Evaluation on Route Guidance System and Its Application

A Microscopic Traffic Simulator for evaluation of dynamic traffic management systems

In order to optimize the existing control subarea division methods, a new dynamic subarea division method based on node importance evaluating is proposed for regional coordinated control. Firstly, considering the characteristics of road network and traffic flow between adjacent intersections, correlation degree model is established by calculating the correlation coefficients of traffic flow, signal cycle, and traffic state. Then, road traffic network is abstracted into a network topology structure graph. From the global perspective of the road network, intersection position information and the importance contribution between adjacent intersections are taken into account, and the correlation degrees between adjacent intersections are taken as the edge weights to construct intersection importance evaluation matrix. Finally, an actual road network is selected, and an improved Newman algorithm is employed to verify and analyze the method proposed in this paper. Results show that, compared with other methods, the control subarea division result of the new proposed method is more elaborate and more in line with the actual traffic flow characteristics. Moreover, dynamic subarea division can be realized according to the traffic characteristics of different periods, which can provide a good basis for the formulation of the signal control schemes in the next stage.

Traffic signal controllers and route guidance systems are two major subsystems of Intelligent Transportation Systems that influence each other directly. Due to correlation between these subsystems, some research has been done to combine them into an integrated system. In this paper, PersianGulf - an autonomous combined traffic signal controller and route guidance system - will be proposed which has two unique features as compared to similar research. First, it is totally distributed because calculation of optimal routes are done independently in traffic signal controllers of intersections and second, it is totally autonomous because there is no need to communicate/cooperate with either traffic supervisors such as traffic management centers or the vehicles/drivers. Also, Simulation results show that PersianGulf improve the average speed of vehicles significantly in the simulated scenarios.

In this paper, the characteristics of traffic flow on urban expressway in Beijing are investigated. Based on the real data, some classical traffic flow models are used to explore the relationships among traffic flow, speed and time occupancy. The FCM (fuzzy C-means method) clustering algorithm is applied to classify the traffic flow state. The results show that the Greenshields model is the best suitable model for the mathematical description of traffic flow, i.e. traffic speed and time occupancy is in linear relation while traffic volume and time occupancy (traffic speed) is in parabolic relation. Four different traffic flow states, including free flow, steady flow, synchronized flow and congested flow, are identified according to the FCM clustering method. For the free traffic flow, the time occupancy cluster center is equal to 0.16, and the traffic volume cluster center is equal to 980 pcu/h. For the steady traffic flow, the time occupancy cluster center is equal to 0.30, and the traffic volume cluster center is equal to 1737 pcu/h. For the synchronized traffic flow, the time occupancy cluster center is equal to 0.50, and the traffic volume cluster center is equal to 1896 pcu/h. For the congested traffic flow, the time occupancy cluster center is equal to 0.79, and the traffic volume cluster center is equal to 1184 pcu/h. The analysis of traffic flow characteristics in this study can provide the method and data foundation to evaluate the traffic service level and enhance the traffic organization and management.

As a criterion of intelligent transport systems (ITS) effectiveness, it is proposed to use the assessment of a road traffic management (RTM) measures impact on the population health living near the highway. ITS are designed, among other things, for regulating traffic in automatic mode. To build mathematical models of this regulation impact on the automobile traffic output indicators, various subroutines are needed to determine the desired dependencies. One of the most important indicators of automobile traffic is the degree of its impact on the environment and public health. In this article, using the example of several most typical scenarios of traffic regulation, the degree of automobile traffic influence on the public health risk indicators is shown. Provides environmental assessment of such RTM measures, as the traffic congestion elimination, the narrowing car roadway with the vacant lanes for non-motorized transport (NMT) movement organization, the ban on heavy cars movement, the ban on the movement of vehicles low then a third ecological class on this street section. For this purpose, based on the assessment of gross pollutant emissions by the traffic flow with the specified traffic characteristics and composition, determined using ITS, the average annual surface concentrations of pollutants on adjacent territory and the population health risks are determined. It was found that the greatest environmental effect is caused by measures to organize the NMT movement and the ban on a movement of low environmental classes vehicles.

Improving traffic management through consideration of uncertainty and stochastics in traffic flow

This paper studies the risk assessment of traffic flow on major highways under high-speed driving conditions and the safety warning after traffic incidents. Firstly, by analyzing the operation characteristics of the main line traffic flow and the evolution characteristics of the upstream traffic flow after the event, a collaborative control strategy for the dynamic assessment and accurate early warning of the main line traffic flow is proposed. Secondly, based on the operating speed, traffic flow and head-time distance state parameters of the main traffic flow, the risk assessment model of the main traffic flow is established, which provides an algorithm basis for the safe operation status evaluation and active control of the main traffic flow. Third, based on the driver’s reaction process after the traffic incident and the evolution process of main traffic flow, a traffic incident safety warning distance function is proposed, which provides a quantitative function for the accurate early warning and prevention of traffic accidents in the upstream traffic flow after traffic incidents. Through the dynamic assessment and control of operation risks of expressway main line traffic flow, the accurate risk warning of expressway main line traffic flow under the traffic event conditions will significantly improve the dynamic safety control level and risk warning ability of the expressway main line.

Why standard modelling and evaluation procedures are inadequate for assessing traffic congestion measures

<div class="htmlview paragraph">Recently, the control of traffic flow has been proposed using several types of criteria (e.g. minimum-time control, minimum fuel control and so on). Most recently, an environmental noise pollution problem caused by the road traffic is being aggravated more and more by the consolidation and expansion of roadway system particularly in urban areas. However, the objective of this paper is to control road traffic flow by regulating traffic noise propagation in an urban area in Cairo city. The results of traffic noise prediction obtained by trending of the experimental data collecting by systematic noise measurement and the evaluation of the traffic noise which is in close connection with physical parameters of traffic flow and noise propagation characteristics is presented. The analysis of road traffic flow noise control is based on the mixed integer non-linear programming technique, where the optimal control strategy is used. The results indicate that significant information gained for controlling road traffic in urban areas.</div>

In recent years, due to the implementation of the highway-free policy during holidays, the travel demand and traffic volume during holidays have increased significantly, and the resulting congestion problem is more serious. To better analyze and study the traffic flow characteristics of expressway hot toll stations during holidays, and put forward targeted optimization strategies to achieve the purpose of improving the efficiency of highway operation during holidays, this paper takes the toll collection data of more than 5 million lines of expressways in Jilin Province in 25 days from September to October as the research object. By using the characteristics of traffic flow on different characteristic days, this paper summarizes the characteristic data of traffic flow by statistical means and depicts the trend chart of hot toll stations based on geographic information using the digital visualization method. Based on basic data cleaning and classification analysis, a flow rate of hot toll station phase change analysis, according to the characteristic of geographic information data, and Jilin province, based on the three-dimensional map heat flow variation, the comprehensive finish holiday hot spots for highway toll station traffic flow characteristics of the impression. Based on this, the paper puts forward the optimization policy of highway holiday travel optimization.

Road network traffic flow prediction: A personalized federated learning method based on client reputation

PurposeIn order to explore the effect of curb parking on dynamic traffic and formulate some reasonable and effective traffic management measures, the effects on capacity and traffic safety are studied.MethodsFour road segments with curb parking were selected as the investigation location. Several traffic characteristics and parameters were then investigated and counted, including traffic flow volume, speed, headway and traffic conflict. Based on a reduction of lane effective width and the Gap Acceptance Theory, two effect models describing curb parking and road capacity were constructed. Considering the factors involved in motor vehicle conflicts (such as non-motor vehicle lane distribution and stopping sight distance), the effects of curb parking on both motor vehicle and non-motor vehicle traffic safety was analyzed, as well as pedestrian crossing safety. This case study analyzes both the capacity and traffic safety of all four investigation segments.ResultsResults show that the lane effective width of road segment with curb parking significantly influences the road capacity and impacts the traffic flow volumes of the parking lane and its adjacent lane.ConclusionsCurb parking significantly effects traffic operation safety; however, it can be improved by implementing traffic safety management measures.

Based on the analysis of the macroscopic characteristics of the traffic flow in a large busy airport, this paper explores the relationship between the basic parameters of the traffic flow and its phase transformation process. Firstly, considering the physical structure of airport surface and ground control rules, this paper uses the variable cell transmission model to simulate the surface operation. Then, the macro characteristics of the traffic flow in taxiway and apron area are analysed by constructing the fundamental diagrams. It is proved that there is an interconnection between the basic parameters such as flow, velocity and density. With the change of parameters, the traffic presents three phase states as free-flow state, metastable state and blocked state, and the evolution characteristics of traffic flow are different in different states. The results of this paper can provide theoretical support for airport surface operation management.

With the development of urbanization, the number of residents’ motor vehicles has increased sharply, and traffic congestion problem has become increasingly serious. The construction of Intelligent Traffic System (ITS) has become the main means to alleviate traffic congestion. Short-term traffic flow prediction has guiding significance for residents’ travel planning and intelligent management of transportation, and has become one of the research hotspots in intelligent transportation field.Therefore, A short-term traffic flow prediction method based on the spatio-temporal characteristics of complex road networks is proposed to further improve the prediction accuracy and reduce the prediction cost. Firstly, a graph convolutional network (GCN) capable of processing non-Euclidean data structures is used to extract the spatial characteristics of traffic flow data. Then, the long and short-term memory (LSTM) neural network is used to process the time characteristics. Finally, the two are combined to realize the effective processing of the spatio-temporal characteristics of traffic flow data. Experimental results on the real traffic flow dataset prove the feasibility and effectiveness of the proposed method, and can provide a basis for intelligent traffic control and smart city construction.

A real-time control method-based simulation for high-speed trains on large-scale rail network