parameters within the catchment area are integrated into structured descriptive units, transforming the fractured segments from discontinuous road cross-sections into computable spatial units. Through this spatial extraction and structuring process, the fractured segments acquire geometric boundaries corresponding to the catchment areas of the contact points, providing a matching data foundation for subsequent construction of catchment channels.

[0035] After spatial extraction of the fractured segments, boundary connection channels are established around the sequence of connected contact points. These channels connect the road structures on both sides of the fracture, providing a continuous and accessible path for the fractured segments in space. When constructing the connection channels, each connected contact point is used as a core node, and a connecting path is generated along the outer edge of its accessible range. This path starts at the upstream boundary of the fractured segment and ends at the downstream boundary, maintaining the same directional properties as the connected contact point. To ensure the spatial rationality of the connection channels, the original road alignment parameters, intersection layout, and vehicle trajectory distribution patterns are considered during path generation, ensuring that the connection channels spatially maintain the original road geometry. In the temporal dimension, a certain time window is extended forward and backward from the temporal position of the connected contact point, allowing the connection channels to maintain consistency with the changing rhythm of road traffic conditions over time. Through this bidirectional spatial and temporal construction method, the connection channels spatially connect the fractured locations and temporally maintain the extension of the traffic state, laying the structural foundation for subsequent threshold settings.

[0036] After the boundary connection channel is constructed, a channel threshold is set, and the broken segments are transformed into connectable gaps. The channel threshold is used to limit the migration range of the cross-regional road connectivity simulation, ensuring that the connection process takes place within a certain boundary. When setting the channel threshold, the spatial path of the connection channel is used as the axis, extending a certain width to both sides to form a channel boundary band. The width of this boundary band is determined based on the connectable range of the connection point and adjusted in conjunction with road grade, number of lanes, and traffic density factors. The strength and constraint conditions of the channel threshold also differ for different types of broken segments. For example, a narrower channel threshold range can be used for traffic flow mutation-type breaks to maintain consistent traffic direction, while a wider threshold range can be used for coded chain-breaking breaks to facilitate multi-path connection. Simultaneously with setting the threshold, the spatial area of ​​the broken segment within the connection channel is defined as a connectable gap. A connectable gap is a spatial extension of the broken segment, overlapping with the connection point and maintaining the same shape as the channel path. In this way, the broken segment is transformed from its original disconnected state into a spatial segment with connectable attributes, providing a continuous connection path for the cross-regional road migration simulation.

[0037] After setting the channel thresholds, a threshold table is generated, and the migration constraints for cross-regional road connectivity simulation are determined. The threshold table is a centralized description of all threshold parameters in the connecting channel, including channel number, contact point number, threshold range, connecting gap coordinates, and time window range. When generating the threshold table, the threshold parameters corresponding to each contact point are recorded and arranged using the connectivity contact point sequence as an index, forming a unified index system for all connecting relationships in time and space. This threshold table serves as the input basis for subsequent cross-regional road connectivity simulation, limiting road segments from exceeding the specified connecting range during migration. By establishing a bidirectional mapping relationship between channel numbers and road numbers in the threshold table, connecting paths can be dynamically tracked and updated, thus maintaining the controllability and continuity of connectivity relationships during cross-administrative region data migration. Through the generation of the threshold table, the structure and constraints of the boundary connecting channels are fully solidified, providing accurate input for subsequent connectivity control phases.

[0038] Based on the threshold table, pulse silence interleaving control is performed within the time window of cross-administrative region boundaries. By injecting short-term silence segments and micro-delay segments in stages, the fracture edge is gradually translated along the channel threshold direction and the migration rhythm of the cross-regional road connectivity chain is maintained, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships. To dynamically balance and adjust road connectivity within cross-administrative boundary time windows, it is necessary to implement pulse-silent staggered control of broken segments within the boundary acceptance channels based on the acceptance threshold table. By introducing short-term silent segments and micro-delay segments, the broken edges gradually shift along the channel threshold direction, thereby maintaining the coordinated migration of cross-regional road connectivity chains in both time and space, and completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships. Under the constraints established by the acceptance threshold table, this process processes the time windows at the cross-regional boundaries in stages, enabling flexible transitions and rhythm matching of road traffic data between different areas, thus avoiding the misidentification of broken areas as structural blockages during planning and analysis. The specific steps are as follows: The time window range for pulse-based silent control is determined based on a threshold table. This table records the channel number, contact number, threshold range, and the start and end information of the corresponding time window. Using this threshold table, the start and end times at the boundary are extracted within the time period corresponding to each cross-administrative region channel, forming an adjustable time window. To ensure the time window covers the entire traffic cycle of the fragmented segment, the extraction is extended by one sampling period both before and after, allowing the control interval to encompass the complete evolution of the fragmented segment. Subsequently, the time window is divided into multiple stages, each corresponding to a pulse control cycle. The stage division is based on the rate of change of road traffic flow and the amplitude of change in vehicle trajectory density. When the rate of change is high, the stage length is appropriately shortened to enhance the sensitivity of the control response; when the amplitude of change is low, the stage length is appropriately extended to maintain data stability. In this way, segmented control intervals are formed in the time dimension, providing a time framework for the subsequent injection of silent and delayed segments.

[0039] After determining the time window, short-duration silent segments are injected into the cross-administrative boundary receiving channels. These short-duration silent segments are used to artificially create extremely short data-free intervals in the time series, forming a transition buffer layer for the passing data. The injection process is constrained by the channel threshold range in the receiving threshold table, and multiple injection positions are selected at equal intervals on both sides of the channel centerline to ensure that the spatial distribution of the silent segments covers the main area of ​​the break edge. The duration of the silent segments is usually controlled between 1% and 5% of the original sampling period to mitigate the inconsistency effect caused by data mutations without disrupting the overall continuity. After the silent segments are injected, the passing flow curves on both sides of the break edge form a flexible transition zone on the time axis, gradually smoothing out the peak and trough values ​​of the flow within the channel, thus creating a stable data foundation for subsequent delayed injection. Through the deployment of short-duration silent segments, the temporal fluctuations of the break segments are temporarily suppressed, and cross-regional data form a stable connection buffer structure within the channel.

[0040] After the short-term silent segment takes effect, a small delay segment is injected along the threshold direction of the receiving channel to adjust the migration rhythm of the fracture edge in the time dimension. The small delay segment introduces a minimal time delay into the original time series, allowing the fracture edge to shift controllably along the time axis. During injection, using the time position of the connecting contact point as a reference, the delay segment is evenly distributed across the time periods before and after the fracture area, causing the fracture edge to gradually shift along the channel threshold direction. The injection duration of the delay segment is determined based on the time window range and channel length in the receiving threshold table, generally controlled within 10% of the original time step. The addition of the delay segment creates a continuous, small shift effect in the fracture area within the time series, thus avoiding abrupt changes in the fracture edge during analysis. With the phased injection of delay segments, the traffic status within the channel gradually becomes smoother in the time dimension, and the cross-regional road traffic data shows a natural connection trend in continuity judgment. Through the effect of time delay segments, the fracture edge is reshaped in the time dimension, forming a transition zone with controllable extensibility, providing temporal continuity support for the final stable rearrangement of connectivity.

[0041] Under the combined effect of short-duration silent segments and minute delay segments, the traffic data within the cross-administrative boundary time window is comprehensively regulated to maintain a coordinated and unified migration rhythm of the cross-regional road connectivity chain. During this stage, by continuously adjusting the traffic status at each stage of the time window, the break edge slowly shifts along the channel threshold direction in time and remains consistent with the geometric center of the receiving channel in space, thus forming a dynamic equilibrium state of synchronous temporal and spatial advancement. When the pulse silence and delay effects of all stages are superimposed, the cross-regional road traffic flow curve gradually stabilizes, the trajectory density transitions continuously at the boundary, and the road connectivity chain regains continuity in time and space. Subsequently, based on the balanced traffic status, the time window status of each channel is recorded, generating a dynamically stable rearranged connectivity dataset, which is then written into the road planning database as the basis for subsequent planning calculations and connectivity analysis.

[0042] This invention constructs a time window boundary marking zone and a cross-regional continuity discrimination zone during the urban road planning data generation stage. This enables synchronous correlation of data collected from different administrative regions in both time and space, allowing for the identification and labeling of break locations and morphologies caused by differences in data collection. Through this method, cross-regional traffic data possesses continuity recognition capabilities during alignment and fusion, effectively preventing data interruptions caused by temporal heterogeneity from being misjudged as traffic disruptions. This maintains a complete representation of road traffic conditions in planning analysis, making the cross-regional road network structure more consistent with actual traffic patterns in layout design.

[0043] This invention establishes a sequence of connected contact points and boundary acceptance channels, generates acceptable gaps at fracture points and applies channel threshold constraints, and combines pulse-silent interleaved regulation to achieve gradual translation of fracture edges, enabling cross-administrative region roads to maintain coordinated migration in time and space. Through this method, road connectivity chains can continuously and stably extend during dynamic planning, and cross-regional traffic structures maintain adaptive consistency in data updates and traffic changes, thereby improving the rationality and long-term applicability of road planning and design results.

[0044] This invention provides, for example Figure 2 The urban road planning and design system based on big data shown includes a boundary marking module, a continuity discrimination module, a touchpoint analysis module, a connecting channel module, and a connectivity control module. The boundary marking module constructs a time window boundary marking zone, synchronously collecting road traffic flow, vehicle trajectory data, and intersection signal data during the generation of urban road planning data. It also records the time difference, update time difference, and timestamp granularity difference between adjacent administrative regions within the same planning period, determines the data break location, marks the break shape, and forms a boundary marking list. The continuous discrimination module constructs a cross-regional continuous discrimination zone based on the boundary description list, maps the road traffic flow direction, vehicle trajectory density and road segment code before and after the break to a unified time baseline, extracts the dynamic features of the break and generates a break type label, forming a suspected blockage index. The contact point analysis module traces the cross-regional road connectivity chain based on the suspected blocking index, extracts the entry sequence, exit sequence and turning sequence of the corresponding interface road segment, constructs the connectivity contact point sequence and marks the acceptable range of the contact point; The receiving channel module constructs boundary receiving channels based on the sequence of connected contact points, transforms the broken segments corresponding to the boundary description list into receiving gaps and writes them into the channel threshold, limits the migration of continuous segments in the cross-regional road connectivity simulation within the channel threshold range, and generates a receiving threshold table. The connectivity control module performs pulse-silent interleaved control within the cross-administrative region boundary time window based on the acceptance threshold table. By injecting short-term silent segments and micro-delay segments in stages, it gradually shifts the fracture edge along the channel threshold direction and maintains the migration rhythm of the cross-regional road connectivity chain, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships.

[0045] The present invention provides a big data-based urban road planning and design method, which is implemented through the above-mentioned big data-based urban road planning and design system. For details of the specific methods and processes of the big data-based urban road planning and design system, please refer to the above-mentioned embodiment of the big data-based urban road planning and design method, which will not be repeated here.

[0046] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for urban road planning and design based on big data, characterized in that, Includes the following steps: Construct a time window boundary marking zone, and simultaneously collect road traffic flow, vehicle trajectory data and intersection signal data during the generation of urban road planning data. Record the time difference, update time difference and timestamp granularity difference between adjacent administrative regions in the same planning period, determine the data break location and mark the break shape, and form a boundary marking list. Based on the boundary description list, a cross-regional continuity discrimination zone is constructed, and the road traffic flow direction, vehicle trajectory density and road segment code before and after the break are mapped to a unified time baseline. The dynamic features of the break are extracted and the break type label is generated to form a suspected blockage index. Based on the suspected blocking index, the cross-regional road connectivity chain is traced back, the entry sequence, exit sequence and turning sequence of the corresponding interface road segment are extracted, the connectivity contact point sequence is constructed and the acceptable range of the contact point is marked. Based on the sequence of connected contact points, a boundary acceptance channel is constructed. The broken segments corresponding to the boundary description list are transformed into acceptable gaps and written into the channel threshold. The cross-regional road connectivity simulation is limited to continuous segment migration within the channel threshold range, and an acceptance threshold table is generated. Based on the threshold table, pulse silence interleaving control is performed within the time window of cross-administrative region boundaries. By injecting short-term silence segments and micro-delay segments in stages, the fracture edge gradually shifts along the channel threshold direction and maintains the migration rhythm of the cross-regional road connectivity chain, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships.

2. The urban road planning and design method based on big data according to claim 1, characterized in that, The steps for generating the boundary description list are as follows: During the urban road planning data generation phase, data collection areas are set around the main roads, secondary roads and intersections of the city. Road traffic flow, vehicle trajectory data and intersection signal data are collected synchronously, and the time starting point of the collection terminals of each administrative region is unified during the synchronous collection process. After completing the synchronous collection, the collected data from different administrative regions are input into the time window boundary recording tape, the time difference of collection time, the time difference of update time and the time stamp granularity difference are recorded, and the spatial correlation information of road traffic flow, vehicle trajectory and intersection signal data is written into the recording tape; The fracture location is determined in the time window boundary tracing band based on the joint analysis results of the acquisition time difference, update time difference, and timestamp granularity difference, and the time interval and spatial coordinates corresponding to the fracture location are written into the tracing band. After determining the location of the fracture, the fracture morphology is marked according to the temporal pattern and spatial distribution characteristics of the fracture segment, and a boundary description list is generated.

3. The urban road planning and design method based on big data according to claim 2, characterized in that, When morphologically labeling the fracture location, the temporal pattern and spatial distribution characteristics of the fracture segment are combined. The fracture segments are classified according to the degree of abrupt change in road traffic flow, the sudden drop in vehicle trajectory density, and the duration of intersection signal switching. Labeling fields are established in the time window boundary marking zone to record the temporal range, spatial coordinates, and associated road information of the fracture.

4. The urban road planning and design method based on big data according to claim 2, characterized in that, The steps for generating a blocking suspect index are as follows: Based on the boundary delineation list, the road traffic flow data, vehicle trajectory data and road segment coding information before and after the fracture are read, and the time distribution of the data is balanced according to the time difference of collection, update time difference and timestamp granularity difference, and the data before and after the fracture are mapped to the corresponding road nodes and intersections in the spatial dimension. After completing the data mapping, a unified time baseline is constructed based on the time window range in the boundary description list. The road traffic flow direction, vehicle trajectory density and road segment coding information before and after the break are aligned to the unified time axis, so that the data maintains structural continuity on the time baseline. After establishing a unified time baseline, the trend of road traffic flow changes, changes in vehicle trajectory density distribution, and road segment coding connection relationships before and after the fracture are extracted to form a fracture dynamic feature set. Based on the dynamic feature set of fractures, fracture type labels are generated and a suspected blockage index is formed to measure the impact of fractures on the continuity of traffic on roads across administrative regions.

5. The urban road planning and design method based on big data according to claim 4, characterized in that, In the process of generating fracture type labels, based on the differences in road traffic flow direction before and after the fracture, the magnitude of changes in vehicle trajectory density, and the continuity offset characteristics of road segment coding, fracture types are classified into traffic abrupt change type, trajectory sparse type, coding chain break type, and composite offset type. The time period, spatial range, and affected road number are recorded in the fracture type label.

6. The urban road planning and design method based on big data according to claim 4, characterized in that, The steps for constructing a connected contact sequence are as follows: Based on the suspected blocking index, backtracking analysis of cross-administrative region road data is performed. The road traffic flow, vehicle trajectory density and road segment coding information are tracked along the time period before and after the break, and the road boundary nodes at the break are determined and a road node linked list is formed. Based on the road node linked list, the entry sequence of the interface road segment is extracted. The time window is extended upstream along the time sequence with the break position as the center. Road nodes with vehicle trajectory density greater than the set threshold are recorded and the entry sequence is formed. After the entry sequence is extracted, the corresponding exit sequence is extracted. Starting from the break point, the time window is extended downstream along the time sequence, and the exit nodes are arranged in chronological order to form the exit sequence. Based on the entry and exit sequences, the turning sequence of the break position is extracted, the connected contact sequence is constructed, and the bearing range of the contact is calibrated.

7. The urban road planning and design method based on big data according to claim 6, characterized in that, The steps for generating the acceptance threshold table are as follows: Spatial extraction of fracture segments is performed based on the connected contact sequence and boundary description list. The time interval of the fracture segments is matched with the time position of the connected contact to form the fracture receiving area. The road traffic flow, vehicle trajectory density and road geometric parameters are integrated to generate structured description units. After completing the spatial extraction of the fractured fragments, a boundary receiving channel is established with the connecting contact point as the core. A connection path is generated along the outer edge of the receiving range, so that the receiving channel connects the upstream and downstream boundaries of the fracture in space and maintains the continuity of the passage state in the time dimension. After the receiving channel is constructed, a channel threshold is set and the broken segments are transformed into receptive gaps, forming a channel boundary zone with the spatial path of the receiving channel as the axis; After the channel threshold is set, a receiving threshold table is generated, which records the channel number, contact number, threshold range, receiving gap coordinates, and time window range.

8. The urban road planning and design method based on big data according to claim 7, characterized in that, The threshold setting of the passage is based on the acceptable range of the connecting contact, and the width of the passage boundary zone is determined in combination with the road grade, number of lanes and traffic density. Different types of fractures correspond to different threshold constraints, so that the threshold range of the flow change type fracture keeps the direction of traffic consistent, and the threshold range of the coded chain break type fracture allows multiple paths to be accepted.

9. The urban road planning and design method based on big data according to claim 7, characterized in that, Based on the threshold table, pulse-silent interleaved control is performed within the cross-administrative region boundary time window. Short-term silent segments and micro-delay segments are injected in stages to gradually shift the fracture edge along the channel threshold direction and maintain the migration rhythm of the cross-regional road connectivity chain. The steps are as follows: Based on the threshold table, the time window range of pulse silence control is determined, the start time and end time at the boundary are extracted and divided into multiple stages, so that the time window covers the complete passage cycle of the broken segment. After determining the time window, short-term silent segments are injected into the receiving channels that cross administrative boundaries. Injection positions are set at equal intervals on both sides of the channel centerline to make the traffic flow curve form a flexible transition zone on the time axis and weaken data abrupt changes. After the short-term silent segment takes effect, a small delay segment is injected along the threshold direction of the receiving channel, so that the fracture edge gradually shifts on the time axis and maintains the time continuity of the passage state. By combining short-duration silent segments and minimal delay segments, the traffic data within the boundary time window is regulated as a whole, so that the fracture edge can maintain coordinated migration in time and space and generate a dynamically stable rearranged connected dataset.

10. A big data-based urban road planning and design system, used to implement the big data-based urban road planning and design method according to any one of claims 1-9, characterized in that, It includes a boundary marking module, a continuity discrimination module, a contact point analysis module, a receiving channel module, and a connectivity control module: The boundary marking module constructs a time window boundary marking zone, synchronously collecting road traffic flow, vehicle trajectory data, and intersection signal data during the generation of urban road planning data. It also records the time difference, update time difference, and timestamp granularity difference between adjacent administrative regions within the same planning period, determines the data break location, marks the break shape, and forms a boundary marking list. The continuous discrimination module constructs a cross-regional continuous discrimination zone based on the boundary description list, maps the road traffic flow direction, vehicle trajectory density and road segment code before and after the break to a unified time baseline, extracts the dynamic features of the break and generates a break type label, forming a suspected blockage index. The contact point analysis module traces the cross-regional road connectivity chain based on the suspected blocking index, extracts the entry sequence, exit sequence and turning sequence of the corresponding interface road segment, constructs the connectivity contact point sequence and marks the acceptable range of the contact point; The receiving channel module constructs boundary receiving channels based on the sequence of connected contact points, transforms the broken segments corresponding to the boundary description list into receiving gaps and writes them into the channel threshold, limits the migration of continuous segments in the cross-regional road connectivity simulation within the channel threshold range, and generates a receiving threshold table. The connectivity control module performs pulse-silent interleaved control within the cross-administrative region boundary time window based on the acceptance threshold table. By injecting short-term silent segments and micro-delay segments in stages, it gradually shifts the fracture edge along the channel threshold direction and maintains the migration rhythm of the cross-regional road connectivity chain, thus completing the dynamic and stable rearrangement of cross-administrative region road connectivity relationships.

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