Analysis Of Traffic Conditions Research Articles

Analysis of Traffic Conditions in Urban Region Based on Data from Fixed Detectors

To evaluate traffic conditions in an urban region, the average travel speed in the street network and the average traffic flow per lane are selected as indexes. The results for identifying traffic conditions are obtained using macroscopic fundamental diagram. Because of the difficulty of collecting the traffic parameter of travel speed from widely distributed fixed detectors directly, in this paper, the relationship between average travel speed and queue lengths at signalized intersections within the urban area is established based on an equivalent assumption. Finally, the average travel speed estimation model proposed in this paper is tested with microscopic simulation platform, and the results showed that the average travel speed estimation model performed well with satisfactory accuracy. In addition, the best performance of the network efficiency can be identified based on the reflections of macroscopic fundamental diagram, and the evaluation system is simple enough for application in engineering. Therefore, the result is instructive both for generating traffic control strategies and for making route choices.

Modeling Impact of Traffic Conditions on Variability of Midblock Roadside Fine Particulate Matter

The objective of this study was to examine the concentration variation of midblock roadside particulate matter less than 2.5 Μm (PM2.5) as a function of very high resolution meteorological and traffic data. Morning peak period measurements were taken at a midblock roadside location on an urban arterial commuter roadway. For the impact of dynamic traffic conditions to be captured, data were analyzed at 10-s intervals, a substantially higher resolution than that used in typical roadside air quality study designs. Particular attention was paid to changes in traffic conditions, including fleet mix, queuing, and vehicle platooning over the course of the study period, and the effect of these changes on PM2.5. Significant correlations were observed between vehicle platoons and increases in PM2.5 concentrations. Traffic state analysis was employed to determine median PM2.5 levels before and after the onset of congestion. A multivariate regression model was estimated to determine significant PM2.5 predictors while controlling for autocorrelation. Significance was found not only in the simultaneous traffic variables but also in lagged traffic variables; in addition, the effects of vehicle types and wind direction were quantified. Modeling results indicated that traffic state (e.g., congestion) and vehicle type had a significant impact on roadside PM2.5 concentrations. This study serves as a demonstration of the abilities of very-high-resolution data to identify the effects of relatively minute changes in traffic conditions on air pollutant concentrations.

Traffic Congestion Evaluation Method for Urban Arterials

Quantitative analysis of traffic conditions provides a benchmark for evaluating traffic states for effective operation and management. Most existing studies focus on measuring congestion in freeway continuous traffic flow. This paper quantifies states of urban interrupted traffic flow by using field traffic data from arterial roads in Changzhou, Jiangsu Province, China, as a study case. Development of the average congestion index considered traffic volumes on various segments to reflect the congestion state of the entire road. The congestion travel rate reflected the difference between the studied state and the free-flow state. The two indexes were adopted for measuring congestion quantitatively for both weekday (March 24, 2010) and weekend (March 28, 2010) traffic. In addition, the fuzzy clustering method was used to obtain threshold values for various traffic states, and three states were proposed from the empirical study on traffic conditions in Changzhou. Under this classification, congestion quantifications of field-observed trends from both the weekday and the weekend were found to be consistent with the definitions of the Urban Traffic Management Evaluation System of China. This finding further validated the effectiveness of the proposed average congestion index indicator.

Detecting Research for Vehicles Track at Roundabout Based on Dual Data Source

Extracting vehicles track at roundabout is the basis research for motion characteristics of vehicles. At present, most of the vehicle trajectory was obtained by using single data source. However, the precision of the method needs to be improved. In this paper, two cameras are set at two different directions shooting the same scene image to obtain image data. And then a new method to extracted vehicles track more accurately by integrate the dual data source organically was proposed. In the case analysis, through the contrastive analysis of 4 different curves, the result shows that the error of dual data detection is decreased by 2.7% than single data detection. The method to extract vehicles track by dual data source can provide the theoretical support for the analysis of traffic conditions at roundabout.

Artificial immune K ‐means grid‐density clustering algorithm for real‐time monitoring and analysis of urban traffic

A novel clustering algorithm is presented for monitoring and analysing traffic conditions in real-time and automatically. The existing methods concentrate on analysis of traffic flow based on historical information, and they cannot provide timely analysis of traffic conditions. Regarding the vehicles on the roads as data points, a K -means grid-density clustering algorithm is proposed based on an artificial immune network to partition the vehicles data into proper clusters, and marks the densities for monitoring and analysing the traffic conditions. Simulated experimental results show that the proposed algorithm obtains higher efficiency and stability than traditional methods.

Statistical traffic state analysis in large‐scale transportation networks using locality‐preserving non‐negative matrix factorisation

Statistical traffic data analysis is a hot topic in traffic management and control. In this field, current research progresses focus on analysing traffic flows of individual links or local regions in a transportation network. Less attention are paid to the global view of traffic states over the entire network, which is important for modelling large-scale traffic scenes. Our aim is precisely to propose a new methodology for extracting spatiotemporal traffic patterns, ultimately for modelling large-scale traffic dynamics, and long-term traffic forecasting. The authors attack this issue by utilising locality-preserving non-negative matrix factorisation (LPNMF) to derive low-dimensional representation of network-level traffic states. Clustering is performed on the compact LPNMF projections to unveil typical spatial patterns and temporal dynamics of network-level traffic states. The authors have tested the proposed method on simulated traffic data generated for a large-scale road network, and reported experimental results validate the ability of our approach for extracting meaningful large-scale space-time traffic patterns. Furthermore, the derived clustering results provide an intuitive understanding of spatial-temporal characteristics of traffic flows in the large-scale network and a basis for potential long-term forecasting.

Quantifying errors in micro-scale emissions models using a case-study approach

To quantify the level of uncertainty attached to forecasts of CO2 emissions, an analysis of errors is undertaken; looking at both errors inherent in the model structure and the uncertainties in the input data. Both error types are treated in relation to CO2 emissions modelling using a case-study from Brisbane, Australia. To estimate input data uncertainty, an analysis of traffic conditions using Monte Carlo simulation is used. Model structure induced uncertainties are also quantified by statistical analysis for a number of traffic scenarios. To arrive at an optimal overall CO2 prediction, the interaction between the two components is taken into account. Since a more complex model does not necessarily yield higher overall accuracy, a compromise solution is found. The results suggest that the CO2 model used in the analysis produces low overall uncertainty under free flow traffic conditions. When average traffic speeds approach congested conditions, however, there are significant errors associated with emissions estimates.

Urban Regional Traffic State Analysis Software System Emphasizing Pattern Transition

Urban traffic state evolution analysis is very significant and constructive for traffic guidance and control. In this paper, firstly, a quantitative method for analyzing regional traffic state evolution was proposed by constructing traffic state pattern transition network to mine regional traffic state information and state pattern transition characteristics from massive data. Secondly, a GIS-based urban regional traffic state analysis soft ware system URTSAS based on the method was designed and implemented. Application scenarios and effect shows that traffic state transition analysis in URTSAS has a wide application prospect in improving urban traffic management and decision-making.

Approximate Solution Procedure for Dynamic Traffic Assignment

This paper proposes an approximate dynamic traffic assignment algorithm for the analysis of traffic conditions in large-scale road networks over several days. The time-dependent origin-destination trips are assumed to be known. A case study for evacuation of the New Orleans metropolitan area prior to the landfall of Hurricane Katrina is presented to test the efficiency and effectiveness of the proposed procedure. The model results are compared to the traffic counts collected during the evacuation and then further tested by the mesoscopic simulation-based model, DynusT. The study shows that the traffic pattern produced by the proposed procedure is a good approximation to traffic count data and that the algorithm provides a good approximation to the computations performed by DynusT.

Research on Traffic Characteristics and Traffic Conflicts of the One-Way-Closure Work Zone on Freeway

By analyzing the traffic characteristics and traffic conflicts of the typical one-way-closure work zone on four-lane freeway, the queuing characteristics of vehicles are determined, and the Erlang distribution model which can describe the distribution of time headway is calibrated. The speed distribution characteristics of each component of the work zone are concluded, and the speed limit scales for these components are put forward based on the statistic analysis. The types of traffic conflicts are firstly concluded, and then the identification method of the rear-end conflicts’ severity degree based on TTC technique as well as the prediction model of rear-end conflicts based on Negative Binomial distribution are put forward. The research results are useful to the analysis of traffic conditions of work zones, and they can also be used to evaluate the safety situations of freeway work zones

Urban Network Traffic State Evaluation Based on a Traffic State Coefficient

AbstractUrban traffic network state is evaluated based on the traffic state evaluation of its component units (junctions and road sections). However, previous research viewed the intersection into road sections more from the meso perspective, ignoring the effects of the intersection on traffic network state. In the current work, the basic parameters of traffic network state evaluation such as the intersection entrance saturation and the mean space speed of road sections are determined by combining the macro road network state evaluation and microscopic traffic state analysis. The traffic network state coefficient is defined as the traffic flow moving resistance, and the critical value of the traffic network coefficient is studied and determined. A new method of road traffic network state analysis is proposed, and the whole simulated road network state is analyzed. Finally, the whole road network state is evaluated and analyzed according to accessibility and connectivity.

Capacities of Unsignalized Intersections under Mixed Vehicular and Nonmotorized Traffic Conditions

Unsignalized intersections consist of three types–-two-way stop-controlled, all-way stop-controlled, and uncontrolled intersections–- all with different priority relationships between traffic movements according to traffic laws. A conflict technique method was used to develop capacity models for the three types of unsignalized intersections under mixed traffic conditions involving vehicular, bicycle, and pedestrian movements. With field data collected from several unsignalized intersections, the model parameters were calibrated by a comparison analysis of traffic conditions in China and were modified on the basis of actual traffic conditions. The capacities obtained by the proposed models matched well with the observed capacities and the capacities calculated by conventional methods, both of which verified the effectiveness of the proposed models. The models proved to be valuable tools for determining capacities of vehicular movements at unsignalized intersections.

Microscopic traffic simulation: A tool for the design, analysis and evaluation of intelligent transport systems

This paper summarises some of the main modelling and interface developments made recently in the AIMSUN microscopic traffic simulator to provide a better response to the requirements for the assessment of ITS systems, advanced transport analysis and ATMS. The description addresses two main areas: improvements on the dynamic assignment capabilities, and the embedding of the simulator in the AIMSUN/ISM (Intermodal Strategy Manager) a versatile graphic environment for model manipulation and simulation based traffic analysis and evaluation of advanced traffic management strategies. AIMSUN/ISM includes two specific tools, the Scenario Analysis Module to generate and simulate the traffic management strategies, and the (ODTool) to generate and manipulate the Origin-Destination matrices describing the mobility patterns required by the dynamic analysis of traffic conditions. The matrix calculation procedures have been implemented on basis to a flexible interface with the EMME/2 transport planning software.