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Aiming at the problem of traffic congestion in freeway on-ramp entrance under the condition of high traffic flow, this paper proposed a cooperative merging control solution of connected and automated vehicles（CAVs） at freeway on-ramp entrance, which divided the problem into two parts: multi-vehicle sequential decision making and vehicle motion planning. Multi-vehicle sequential decision making played an important role in traffic efficiency, so this paper proposed a multi-vehicle sequential decision algorithm based on the state evaluation model（SEM）, the algorithm first established the state space and initialization, considered the traffic efficiency and the vehicle delay design state evaluation function, select the optimal state through the state transition relationship, and finally got the optimal passing order by backtracking. According to the state of the vehicles and the time to reach the conflict point, the controller deduced the analytic solution of the longitudinal velocity of each vehicle in real time to realize the vehicle motion planning. Simulation and experiment results show that the solution can not only meet the real-time requirements of the traffic system, but also effectively improve the efficiency of freeway on-ramp entrance, shorten vehicle delay and reduce fuel consumption. [ABSTRACT FROM AUTHOR]

VANET plays an increasingly important role in life. It can effectively prevent traffic congestion and reduce traffic accidents. However, in VANET, there are always illegal vehicles trying to access the VANET and publishing false information. In addition, most of the existing schemes have the problem of low computational efficiency. Aiming at the above problems, this paper proposed the conditional privacy-preserving authentication scheme based on fog computing and multi-TA. Under the condition of protecting the identity of vehicle users, it realized the identity authentication among vehicle, fog node and TA, and the real identity of vehicle users could be restored in the vehicle tracking stage, thus realizing conditional privacy protection. The use of fog computing reduced the calculation and communication overhead of the scheme, and the use of multi TA model also solved the problem of single TA single point fault. The results of security and performance analysis show that the scheme is safe and efficient. Finally, it summarized the current scheme and prospected the future research. [ABSTRACT FROM AUTHOR]

Objectives: With the rapid development of urbanization, traffic congestion has become a common problem faced by big cities all over the world. Scientific analysis of road network carrying capacity and traffic impact factors is a prerequisite for optimizing the spatial allocation of road traffic factors. How to give full play to the advantages of spatial information technology, efficiently and accurately analyze the balance of regional road network carrying capacity, and find the spatial change relationship between traffic state and influencing factors, is very important for alleviating urban traffic congestion. Methods: The road grid geographically weighted regression (RG-GWR) analysis method is proposed. The carrying capacity ratio of regional road network is calculated by the nine-grids model composed of two kinds of nested grids. By calculating the carrying capacity ratio of the central cell of the nine grids and analyzing the ratio according to the law of conservation of flow, the unbalanced area of road network configuration is identified. By analyzing the regression relationship between the grid cell traffic situation and the influencing factors, the traffic spacetime operation situation is obtained. Taking Chengdu city as an example, three grid models with different sizes are constructed. Results: The results match the actual road conditions of AMap by 62.5% and 87.5%, respectively. By further analyzing the traffic influencing factors, the fitting degree of RG-GWR model in traffic situation of different periods could be more than 80%. Conclusions: The grid model is an efficient and feasible method to analyze the road network carrying capacity and traffic impact factors from the perspective of space and has a broad prospect to serve the intelligent platform and intelligent transportation. [ABSTRACT FROM AUTHOR]

Ride-sharing is an effective way to solve traffic congestion. However, passengers’ lack of trust in ride-sharing behavior is a problem that affects the development of ride-sharing. To solve this problem, by introducing trust weight and user preferences to measure by the trust level, taking the shortest total driving distance of the vehicle and the highest total trust value as the objective function, and considering the vehicle loading capacity constraints, vehicle travel distance constraints, passenger demand response constraints and vehicle station service constraints, this paper constructed a ride-sharing model considering passenger trust degree, and used an improved genetic algorithm to solve the model. Finally, this paper used the data of operating vehicles in the surrounding areas of Beijing Xinfa to verify the algorithm. The results show that the model can effectively reduce the total vehicle distance while ensuring a high level of passenger ride-sharing trust. The distance cost is 14.8% less than the model only considering distance optimization, and the trust level is 3.3 times higher. This paper verified the effectiveness of the model and the algorithm through the comparative analysis of the optimization results. [ABSTRACT FROM AUTHOR]

At present, the congestion of highways in China is severe. Traffic flow prediction plays an important role in the intelligent transportation system. If it can achieve high-precision prediction, it will be able to efficiently manage traffic and alleviate congestion. To solve this issue, this paper proposed a multi-channel traffic flow prediction method (MCST-Transformer)considering spatiotemporal correlation. Firstly, it used Transformer to extract the internal laws of different data, and then introduced a spatial correlation module to mine the association features of different data. Finally, it integrated global information through channel attention. Using the data of Guangdong province highway, the proposed method realized the traffic flow prediction of 92 toll stations within two hours with high precision. The results show that MCST-Transformer is superior to traditional machine learning methods and time series models based on the attention mechanism. Under the prediction horizon of 120 min, MAPE decreases by 5. 1 % compared with Bayesian regression. Compared with deep learning algorithms like Seq2Seq-Att and Seq2Seq, the overall MAPE of the proposed method can also be reduced by 0. 5%. It indicates that the multi-channel approach can distinguish the characteristics of different data, so as to acquire better performance. [ABSTRACT FROM AUTHOR]

At present, the problem of airspace resource shortage caused by the surge of air traffic is becoming more and more prominent. In order to alleviate this situation, the study of aircraft rerouting based on the flow management was carried out. Firstly, the airspace environment was discretized by rasterization, and the airspace was divided into different types of raster regions according to the congestion degree of waypoint flow. Secondly, it was used to model by improving the reward function of Markov decision process in reinforcement learning. Based on the ε-greedy strategy, Q-Learning algorithm was used for iterative solution, and the corresponding parameter value was explored and compared to improve the applicability of the results. Finally, the optimal path and the corresponding performance indexes under different parameter assignments were calculated through simulation. The results show that the model and algorithm can be used to search for an appropriate rerouting path for the congested airspace in a certain period of time, so that the aircraft can avoid the congested waypoints, shorten the delay time in the air, and effectively improve the status of airspace congestion. [ABSTRACT FROM AUTHOR]

Aiming at the problem that multi lane unsignalized intersections are prone to congestion at high traffic flow, this paper proposes a solution suitable for connected automated vehicle(CAV) at intersections, which decouples the problem into two problems: sequential decision-making and distributed control. Vehicle scheduling is the key point in the scheme, which has a great impact on traffic efficiency, and the complexity of the problem is exponential. this paper proposes a decision method named queue evaluation spanning tree(QEST) to solve this problem based on queue evaluation model, and establishes a cost function based on traffic efficiency and vehicle delay, so as to evaluate the queue, and continuously select the best queue, optimize the traffic sequence of vehicles at intersections and effectively improve the traffic efficiency. For the second problem, this paper proposes a distributed control framework to make vehicles pass through intersections in a predetermined order. The results show that the scheme can effectively improve the traffic efficiency and reduce vehicle delay and energy consumption at intersections with medium and high traffic flow. [ABSTRACT FROM AUTHOR]

To solve the problem of congestion in the interweaving area of Nanjing inner ring expressway during rush hour, an non-interrupt weaving area control strategy was proposed based on five-lane weaving area with 2 ramps for vehicles driving in 4.5 lanes on average. For the priority to improve the main road capacity and increase the speed of weaving vehicles, the traffic diversion of weaving and non-weaving traffic flow in advance made the vehicles run orderly, and the number of available lanes for weaving traffic flow was increased by one-way lane changing on the ramp. The capacity and the influence factors of service level in weaving area were analyzed, and three methods of speeding up, access control and sign-and-marks control were introduced for alleviating traffic congestion. The non-interrupt weaving area control strategy of vehicles driving in 4.5 lanes on average was proposed, and the simulation models were built to compare the average speeds of main road and side road in different schemes by VISSIM. The results show that under the conditions of heavy traffic and small interweave ratio in the weaving area, compared with no control measures, scheme B 4.5 lane weaving with one-way lane changing on the auxiliary line has significant effect in optimizing the main line driving speed with average increasing of more than 8%, and scheme D of one-way lane changing on the auxiliary line with separation of flow lines has significant effect in increasing the auxiliary line driving speed with average increasing of 6%-24%. [ABSTRACT FROM AUTHOR]

To solve the problem of congestion in the interweaving area of Nanjing inner ring expressway during rush hour, an non-interrupt weaving area control strategy was proposed based on five-lane weaving area with 2 ramps for vehicles driving in 4.5 lanes on average. For the priority to improve the main road capacity and increase the speed of weaving vehicles, the traffic diversion of weaving and non-weaving traffic flow in advance made the vehicles run orderly, and the number of available lanes for weaving traffic flow was increased by one-way lane changing on the ramp. The capacity and the influence factors of service level in weaving area were analyzed, and three methods of speeding up, access control and sign-and-marks control were introduced for alleviating traffic congestion. The non-interrupt weaving area control strategy of vehicles driving in 4.5 lanes on average was proposed, and the simulation models were built to compare the average speeds of main road and side road in different schemes by VISSIM. The results show that under the conditions of heavy traffic and small interweave ratio in the weaving area, compared with no control measures, scheme B 4.5 lane weaving with one-way lane changing on the auxiliary line has significant effect in optimizing the main line driving speed with average increasing of more than 8%, and scheme D of one-way lane changing on the auxiliary line with separation of flow lines has significant effect in increasing the auxiliary line driving speed with average increasing of 6%-24%. [ABSTRACT FROM AUTHOR]

The new intelligent transportation system plays an important role in improving traffic flow, optimizing fuel efficiency, reducing delays and improving the overall driving experience. Nowadays, traffic congestion is a very serious problem that disturbs human beings, especially the intersection with dense traffic in some cities may be more serious. Improves the reward mechanism of signal control system, the reward mechanism of all intersections to each intersection sharing a unique reward, and through the combination of intensive sampling strategy and multi-intersection signal control, using the popular deep reinforcement learning to solve the traffic signal timing problem. Simulation experiments are based on the current international mainstream traffic simulation software (SUMO). The experimental results show that the improved deep reinforcement learning multi-junction signal control method has better control effect than the traditional reinforcement learning method. [ABSTRACT FROM AUTHOR]

In order to solve problems such as traffic congestion, traffic safety and environmental pollution of urban roads, a variety of technologies including path planning algorithm and vehicle self-organizing network have gradually become important research directions in the field of intelligent transportation and attracted a lot of attention. In recent years, the application and popularization of intelligent transportation provide rich and diverse research topics for the research of path planning algorithm, and the research of path planning algorithm also effectively promotes the development of cutting-edge technology of intelligent transportation. By reviewing the research of multiple path planning algorithms, this study summarizes the existing problems in the research of path planning algorithms. On this basis, this study deeply studies and analyzes the advantages and disadvantages of static and dynamic path planning algorithms, and puts forward the future research trend and methods of path planning algorithms in intelligent transportation. [ABSTRACT FROM AUTHOR]

Objectives: Traffic congestion detection is one of the key points and difficulties of urban traffic management. The existing congestion detection methods are based on road sections, which is not conducive to the extraction of spatiotemporal evolution information of congestion. Moreover, most of the detection only involves the degree of congestion but lacks the congestion type identification. With the classification and regression tree (CART) algorithm, this paper proposes a method for the classification and detection of traffic congestion points, which takes the road section point as the detection unit. In the practical application of this method, congestion points and their categories can be detected in real time according to the average running speed on the road section. Methods: Firstly, the road section is divided at a specific interval and mapped to be road section points. According to the abnormal rules and patterns of spatiotemporal road conditions, the spatiotemporal evolution patterns of four congestion types are analyzed with road section points as units. Secondly, the spatial and temporal sequence of road conditions of road section points is extracted on the basis of the road condition detection of road sections, and the spatial and temporal sequence of road conditions is classified and labeled according to different congestion types. Thirdly, four speed indexes are selected to constitute the attribute set of samples, and the speed of each road section point at each period is extracted according to the attribute set, which forms the dataset of decision tree learning. Finally, with the CART algorithm, the optimal model is obtained by the training with cross-validation to achieve the best generalization ability. Results: This paper proposes a classification and detection method of traffic congestion points based on CART. On one hand, congestion point detection is added to refine the basic unit of congestion detection, and on the other hand, congestion point type detection is also involved. Classification and detection of congestion points is helpful to improve the efficiency of traffic management. Conclusions: The proposed method is compared with the support vector machine classification model, and the experimental results show that the method in this paper has higher accuracy, higher recall rate, and better classification and detection timeliness. [ABSTRACT FROM AUTHOR]

Objectives: The signal control with fixed phase duration can not be adjusted adaptively according to the real-time road conditions, the improvement of traffic congestion phenomenon is limited. In order to simulate the phase adaptation of traffic lights according to the real-time road conditions, reasonably configure the phase duration of traffic lights and alleviate the traffic congestion, a closed loop system of traffic lights timing optimization and self feedback adjustment which include vehicles flow video acquisition, flow statistics, timing calculation, timing feedback, phase regulation, flow statistics and timing optimization is constructed. Methods: Firstly, combining virtual simulation and computer vision technology, a road traffic simulation scene built on Webster algorithm is constructed to simulate vehicle starting and stopping, driving and signal lights control based on Unity3D. Secondly, the OpenCV library is used to process the traffic flow video captured by Camera Object in the scene, count the traffic flow, calculate the optimal signal cycle, and determine the traffic phase. Finally, the result of timing calculation is applicable to the simulation scene, and further timing optimization is implemented according to the real-time scene to realize the signal phase adjustment and optimization cycle. Results: Traffic flow generation is built on the number of vehicles arriving at the intersection during peak hours. Vehicles are randomly generated in each direction of intersection every minute, including 15-30 vehicles in congestion direction and 5-15 vehicles in non-congestion direction. The initial setting of intersection signal lights is the traditional fixed timing schema, in which the left turn green light is on for 20 s in the north -south direction, the yellow light is on for 3 s, the straight green light is 30 s, and the red light is on for 56 s. The straight red light is on for 56 s, the left turn green light is on for 20 s in the east-west direction, the yellow light is on for 3 s, and the straight green light is on for 30 s. The average waiting time of intersection vehicles has decreased by 17 s, and the traffic volume has increased by 190 vehicles per hour with real time timing optimization scheme. Conclusions: Simulation experiment of traffic signal timing using Unity3D provides a very effective method for the verification of traffic signal timing algorithm. The closed -loop system of signal lights adaptive timing optimization makes up for the limitations of existing traffic lights timing optimization schemes, and achieves real time timing optimization. Simulation results show that the closed loop feedback of signal lamp adaptive timing optimization can greatly reduce the waiting time of vehicles and effectively alleviate traffic congestion. [ABSTRACT FROM AUTHOR]

Focusing on the problem with traffic congestion under changing environmental conditions, this paper proposed a trajectory reward light (TR-light) model by combining reinforcement learning, neural network, multi-agent and traffic simulation technology to optimize the traffic at multi-intersections. This method had considerable merits in the following aspects. The traffic organization plan was formulated based on traffic lights; multi-agent reinforcement learning was used on traffic light control; regional traffic organization was optimized through the coordination of traffic lights; the agent implemented trajectory reconstruction after the execution of each behavior so as to change the vehicle travel path without changing the OD pair, and to calculate the final reward of the agent according to the plan and reconstructed trajectory. Finally, it conducted a traffic simulation experiment through SUMO. The comparison of traffic indicators verifies that the proposed model improves the smoothness of the road network and the traffic state at the multi-intersections. Experiments show that the model is feasible and effectively mitigates the traffic congestion. [ABSTRACT FROM AUTHOR]

Objectives: As the acceleration of global urbanization, traffic congestion and environmental degradation have emerged in the urban area. Based on the light and statistical data, this paper studied the spatial evolution between urban people and land, and revealed the significance of its coupling and coordination characteristics for the sustainable development of cities. Methods: For primary data, a series of preprocessing are needed to eliminate the problems of supersaturation and discontinuity of inter‑annual data. Based on the lighting threshold, this paper excerpted the built‑up areas of urban agglomeration in Zhejiang Province year by year, compared them with the statistical data, and analyzed the corrected data source relatively. Firstly, based on the order‑scale distribution model of urban order and urban population in Zhejiang Province from 1992 to 2020, we made a dynamic analysis on population aggregation and distribution in its development process. Then, we constructed the population‑land urbanization allometric growth model by using population and light area, as well as judged the spatialization of man‑land relationship in urban development. Finally, according to the lag phenomenon of population growth relative to land development, we proposed an allometric growth model with lag factor, and used the lag term model to judge the characteristics of unequal growth of people and land in different cities. Results: The structural system of urban agglomeration is relatively mature in Zhejiang Province, and the distribution of cities is reasonable. However, the primacy of city is gradually improved, and the population is gradually gathering. The results of allometric growth model show that the man‑land relationship of urban agglomeration in Zhejiang Province is generally low in the eastern coastal cities and high in the western inland cities, and the planning of the four metropolitan areas is reasonable. The improvement of fitting accuracy of the proposed model with lag factor obviously shows that there is lag effect between population urbanization and land urbanization, with an average increase of 6.47% and the highest increase of 12.61%. Among the influencing factors on land urbanization, the dominant factor in Hangzhou is the existing population in urban areas, while the dominant factor in Ningbo is the new population in urban areas. Conclusions: The proposed allometric growth model with lag factor can correct the model errors and improve the fitting accuracy of urban man‑land relationship. It can also effectively evaluate the temporal and spatial evolution characteristics of man‑land relationship in regional system, explore its development and put forward countermeasures. [ABSTRACT FROM AUTHOR]

Objectives: Based on taxi movement trajectories, urban traffic operating conditions can be analyzed. At present, the relevant research mainly focuses on the investigation of traffic origin and destination points and the extraction of traffic hotspots, but seldom analyzes the interaction between traffic hotspots. We focus on exploring the temporal and spatial patterns of urban traffic hotspots, with the purpose of providing a scientific basis for traffic management departments for traffic management in different periods and sections.Methods: We take the main urban city of Nanjing City as the research area, and use taxi GPS data in 2015, 2016, and 2017 for experiments. Firstly, the effective trajectory flow is extracted from the taxi GPS data through the local anomaly test method. Secondly, based on the GeoJSON geocoding to realize map matching, the Pathlet method is used to process the trajectory flow into a sequence which can be optimally solved by dynamic programming. Finally, based on the standard for evaluation of urban traffic operation status, the macroscopic fundamental diagram model is constructed according to the relationship be‑ tween traffic flow, speed and density in the road network, and the evaluation index is established by combining travel time ratio and the delay time ratio.Results: (1) Judging from the average of the traffic operation indicators, the main urban area of Nanjing is the most congested in the morning and evening rush hours, and the traffic is smooth in the early morning hours, and the traffic hotspots are more active on working days than on rest days. (2) Judging from the traffic operation indicators of the nine different nodes, the traffic congestion near the parking lot and office building nodes is relatively increased on weekdays, and the traffic congestion near the nodes of shopping malls and residential quarters is relatively increased on the rest days.(3) Judging from the perspective of spatial distribution of traffic hotspots in five representative periods, traffic hotspots mostly appear near intersections and ramps, and there are more interactions between main roads and express roads, but between townships and village roads and county roads. There is less interaction. (4) Judging from the perspective of the temporal and spatial patterns of traffic hotspots near the school during the morning rush hour, the temporal and spatial interaction characteristics of traffic hotspots are significant in areas with high node coverage, while the spatial distribution characteristics of traffic hotspots change unclearly with time in areas with low node coverage.Conclusions: Urban traffic hotspots show significant differences in time and space distribution characteristics, and their spatiotemporal interactions be‑ come stronger with time and space aggregation, which has a significant positive correlation. [ABSTRACT FROM AUTHOR]

Objectives: Citizen commuting analysis is useful for solving jobs‑housing imbalance and traffic congestion. Mobile trajectory data, strengthening the observation of citizen commuting in data types, data volume, sampling frequency, and information content, is helpful for exploring jobs‑housing patterns and citizen commuting distribution.Methods: We have investigated the research progress of citizen commuting and mobile trajectory analysis, and have worked out relevant concepts, indexes, metrics, models and theoretical methods of commuting activity analysis. The representative results of spatial interaction model, transportation planning model, linear programming model, and micro‑physical model are compared, and the characteristics of their application in the analysis of citizen commuting activities are discussed from a multidisciplinary perspective. Results: Four types of trajectory data characteristics of citizen commuting activities are summarized. From the perspectives of citizen commuting behaviors pattern and its jobs‑housing restrictions, we have proposed the architecture of exploring the relationships between citizen commuting and jobs‑housing from mobile trajectory data. Conclusions: The technology of multidisciplinary development of citizen commuting analysis is addressed, and the comprehensive method of analyzing trajectory big data, multi‑source data fusion, and commuting activity prediction are the focus of future research. [ABSTRACT FROM AUTHOR]

To deal with the low accuracy of existing decision methods of traffic congestion under the condition of the uncertain and incomplete evidences, this paper proposed a weight-optimized neutral network. At first, this paper applied the quadraticform membership function to present the characteristics of evidences. It achieved the evidence contributions by using the information entropy, which could be considered as the weights on input layer in the neutral network. Moreover, the weights on the hidden and output layers were adaptively computed on the basis of initial weight and previous gradient sum. It reduced the accumulated error from the uncertain and incomplete evidences. Finally, the numerical example proved both accuracy and convergence of the proposed method in terms of actual traffic environment. The results indicate that the proposed method can make the stable decision on traffic congestion. [ABSTRACT FROM AUTHOR]

To ease the traffic pressure on the plain urban road net work and reduce t he traffic accident risk an annular radial pattern was applied, with elastic topology network and the topology theory as the reference, in determining the road network path at the same time, the aggregation coefficient of the main road was calculated to complete the study of urban road network on the basic form. On this basis, the actual planning capacity of urban road was calculated according to the construction demand of step-by-step network, and then the planning layout model of urban road network was designed by balancing supply and demand of layout. It was found that after the application of the layout model, the TPI value matching with the trunk road decreased to 0.15, and the traffic flow at the fixed junction per unit time also increased effectively. The results show that compared with the original road network layout model, this model alleviates the traffic congestion pressure of urban road network effectively. [ABSTRACT FROM AUTHOR]

In order to analyze the intersection traffic conditions better and provide data for traffic flow detection and traffic congestion identification, the vehicle queue length of intersection was investigated based on the probability theory.The number of vehicles into/out the intersection and time were used to fit vehicle-time curve. The correction of starting time was established for revising the time from the vehicle driving into the intersection to the vehicle leaving the intersection.The speed-distance model was established to deduce the correction of starting time by analyzing the traffic flow status, and the calculation method of the vehicle queue length was deduced by the differential and integral calculus method.The Hongqi street and Huxi road intersection traffic data in Changchun city were taken as example, and the experiment was carried out to verify the method. The results show that the method can conveniently collect data with simple facility layout, which makes the method easier for large-scale application.The relative errors of E of 14 time points in 16 time points are less than 6% in the queue length, which illuminates that the calculation method is accurate enough for the measurement of vehicle queue length of intersection. [ABSTRACT FROM AUTHOR]

Because of the drawback of existing method, the paper proposed a traffic congestion detection method based on Internet of Vehicles and fuzzy logic. Firstly, this method constructed a neighbor table of vehicle based on the obtained real-time information of neighbor vehicles. Secondly, it created a fuzzy controller according to the speed, traffic density and traffic congestion rating system, and evaluated the local traffic congestion level. Thirdly, it realized the inquiry of traffic congestion status of neighbor vehicles based on real-time communication between neighbor vehicles, and verified the local traffic congestion level based on large sub-sample hypothesis test, then completed the detection of regional traffic congestion level. Finally, it built a simulated test scenario based on Veins platform, then it compared the accuracy of detecting traffic congestion, and calculated the backoff slots and received broadcast packets of vehicle nodes in the simulated test scenario. The results show that the accuracy of traffic congestion detection of the proposed method is increased by 5. 5% and 7 . 5% compared with " no trigger" method and CoTEC method, respectively. The proposed method reduces the network congestion of vehicle communication by 90. 8% compared with CoTEC method, and the communication load of communication nodes significantly decreases when there is no traffic congestion. [ABSTRACT FROM AUTHOR]

The traffic flow fluctuation caused by vehicles following each other is not only easy to cause traffic accidents, but also one of the important reasons for the reduction of road traffic efficiency or traffic congestion. Therefore, in this paper, the transfer function of the control system of the vehicle - following model with stimulus - response is established, and then Laplace transform of the transfer function is applied. It is found that the characteristic equation of the control system is a transcendental equation with driver sensitive parameter dependence. The root distribution state of the characteristic equation is estimated to ensure the stability of the control system by using the zero point theorem, and then the range of the driver sensitivity parameters is obtained. The results of numerical simulation show that the range of driver sensitivity parameters obtained in this paper can not only guarantee the stability of vehicle - following system on the micro level, hut also the stability and rapidity of traffic flow on the macro level, and reduces the traffic flow fluctuation objectively, and improves the traffic efficiency. [ABSTRACT FROM AUTHOR]

With the development of economy and urbanization in China, the issue of traffic congestion is increasingly prominent. Highways as the lifelines between cities are particularly vulnerable during the holidays. In order to manage highways more efficiently and regulate traffic more timely, it is necessary to detect congestion events on highways to realize the supervision of highway traffic. Using recognition data of highway path recognition system, transactions data of toll station, and GPS trajectory data of coach buses, touring buses and dangerous goods transport vehicles, this paper proposes a hierarchical congestion interval detection method which adopts fuzzy comprehensive evaluation algorithm to identify the traffic status of road sections. Taking the Changsha-Zhuzhou-Xiangtan urban agglomeration region of Hunan province as a case study, this paper uses the proposed method to detect and analyze traffic status of the experimental area in two weeks in February, 2018. [ABSTRACT FROM AUTHOR]

In order to optimize the in - road parking layout and improve the utilization rate of parking facilities in the city, so as to improve the city * s static traffic situation and solve the traffic congestion problem, this paper first conducts a data survey on the parking situation in the commercial district of Le Song in Harbin, and obtains the basic data such as the supply of parking spaces on the road, the number of parking during rush hours and the parking characteristic parameters. After finishing, the parking characteristics and sat¬isfaction degree of parking status are analyzed, and the factors that affect the demand and supply of parking spaces are obtained. Then, an in - road parking demand model based on the regional road network capacity, the comprehensive reduction factor of road network us¬age and the proportion of parking behaviors is established. The demand for in - road parking spaces in Harbin * s Le Song commercial district is predicted and corrected. The number of available parking spaces for two different parking modes, oblique parking and vertical parking, is calculated. The analysis results show that it is more reasonable to set up parking spaces at an angle of 60 degrees. At last, it puts forward various schemes to adjust the parking price system on the road, feasible suggestions to improve parking utilization rate and management methods. The research results provide a reliable theoretical basis for the formulation of on - road parking planning schemes and management strategies [ABSTRACT FROM AUTHOR]

For intersection traffic congestion phenomenon, combined fog computing and reinforcement learning theory, this paper proposed a traffic light control model FRTL. The model performed intelligent coordinated control of traffic lights based on real-time traffic flow information. The fog node uploaded the collected real-time traffic flow information to the fog server, and the fog server realized information sharing on the fog platform, and the fog platform combined the processed shared data and Q learning to formulate a traffic light control algorithm. The algorithm used the detected real-time traffic data to calculate a suitable traffic light timing scheme, which was finally applied to the traffic light. The simulation results show that compared with the traditional time-phase control method and the main road control method (ATL), the FRTL control method improves the throughput of intersections, reduces the average waiting time of vehicles, and achieves the goal of properly regulating traffic lights and alleviating traffic congestion. [ABSTRACT FROM AUTHOR]

At present,many cities in China are short of pipeline-flow observations,which leads to large challenges to construct urban hydrological models for detailed rainfall-runoff simulations. In this study,the core district of Yizhuang Economic Development Zone was selected as the study area. Based on the accurate digitalized land-surface data,field survey and empirical verification of urban storm process was carried out in terms of the maximum runoff depth at specific spots,and the SWMM model was calibrated and verified for the two typical storm events in July 21st,2012 and June 23rd,2011. Subsequently,the runoff response rate and traffic congestion risk of design rainstorms in different return periods were analyzed and evaluated in sub-catchments with various land-uses. The results show that as return period increases,street and transportation land-uses have a higher response rate to the increase of rainstorm than park and green land-uses do,and the former has a higher risk of waterlogging-triggered traffic congestion than the latter. This finding indirectly reflects the variability of runoff response rates under different land-surface conditions. This study is potential to provide decision-makers with valuable suggestions on effective local urban-flood control and early warning. [ABSTRACT FROM AUTHOR]

In view of the different impacts of different traffic periods on traffic congestion and single factor fail to accurately characterize the traffic congestion state, this paper proposed a multi-index fuzzy comprehensive evaluation method for traffic congestion state evaluation. The method used the particle swarm optimization algorithm to optimize the support vector regression to predict the average road speed and traffic flow, obtained the predicted values of the average speed v, traffic flow density D, and road saturation S. It input the three factor indexes to multi-index fuzzy comprehensive evaluation model to establish the set of factors and evaluation (level) for traffic congestion. It determined the weight coefficients of three factors under the morning peak, the evening peak and other periods by the entropy method, then determined the degree of membership of each index in each period by the trapezoidal membership function. Finally, it divided the traffic congestion state into six levels. The results of predictive evaluation at the traffic data of the 1405 highway in PeMS show that the traffic congestion state evaluated by the proposed method is basically consistent with the actual state, the proposed method has a high prediction accuracy, the correct rate can reach 94.79 % . [ABSTRACT FROM AUTHOR]

With the increase in travel demand and car ownership, traffic congestion is becoming more and more serious. To alleviate traffic congestion, based on the user heterogeneity, this paper proposes to implement both toll and tradable credit scheme for the public-private partnership transportation network, i.e., tolling and charging tradable credits for the users who use the government-built public roads and BOT private roads, respectively. Based on the travelers' routing behavior under this mixed strategy, we build the variational inequality model of user equilibrium and market equilibrium. Then, according to the system optimal model, the mixed strategy set can be obtained that promotes the user equilibrium flow pattern to the system optimal flow pattern, and the upper bound of system efficiency loss under mixed strategy is also derived. Furthermore, we propose two bi-level programming models covering other objectives and obtain the optimal mixed strategy. Finally, a numerical experiment on a specific road network is conducted, which can obtain the specific amount of tradable credits and charging value for each public road and BOT private road respectively, and the total number of windows for that need to be set in the road network. [ABSTRACT FROM AUTHOR]

The intensive usage of vehicles has led to many urban problems including the traffic jams and the environmental pollutions. To handle these problems, most previous studies have used macro-based models to estimate and analyze the CO2 emission inventories, but very few studies have focused on computing vehi⁃ cle CO2 emissions using a micro-based model. This paper presents an in-depth study on computing the CO2 emissions from taxi trajectory data and further analyzing their spatiotemporal patterns from three aspects. Taking the Wuhan city as a case study, this paper uses the comprehensive modal emission model to quanti⁃ tatively compute the CO2 emissions from the taxi trajectory, and statistical results suggest that CO2 emissions of the entire city has experienced a remarkable regularity in times of the day and days of the week. Specifi⁃ cally, the spatiotemporal patterns of CO2 emissions from taxi trajectories are analyzed from three different aspects. Firstly, a spatial clustering algorithm is used to aggregate the taxi trajectory points with high CO2 emissions, and the number of clusters displayed a regular change pattern. For example, the cluster number is gradually increased from workdays to weekends or holidays and from normal time period to peak time period in one day. Secondly, the data field model is used to allocate the CO2 emissions of taxi trajecto⁃ ry to the individual streets, and the emission from street network exhibited a remarkable distribution in space and time. For instance, streets with high CO2 emission tend to appear in the morning peak time period of workdays and evening peak time period of weekends or holidays, and they are spatially adjacent to the universities, railway stations, or central business districts. Thirdly, a spatiotemporal autocorrelation technique is adopted to examine the concentration of taxi trajectory emissions in space, and different regions are positively auto-correlated with each other in both times of the day and days of the week. These results can help to the proposal of efficient CO2 emissions reduction strategies, and they can provide guidance for taxis management, low-carbon traveling, and so on. [ABSTRACT FROM AUTHOR]

ETC system used in the parking lot can effectively alleviate the traffic congestion, reduce vehicle traffic delay time and the average queue length, improve the overall lane capacity and service level. Based on the traffic flow characteristics of the parking lot, the vehicle arrival characteristics, vehicle transit process characteristics, the ETC, MTC lane capacities are analyzed. This paper presents an ETC lane capacity calculation model with MTC misappropriation rate. The M/G/K queuing theory model is used to analyze the MTC lane capacity, and the evaluation index and calculation method of parking service fee are set up. Through the actual survey of the parking lot calibration parameters and the use of Vissim simulation model, the traffic and ETC use rates in different proportions, the vehicle traffic parking lot lane average delay time are obtained. For the cases that ETC utilization rates are 30% , 50% , 70% and the traffic volume is 180 pcu/ha, optimal allocation schemes of ETC lane number are put forward, respectively, which can provide reference for the use of ETC system. [ABSTRACT FROM AUTHOR]

Robustness analysis of street network can contribute to the precaution and loss reduction of terrorism attacks, natural disasters and traffic congestion. We have obtained 50 urban road networks around the world from OpenStreetMap. On the basis of complex network robustness analysis method, we utilize the successive removal model and the cascade model to analyze the urban road network represented by the intersecting relationship of patterns, and discuss the relationship between the robustness of the road network and its topological patterns. It is found that the robustness varies when the network is under different attack model; it also differentiates when the attach strategy is targeting high-degree or high-betweenness nodes. The robustness of urban street networks is sensitive to the attach model and strategy. The road networks show less robustness under consecutive attack, while they vary considerably under cascade attack. In terms of the attack strategies, the betweenness strategy is more destructive than degree strategy under successive removal and the cascade models, which signifies that the high-betweenness nodes play a more im - portant role. The assortativity of street network is significantly positively correlated with its robustness against successive removal of nodes while significant difference observed for the robustness of scale-free and non-scale-free networks under the same model. The robustness under cascade attack shows no correlation with network assortativity and does not differ significantly between groups of different scale-free properties. [ABSTRACT FROM AUTHOR]

The existing traffic assignment theorem hardly dealt with the congested traffic state of link. To solve the above problem, based on the classic straight line inverse λ fundamental diagram, this paper presented a static traffic assignment method with given states of links. Firstly, through analyzing the fundamental diagram, it obtained the travel time function of link with two stages. Secondly, by introducing the indicating label of traffic state of link and constructing the flow conservation equations at nodes, it formulated the system optimal and user equilibrium traffic assignment models. At last, to solve the non-convex user equilibrium model, it proposed a branch and bound algorithm with relaxed partial objective function. This paper used numerical examples to demonstrate the effectiveness of the new model and algorithm. By extending the one-sided assumption of monotone increasing of link travel time function, the new theory can deal with the congested traffic state of link effectively and improve the practicality of existing theories. [ABSTRACT FROM AUTHOR]

This paper considered the congestion pricing to be the effective way to solve the traffic congestion, the main idea of road traffic congestion was to charge for some easy to cause road congestion, and appropriated compensation for other underutilized roads. It presented a subgradient heuristic traffic delay compensation strategy based on function. Firstly, it used a nonlinear programming model in the road toll/subsidies, Beckmann was the main realization based on minimizing the objective function, and used the Kuhn Hills-Lagrange multiplier model to construct the constraint condition. Secondly, the algorithm used the pricing compensation strategy to establish the road traffic model based on heuristic algorithm, and also used the marginal cost model to establish the delay function analysis model. Finally, the simulation experiments on real road networks show that the proposed algorithm has better performance in terms of travel time, traffic flow, convergence and so on, and the effectiveness of the proposed algorithm is verified. [ABSTRACT FROM AUTHOR]

In order to improve the urban traffic congestion detection and control efficiency, this paper proposed a new clustering analysis method based on multi-processor and space potential field modification for traffic congestion analysis. Firstly, based on the city road congestion spatial-temporal model with GIS four-dimensional spatial temporal data, this paper constructed field correction method for multi-processor parallel clustering method by using parallel Euclidean distance matrix computation, parallel neighborhood radius computing and parallel density index calculation. Secondly, it gave the complexity theorems of the parallel computation procedure, so as to theoretically analysis the computational complexity of the; algorithm. Finally, taking Beijing city as a test area, it verified the performance of the algorithm in analyzing the traffic congestion. Experimental results show that the method can achieve effective detection for rapid analysis of urban traffic congestion, which can provide data support for traffic congestion management. [ABSTRACT FROM AUTHOR]

With the rapid development of highway,the emergence of increased congestion,monitoring difficulty and other issues are increasingly seriously. Firstly based on the urban traffic performance congestion index of Beijing,this paper proposed a method to evaluate the status of highways through utilizing traffic performance index. Then based on the big data platform of Storm,this paper implemented data process,data analysis and key algorithms of index background calculation. Finally it published the real-time traffic performance index in the form of mobile phone APPs and official accounts of Wechat. The experimental results show that highway traffic performance index not only can reflect the overall status of highways,but also can reflect the real-time congestion situation of specific highways or specific highways range,and can real-time monitor the congestion situation of highway road network,which provides a reference for people and plays a positive role to ease road congestion. [ABSTRACT FROM AUTHOR]

In order to ease the congestion of macro traffic network and reduce the fuel consumption of vehicles, the equilibrium equations of the traffic flow in the congested area are established based on subregions classified by macroscopic fundamental diagram (MFD) according to different network state. Then the road network is divided into two categories, such as intersection and road section and a network energy consumption estimation model is established according to the parameter of MFD. Dual objective optimal control model of the congestion area boundary is built up with the goal of lowest energy consumption and the highest travel completion rate of vehicles in macro network. Finally, the actual city road network is used as the test object. By comparing the control scheme of the no boundary control, Bang-Bang entrance boundary control and dual objective optimal control scheme, the following conclusions are got: 1) At the peak time, the network evacuation capability under the dual objective optimal control is improved by 20.14% and 2.1% compared With the no boundary control and Bang-Bang entrance boundary control at the same time, vehicle fuel consumption decreased by 43.14% and 24.48% respectively. 2) Dual objective optimal control method can effectively improve the traffic density equilibrium inside and outside the congested area. 3) The boundary control of the congested area in macro network can effectively reduce the congestion level during rush hour and improve the evacuation ability of the whole network. [ABSTRACT FROM AUTHOR]

Traffic flow prediction is a very important research area of intelligent transportation system, and has a very important academic value and practical significance to improve the traffic congestion problems. Traditional prediction methods which used determined mathematical model would not meet the needs of prediction accuracy and convergence speed during the traffic management control because of nonlinear, complexity and uncertainty of traffic flow. In order to forecast traffic flow accurately, real-timely and efficiently, a new algorithm is proposed by combining wavelet theory and neural network, and constructing an IWNN( improved wavelet neural network) with improved network training methods. At the same time, the initial weights are optimized by GA ( genetic algorithm). It can improve prediction accuracy, speed up the convergence speed and avoid entering local minima. The simulation results show that it can get better prediction results. [ABSTRACT FROM AUTHOR]

In order to predict the traffic congestion in city, this paper proposed the prediction model based on the deep learning. The traffic data like flow parameters, environmental situation, times of day and so on were summarized and composed into the feature vector, and defined four kinds of traffic flow pattern. It learned the unlabelled traffic dataset by the auto-encoder network to build the hidden layer function and generate the new feature dataset, and used the softmax regression to classify the traffic pattern based on the labeled feature dataset learning. Demonstrated by the simulation, the prediction model has better performance than the model without the feature learning, the average prediction accuracy can reach 85%. [ABSTRACT FROM AUTHOR]

In order to alleviate traffic congestion and detect the effect of speed limit scheme on transportation system, this paper investigated the traffic assignment problem in a general multi-mode network under a fixed speed limits scheme. It constructed an optimizing model and compared the distinctions between flow patterns in the network as well as the travel cost. It provided the solution algorithm and utilized the numerical example to demonstrate the feasibility of the model and algorithm. It shows that in a general multi-mode traffic network, the different traffic modes have different share ratio due to various values of diffusion coefficient. Analysis result proves that speed limit scheme has the effect to convert travel demand from private cars to public transit. This result is worth for the researches of optimizing schemes to mitigate congestion. [ABSTRACT FROM AUTHOR]

To tackle the network congestion issue caused by redundant traffic by users' repeated access to the same network resources, this paper proposed a weighted bipartite network (WBN) model which evolved with time. Through the analysis of users' network behavior and redundant traffic' formation and evolution mechanism, WBN model adopted ways of preferential connection and topology growth to complete network evolution. Simulation experiment results show that strength of user nodes has experienced from the exponential distribution to power-law distribution and then random distribution. It effectively simulates the evolution of real network redundant traffic. Simulation results are also consistent with theoretical analysis and show that WBN model is accurate and practical. [ABSTRACT FROM AUTHOR]

Road traffic congestion pressure becomes more serious as the number of vehicles increases. Accurate traffic situation detection methods are needed to help in alleviating them. This paper proposed a TraSD-VANET method to detect the traffic situation. In this method, vehicles constituted clusters autonomously and then sent their speed and locations to cluster heads. After receiving data from cluster members, the cluster head calculated the lane weighted average speed and the traffic density adaptively. Afterwards, it estimated the traffic situation in its cluster according to the above calculation results by using fuzzy theory. The simulation results show that the average precision of estimation is improved 16% compared with the CoTEC in four traffic scenarios. This method has important practical value in traffic congestion detection on road. [ABSTRACT FROM AUTHOR]

In recent years, contradiction between supply and demand of urban transport of China is increasingly prominent, and urban traffic jam is getting more and more grave, seriously impact urban residents' normal travel, cause environmental pollution, as well as seriously impact normal operation of urban logistics and become development constraints of the whole city economy. This paper starts with phenomenon of urban traffic jam, and analyzes the present situation, the reasons, the effect and the root of urban traffic jam, and summaries the existing measures for the governance of urban traffic jam from the perspective of urban residents travel and urban logistics. On the basis of summarizing the plugging measures as well as considering the actual situation of our country, this paper establishes the system dynamics model of the management of urban traffic jam with the method of system dynamics. In the last place, this paper takes Beijing as an example, simulates the effect of the typical plugging measures in Beijing, and reaches the suggestions for China to solve urban traffic jam. [ABSTRACT FROM AUTHOR]

Extracting high-efficient routing strategy is important to improve network throughput and reduce traffic congestion. From the viewpoint of gravitational-field theory, this paper studied the aggregation effect of node on traffic flow during transmission, defined the gravitational-field model with considering the unblocked reliability of node itself and its neighbors and the travel path length.and proposed a gravitational-field routing strategy based on node aggregation ability. In order to testify the efficiency of the routing strategy, the experiments for different routing algorithm were simulated for comparison. The results show that compared with the shortest-palh routing algorithm, this proposed method not only greatly improves the network throughput, but also is stable and reliable. [ABSTRACT FROM AUTHOR]

Large-scale sports are often held in large cities with heavy traffic, which makes it difficult to satisfy the transportation requirement. To solve this problem, lane reservation method is often adopted. However, it may make the host city's own transportation even worse. Therefore, it is necessary to study how to make lane reservation. While previous studies mainly focus on minimizing the effect on regular transportation, the present study also discusses the possibility of reducing the number of transporting vehicles. By evaluating in advance, some transport tasks can be merged. Accordingly, the number of transport vehicles is cut down and operation cost is reduced. Based on this, a linear integer programming model is formulated. The model is different from the existing models with transportation network, constraint of task path, constraint and measure of making reservation lane. It is shown that the problem is NP-hard. It can be solved by exact methods if it is not too large. The model is proved to be valid and practical by the results shown by Lingo, a Mathematical programming software as in the example of Guangzhou Asia Games. [ABSTRACT FROM AUTHOR]

To resolve the problems of network congestion leading to high end-to-end delay and low throughput in MANET (mobile Ad hoc network), this paper proposed an algorithm of load-balancing based on probability. In this algorithm, nodes mapped the load state of network historical load information and judge route access by probability to balance the load in the networks. Mapping the load state of network by historical load information was an effective solution to the problem of difficult to judge load state in distributed operation. Probabilistic algorithms could effectively overcome the problem of fuzzy recognition in the rule of threshold, while a significant reduction the flooding of broadcast and saving channel resources. Combined with classical reactive routing protocol, it developed a new routing protocol called H&P_DSR. The computer simulation confirms the theoretical analysis and shows the load balancing algorithm could balance network load accurately and efficiently, H&P_DSR protocol improves network throughput and reduces the end-to-end delay effectively without extra route overhead. [ABSTRACT FROM AUTHOR]

In order to get insight into the dynamics of transportation network congestion and develop an effective decision making tool for transportation network congestion government, this paper presented a complex network based simulation model for transportation network congestion evaluation. Through introducing the concept of road impedance in complex network theory, complex network model and traffic simulation model were combined successfully to form a complete transportation network congestion simulation model. In addition, this paper also presented a transportation network capacity assessment method based on virtual test vehicle traversing. This approach could efficiently and comprehensively evaluate the network capacity under different conditions. Finally, it implemented a complete transportation network congestion assessment simulation system on PC system based on the above model and conducted simulation experiments to analyze the influence on the transportation network traffic capacity imposed by the number of congested road sections, traffic flow and road network topology. The results of simulation experiments match the classical transportation theory well and it disclosed more dynamic information of transportation network congestion evolution, which means this model can work well for transportation congestion government decision-making. [ABSTRACT FROM AUTHOR]

In order to explore impact of the area-road congestion charging about the residents' residential location and transportation modes, the satisfaction assessment model was proposed to assess the residential location, and the household consumption remaining model was established by the satisfaction, household income and house prices. Area-road congestion charging regimes were implemented, and the generalized commuting traffic impedance and generalized holiday entertainment traffic impedance were got by different trip purpose travel chain characteristics and the corresponding travel mode of family members. The residence of the largest family remaining was got by the household consumption remaining model. The results indicate that area-road congestion charging regimes don't affect low-income mobile home residential choice. A lower level congestion charging does not affect high-income mobile home residential choice, and a higher levels congestion charging makes high-income families mobile home residential from the suburbs to charging regional-border, and it has no affect when the charging level is high. On weekdays and holidays, there is an optimum point both the regional congestion charging level, and the holidays charging optimum point is higher, so it is conducive to maximize for economic efficiency and social utility when the best charging point is implemented. [ABSTRACT FROM AUTHOR]

For the two traffic management strategies of information providing and congestion pricing, this paper studied a union pricing strategy. Firstly, it constructed the decision space of the government and the traffic information supplier, calculated the information market penetration. Then, based on the assumption of elastic demand, it presented an equilibrium model which included two travelers (with/without information), and got the travelers' decision space. It also presented a union pricing model based on the game theory at the same time. Last, it used a testing network to analyze the model. The results show that the level of social benefits influence the information and the congestion pricing more significantly. It also find some results of the model which are in accordance with the practical experience. All of these show the reasonable of the model. [ABSTRACT FROM AUTHOR]

The port trucks congestion problem existed in many ports. For this reason, the port trucks route cost optimization model faced the 'work surface' was established by exploring the effect factors of port trucks operation efficiency and the cost composition of the truck route in the container gantry crane system. Then genetic algorithm-ant colony optimization algorithm (GA-ACO) is proposed in view of the model and analyzed the problems with an example, compared optimization results with those by ant colony algorithm from the changes of truck route convergence, variable cost, penalty cost and total cost. The results show that genetic algorithm-ant colony optimization algorithm is faster converge to the optimal solution and gain less cost. [ABSTRACT FROM AUTHOR]

This paper presents a vehicle routing problem in dynamic urban traffic network with real-time traffic information. Both re-current and non-recurrent congestion are considered in the problem. We develop a method to solve the problem by combining the initial routes arrangement with the real-time route adjustment. The initial route planning is made by solving a time-dependent vehicle routing problem under re-current congestion conditions. The genetic algorithm is applied. During the plan implementation, a new mechanism updating at the critical node is proposed to adjust the routes with real-time traffic information subject to the unexpected traffic accidents in non-recurrent congestion environment. Through the numerical simulation, the results show that the new route updating mechanism is more effective than others in the literatures, and the advantage by adopting the new mechanism becomes more prominent when the network becomes more dynamic. [ABSTRACT FROM AUTHOR]