Congestion Situation Research Articles

Real-Time Monitoring of Visitor Carrying Capacity in Crowded Historic Streets Through Digital Technologies

This paper addresses methodological issues related to the identification and monitoring of visitor overcrowding and congestion situations in historic centres. Once the visitor carrying capacity was estimated for public spaces, taking into consideration the standards of quality and comfort for visitor experience and those related to the desired conditions for heritage assets’ conservation, digital real-time monitoring tools were implemented in an experimental urban area in Valencia, Spain, in order to know, through the establishment of proxemic triggers, when the standards were violated (or may soon be violated); then, the carrying capacity was exceeded, and management actions may be required. The results show that these digital monitoring tools are very efficient and accurate in micro-scale public spaces, user-friendly and affordably priced.

Multi-Path Data Transmission System Based on 5G Communication Technology

Due to the current problems of 5G(5th Generation Mobile Communication Technology) networks such as discontinuous coverage, poor coverage performance, and insufficient uplink rate, the real-time transmission performance of 5G networks has been greatly affected, and cannot meet the growing needs of high-speed communication and applications based on the Internet of Things. This paper aims to improve the transmission effect of 5G communication technology by improving the algorithm. By analyzing the problems of existing 5G bandwidth estimation algorithm, this paper proposes a Westwood-based coupling adaptive bandwidth estimation algorithm, and describes the algorithm ideas involved in the algorithm point-by-point. Moreover, this paper uses adaptive bandwidth estimation algorithm to update the slow start threshold in the fast retransmission phase, which makes the congestion window size of path transmission more reasonable. Simulation results show that the congestion control algorithm proposed in this paper improves the accuracy of link bandwidth estimation to a certain extent, improves the link congestion situation and improves the throughput of multipath transmission links. This article can be applied to the algorithm in multipath data transmission to further improve data processing efficiency and processing speed.Therefore, the improved method in this paper can be used in the practice of 5G communication to further improve the efficiency of 5G communication.

Smart port vs. port integration to mitigate congestion: ESG performance and data validation

In practice, ports compete on both service volume and service quality. The latter can be measured by the port congestion situation so the mitigation of congestion helps improve customers’ experience. We observe that smart ports are widely built and many local governments are promoting port integration to ease competition and reduce congestion. One immediate question is: Are the two strategies really effective that further enable the improvement of ESG (Environment, Social and Governance) performance? In this study, by taking the do-nothing strategy as the benchmark, we examine how smart port and port integration strategies work in port congestion reduction and ESG improvement. We reveal that the smart port strategy brings the Matthew effect that the large port obtains a larger market share and the smaller port worries about the win-lose situation. We also reveal that smart port can make each port and the entire port system more congested, resulting in the investment dilemma. Differently, the port integration strategy can effectively reduce congestion but hurt social welfare. We further discuss a mixed strategy where both strategies are implemented. Interestingly, under the mixed strategy, the risk of falling into the investment dilemma can be reduced and social welfare can be increased. We compare the ESG performances under three strategies and highlight that the mixed strategy achieves the highest system profit, the smart port strategy yields the highest social welfare, and the port integration strategy may outperform the other strategies in terms of environmental sustainability.

Efficient message authentication scheme with forward and backward security in Vehicle Cloud Network towards sustainable smart city

The Vehicular Cloud Network (VCN) serves as a crucial component of Intelligent Transportation Systems (ITS), playing an instrumental role in the development of sustainable smart cities. It merges the benefits of both Vehicular Ad Hoc Networks (VANET) and cloud computing. However, VCN faces significant security challenges due to the complexity of communication, the dynamic nature of the environment, and the privacy concerns of data. To address the issues of message security and privacy preservation in VCN, this paper introduces an identity-based key-insulated ring signature (ID-KIRS) scheme for VCN message authentication. Our scheme integrates a secure key update function to address key exposure issues, providing both forward and backward security. The security analysis confirms that our scheme ensures message integrity, unconditional anonymity, and unforgeability. The performance evaluation clearly demonstrates our scheme is efficient, and applicable to vehicle congestion situations, especially car accident scenarios.

Adaptive Speed Control Scheme Based on Congestion Level and Inter-Vehicle Distance

Cellular vehicle-to-everything (C-V2X) enables short-distance communication between vehicles and other users to improve road safety through data sharing. Conventional research on C-V2X typically assumes that vehicles travel at the same speed with a fixed inter-vehicle distance (Disinter). However, this assumption does not reflect the real driving environment or promote road traffic efficiency. Conversely, assigning different speeds to vehicles without a structured approach inevitably increases the collision risk. Therefore, determining appropriate speeds for each vehicle in the C-V2X framework is crucial. To this end, considering the road environment and mobility, this study introduces an adaptive speed mechanism based on the congestion level of a zone and Disinter. First, the given scenario is divided into several zones. Subsequently, based on the congestion level of a zone and the Disinter level, an adaptive speed is defined for each vehicle. This approach ensured that vehicles adopt lower speeds in congested situations to reduce the collision probability and higher speeds in sparse traffic cases to improve traffic efficiency. The performance of the proposed adaptive speed scheme is compared with that of conventional fixed-speed settings. The results show that the adaptive speed control scheme outperforms conventional fixed-speed schemes in terms of the packet reception ratio (PRR) and collision ratio (CR). Specifically, the proposed mechanism can reduce the CR to 0 and ensure that the PRR is higher than 0.98 in low-density scenarios.

Production scale expansion and congestion in two-stage network systems

In managerial practice, decision-makers usually confront the problem of whether an organization (or decision-making unit, DMU) could expand its production to increase output. This paper develops new approaches for production scale expansion analysis and target setting of two-stage network systems based on data envelopment analysis. First, the technique of fixing the strongly efficient frontier is adopted to ensure that the analysis proceeds on the efficient frontier. Second, a model is proposed to obtain the maximum aggregated output for each DMU. A two-step procedure is then developed for production scale expansion analysis to check if expanding a DMU’s production scale (i.e., increasing the inputs and intermediate measures) would increase, maintain, or decrease its outputs (due to congestion). Further, we build a model to set appropriate production scale expansion targets for DMUs capable of increasing outputs through production scale expansion, considering their limited ability to increase inputs. Our approach always proceeds with production scale expansion analysis on the production efficient frontier. It also provides a simple sufficient and necessary condition to judge the congestion situation of a DMU in production scale expansion. Finally, we illustrate the proposed approach using a simple numerical example and a case study of China’s agricultural industry.

Optimal object stitching and video condensation-aided improved YOLOv5-oriented anomaly object detection framework

Recent advances in intelligent surveillance to boost public security have increased interest in anomaly location and identification among computer vision researchers in congested situations. Unrestricted video monitoring is required due to its extensive use in private and public spheres. Particularly, research on finding anomalies in surveillance videos has drawn much interest. Video condensation is an efficient method for quickly scanning and retrieving lengthy surveillance films. Reordering the video events in the spatial or temporal domain seeks to condense large video sequences into their equivalent compact video representation. Additionally, if a delay occurs in anomaly detection, it leads to time consumption for rectifying it. Therefore, the core aim of this task is to reduce the time consumption of detecting the instance of video anomaly detection faster by introducing the optimal object stitching through the deep learning-based video condensation concept. The steps include video condensation and deep learning-based anomaly detection. Initially, the necessary video for anomaly detection is gathered from the datasets. The gathered video is converted into frames and is used for object detection in each frame using Improved YOLOv5 (I-YOLOv5). Then, the optimal frame selection is performed using the hybrid Fitness of Wild Geese and Path Finder (FWGPF) for stitching the detected objects into the selected optimal frames, thus compressing the relevant frames. In the second phase, the condensed (compressed) frames are utilized for determining the anomaly frames with the support of Parameter Tuning in Dilated MobileNet (PTDM), and further, the anomaly objects are detected on the classified condensed frames based on the I-YOLOv5. Here, the tuning of constraint is done in the anomaly detection phase by the same hybrid FWGPF to reduce the time consumption. The experimental analysis of the developed model is performed with baseline algorithms and detection techniques to confirm the developed model’s efficiency.

Potential Spatial Accessibility to Cardiovascular Hospitals in Romania

Cardiovascular diseases (CVDs) represent the leading cause of death globally. Romania recorded the highest mortality rate due to CVDs in the EU in 2022, with 162,984 deaths, while the number of registered patients with CVDs surpassed 4 million. This study aims to measure the population’s potential spatial accessibility to cardiovascular hospitals in Romania, as timely access to such healthcare facilities is crucial to minimise avoidable mortality due to CVDs. Although distance is an essential parameter of spatial accessibility, time-based analysis is more reflective of real-world scenarios due to the unpredictability of travel. The potential spatial accessibility was measured using the Application Program Interface (API) offered through the Google Maps platform and a personal car as the transportation mode. The country’s cardiovascular hospital network comprises 161 units, of which 84 can provide complex care. Because all of them are located in urban areas, three different time slots were considered to distinguish between high and low traffic congestion situations. We created hierarchies of ten-minute and five km intervals for travel time and distance, respectively, to emphasize the population percentages with better or low potential spatial accessibility. Results showed that only 15% of the population can reach the nearest cardiovascular hospital in less than 20 min, and 23% must travel for over 60 min, while 45.7% live farther than 20 km from a cardiovascular hospital. Inhabitants living in remote areas, especially rural ones, are the most vulnerable, having to travel for the longest time and distance. Actions like improving the existing transport infrastructure and upgrading healthcare facilities and equipment are needed to ensure better medical care and an adequate response to population needs. This study can support local authorities in optimising spatial accessibility to cardiovascular care by identifying the most burdened hospitals in the context of low medical specialised staff and large catchment areas.

Implications of Singapore's Congestion Pricing Policy for China's Transportation Governance

With the advent of the post-epidemic era, traffic congestion in urbanized areas around the world is showing a serious trend. China, as the world's largest developing country, faces serious traffic problems during urbanization. In contrast, Singapore, as one of the Asian countries, has successfully implemented a series of traffic management policies, including congestion pricing. The main theme of this paper is to study the inspiration of Singapore's congestion pricing policy on China's transportation governance. This paper mainly analyzes the reasons for the success of Singapore's congestion pricing policy. At the same time, according to the current situation of traffic congestion in China and related research results, it summarizes the three aspects of congestion pricing in China to implement the proposal. First, congestion pricing policies should be implemented in parallel with other means of transportation management. Secondly, the congestion charging policy should be flexibly adjusted in the light of urban conditions. Finally, the congestion charging policy should focus on publicity and recognition by the public. Through this study, it is hoped that it can provide the right direction guidance and reference suggestions when the Chinese government considers the implementation of congestion pricing and similar policies in the future, and it is hoped to come up with more comprehensive and universal reference suggestions if further studies are conducted.

A millimeter-wave MIMO antenna applied to the n260 frequency band

In order to effectively alleviate the current situation of low-frequency spectrum congestion and meet people's demand for high-speed communication, a four element multiple input multiple output (MIMO) millimeter wave antenna was designed for the n260 frequency band (37-40GHz), with an overall size of 10mm12mm 0.508mm. This antenna is based on a dipole broadband millimeter wave unit antenna and adopts a coplanar waveguide feeding method. The four element antenna is placed orthogonally to improve the isolation of the antenna. The operating bandwidth is 36.76-41.73GHz, fully covering the n260 frequency band of 5G, with a relative bandwidth of 12.7%. The simulation results show that the impedance bandwidth of each port of the antenna covers this frequency band, and the isolation degree between each antenna unit port is less than -15dB. The envelope correlation coefficient (ECC) is less than 0.05, and has good radiation characteristics, which meets the performance requirements of MIMO antenna and can ensure the normal operation of the antenna.

A Short-Term Traffic Flow Prediction Method for Airport Group Route Waypoints Based on the Spatiotemporal Features of Traffic Flow

To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study was conducted on a traffic flow prediction method based on deep learning considering spatiotemporal factors. A waypoint network topology graph was constructed, and a neural network model called graph convolution and self-attention-based long short-term memory neural network (GC-SALSTM) was proposed. This model utilized waypoint flow and network efficiency loss rate as input features, with graph convolution extracting spatial features from the waypoint network. Additionally, a long short-term memory network based on a self-attention mechanism was used to extract temporal features, achieving accurate prediction of waypoint traffic. An example analysis was performed on a typical busy sector of airports in the Central and Southern China region. The effectiveness of adding the network efficiency loss rate as an input feature to improve the accuracy of critical waypoint traffic prediction was validated. The performance of the proposed model was compared with various typical prediction models. The results indicated that, with the addition of the network efficiency loss rate, the root mean square error (RMSE) for eight waypoints decreased by more than 10%. Compared to the historical average (HA), autoregressive integrated moving average (ARIMA), support vector regression (SVR), long short-term memory (LSTM), and graph convolution network and long short-term memory network (GCN-LSTM) models, the RMSE of the proposed model decreased by 11.78%, 5.55%, 0.29%, 2.53%, and 1.09%, respectively. This suggests that the adopted network efficiency loss rate indicator effectively enhances prediction accuracy, and the constructed model exhibits superior predictive performance in short-term waypoint traffic forecasting compared to other prediction models. It contributes to optimizing flight paths and high-altitude air routes, minimizing flight delays and airborne congestion to the greatest extent, thus enhancing the overall efficiency of the entire aviation system.

Genetic Programming for Estimating Passenger Car Equivalent in Unsignalized Intersections

The study concentrates on two different Genetic Programming approaches for determining Passenger Car Equivalent(PCE) values and observing the impact on capacity estimation at urban unsignalized intersections. Considering heterogeneoustraffic conditions, a new PCE value is introduced to encompass sustainable modes of public transit vehicles, specifically Slow-moving three-wheelers (SM3W), commonly known as E-Rickshaws. Since PCE value is considered an important parameter forcapacity calculations, the present study considered 14 unsignalized intersections located in Ranchi city of India. An automaticplate recognition system is employed to have the count of vehicular traffic. The methodologies include Age layered populationstructure genetic programming (ALPSGP), and the Offspring selection genetic programming (OSGP) approach that incorporatesstatic and dynamic variables. Based on the significance test and ranking of the Genetic programming (GP) models, the OSGPmodel is recommended as the most appropriate model for heterogeneous traffic. Sensitivity analysis reported that laggingheadway (����) is the most contributing factor in PCE estimation. The PCE value of SM3W is found to be 0.81 and that could beincorporated as a new classification of vehicles in Indo-HCM. It is observed that evaluated capacity based on OSGP’s PCEvalues performed admirably in both normal and congested traffic situations.

A hybrid virtual–real traffic simulation approach to reproducing the spatiotemporal distribution of bridge loads

AbstractCurrent traffic simulation approaches analyze vehicle loads and load effects from a statistical perspective; however, they fail to reproduce the spatiotemporal distribution of bridge loads and resultant load effects at every moment, hindering real‐time bridge health management. This paper proposes a two‐step hybrid virtual–real traffic simulation (HvrTS) approach to reproduce the spatiotemporal distribution of bridge loads. Vehicle load sequences are first identified using computer vision based on traffic video from two surveillance cameras installed along the bridge. Next, traffic microsimulation is optimized with the identified vehicle load sequences from the two cameras serving as the known input and validated output. Using a cable‐stayed bridge under free‐flowing traffic, the HvrTS approach achieved a weighted mean square matching error of ≤0.3 m for the vehicle longitudinal location and a matching error of ≤7% for the vehicle lane position, whereas with congested traffic, the matching errors were much higher due to the inherent complexities and challenges associated with reproducing vehicle behavior in heavily congested situations. The traffic load effects calculated via HvrTS presented excellent spatiotemporal matching with those measured by a structural health monitoring system, especially in free‐flow traffic conditions. Applications on a continuous rigid frame girder bridge further validate these findings. Hence, the proposed HvrTS approach can overcome the challenge of spatiotemporal matching between vehicle loads and load effects in field monitoring.

ЗАКОНОМЕРНОСТИ ПОКАЗАТЕЛЯ ТРАНСПОРТНОГО ЗАТОРА НА НЕКОТОРЫХ ПЕРЕСЕЧЕНИЯХ УЛИЧНО-ДОРОЖНОЙ СЕТИ

The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban roads, which will allow us to develop scientifically based recommendations for predicting congestion situations, substantiating, and making optimal decisions on measures to promptly eliminate traffic congestion. The object of study is the traffic flow at three types of intersections of the Perm city road network, equipped with a photo and video recording software and hardware complex. The subject of the study is the regularities of the evolution of the listed deterministic indicators of traffic flows, which can be used for operational forecasting of the formation, development, and elimination of traffic congestion. The theoretical and methodological approach is based on the methods of mathematical statistics used to process the results of observations of traffic flows at different types of intersections using a «sliding window», calculating the average daily value and standard deviation. The initial data were obtained with the help of hardware and software complexes for fixing violations of traffic rules installed on the street and road network of the Perm city. As a result of the study, the rational parameters of the «sliding window» were determined, ensuring the structuring of the traffic congestion indicator; the facts of the congestion situations formation were revealed; the features of the congestion evolution and the presence of problematic traffic directions for which it is advisable to change the traffic light regulation mode were determined. The theoretical and practical significance of the work consists in checking the operability of the proposed indicator and criterion of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, adjusting the operating modes of traffic lights, etc. It is also possible to use the proposed traffic congestion indicator to assess the effectiveness of traffic light regulation on the Perm city road network. The direction of further research is to study the patterns of traffic congestion at intersections of the urban road network, of various types that are not included in this study.

The Impact of Connected and Autonomous Vehicle Platoon’s Length on Expressway Traffic Flow Characteristics Based on Symmetry Lane Changing Rules

This study mainly investigates the maximum length of CAV (Connected and Autonomous Vehicle) platoons in a heterogeneous traffic flow environment. By employing MATLAB to simulate the heterogeneous traffic flow on expressways, this study focuses on the maximum platoon length of CAV platoons and explores their impact on the traffic flow characteristics on expressways. Firstly, based on four different car-following modes of heterogeneous traffic flow, F-STCA (Flexible–Symmetric Two-Lane Cellular Automata Model) and the symmetric lane-changing strategy, the study refines and improves the construction of the NaSch (Nagel and Schreckenberg) model introduced into the Gipps safety distance formula. The whole improvement process is based on the acceleration decay characteristics of vehicles on expressway. Secondly, the congestion situations under different maximum platoon lengths are compared using fundamental heat maps of the simulation data. The evolution of the fundamental diagram with changes in maximum platoon length is studied to investigate the impact and magnitude of maximum platoon lengths on the road capacity under different CAV permeabilities. Finally, the study explores the stability and safety of heterogeneous traffic flow involving CAV platoons using SD (Standard Deviation) and TERCRI (Time-Exposed Rear-End Collision Risk Index). The results show that when the CAV’s permeability does not reach a high level on heavily trafficked sections of the expressway, considering the overall average speed, the maximum platoon length should not be set too long and should be around five vehicles. This restriction does not apply when the CAV permeability approaches 100%.

Analysis of Traffic Characteristics in Beijing --Based on the Traffic Performance Index

This study aims to deal with the increasingly serious urban traffic congestion problem, taking Beijing as a case study. With the increase in population, traffic congestion has become a serious problem affecting peoples life quality and social and economic development. This study uses the time series analysis and uses the ARIMA (1,0,0) (0,1,1)12 model to forecast the traffic performance index (TPI) data of the past ten years, and deeply analyzes the traffic congestion situation of the next twelve months. The results show that this model can capture the seasonal trend of traffic congestion well, and provide strong decision support for traffic management departments. Through the interpretation and analysis of the forecast, this study gives a series of traffic management suggestions for different months to achieve the alleviation and optimization of urban traffic congestion. In conclusion, this study provides a useful reference for urban traffic management and planning and contributes to the construction of a more efficient, convenient, and sustainable urban transportation system.

Study on flying car transportation system

With the rapid growth of population in large cities, traditional transportation modes like buses, private cars, and subways have formed a more serious traffic congestion or crowded situation. In order to solve this problem, engineers and researchers start to shift the research on the future development of transportation systems to the near-ground space (NGS). The flying car transportation system (FCTS) has become one of the major research projects. The concept of FCTS introduces a new dimension to transportation, utilizing unoccupied near-ground spaces to redefine the way both individuals and goods move within cities. FCTS, using flying cars as the main transportation means, has good development prospects. This article analyzes various aspects of FCTS in detail. The design of FCTS is introduced. The related technologies are summarized. The challenges of the future development of FCTS are also discussed. This article may offer a reference for the development of FCTS.

Review on the Development of Left Turn Crossing Theory of Non-Motor Vehicles

Non-motor vehicles are an important part of urban road traffic system, which plays an important role in the daily travel of urban residents. In recent years, the congestion of urban road traffic system has become more and more serious. In order to alleviate the congestion situation, on the one hand, the traffic management department reduces the road congestion by limiting the number of motor vehicles; on the other hand, the government vigorously advocates public transportation and green and low-carbon travel to adjust the travel mode structure. This paper systematically combs, summarizes and summarizes the views of domestic and foreign scholars from two aspects of the mode and theoretical development of non-motor vehicles turning left across the street. It is found that the left-turn crossing behavior of non-motor vehicles is from simple to comprehensive, from immature to gradually mature. Finally, the research on the development of non-motor vehicle holiday behavior is summarized and prospected.

Analysis of Automated Emergency Braking System to Investigate Forward Collision Condition Using Scenario-Based Virtual Assessment

In the recent trend of automotive technologies, active safety systems for vehicles have become one of the key elements to reduce road traffic conditions. Automated vehicles are known as one of the active safety systems to minimize road traffic congestion and unwanted road hazardous situations. Generally, automated vehicles are designed using advanced driving assistance system (ADAS) technology to enhance the safety capability of the vehicles. Moreover, automated vehicles are designed to adopt multiple scenarios with different types of traffic situations. Generally, the performance of automated vehicles is evaluated to adapt with various road conditions and different type of traffic conditions, autonomously. Nonetheless, most of the safety testing was conducted in a controlled environment and with less traffic conditions. Moreover, this technology is tested in developed countries and mostly evaluated for highway driving scenarios, with less pedestrians and motorist’s road users. On the other hand, in developing countries such as Malaysia, most of the automotive researchers have initiated research related to automated vehicle based on controlled environment only. One of the primary focuses for the current automotive researchers is to reduce road accidents due to frontal collision. Thus, automated emergency braking systems have been heavily investigated by most developers to minimize road accidents. Most of the researchers analyze the system in terms of theoretical based simulation and tested using actual vehicle for physical testing. However, this type of testing is not sufficient to optimize the performance of automatedemergency braking systems for developing countries. Therefore, this study focuses on scenario-based virtual assessment to evaluate the capability of autonomous vehicles using automated emergency braking system without causing road casualties with the distance range is 4.5m to 0.5m depending on vehicle speed.

Assessing urban pluvial waterlogging resilience based on sewer congestion risk and climate change impacts

Urban waterlogging is a critical issue in urban governance, as without proper preventive measures, stagnant water can lead to damage or even casualties. Identifying waterlogging risk points is often desired in urban waterlogging management. Evaluation strategies should be tailored due to the dynamic features of climate warming and high uncertainty in rainfall patterns. An urban pluvial waterlogging resilience (UPWR) analysis framework is proposed as the basis and the tool for dynamically evaluating the spatial distribution of urban waterlogging resilience. UPWR combines hydrological modelling with drainage capacity calculation, extending the original urban waterlogging analysis into a spatial–temporal resilience analysis paradigm for urban waterlogging management in a future climate. An area in Wuhan city, which has suffered from severe waterlogging disaster events for years, was selected for a case study to test the effectiveness and applicability of the proposed approach. This study found that (1) as the drainage network congestion situation intensifies, the UPWR grade decreases in 14% of the study areas; (2) from 2030 to 2100, the UPWR in Wuhan shows a worsening trend under each Representative Concentration Pathway (RCP), and the UPWR under the RCP45 scenario is the worst; and (3) the analysis results can be used to predict future UPWR changes and determine in advance which areas require special maintenance. The novelty of this research lies in the following: (a) the two levels of precipitation and drainage are combined to construct an UPWR assessment framework, providing a quantitative spatial distribution that lays the foundation for exploring urban waterlogging management solutions; and (b) consideration is given to the dynamic change in climate and urban resistance to waterlogging when predicting the future UPWR via a continuous time series, which can provide a basis for urban waterlogging control planning.