Intelligent route planning system and method for urban and rural planning

Abstract

The invention relates to the technical field of route planning, and discloses an intelligent route planning system and method for urban and rural planning, and the system comprises a data collection and processing module, a road network construction module, a traffic demand analysis module, a route planning module, and a real-time traffic monitoring module. The data acquisition and processing module is used for collecting, sorting and preprocessing geographic data of urban and rural areas, the road network construction module is used for establishing a road network model of the urban and rural areas by utilizing the processed data and is responsible for updating road network information, and the traffic demand analysis module is used for analyzing traffic demand modes of the urban and rural areas. The system is used for acquiring traffic conditions and demand characteristics of different time periods and regions, the route planning module is used for performing urban and rural route planning based on geographic information, road network data and traffic demand analysis results, and the real-time traffic monitoring module is used for monitoring the traffic conditions of urban and rural regions in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of route planning, and in particular to an intelligent route planning system and method for urban and rural planning. Background Art

[0002] With the development of the times, urban and rural route planning has become an important task. With the acceleration of the process of urban and rural integration and the development of rural economy and society, the travel needs of rural residents are increasing. Good traffic organization and convenient travel methods are one of the key factors to promote urban and rural economic development and improve the living standards of residents. Effective urban and rural route planning can not only optimize the traffic layout and improve transportation efficiency, but also promote the rational use of rural resources and the development of industries, and help achieve the goal of urban and rural integration. However, there are also many problems in urban and rural route planning, including backward road conditions, imperfect transportation infrastructure, and low level of informatization, which lead to inconvenience in travel and traffic congestion for rural residents. Therefore, it is necessary to design an intelligent route planning system and method for urban and rural planning to improve the quality and efficiency of urban and rural route planning. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent route planning system and method for urban and rural planning, which solves the problems of poor quality and low efficiency of urban and rural transportation networks in the prior art.

[0004] In order to achieve the above-mentioned purpose of improving the quality and efficiency of urban and rural transportation networks, the present invention provides the following technical solutions: an intelligent route planning system and method for urban and rural planning, including a data acquisition and processing module, a road network construction module, a traffic demand analysis module, a route planning module, and a real-time traffic monitoring module. The data acquisition and processing module is used to collect, organize and pre-process the geographic data of urban and rural areas, and provide the required basic data for the intelligent route planning system. The road network construction module uses the processed data to establish a road network model of urban and rural areas and is responsible for updating the road network information. The traffic demand analysis module analyzes the traffic demand pattern in urban and rural areas and understands the traffic conditions and demand characteristics in different time periods and regions. The route planning module performs urban and rural path planning based on geographic information, road network data and traffic demand analysis results. The real-time traffic monitoring module is used to monitor the traffic conditions in urban and rural areas in real time, and based on the real-time monitoring results, timely adjust the route planning to avoid congested sections or provide alternative routes. The data collection and processing module includes a geographic data module and a population data module. The geographic data module is used to collect urban and rural geographic information data, including terrain, landforms, and road networks. The population data module is used to obtain urban and rural population distribution and traffic flow; the road network construction module includes a road data processing module and a road network modeling module. The road data processing module is used to convert the collected geographic information data into usable road network data. The road network modeling module is used to build an urban and rural road network model, including road connection relationships and road attributes; the traffic demand analysis module includes a population distribution analysis module and a traffic flow prediction module. The population distribution analysis module is used to analyze the urban and rural population distribution and determine the population distribution in each area. The traffic flow prediction uses historical data and models to predict future traffic flow, including the flow in different time periods and sections; the route planning module includes a shortest path planning module and an optimal route planning module. The shortest path planning module calculates the shortest path within urban and rural areas based on road network data and traffic demand analysis results. The optimal route planning module considers traffic congestion and road conditions to plan the optimal driving route; the real-time traffic monitoring module includes a traffic flow monitoring module and a route adjustment module. The traffic flow monitoring module monitors the traffic flow and road conditions of urban and rural roads in real time through sensors and camera equipment. The route adjustment module is used to adjust the planned route according to the real-time monitoring data and provide real-time route navigation services.

[0005] According to the above technical solution, the road network model of urban and rural areas is established by using the processed data, specifically: the processed geographic data is imported into the road network construction system, including the road centerline, intersection location, and road attributes, and the topological structure of the road network is constructed based on the imported geographic data. According to the road centerline and intersection location, the connection relationship between roads and the topological relationship of road sections are established, a real-time update mechanism for road network data is established, the road network information of urban and rural areas is updated regularly, and additional attribute information of roads is added, such as road grade, road width, and number of lanes.

[0006] According to the above technical solution, the analysis of traffic demand patterns in urban and rural areas is specifically as follows: collecting traffic data in urban and rural areas, conducting travel surveys in urban and rural areas, understanding residents' travel methods, travel purposes, and travel times, analyzing travel data, identifying characteristics and demand patterns, analyzing traffic flow distribution and changing trends in different time periods in urban and rural areas, using time series analysis technology to predict traffic demand, and analyzing traffic characteristics in different areas of urban and rural areas.

[0007] According to the above technical solution, the analysis results based on geographic information, road network data and traffic demand are specifically as follows: according to user input or system requirements, the starting point and end point of urban and rural path planning are determined. The user can specify the starting point and end point through the interactive interface, or automatically select the starting point and end point according to needs. Based on graph theory and search algorithms, a path search algorithm is designed to find the optimal path from the starting point to the end point, and the searched path is optimized. The path is optimized using heuristic search and simulated annealing algorithms.

[0008] According to the above technical solution, based on graph theory and search algorithm, a path search algorithm is designed to find the optimal path from the starting point to the end point, specifically: The path search problem is solved based on the ant colony algorithm. The ant colony algorithm is a heuristic search algorithm that simulates the behavior of ants looking for food and guides ants to search for the optimal path through the secretion and volatilization of pheromones. Place a certain number of ants on each path, initialize the pheromone concentration of each node on the path, set the probability of ant movement and the pheromone volatilization rate parameters, Each ant selects the next node to move to according to a certain probability. The probability is affected by the pheromone concentration and distance of the nodes on the path. Each ant moves step by step according to the path selection rules until it reaches the end point. When all ants have completed their movement, the pheromone concentration of the nodes on the path is updated according to the ants' movement path. The update of pheromones follows the pheromone update rule, increasing the pheromone concentration and taking into account the volatilization of pheromones. Repeat the ant colony search and pheromone update until the stop condition is met. During the movement, the ant selects the next node to move according to a certain probability. The probability calculation formula is as follows: ; in, is the probability of moving from node i to node j, is the pheromone concentration from node i to node j, is the heuristic information from node i to node j, and is the adjustment parameter used to balance the influence of pheromone concentration and heuristic information, After each iteration, the pheromone concentration is updated according to the ant's moving path. The pheromone update formula is as follows: ; Among them, P is the pheromone volatility rate, which controls the persistence of pheromone. is the increment of pheromone left by the mth ant, which is usually inversely proportional to the total length of the path taken by the ant; According to the above technical solution, the intelligent route planning method for urban and rural planning includes the following steps: S1: Collect geographic data of urban and rural areas, conduct geographic data analysis, and explore regional characteristics; S2: Conduct a traffic demand survey in urban and rural areas to understand the characteristics of travel demand in different time periods and regions, and identify and establish traffic demand patterns in urban and rural areas based on data surveys and using data mining and pattern recognition techniques; S3: Use intelligent algorithms to combine geographic data and traffic demand patterns to search and plan routes, and optimize route planning algorithms to make them more adaptable to urban and rural environments; S4: Design a real-time path update strategy, adjust the path planning scheme according to real-time traffic data, introduce an adaptive planning mechanism, and respond to traffic changes and emergencies in a timely manner.

[0009] According to the above technical solution, step 3 further includes using an evolutionary algorithm to optimize the path search process, to minimize the total cost of the path, including distance, time and other costs, and the fitness function is expressed as: ; Where p represents the path planning scheme, Distance(p) represents the total distance of the path, Time(p) represents the total time of the path, and Cost(p) represents other costs. Represents weights of distance, time, and other costs.

[0010] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: compared with the prior art, the present invention provides an intelligent route planning system and method for urban and rural planning, which has the following beneficial effects: The intelligent route planning system and method for urban and rural planning, by constructing the topological structure of the road network, establishes the connection relationship between roads and the topological relationship of road sections according to the road centerline and intersection location, establishes a real-time update mechanism for road network data, regularly updates the road network information in urban and rural areas, adds additional attribute information of roads, uses time series analysis technology to predict traffic demand, and analyzes the traffic characteristics of different areas in urban and rural areas, thereby improving the quality and efficiency of urban and rural route planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0013] See also Figure 1The present invention provides a technical solution: an intelligent route planning system and method for urban and rural planning, comprising a data acquisition and processing module, a road network construction module, a traffic demand analysis module, a route planning module, and a real-time traffic monitoring module, characterized in that the data acquisition and processing module is used to collect, organize and pre-process the geographic data of urban and rural areas, and provide the required basic data for the intelligent route planning system; the road network construction module uses the processed data to establish a road network model of urban and rural areas, and is responsible for updating the road network information; the traffic demand analysis module analyzes the traffic demand pattern of urban and rural areas, and understands the traffic conditions and demand characteristics of different time periods and regions; the route planning module performs urban and rural path planning based on geographic information, road network data and traffic demand analysis results; the real-time traffic monitoring module is used to monitor the traffic conditions in urban and rural areas in real time, and adjust the route planning in time based on the real-time monitoring results to avoid congested sections or provide alternative routes. The data collection and processing module includes a geographic data module and a population data module. The geographic data module is used to collect urban and rural geographic information data, including terrain, landforms, and road networks. The population data module is used to obtain urban and rural population distribution and traffic flow; the road network construction module includes a road data processing module and a road network modeling module. The road data processing module is used to convert the collected geographic information data into usable road network data. The road network modeling module is used to build an urban and rural road network model, including road connection relationships and road attributes; the traffic demand analysis module includes a population distribution analysis module and a traffic flow prediction module. The population distribution analysis module is used to analyze the urban and rural population distribution and determine the population distribution in each area. The traffic flow prediction uses historical data and models to predict future traffic flow, including the flow in different time periods and sections; the route planning module includes a shortest path planning module and an optimal route planning module. The shortest path planning module calculates the shortest path within urban and rural areas based on road network data and traffic demand analysis results. The optimal route planning module considers traffic congestion and road conditions to plan the optimal driving route; the real-time traffic monitoring module includes a traffic flow monitoring module and a route adjustment module. The traffic flow monitoring module monitors the traffic flow and road conditions of urban and rural roads in real time through sensors and camera equipment. The route adjustment module is used to adjust the planned route according to the real-time monitoring data and provide real-time route navigation services.

[0014] The intelligent route planning method for urban and rural planning includes the following steps: S1: Collect geographic data of urban and rural areas, conduct geographic data analysis, and explore regional characteristics; S2: Conduct a traffic demand survey in urban and rural areas to understand the characteristics of travel demand in different time periods and regions, and identify and establish traffic demand patterns in urban and rural areas based on data surveys and using data mining and pattern recognition techniques; S3: Use intelligent algorithms to combine geographic data and traffic demand patterns to search and plan routes, and optimize route planning algorithms to make them more adaptable to urban and rural environments; S4: Design a real-time path update strategy, adjust the path planning scheme according to real-time traffic data, introduce an adaptive planning mechanism, and respond to traffic changes and emergencies in a timely manner.

[0015] Step 3 further includes using an evolutionary algorithm to optimize the path search process to minimize the total cost of the path, including distance, time and other costs. The fitness function is expressed as: ; Where p represents the path planning scheme, Distance(p) represents the total distance of the path, Time(p) represents the total time of the path, and Cost(p) represents other costs. Represents weights of distance, time, and other costs.

[0016] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0017] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent route planning system for urban and rural planning, comprising a data acquisition and processing module, a road network construction module, a traffic demand analysis module, a route planning module, and a real-time traffic monitoring module, characterized in that: The data acquisition and processing module is used to collect, organize and pre-process the geographical data of urban and rural areas to provide the basic data required for the intelligent route planning system; The road network construction module uses the processed data to establish a road network model for urban and rural areas and is responsible for updating the road network information; The traffic demand analysis module analyzes the traffic demand patterns in urban and rural areas to understand the traffic conditions and demand characteristics in different time periods and regions; The route planning module performs urban and rural route planning based on geographic information, road network data and traffic demand analysis results; The real-time traffic monitoring module is used to monitor the traffic conditions in urban and rural areas in real time, and adjust the route planning in time based on the real-time monitoring results to avoid congested sections or provide alternative routes; The data collection and processing module includes a geographic data module and a population data module. The geographic data module is used to collect urban and rural geographic information data, including topography, landforms, and road networks. The population data module is used to obtain urban and rural population distribution and traffic flow. The road network construction module includes a road data processing module and a road network modeling module. The road data processing module is used to convert the collected geographic information data into usable road network data. The road network modeling module is used to build an urban and rural road network model, including road connection relationships and road attributes. The traffic demand analysis module includes a population distribution analysis module and a traffic flow prediction module. The population distribution analysis module is used to analyze the distribution of urban and rural populations and determine the population density of each area. The traffic flow prediction module predicts future traffic flow through historical data and models, including the flow in different time periods and sections. The route planning module includes a shortest path planning module and an optimal route planning module. The shortest path planning module calculates the shortest path within urban and rural areas based on road network data and traffic demand analysis results, and the optimal route planning module considers traffic congestion and road conditions to plan the optimal driving route; The real-time traffic monitoring module includes a traffic flow monitoring module and a route adjustment module. The traffic flow monitoring module monitors the traffic flow and road conditions of urban and rural roads in real time through sensors and camera equipment. The route adjustment module is used to adjust the planned route according to the real-time monitoring data and provide real-time route navigation services.

2. The intelligent route planning system for urban and rural planning according to claim 1 is characterized in that: The collection, organization and pre-processing of geographic data in urban and rural areas are specifically: Obtain geographic data of urban and rural areas through various data sources, organize and clean the collected data, remove duplicate data, correct erroneous data, fill in missing data, convert and unify geographic data in different formats, and perform spatial data processing on geographic data.

3. The intelligent route planning system for urban and rural planning according to claim 1 is characterized in that: The method of using the processed data to establish a road network model in urban and rural areas is specifically as follows: Import the processed geographic data into the road network construction system, including road centerlines, intersection locations, and road attributes. Based on the imported geographic data, build the topological structure of the road network. According to the road centerlines and intersection locations, establish the connection relationship between roads and the topological relationship of road sections. Establish a real-time update mechanism for road network data, regularly update road network information in urban and rural areas, and add additional attribute information of roads.

4. The intelligent route planning system for urban and rural planning according to claim 1, characterized in that: The analysis of the traffic demand patterns in urban and rural areas is as follows: Collect traffic data in urban and rural areas, conduct travel surveys in urban and rural areas, understand residents' travel methods, travel purposes, and travel times, analyze travel data, identify characteristics and demand patterns, analyze traffic flow distribution and changing trends in different time periods in urban and rural areas, use time series analysis technology to predict traffic demand, and analyze traffic characteristics in different areas of urban and rural areas.

5. The intelligent route planning system for urban and rural planning according to claim 1, characterized in that: The analysis results based on geographic information, road network data and traffic demand are specifically: The starting point and end point of urban and rural path planning are determined based on user input or system requirements. Users can specify the starting point and end point through the interactive interface, or they can automatically select the starting point and end point according to their needs. Based on graph theory and search algorithms, a path search algorithm is designed to find the optimal path from the starting point to the end point, optimize the searched path, and use heuristic search and simulated annealing algorithms to optimize the path.

6. The intelligent route planning system for urban and rural planning according to claim 5, characterized in that: Based on graph theory and search algorithm, a path search algorithm is designed to find the optimal path from the starting point to the end point, specifically: The path search problem is solved based on the ant colony algorithm. The ant colony algorithm is a heuristic search algorithm that simulates the behavior of ants looking for food and guides ants to search for the optimal path through the secretion and volatilization of pheromones. Place ants on each path, initialize the pheromone concentration of each node on the path, set the probability of ant movement and the pheromone volatilization rate parameters, Each ant selects the next node to move to based on the probability calculation formula. The probability is affected by the pheromone concentration and distance of the nodes on the path. Each ant moves step by step according to the path selection rules until it reaches the end point. When all ants have completed their movement, the pheromone concentration of the nodes on the path is updated according to the ants' movement path. The update of pheromones follows the pheromone update rule, increasing the pheromone concentration and taking into account the volatilization of pheromones. Repeat the ant colony search and pheromone update until the stop condition is met. During the movement, the ant selects the next node to move according to the probability calculation formula. The probability calculation formula is as follows: ； in, is the probability of moving from node i to node j, is the pheromone concentration from node i to node j, is the heuristic information from node i to node j, α and β are adjustment parameters used to balance the influence of pheromone concentration and heuristic information, After each iteration, the pheromone concentration is updated according to the ant's moving path. The pheromone update formula is as follows: ； Among them, P is the pheromone volatility rate, which controls the persistence of pheromone. is the increment of pheromone left by the mth ant, which is inversely proportional to the total length of the path taken by the ant.

7. An intelligent route planning method for urban and rural planning, applied to an intelligent route planning system for urban and rural planning as claimed in any one of claims 1 to 6, characterized in that: The following steps are involved: S1: Collect geographic data of urban and rural areas, conduct geographic data analysis, and explore regional characteristics; S2: Conduct a traffic demand survey in urban and rural areas to understand the characteristics of travel demand in different time periods and regions, and identify and establish traffic demand patterns in urban and rural areas based on data surveys and using data mining and pattern recognition techniques; S3: Use intelligent algorithms to combine geographic data and traffic demand patterns to search and plan routes, and optimize route planning algorithms to make them more adaptable to urban and rural environments; S4: Design a real-time path update strategy, adjust the path planning scheme according to real-time traffic data, introduce an adaptive planning mechanism, and respond to traffic changes and emergencies in a timely manner.

8. The intelligent route planning method for urban and rural planning according to claim 7, characterized in that: The step 3 further includes using an evolutionary algorithm to optimize the path search process to minimize the total cost of the path, including distance, time and other costs. The fitness function is expressed as: ； Where p represents the path planning scheme, Distance(p) represents the total distance of the path, Time(p) represents the total time of the path, and Cost(p) represents other costs. , , Represents weights of distance, time, and other costs.

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