A method and system for evaluating the adaptability of highway network layout structure

Abstract

The present invention discloses a method and system for evaluating the adaptability of a highway network layout structure. The present invention comprises the following steps: constructing a network model: constructing a traffic flow database and a highway network structure model; tracing the traffic flow OD: analyzing and tracing the traffic flow OD of highways; evaluating the network structure: calculating and analyzing the accessibility of the highway network, the matching degree between the network structure center and the travel demand center based on the traffic flow database and the highway network structure model, and measuring the adaptability of the network structure layout through the matching degree index; optimizing the structure strategy: proposing ideas and strategies for optimizing the highway network structure based on the adaptability calculation results. The present invention is of great significance to the evaluation, optimization and planning of highway networks.

Description

Technical Field

[0001] The present invention relates to the field of public transportation, and more specifically, to a method and system for evaluating the adaptability of a highway network layout structure. Background Art

[0002] As the foundation and main framework of the comprehensive three-dimensional transportation network, expressways are important carriers of urban economic operation, and play a key role in improving the efficiency of urban transportation operation, influencing urban industrial development and layout, and coordinating and balancing regional economic development. Among them, the effective adaptation of the expressway network layout structure and demand distribution is the basis for ensuring smooth travel for residents, orderly and safe freight transportation, and healthy social and economic development.

[0003] At present, domestic and foreign scholars mainly focus on the following two aspects in the evaluation of highway networks: first, applying complex network theory to analyze the characteristics of network structure and constructing an evaluation index system based on aspects such as network structure performance and operation quality, focusing on the characteristics of network structure and ignoring the actual use demand characteristics of highways; second, focusing on the analysis of travel demand characteristics and distribution characteristics of highways, lacking an overall consideration of the impact of network structure on the distribution of demand characteristics.

[0004] The main reference technologies currently include the following:

[0005] Zheng Yibin et al. (Zheng Yibin, Cai Hangpeng, Lai Weiwei et al. Analysis of Hubei Province Expressway Network Characteristics Based on Complex Network [J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2021, 40(5): 31-37) publicly selected the Space-P method to establish a network topology structure to analyze the static characteristics, centrality and robustness of the expressway network; Wu Yangping et al. (Wu Yangping, Guo Fei, Zeng Minghua. Analysis and optimization of urban comprehensive transportation network characteristics based on complex network [J]. Journal of Jiangxi Normal University (Natural Science Edition), 2015, 39(3): 326-330.) proposed a research method for adjustment analysis and optimization of urban comprehensive transportation network based on complex network; Wen Zhenguo (Wen Zhenguo. Research on structural characteristics and robustness of Shaanxi Province Expressway Network based on complex network theory [D]. Xi'an: Chang'an University, 2019.) proposed a network based on complex network. The network efficiency change value is used as a quantitative evaluation indicator for key nodes and key sections of the road network; Gao Wei et al. (Gao Wei, Yao Enjian, Xun Ning, Dai Hongna. A method for identifying highway network risk points based on flow weighting [A]. China Highway and Transport Society, World Transportation Congress Executive Committee, Xi'an Municipal People's Government, Shaanxi Provincial Science and Technology Association. Proceedings of the World Transportation Engineering Technology Forum (WTC2021) (Part 2) [C]. China Highway and Transport Society, World Transportation Congress Executive Committee, Xi'an Municipal People's Government, Shaanxi Provincial Science and Technology Association: China Highway and Transport Society, 2021: 8.) proposed a method for identifying highway network risk points based on flow weighting; Weng Xiaoxiong et al. (Weng Xiaoxiong, Xie Zhipeng. Research on the importance of highway nodes based on multi-layer complex networks [J]. Journal of Guangxi Normal University (Natural Science Edition), 2021, 39(5): 78-88.) constructed Page Rank-TOPSIS fusion algorithm is used to analyze and evaluate the importance of highway nodes; Zhang Xiping et al. (Zhang Xiping, Li Yongshu, Liu Gang, Wang Lei. Method for evaluating the importance of roads in urban complex transportation networks [J]. Complex Systems and Complexity Sciences, 2015, 12(3): 7-13.) proposed a method for evaluating the importance of road network segments based on dual topological structure. The above existing technologies are based on the evaluation perspective of highway network structure, mainly evaluating the importance of network nodes and road segments based on highway road network characteristics, without considering the characteristics of highway network travelers as network operation subjects, OD demand distribution and driving path characteristics.

[0006] Lei Xiaoshi (Lei Xiaoshi. Prediction of highway OD distribution based on vehicle classification and identification [D]. Chongqing: Chongqing Jiaotong University, 2021.) proposed a prediction method for highway OD distribution based on the ARIMA-LSTM model; Liu Xudong et al. (Liu Xudong, Zou Jiyuan. Analysis of highway travel characteristics based on networked toll data [J]. Comprehensive Transportation, 2019, 41(10): 113-117.) analyzed the travel characteristics of highways based on networked toll data; Xia Yanqing (Xia Yanqing. Analysis of highway travel characteristics based on spatiotemporal big data technology [D]. Beijing: North China University of Technology, 2020.) realized the travel trend analysis of highway network groups and the user characteristics of individual users; Tian Tian (Tian Tian. Highway travel characteristics based on toll data Highway travel characteristics analysis and demand forecasting [D]. Chongqing: Chongqing Jiaotong University, 2020.) Based on toll data, the training sample set of the random forest prediction model is established to realize the OD flow forecast of highway traffic flow; Guo Ruijun et al. (Guo Ruijun, Yu Jing, Sun Xiaoliang, Niu Shuyun. Highway traffic flow characteristics analysis based on electronic toll data [J]. Journal of Dalian Jiaotong University, 2018, 39(1):17-22.) Conduct highway traffic flow characteristics analysis based on electronic toll data; Cui Hongjun et al. (Cui Hongjun, Ren Zhixiao, Zhu Minqing, Wang Zipeng, He Meimei. Highway travel distance characteristics analysis and application [J]. Science, Technology and Engineering, 2020, 20(8):3323-3329.) Conduct highway travel distance characteristics analysis and application research. The above-mentioned public content is based on the perspective of highway traffic flow OD research, mainly relying on electronic toll data to study highway traffic flow characteristics analysis and OD distribution. Highway travel OD analysis is limited to the OD level of toll stations, lacking in-depth research from the actual starting point to the end point of demand.

[0007] Han Jianfei et al. (Han Jianfei, Zong Gang. Evaluation of highway operation efficiency based on complex network [J]. Journal of Wuhan University of Technology (Social Science Edition), 2012, 25(6):882-887.) proposed a highway operation efficiency evaluation method based on complex network; Yang Ming et al. (Yang Ming, Gao Yong, Liu Hongye. Evaluation of highway operation efficiency based on support vector machine model [J]. Systems Engineering, 2009(2):90-95.) established a support vector machine evaluation model for highway enterprise operation efficiency evaluation; Xie Hongxin et al. (Xie Hongxin, Xiao Shen. Application of neural network in comprehensive evaluation of highway network [J]. Journal of Highway and Transportation Research and Development, 2005(8):106-110.) applied multi-level analysis method and neural network model to study the evaluation indicators and comprehensive evaluation methods of highway network; Ji Keke et al. (Ji Keke, Chen Jian, Wu Gaixuan et al. Evaluation of highway network traffic adaptability based on combined weighted cloud model [J]. Highway, 2021(3):193-200.) proposed a highway network traffic adaptability evaluation method based on combined weighted cloud model; Zhang Huili et al. (Zhang Huili, Tan Guifei. Research on traffic adaptability of national and provincial trunk road network in Hebei Province [J]. Highway, 2018, 63(4):173-178.) constructed a traffic adaptability evaluation index system based on the structural performance and operation quality of the road network; Li Limin et al. (Li Limin, Liu Meishuang. Analysis of traffic adaptability of highway network in Heilongjiang Province [J]. Forest Highway, 2007, (4):61-63.) evaluated the highway network from the aspects of structural performance and operation quality based on the fuzzy comprehensive evaluation method, and selected comprehensive density and other indicators. The above-mentioned public content is based on the perspective of comprehensive evaluation of highways. Existing evaluation research mainly focuses on the evaluation of highway traffic adaptability and the research on network operation efficiency, and lacks the evaluation of the adaptability of highway network layout structure and highway traffic travel OD. Summary of the invention

[0008] In order to solve the above problems, the present invention first proposes a highway network layout structure adaptability evaluation method. The method reasonably evaluates the network layout structure based on the matching degree between the highway network layout structure characteristics and the actual use demand characteristics, and can provide ideas for highway network structure evaluation and optimization.

[0009] The invention also proposes a highway network layout structure adaptability evaluation system.

[0010] In order to achieve the above object, the technical solution of the present invention is:

[0011] A method for evaluating the adaptability of a highway network layout structure comprises the following steps:

[0012] Build network model: build traffic flow database and highway network structure model;

[0013] Tracing the source of traffic flow OD: highway traffic flow OD analysis and tracing;

[0014] Evaluate network structure: Based on the traffic flow database and highway network structure model, calculate and analyze the accessibility of the highway network, the matching degree between the network structure center and the travel demand center, and measure the adaptability of the network structure layout through the matching degree index;

[0015] Optimization structure strategy: Based on the adaptability calculation results, ideas and strategies for optimizing the highway network structure are proposed.

[0016] Preferably, the traffic flow database is constructed by collecting data including highway toll data and license plate recognition data of high-definition road checkpoints: and is obtained by establishing a spatial association relationship between the location of highway toll stations, the location of high-definition road checkpoints and network structure traffic geographic information; wherein the network structure traffic geographic information is a network structure physical model based on GIS software, including highway network and highway intersections, and traffic community geographic information.

[0017] The construction of the highway network structure model includes constructing a highway structure model and dividing traffic zones.

[0018] Preferably, the tracing of traffic flow OD is based on highway toll data and road high-definition checkpoint license plate recognition data, that is, extending the highway toll station OD to the urban road to obtain the OD distribution of the actual departure and arrival points of a single vehicle, and dividing the OD clusters into traffic areas, a traffic flow OD tracing method.

[0019] Preferably, the specific process of the tracing vehicle flow OD method is:

[0020] Step 1: Highway toll station OD recognition

[0021] (1) Construct a single vehicle highway travel information database; establish a sequence of toll stations at the entrance and exit of the highway {X s1 ,X s2 ,X s3 ......,X sn} and the time series of vehicle entrances and exits of highways {T s1 ,T s2 ,T s3 ......,T sn}, where n is the total number of toll stations that the vehicle passes during the study period, X si is the i-th toll station that the vehicle passes during the study period, T si is the time when the vehicle passes through the i-th toll station during the study period, i∈(1,n);

[0022] (2) Segmenting travel information and extracting highway toll ODs; The daily toll records of a single vehicle contain multiple toll travel information records. The travel information of the vehicle passing through all highway toll stations is segmented to extract the toll station ODs. The travel sequence of each vehicle is segmented into {(O s1 ,D s1 ,OT s1 ,DT s1 ),(O s2 ,D s2 ,OT s2 ,DT s2 )......,(O sm ,D sm ,OT sm ,DT sm )},(O si ,D si ,OT si ,DT si ) are the starting point, the end point, the entry time at the starting point and the exit time at the end point of the vehicle at the i-th section of the expressway toll OD during the study period, i∈(1,m), m≤n / 2;

[0023] Step 2: OD extension of highway toll station

[0024] (1) Establish a perception sequence of checkpoint recognition data; Establish a perception sequence of road high-definition checkpoint recognition data {X k1 ,X k2 ,X k3 ......,X kq} and the time series of the bayonet recognition {T k1 ,T k2 ,T k3 ......,T kq}, where q is the total number of checkpoints that the vehicle passes during the study period, X ki is the i-th checkpoint that the vehicle passes during the study period, T ki is the time when the vehicle passes the i-th checkpoint during the study period, i∈(1,q);

[0025] (2) Construct a single vehicle travel information database; extract the high-definition checkpoint perception sequence of vehicles traveling at highway toll stations, and splice the perception sequence of high-definition checkpoint recognition data with the highway toll OD sequence according to time. The travel sequence of each vehicle is spliced ​​into {X k1 ,...,O s1 ,...,D s1 ,...,X ki ,...,O sm ,...,D sm ,...,X kq}, the corresponding time series is {Tk1 ,...,OT s1 ,...,DT s1 ,...,T ki ,...,OT sm ,...,DT sm ,...,T kq};

[0026] (3) Distinguish a single OD trip based on the travel time threshold; Set the travel time threshold to B, and distinguish a single trip based on the travel time threshold. If the time difference between the first sequence point and the second sequence point is less than or equal to the travel time threshold B, then the two sequence points are considered to belong to the same trip; if it is greater than the travel time threshold B, then the second sequence point belongs to the next trip; Based on whether two adjacent sequence points belong to the same trip, extract the travel OD chain of each vehicle;

[0027] (4) Extraction of highway travel OD: extract the travel OD containing the toll station OD in the travel OD to obtain the travel OD information of individual vehicles traveling on the highway;

[0028] Step 3 Traffic zone OD aggregation: The obtained individual vehicle travel OD information is combined with the vehicle’s last checkpoint location and traffic zone division information to integrate the traffic flow OD into the traffic zone, thereby realizing the traffic flow OD tracing analysis.

[0029] Preferably, the evaluation network structure is based on the overall travel OD data of the highway, and the structure of the highway network is evaluated from three dimensions: network, node, and section. The accessibility of the highway network is evaluated at the network level, and the structural adaptability of the highway network is evaluated at the node level and section level. The specific process is as follows:

[0030] (1) Highway network accessibility assessment: including highway network accessibility assessment of traffic communities and regional highway network accessibility assessment;

[0031] (101) The evaluation of the accessibility of a traffic zone to the highway network is to measure the convenience of the traffic zone to reach the highway network system: based on the OD information of vehicle highway travel, the average travel time of vehicles with the centroid of traffic zone i as the starting point or end point to reach the highway toll station is calculated as the highway accessibility D of the traffic zone. i :

[0032]

[0033] Where: D i —Accessibility of the highway network of the ith traffic zone; T in —The starting point of the trip is located in traffic area i, and the time to get on the highway from traffic area i; Tmi —The time it takes for the vehicle flow OD to reach the traffic zone i when the destination is in the traffic zone i; N—The number of vehicles O integrated into the traffic zone i; M—The number of vehicles D integrated into the traffic zone i;

[0034] (102) Regional highway network accessibility assessment is to measure the convenience of a region to reach the highway network: based on the OD information of vehicle highway travel, the average travel time of vehicles with the centroid of the traffic community in a certain area as the starting point or starting point to reach the highway toll station is calculated; this is used as the regional highway accessibility D:

[0035]

[0036] Where: D—accessibility of highways in the area; D i —Accessibility of highway to the ith traffic zone; M i —The traffic volume of the ith traffic zone; I—the number of traffic zones in a certain area;

[0037] (2) Highway network structure adaptability assessment: Based on the dimensions of nodes and road sections, the intermediate indicators of highway network structure and travel demand are calculated to determine the degree of match between the network structure operation center and the actual network operation center.

[0038] (201) Generate the shortest path set of nodes: Based on the highway network structure model, take the centroid of the traffic zone as the starting and ending points of the trip, and generate the shortest path set between the centroids of the traffic zones;

[0039] (202) Network structure mediating index calculation: including interchange node mediating index and road section structure mediating index, which are calculated based on the importance of interchange transfer and expressway section in the network structure respectively;

[0040] (2021) Interchange node intermediary index: Count the number of shortest paths between the centroids of traffic communities that pass through interchanges. The ratio of the interchange conversion path to the total number of shortest paths is the interchange node intermediary index;

[0041]

[0042]

[0043] Where: WN i —Structural intermediate index of the ith interchange; LN i —The number of shortest paths passing through the ith interchange; LN—The number of shortest paths; WNS—The variance of the interchange intermediate index; N—The total number of interchanges;

[0044] (2022) Intermediate index of road structure: the number of road sections that the shortest path between the centroids of traffic communities passes through is counted, and the ratio of the number of shortest paths passing through this road section to the total number of shortest paths is the intermediate index of the road section;

[0045]

[0046]

[0047] Where: WL j —Structural intermediate index of the jth road section; LN j —The number of shortest paths passing through the jth road segment; LN—The number of shortest paths; WLS—The variance of the intermediate index of the road segment structure; M—The total number of road segments;

[0048] (203) Calculation of travel demand intermediary indicators: The identified OD traffic flow based on the traffic zone level is matched to the highway network section according to the shortest path, and the travel demand intermediary indicators are calculated based on the network structure model. The variance of the intermediary indicators is used to reflect the demand distribution. The larger the variance value, the higher the concentration of travel demand.

[0049] (2031) Interchange demand intermediate index; the flow of OD traffic distributed by the shortest path between the centroids of the traffic zone passing through the interchange is counted and recorded as the conversion traffic of the interchange; the ratio of the conversion traffic of the interchange to the OD traffic of the highway is the intermediate index of the interchange demand;

[0050]

[0051]

[0052] Where: QN i is the demand intermediate index of the ith interchange; LQ i is the OD volume of the shortest path traffic through the i-th interchange; LQ is the total OD volume of high-speed travel; QNS is the variance of the intermediate indicator of interchange demand; N is the total number of interchanges;

[0053] (2032) Intermediary index of road section demand; the traffic volume of OD traffic flow distributed by the shortest path between the centroids of traffic communities passing through the road section is counted, which is recorded as the actual operation traffic volume of the road section; the proportion of the operation traffic volume of the road section to the OD traffic volume of the highway is the actual operation centrality of the road section;

[0054]

[0055]

[0056] Where: QL j —Demand intermediate index of the jth road segment; LQ j—The shortest path traffic volume passing through the jth road segment; LQ—the total OD volume of high-speed travel; QLS—the variance of the intermediate index of road segment demand; M—the total number of road segments;

[0057] (3) Network structure matching degree calculation: Spatial clustering of interchanges and road sections is performed using the intermediate index of interchange structure, intermediate index of road section structure, intermediate index of demand structure, and intermediate index of road section demand as the weights of spatial clustering of interchanges and road sections, and the degree of matching between highway network structure and demand is determined based on geographical distance;

[0058] (301) Select the interchanges ranked in the top C% in terms of interchange intermediate index, use the intermediate index of each interchange as a weight value, perform spatial clustering based on the location information of the interchange, and respectively calculate the location value of the network structure interchange center index and the location value of the interchange demand intermediate index; the offset of the demand interchange center position relative to the structure interchange center position is used as the interchange matching degree measurement value;

[0059] (302) Select the road sections whose intermediate index is ranked in the top C%, use the intermediate index of each road section as a weight value, perform spatial clustering based on the location information (latitude and longitude) of the road section, and respectively calculate the tangent value of the network structure intermediate index and the tangent value of the demand road section intermediate index; the offset of the demand road section tangent relative to the structure tangent is used as the road section matching degree measurement value;

[0060] (4) Construction of a structural evaluation index system: The network structure adaptability evaluation index includes the accessibility of traffic communities and regional highways, the median variance between interchange nodes and road sections, the median variance between interchange demand and road sections, and the matching degree between interchange nodes and road sections. By comparing with the set evaluation standards of various indicators, the adaptability of the highway network structure is comprehensively evaluated.

[0061] Preferably, the optimization structure strategy includes "addition" and "subtraction" strategies:

[0062] "Addition" strategy: To address the problem of poor accessibility of individual traffic areas, increase the road network functions of traffic areas with poor accessibility; to address the problem of poor accessibility of regional highways, increase the planning and design of highway function projects in the serial areas; to address the road sections with high concentration, add parallel functional line designs; to address the mismatch between interchanges and road sections, and the deviation between the network layout center and the actual operation center, increase the highway function and node conversion function design in the weak-core area;

[0063] "Subtraction" strategy: For sections or nodes with high concentration, overall functional design should be carried out before highway planning and design to avoid introducing new lines into sections with high concentration; for sections or nodes with obviously low concentration, functions should be reduced by passing through the fewest sections or ramps with the shortest path.

[0064] A highway network layout structure adaptability evaluation system, the evaluation system applies the highway network layout structure adaptability evaluation method.

[0065] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the highway network layout structure adaptability evaluation method when executing the computer program.

[0066] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for evaluating the adaptability of a highway network layout structure.

[0067] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention proposes a method for evaluating the adaptability of a highway network layout structure, which evaluates the scientificity and rationality of the highway network structure from the perspective of whether the network structure layout is compatible with actual usage needs, and provides an adaptation strategy for subsequent optimization and adjustment of the highway network structure, which is of great significance to highway network evaluation, optimization and planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is the overall framework diagram of a highway network layout structure adaptability assessment method.

[0069] Figure 2 This is a flowchart of high-speed bus trip OD tracing based on the traffic database.

[0070] Figure 3 This is a flow chart for highway network structure assessment based on the network structure model. DETAILED DESCRIPTION

[0071] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0072] This paper proposes a highway network structure adaptability assessment method. Based on the highway traffic database and network structure model, it comprehensively assesses the matching degree between the highway network structure layout and the actual use demand, and proposes a network structure optimization strategy based on the adaptation results. It is of great significance to the evaluation, optimization and planning of highway networks. The flow chart of the assessment method is shown in the figure. Figure 1 , including four aspects: building a network model, tracing the traffic flow OD, network structure evaluation, and structure optimization strategy. It is specifically divided into the following six steps: (1) building a traffic flow database; (2) building a highway network structure model; (3) analyzing and tracing the traffic flow OD of highways; (4) calculating and analyzing the characteristic indicators of the network structure; (5) calculating the matching degree of the network structure to determine the degree of adaptation of the highway network structure; and (7) designing a network structure optimization strategy.

[0073] 1. Building a data model

[0074] 1. Construct a traffic flow database. It mainly includes highway toll data and high-definition license plate recognition data of road checkpoints. (1) Highway toll data, including static data and dynamic data. The static data includes basic information such as the name of the toll station and the name of the ETC, ID code, longitude and latitude, and the dynamic data includes vehicle flow data (license plate number, vehicle type, entrance name, entry time, exit name, exit time, transaction amount, etc.); static data and dynamic data can be associated through information such as the toll station name and the entrance and exit name. (2) Road high-definition license plate recognition data, the data mainly includes checkpoint name, direction number, lane number, passing time, license plate number, etc. The traffic flow database establishes a spatial association relationship through the toll station location (longitude and latitude), checkpoint location (longitude and latitude) and the network structure traffic geographic information model.

[0075] 2. Constructing the network structure model. This mainly includes the construction of the highway network structure model and the division of traffic zones. (1) The highway network structure model includes two types: nodes and sections. Nodes include toll stations, interchanges, and virtual nodes. Sections include the main line of the highway, main line bridges, ramp bridges, transition sections, virtual paths, etc. (2) The division of traffic zones considers the road network structure, land use, population job distribution, and social and economic conditions, and decomposes the complex traffic network into several traffic areas. The travel of highway users (vehicles) consists of three parts: toll highways and toll expressways, non-toll expressways, and urban road connecting sections. Among them, the toll station is the most critical node unit of the highway, and it is also the generation point and attraction point of the highway. The traffic zone is the generation point and attraction point of the source end of the highway user's travel. It is the tracing unit of the highway vehicle on the urban road after leaving the toll station.

[0076] 2. Tracing the source of traffic OD

[0077] In this embodiment, the tracing vehicle flow OD is a vehicle travel OD tracing method based on highway toll data and road high-definition card gate license plate recognition data, that is, the highway toll station OD is extended to the urban road to obtain the OD distribution of the actual departure and arrival points of a single vehicle, and finally the OD set plan is divided into traffic areas. A vehicle flow OD tracing method. The vehicle flow OD tracing method in this embodiment is mainly based on highway toll data and road high-definition card gate license plate recognition data, and can be combined with various Internet location data, operator signaling data, etc. in actual application.

[0078] The traffic OD tracing method is mainly based on highway toll data and road high-definition card plate recognition data, such as Figure 2 , the specific steps are as follows:

[0079] Step 1 Highway toll station OD recognition

[0080] (1) Construct a single vehicle highway travel information database. Establish a sequence of toll booths at the entrance and exit of the highway {X s1 ,X s2 ,X s3 ......,X sn} and the time series of vehicle entrances and exits of highways {T s1 ,T s2 ,T s3 ......,T sn}, where n is the total number of toll stations that the vehicle passes during the study period, X si is the i-th toll station that the vehicle passes during the study period, T si is the time when the vehicle passes through the i-th toll station during the study period, i∈(1,n).

[0081] (2) Segmenting travel information and extracting highway toll OD. The daily toll record of a single vehicle contains multiple toll travel information records. The travel information of the vehicle passing through all highway toll stations is segmented to extract the toll station OD. The travel sequence of each vehicle is segmented into {(O s1 ,D s1 ,OT s1 ,DT s1 ),(O s2 ,D s2 ,OT s2 ,DT s2 )......,(O sm ,D sm ,OT sm ,DT sm )},(O si ,D si ,OT si ,DT si ) are the starting point, end point, entry time at the starting point and exit time at the end point of the vehicle at the i-th section of expressway toll OD during the study period, i∈(1,m), m≤n / 2.

[0082] Step 2Extension of highway toll station OD

[0083] (1) Establish a perception sequence of checkpoint recognition data. Establish a perception sequence of high-definition road checkpoint recognition data {X k1 ,X k2 ,X k3 ......,X kq} and the time series of the bayonet recognition {T k1 ,T k2 ,T k3 ......,T kq}, where q is the total number of checkpoints that the vehicle passes during the study period, X ki is the i-th checkpoint that the vehicle passes during the study period, T ki is the time when the vehicle passes the i-th checkpoint during the study period, i∈(1,q).

[0084] (2) Construct a single vehicle travel information database. Extract the high-definition card gate perception sequence of vehicles traveling at highway toll stations, and splice the perception sequence of high-definition card gate recognition data with the highway toll OD sequence according to time. The travel sequence of each vehicle is spliced ​​into {X k1 ,...,O s1 ,...,D s1 ,...,X ki ,...,O sm ,...,D sm ,...,X kq}, the corresponding time series is {T k1 ,...,OT s1 ,...,DT s1 ,...,T ki ,...,OT sm ,...,DT sm ,...,T kq}.

[0085] (3) Distinguishing a single OD trip based on the travel time threshold. Set the travel time threshold to B. In this embodiment, the travel time threshold is determined based on the average time of a taxi overload, and B is the 95th percentile travel time of the travel perception pair in the GPS overload trip. Distinguish a single trip based on the travel time threshold. If the time difference between the first sequence point and the second sequence point meets the travel time threshold B, the two sequence points are considered to belong to the same trip. If the time threshold is not met, the second sequence point belongs to the next trip. Based on whether two adjacent sequence points belong to the same trip, the travel OD chain of each vehicle can be extracted.

[0086] (4) Extraction of highway trip OD. By extracting the trip ODs that contain toll station ODs, we can obtain the set of trip ODs that have traveled on the highway.

[0087] Step 3: Traffic zone OD aggregation: The obtained individual vehicle travel OD information is combined with the checkpoint location and traffic zone division information of the vehicle's last route, and the vehicle flow OD is integrated into the traffic zone level.

[0088] (III) Evaluating the network structure

[0089] The evaluation of network structure is based on the overall travel OD data of highways. The structure of the highway network is evaluated from three dimensions: network, node, and section. The accessibility of the highway network is evaluated at the network level, and the structural adaptability of the network is evaluated at the node and edge levels. Figure 3 , the specific contents are as follows:

[0090] (1) Highway accessibility assessment. The more reasonable the highway network planning is, the better the spatial accessibility is. This module evaluates accessibility in two dimensions: first, highway accessibility in the traffic community, and second, regional high-speed transportation accessibility.

[0091] Step 101: Accessibility of the highway network of the traffic community. To measure the convenience of the traffic community to reach the highway network system, based on the OD information of the vehicle highway trip, the average travel time for the vehicle to reach the highway toll station with the centroid point of the traffic community i as the starting point or end point is calculated as the highway accessibility of the traffic community.

[0092]

[0093] Where: D i —Accessibility of the highway network of the ith traffic zone; T in —The starting point of the trip is located in traffic area i, and the time to get on the highway from traffic area i; T mi —The trip destination is located in traffic zone i, and the time it takes for traffic flow OD to get off the highway and reach traffic zone i; N—the number of traffic flows O integrated into traffic zone i; M—the number of traffic flows D integrated into traffic zone i.

[0094] Step 102 Regional highway network accessibility. To measure the convenience of regional access to the highway network, based on the OD information of vehicle highway travel, the average travel time of vehicles reaching the highway toll station with the centroid of each traffic community in a certain area as the travel starting point or starting point is calculated as the regional highway accessibility.

[0095]

[0096] Where: D—accessibility of highways in the area; D i —Accessibility of highway to the ith traffic zone; M i —The traffic volume of the ith traffic zone; I—the number of traffic zones in a certain area.

[0097] (2) Evaluation of the adaptability of the highway network structure. Taking nodes and sections as dimensions, the intermediate index of the highway network structure and the intermediate index of travel demand are calculated respectively to determine the degree of match between the network structure operation center and the actual network operation center.

[0098] Step 201 generates a node shortest path set. Based on the highway network structure model, the centroid of the traffic zone is used as the starting and ending point of the trip, and the shortest path set between the centroids of the traffic zones is generated.

[0099] Step 202 Calculation of network structure intermediary index. This includes the intermediary index of interchange nodes and the intermediary index of road section structure, which are calculated based on the importance of interchange conversion and expressway sections in the network structure. The variance of the intermediary index reflects the structure of the network. The larger the variance value, the higher the concentration of the network.

[0100] (2021) Interchange node intermediary index. The number of shortest paths between the centroids of traffic zones passing through interchanges is counted, and the ratio of the interchange conversion paths to the total number of shortest paths is the interchange intermediary index.

[0101]

[0102]

[0103] Where: WN i —Structural intermediate index of the ith interchange; LN i —The number of shortest paths passing through the i-th interchange; LN—The number of shortest paths; WNS—The variance of the interchange intermediate index; N—The total number of interchanges.

[0104] (2022) Intermediate index of road section structure. The number of road sections that the shortest path between the centroids of traffic cells passes through is counted, and the ratio of the number of shortest paths passing through this road section to the total number of shortest paths is the intermediate index of the road section.

[0105]

[0106]

[0107] Where: WL j —Structural intermediate index of the jth road section; LN j —The number of shortest paths passing through the jth road segment; LN—The number of shortest paths; WLS—The variance of the intermediate index of the road segment structure; M—The total number of road segments.

[0108] Step 203: Calculation of travel demand intermediary indicators. The identified OD traffic flow based on the traffic zone level is matched to the highway network section according to the shortest path, and the travel demand intermediary indicators are calculated based on the network structure model. The variance of the intermediary indicators is used to reflect the demand distribution. The larger the variance value, the higher the concentration of travel demand.

[0109] (2031) Interchange demand intermediary index. The flow of OD traffic distributed by the shortest path between the centroids of the traffic zone passing through the interchange is counted and recorded as the interchange conversion traffic; the ratio of the interchange conversion traffic to the high-speed OD traffic is the interchange demand intermediary index.

[0110]

[0111]

[0112] Where: QN i is the demand intermediate index of the ith interchange; LQ i is the OD volume of the shortest path traffic through the i-th interchange; LQ is the total OD volume of high-speed travel; QNS is the variance of the intermediate indicator of interchange demand; N is the total number of interchanges.

[0113] (2032) Intermediary index of road section demand. The traffic volume of the OD traffic flow distributed by the shortest path between the centroids of the traffic cells passing through the road section is counted and recorded as the actual operating traffic volume of the road section; the proportion of the operating traffic flow of the road section to the OD traffic flow of the highway is the actual operating centrality of the road section.

[0114]

[0115]

[0116] Where: QL j —Demand intermediate index of the jth road segment; LQ j —The shortest path traffic volume passing through the jth road segment; LQ—the total OD volume of high-speed travel; QLS—the variance of the intermediate indicator of road segment demand; M—the total number of road segments.

[0117] Step 204: Calculation of network structure matching degree. Spatial clustering of interchanges and road sections is performed using the structure intermediate index of interchanges, the structure intermediate index of road sections, the structure intermediate index of demand, and the demand intermediate index of road sections as the weights of spatial clustering of interchanges and road sections, and the degree of matching between the highway network structure and demand is determined based on the geographical distance.

[0118] (2041) Interchanges ranked in the top C% of the interchange intermediate index are selected, and the intermediate index of each interchange is used as the weight value. Spatial clustering is performed based on the location information (latitude and longitude) of the interchange, and the location value of the network structure interchange center index and the location value of the interchange demand intermediate index are calculated respectively. The offset of the demand interchange center position relative to the structure interchange center position is used as the interchange matching degree measurement value.

[0119] (2042) Select the road sections whose intermediate index is ranked in the top C%, use the intermediate index of each road section as a weight value, perform spatial clustering based on the location information (latitude and longitude) of the road section, and respectively calculate the tangent value of the network structure intermediate index and the tangent value of the demand road section intermediate index. The offset of the demand road section tangent relative to the structure tangent is used as the road section matching degree measurement value.

[0120] Step 205: Construction of structural evaluation index system. The network structure adaptability evaluation index proposed in the present invention includes accessibility of traffic communities and regional highways, median variance of interchange nodes and sections, median variance of interchange demand and section demand, matching degree of interchange nodes and sections, etc. By setting evaluation standards for various indicators, the adaptability of the highway network structure is comprehensively evaluated.

[0121] (IV) Optimization strategy design

[0122] Combined with the evaluation results, the optimization strategy of expressway network structure is proposed, which mainly includes "addition" and "subtraction" strategies:

[0123] (1) “Addition”. To address the problem of poor accessibility of individual traffic areas, increase the road network functions of traffic areas with poor accessibility; to address the problem of poor accessibility of regional highways, increase the planning and design of highway function projects in the serial areas; for sections with high concentration, consider adding parallel functional line designs; to address the problem of mismatch between interchanges and sections, and the deviation between the network layout center and the actual operation center, increase the highway function and node conversion function design in the weak-core area to improve the balance and stability of the road network.

[0124] (2) “Subtraction”. For sections or nodes with high concentration, overall functional design should be conducted before planning and designing the expressway to avoid introducing new routes into sections with high concentration. For sections or nodes with significantly low concentration, the functions of the sections or ramps with the shortest path can be reduced. For example, a small acute left turn in an interchange group can be replaced by a nearby obtuse angle.

[0125] In this embodiment, a highway network layout structure adaptability assessment system using the highway network layout structure adaptability assessment method is also proposed.

[0126] In this embodiment, a computer device is also proposed, including a memory and a processor, the memory stores a computer program, and the processor implements the highway network layout structure adaptability evaluation method when executing the computer program.

[0127] In this embodiment, a computer-readable storage medium is also proposed, on which a computer program is stored. When the computer program is executed by a processor, the method for evaluating the adaptability of the highway network layout structure is implemented.

[0128] The embodiments of the present invention described above do not constitute a limitation on the protection scope of the present invention. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for evaluating the adaptability of a highway network layout structure, characterized in that: include: Build network model: build traffic flow database and highway network structure model; The traffic flow database is constructed by collecting highway toll data and road high-definition checkpoint license plate recognition data; and is obtained by establishing a spatial association relationship between highway toll station locations, road high-definition checkpoint locations and network structure traffic geographic information; The construction of the highway network structure model includes constructing a highway structure model and dividing traffic zones; Tracing traffic OD : Highway traffic OD Analysis and traceability; The traceable traffic flow OD It is based on the highway toll collection data and the high-definition license plate recognition data of the road toll station. OD Extend to urban roads to obtain the actual starting and ending points of a single vehicle OD distributed; Evaluate network structure: Based on the traffic flow database and highway network structure model, calculate and analyze the accessibility of the highway network, the matching degree between the network structure center and the travel demand center, and measure the adaptability of the network structure layout through the matching degree index; The evaluation network structure is based on the overall travel of highways OD Data is collected to evaluate the structure of the highway network from three dimensions: network, node, and section. The accessibility of the highway network is evaluated at the network level, and the structural adaptability of the highway network is evaluated at the node level and section level. Specifically, it includes: Highway network accessibility assessment, including traffic community highway network accessibility assessment is based on vehicle highway travel OD Information, calculation based on traffic area i The average travel time of vehicles with the centroid as the starting point or destination to reach the highway toll station is taken as the high-speed accessibility of the traffic community. ; It also includes the regional highway network accessibility assessment, which measures the convenience of regional access to the highway network: based on vehicle highway travel OD The information is used to calculate the average travel time of vehicles arriving at the expressway toll station with the centroid of each traffic zone in a certain area as the starting point or end point; as the expressway accessibility of the area D； Highway network structure adaptability assessment: Based on the dimensions of nodes and sections, the intermediate indicators of highway network structure and travel demand are calculated respectively to determine the matching degree between the network structure operation center and the actual network operation center; Optimization structure strategy: Based on the adaptability calculation results, ideas and strategies for optimizing the highway network structure are proposed.

2. A highway network layout structure adaptability evaluation method according to claim 1, characterized in that: The traceable traffic flow OD The specific process of the method is: Step 1: Highway toll station OD Identification (1) Construct a single vehicle highway travel information database; establish a sequence of toll booths at the entrances and exits of highways and the time series of vehicle entry and exit of highways ,in n is the total number of toll stations that the vehicle passes during the study period, is the number of times the vehicle passes during the study period. i Toll booths, The vehicle passes the first i The time of toll booths is i ∈(1, n); (2) Segment travel information and extract highway tolls OD ; The daily toll collection record of a single vehicle contains multiple toll travel information records. The travel information of the vehicle passing through all highway toll stations is segmented and the toll station information is extracted. OD , the travel sequence of each vehicle is divided into , The vehicle is in the research period. i Highway toll OD The starting point, end point, entry time at the starting point, and exit time at the end point, i ∈(1, m) ,m≤n / 2 ; Step 2: Highway toll station OD extend (1) Establish a perception sequence for card-entry recognition data; Establish a perception sequence for high-definition card-entry recognition data on roads and bayonet recognition time series ,in q is the total number of checkpoints that the vehicle passed during the study period, is the number of times the vehicle passes during the study period. i A bayonet, The vehicle passed the first i The time of the card slot, i ∈(1,q); (2) Construct a single vehicle travel information database; extract the travel information of highway toll stations OD The vehicle's high-definition card gate perception sequence combines the perception sequence of high-definition card gate recognition data with the highway toll OD The sequences are spliced ​​according to time, and the travel sequence of each vehicle is spliced ​​as follows: , the corresponding time series is ; (3) Distinguishing single trips based on travel time thresholds OD Travel; set the travel time threshold to B , a single trip is identified based on the travel time threshold. If the time difference between the first sequence point and the second sequence point is less than or equal to the travel time threshold, B , then the two sequence points are considered to belong to the same trip; if it is greater than the travel time threshold B , then the second sequence point belongs to the next trip; according to whether the two adjacent sequence points belong to the same trip, the trip OD chain of each vehicle is extracted; (4) Extract high-speed travel OD; OD Contains toll booths OD Travel OD Extract and obtain the trips of individual vehicles on the highway OD information; Step 3 Traffic Community OD Aggregate; the individual vehicle trips obtained OD The information is combined with the checkpoint location and traffic zone division information of the vehicle's last route to OD Integrated into the traffic zone to achieve traffic flow OD Source analysis.

3. A highway network layout structure adaptability evaluation method according to claim 2, characterized in that: The evaluation network structure has high speed accessibility : Where: —No. i The accessibility of the highway network to each transportation zone; —The starting point of the trip is located in the traffic area i , from the traffic area i Time to get on the highway; —The destination of the trip is located in the traffic area i , traffic OD Get off the highway and arrive at the traffic area i time; N —Traffic O Integrated into the traffic zone i the number of M —Traffic D Integrated into the traffic zone i the number of High-speed accessibility of the area D : Where: D —Accessibility of highways in the area; —No. i Highway accessibility of each transportation community; —No. i Traffic volume in each traffic zone; I —The number of traffic zones in a certain area; The specific process of the highway network structure adaptability assessment is as follows: (201) Generate the shortest path set of nodes: Based on the highway network structure model, take the centroid of the traffic zone as the starting and ending points of the trip, and generate the shortest path set between the centroids of the traffic zones; (202) Network structure mediating index calculation: including interchange node mediating index and road section structure mediating index, which are calculated based on the importance of interchange transfer and expressway section in the network structure respectively; (2021) Interchange node intermediary index: Count the number of shortest paths between the centroids of traffic communities that pass through interchanges. The ratio of the interchange conversion path to the total number of shortest paths is the interchange node intermediary index; Where: —No. i The structural mediating index of the interchange; —After the i The number of shortest paths through an interchange; —The number of shortest paths; — Variance of the interchange intermediate index; N —Total number of interchanges; (2022) Intermediate index of road structure: Count the number of road sections that the shortest path between the centroids of traffic communities passes through. The ratio of the number of shortest paths passing through this road section to the total number of shortest paths is the intermediate index of the road section; Where: —No. j Structural intermediate indicators of road sections; —After the j The number of shortest paths for each road segment; —The number of shortest paths; — Variance of the intermediate indicators of the road section structure; M - Total number of road sections; (203) Calculation of intermediary indicators of travel demand: The identified intermediary indicators based on the traffic community level are OD The traffic flow is matched to the highway network sections according to the shortest path. The travel demand intermediary index is calculated based on the network structure model, and the variance of the intermediary index is used to reflect the demand distribution. The larger the variance value, the higher the concentration of travel demand. (2031) Interchange demand intermediary index; Statistics of the distribution of the shortest path between the centroids of traffic communities OD The traffic volume passing through the interchange is recorded as the conversion traffic volume of the interchange; the conversion traffic volume of the interchange accounts for the proportion of highway OD The proportion of traffic is an intermediate indicator of interchange demand; Where: For the i Intermediate demand indicators for interchanges; For the i The shortest path traffic flow of the interchange OD quantity; For high-speed travel OD Total amount; is the variance of the intermediate indicator of interchange demand; N is the total number of interchanges; (2032) Intermediate indicators of road section demand; statistics of the distribution of the shortest path between the centroids of traffic zones OD The traffic volume of vehicles passing through the road section is recorded as the actual operating traffic volume of the road section; The traffic volume on this section accounts for the highway OD The proportion of traffic flow is the actual operation centrality of the road section; Where: —No. j Demand intermediate indicators for road sections; —After the j The shortest path traffic volume of the road segment; —Total OD of high-speed trips; — Variance of the intermediate index of road segment demand; M - total number of road sections; The evaluation of the network structure also includes network structure matching degree measurement; spatially clustering the interchanges and sections according to the intermediate index of the interchange structure, the intermediate index of the section structure, the intermediate index of the demand structure, and the intermediate index of the section demand as the weights of the spatial clustering of the interchanges and sections, and determining the degree of adaptation of the highway network structure and demand based on the geographical distance; (301) Select the interchanges with the top C% of the interchange intermediate index ranking, take the intermediate index of each interchange as the weight value, perform spatial clustering based on the location information of the interchange, and calculate the location value of the network structure interchange center index and the location value of the interchange demand intermediate index respectively; the offset of the demand interchange center position relative to the structure interchange center position is used as the interchange matching degree measurement value; (302) Select the road sections whose intermediate index is ranked in the top C% and use the intermediate index of each road section as a weight value. Perform spatial clustering based on the location information of the road sections and respectively calculate the tangent value of the intermediate index of the network structure and the tangent value of the intermediate index of the demand road section. The offset of the tangent of the demand road section relative to the structure tangent is used as the measurement value of the road section matching degree. The evaluation network structure also includes the construction of a structural evaluation index system: network structure adaptability evaluation indicators, including accessibility of traffic communities and regional highways, median variance of interchange nodes and road sections, median variance of interchange demand and road section demand, and matching degree of interchange nodes and road sections; By comparing with the set evaluation standards of various indicators, the adaptability of the highway network structure is comprehensively evaluated.

4. A highway network layout structure adaptability evaluation method according to claim 3, characterized in that: The optimization structure strategy includes "addition" and "subtraction" strategies: "Addition" strategy: To address the problem of poor accessibility of individual traffic areas, increase the road network functions of traffic areas with poor accessibility; to address the problem of poor accessibility of regional highways, increase the planning and design of highway function projects in the serial areas; to address the road sections with high concentration, add parallel functional line designs; to address the mismatch between interchanges and road sections, and the deviation between the network layout center and the actual operation center, increase the highway function and node conversion function design in the weak-core area; "Subtraction" strategy: For sections or nodes with high concentration, overall functional design should be done before planning and designing the expressway to avoid introducing new lines into sections with high concentration; For sections or nodes with obviously low concentration, the reduction function is performed by passing through several sections or ramps with the least shortest paths.

5. A highway network layout structure adaptability evaluation system, characterized in that: The evaluation system applies the highway network layout structure adaptability evaluation method described in any one of claims 1 to 4.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the highway network layout structure adaptability evaluation method described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for evaluating the adaptability of the highway network layout structure as described in any one of claims 1 to 4 is implemented.

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