Search

With the development of aviation industry, a series of problems have appeared in aviation and airspace, among which the most prominent problem is the congestion of aviation and airspace. Airspace congestion has become a major problem in the development of civil aviation in China. Especially in the central and eastern regions of China, airspace congestion is becoming more and more serious. To better solve the problem of airspace congestion, rough set theory and the Fuzzy C-means (FCM) model are first analyzed. By analyzing the temporal and spatial characteristics of traffic congestion in the control sector, a multisector traffic congestion identification model is established based on radar track data. Four multisector congestion characteristics including equivalent traffic volume, proximity, saturation, and traffic density are established. FCM and rough set theory are used to classify and identify sector congestion. Finally, the model based on FCM-rough set theory is compared with other methods based on the data of the regional control sector in northwest China. The experimental results show that the congestion recognition rate of the model is 92.6%, 93.5%, and 94.2%, and the congestion misjudgment rate is 1.5%, 1.2%, and 1.3%, respectively. Hence, the multisector congestion recognition model has a high recognition rate and a low misjudgment rate, and the overall discrimination result is relatively stable. By comparing the proposed method with other methods, it is concluded that the recognition accuracy of the model based on FCM theory is superior to other methods. In summary, the congestion situation of the sector is affected by a variety of macro- and micro-characteristics of the sector, and the congestion identification model is feasible and efficient. Multisector traffic congestion identification has certain application value for airspace planning, air traffic control-assisted decision making, and air traffic flow management. This work can optimize the aviation and airspace management system and provide relevant suggestions for the study of aviation and airspace congestion. [ABSTRACT FROM AUTHOR]

A lattice hydrodynamic traffic model considering the average optimal flow of multiple grids downstream as a feedback control is proposed. The energy dissipation and fuel consumption are investigated under the feedback control based on the lattice hydrodynamic traffic model. Through linear stability analysis, the stability condition of the model is obtained. The mKdV equation and its kink-antikink density wave solution are derived by using the reduced perturbation method of nonlinear analysis. The variation trends of density wave, energy dissipation, and fuel consumption under traffic control are studied by numerical simulations. The research shows that exerting the feedback control can effectively suppress traffic congestion and improve the stability of traffic system. Meanwhile, it can also reduce the energy dissipation and fuel consumption of traffic system. [ABSTRACT FROM AUTHOR]

Three of the most important objectives of the Federal Road Police (Patrol) when managing the traffic on federal roads in Brazil are to ensure that there is an efficient movement of traffic under stable conditions and minimal traffic congestion problems that the federal highways are safe and that accidents do not occur. Therefore, multiple matters are relevant for road safety and user security, such as prompt maintenance of these highways, regular monitoring of their state of conservation and their characteristics; controlling the traffic; and preventing and combatting criminal activities on the highways. However, considering the vast network and different conditions of roads, the different types of traffic accidents and their consequences, and different levels of violence on federal roads, it is essential that these roads undergo regular maintenance and regular inspections, are constantly patrolled, and are subject to continuous improvements. Therefore, defining the prioritization and criticality of roads takes on the characteristics of a multicriteria decision, given the multidimensional aspects of the risks inherent in them. Thus, this paper presents a multicriteria decision model for prioritizing road sections, based on their criticality and the risks that users face. The model was applied using the FITradeoff method, due to its flexibility and due to it requiring less cognitive effort from the decision-maker with regard to providing information regarding his/her preferences. A case study was undertaken on a set of the federal roads of the state of Pernambuco (Brazil), covering 22 different sections with different characteristics. As a result, it was possible to rank and identify the most critical sections of a highway. The use of FITradeoff gave support to decision-making on ordering the sections and also let a general analysis of the data be undertaken. [ABSTRACT FROM AUTHOR]

Due to increasing traffic demand, many metropolitan areas are experiencing extensive traffic congestion, which demands for efficient traffic signal timing and optimization. However, conventional efficiency measure-based signal optimization cannot handle the ubiquitous uncertainty in the road networks, demanding for the incorporation of reliability measures into signal optimization, which is still in its early stage. Therefore, targeting this issue, based on the recent studies on recognizing travel time reliability (TRR) as an important reliability measure of road networks, a travel time reliability-based urban road traffic network signal timing optimization model is proposed in this paper, with the objective function to optimize a TTR measure, i.e., buffer time index. The proposed optimization model is solved using the heuristic particle swarm optimization approach. A case study is conducted using microscopic traffic simulation for a road network in the City of Nanjing, China. Results demonstrate that the proposed optimization model can improve travel time reliability of the road traffic network and the efficiency of the road traffic network as well. Future studies are recommended to expand the integration of travel time reliability into traffic signal timing optimization. [ABSTRACT FROM AUTHOR]

With the rapid growth of car ownership, traffic congestion has become one of the most serious social problems. For us, accurate real-time travel time predictions are especially important for easing traffic congestion, enabling traffic control and management, and traffic guidance. In this paper, we propose a method to predict urban road travel time by combining XGBoost and LightGBM machine learning models. In order to obtain a relatively complete data set, we mine the GPS data of Beijing and combine them with the weather feature to consider the obtained 14 features as candidate features. By processing and analyzing the data set, we discussed in detail the correlation between each feature and the travel time and the importance of each feature in the model prediction results. Finally, the 10 important features screened by the LightGBM and XGBoost models were used as key features. We use the full feature set and the key feature set as input to the model to explore the effect of different feature combinations on the prediction accuracy of the model and then compare the prediction results of the proposed fusion model with a single model. The results show that the proposed fusion model has great advantages to urban travel time prediction. [ABSTRACT FROM AUTHOR]

Recent years have witnessed the rapid development of intelligent transportation system around the world, which helps to relieve urban traffic congestion problems. For instance, many mega-cities in China have devoted a large amount of money and resources to the development of intelligent transportation system. This poses an intriguing and important issue: how to measure and quantify the contribution of intelligent transportation system to the urban city, which is still a puzzle. This paper proposes a matching difference-in-difference model to calculate the contribution rate of intelligent transportation system on traffic smoothness. Within the model, the main effect indicators of traffic smoothness are first identified, and then the evaluation index system is built, and finally the ideas of the matching pool are introduced. The proposed model is illustrated in Guangzhou, China (capital city of Guangdong province). The results show that introduction of ITS contributes 9.25% to the improvement of traffic smooth in Guangzhou. Also, the research explains the working mechanism of how ITS improves urban traffic smooth. Eventually, some strategy recommendations are put forward to improve urban traffic smooth. [ABSTRACT FROM AUTHOR]

In the process of national economic mobilization, the logistics system usually suffers from negative impact and/or threats of such emergency events as wars and accidents, which implies that adaptability of the logistics system directly determines realization of economic mobilization. And where the real-time rescue operation is concerned, heavy traffic congestion is likely to cause a great loss of or damage to human beings and their properties. To deal with this situation, this article constructs a blocking-resistance optimum model and an optimum restructuring model based on blocking flow theories, of which both are illustrated by numerical cases and compared in characteristics and application. The design of these two models is expected to eliminate or alleviate the congestion situation occurring in the logistics system, thus effectively enhancing its adaptability in the national economic mobilization process. [ABSTRACT FROM AUTHOR]

Rear-end collision often leads to serious casualties and traffic congestion. The consequences are even worse for multiple-vehicle collision. Many previous works focused on collision warning and avoidance strategies of two consecutive vehicles based on onboard sensor detection only. This paper proposes a centralized control strategy for multiple vehicles to minimize the impact of multiplevehicle collision based on vehicle-to-vehicle communication technique. The system is defined as a coupled group of vehicles with wireless communication capability and short following distances. The safety relationship can be represented as lower bound limit on deceleration of the first vehicle and upper bound on maximum deceleration of the last vehicle. The objective is to determine the desired deceleration for each vehicle such that the total impact energy is minimized at each time step. The impact energy is defined as the relative kinetic energy between a consecutive pair of vehicles (approaching only). Model predictive control (MPC) framework is used to formulate the problem to be constrained quadratic programming. Simulations show its effectiveness on collision mitigation. The developed algorithm has the potential to be used for progressive market penetration of connected vehicles in practice. [ABSTRACT FROM AUTHOR]

Proactive traffic control based on macroscopic traffic flow model is an innovative approach to active traffic management. An online, model predictive control (MPC) based active traffic control algorithm, DynaTAM, is proposed to implement integrated control through ramp metering (RM) and variable speed limit (VSL). DynaTAM predicts traffic states to anticipate incoming traffic congestion and to provide control plan recommendations for optimizing the network traffic conditions. However, as with other sophisticated prediction-based control algorithms, a system fine-tuning procedure is required for DynaTAM. In this study, two aspects will be addressed to further improve system performance. First, the control algorithm is evaluated to find the correlations between the prediction horizon length and the controlled system performance to suggest the most efficient prediction horizon length for the control algorithm. Second, safety considerations are quantitatively incorporated into the control algorithm. The control algorithm optimizes the traffic network targeting the cost reductions achieved by both improved mobility and reduced crash risk. A field-data-based simulation study is conducted to evaluate the system performance within various parameters and to determine the most suitable algorithm parameters. Optimized by the refined DynaTAM algorithm, the targeted area shows significant improvements in terms of both traffic safety and mobility. [ABSTRACT FROM AUTHOR]

Theprecise identification and quick dissipation of spillovers are critically important in a traffic control system, especiallywhen heavy congestion occurs. This paper first presents a calculation method for the occupancy per cycle under different traffic conditions and identifies the threshold of occupancy that characterizes the formation of spillovers. Then, capacity adjustments are determined for the incoming and outgoing streams of bottleneck links, with the aim of dissipating the queue to a permissible length within a given period of time, and optimization schemes are defined to calculate splits for the upstream and downstream intersections. Finally, taking average vehicular delay, outputs per cycle, and maximum queue length on the bottleneck link as the evaluation indices, the method of dissipating spillovers proposed in this paper is evaluated using a VISSIM simulation. The results show that the maximum queue length on the bottleneck link and the average vehicular delay at the upstream and downstream intersections decrease significantly under the new signal control plan; meanwhile, the new control schemes have little influence on the outputs of the two intersections per cycle. [ABSTRACT FROM AUTHOR]

The expressways in Beijing are confronted with more serious traffic congestions. Based on the survey data obtained fromthe typical sections at the expressways, the time dependent characteristics of traffic flow parameters were analyzed in detail and the data gap was found in this paper. The Fast Fourier Transform (FFT) method is proposed to transfer the data of traffic flow parameters for describing the fluctuation characteristics of traffic flow. Two methods of identification, the graph method and the control line method, were proposed as to the change time of traffic bottleneck forming and dissipating. The findings in this paper have already been applied in traffic management and ramp control at the expressways in Beijing. [ABSTRACT FROM AUTHOR]

Advances in mobility are clearly illustrated by the rapid development of urbanization and motorization in developing countries. Following the dramatic incensement of traffic demand, the parking problem has been becoming much more seriously important in many metropolises. With the aim of seeking solutions as to how the parking system could operate more efficiently by using new technologies and new methodologies, this paper discusses the application of geographic information system into the parking planning and management for traffic operation effectiveness in metropolis. The concentration of this paper includes the characteristics of parking demand and the causations of parking problems, especially the basic parking principle and strategies for solving parking problems from the perspective of geographic information system are discussed in enough detail in this paper. [ABSTRACT FROM AUTHOR]

Operators of parking guidance and information systems PGIS often encounter difficulty in determining when and how to provide reliable car park availability information to drivers. Reliability has become a key factor to ensure the benefits of urban PGIS. The present paper is the first to define the guiding parking reliability of urban parking variable message signs (VMSs). By analyzing the parking choice under guiding and optional parking lots, a guiding parking reliability model was constructed. A mathematical program was formulated to determine the guiding parking reliability of VMS. The procedures were applied to a numerical example, and the factors that affect guiding reliability were analyzed. The quantitative changes of the parking berths and the display conditions of VMS were found to be the most important factors influencing guiding reliability. The parking guiding VMS achieved the best benefit when the parking supply was close to or was less than the demand. The combination of a guiding parking reliability model and parking choice behavior offers potential for PGIS operators to reduce traffic congestion in central city areas. [ABSTRACT FROM AUTHOR]