Traffic Index Research Articles

MULTISCALE DETRENDED FLUCTUATION ANALYSIS OF TRAFFIC INDEX SERIES

In this paper, we present a multiscale detrended fluctuation analysis (DFA) for describing the traffic fractal dynamics with a spectrum of scale exponents, a(s), rather than by a model of lumped parameters a1 and a2. The method combines DFA with moving fitting window to analyze the traffic index (TI) series in different scales, shows more details of scale properties and provides a reliable analysis. We also quantify the effects of weather, traffic peaks and traffic control on exponent spectra a(s). The results indicate clearly that at large scales, the exponents show large volatility and they all have their own exponent patterns. In addition, for the effect of traffic control, the scale exponents of traffic control are continuously obviously larger than those without traffic control at small scales. The multiscale DFA method provides new ways to measure the TI series and distinguishes groups in different conditions.

Warm mix asphalt by water-containing methodology: a laboratory study on workability properties versus micro-foaming time

This paper focuses on a laboratory investigation of compaction characteristics of warm mix asphalt produced with the addition of synthetic zeolites. The influence of the time elapsed between mixing and compaction operations on mix compactibility was evaluated to define an optimum “micro-foaming time” (MFT), in which the additive can completely release the water contained. A comparison between traditional hot mix asphalt and warm mixes was carried out; two compaction methods (impact and gyratory) were used. Mix compactibility was firstly evaluated in terms of air voids content for each condition of compaction (immediately after mixing or after 1–2 h of storage in an oven). Mix resistance to densification and to distortion was investigated by means of compaction indexes and traffic indexes. Data showed that the foaming process due to the addition of the zeolite has a peak value of intensity after 1 h of MFT. This effect seems to vanish after a longer period of time. Outcomes of this study are expected to benefit both practitioners and researchers.

Delimiting boundaries of market areas of central places using the density of retail facilities in an urban space

When Christaller's central place theory is applied to an anisotropic urban space, the hierarchical structure of the central places in hexagon shapes does not appear. Thus, we have difficulties delimiting boundaries of market areas of central places. In order to overcome this limitation, we suggest the geographic information system (GIS) method based on a hydrological modelling which uses raster density and apply the method to the retail facilities of Seoul, Korea. Kernel density function is used to measure the density of retail facilities, and search radii are set up as 500, 1000, and 5000 m by considering the size of the neighbourhood unit, the neighbourhood district, and the sub-centre region. As a result, we confirm market areas of central places with irregular shapes, which become nested in those of higher order central places. This means that central places in an urban space have the hierarchy, which is the core concept of Christaller's theory. In order to evaluate the result of delimiting market areas, we suggest the normalized internal traffic volume ratio index (NTI). The average NTIs of the market areas of central places are higher than those of administrative units, and thus, we conclude that market areas of central places are effectively delimited and the GIS method based on a hydrological modelling is useful.

Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

An Identification Method of Traffic State Inequality for Urban Roads

Traffic state inequality coefficient, an index characterizing traffic state inequality for urban roads, is presented based on traffic state indexes of intersections and links calculated by traffic flow data collected from fixed traffic detectors. And then it establishes the calculation system for traffic state inequality coefficient of intersections, links and networks and determines the ways to classify traffic state inequality. After that, a case study is conducted using Vissim simulation data reproducing the process and results of the identification.

Risk Index Model Building: Application for Field Ramp Metering Safety Evaluation on Urban Motorway Traffic in Paris

Abstract This paper aims at developing a risk index based on real-data measurements, which can be used either off-line as an evaluation index during the evaluation process which leads to the dramatical reduction of the field test periods, or in real-time like: a safety monitoring tool (e.g. safety user warning system), or a multi-criterion function to be optimized in real time (safety index combined with a traffic index) within several control strategies, such as coordinated ramp metering, speed limit control, route guidance, etc.

Sustainable Development Evaluation of Urban Traffic System

Sustainable development is one of the themes of the world today. Considering growing urban traffic problems and urban environmental problems, developing sustainable transport is particularly important. Based on the urban traffic sustainable development theory, an evaluation index system of traffic sustainable development is built using analysis method and testing methods of index system. Then an improved entropy method is used to define the weight of index of traffic sustainable evaluation index system, and an evaluation model is built, which provides a new perspective for urban sustainable development research.

Research on Freeway Traffic Safety Index Based on Toll Data

Because the current research on traffic level has not yet been achieved classification, it cannot timely and effectively provide the basis for the public transportation and safety management of the traffic control department. Introduce traffic safety index based on toll data to evaluate freeway traffic levels. Firstly, combined with the relevant indicators of traffic engineering, put forward the concept of freeway traffic safety index; secondly, calculate the traffic safety index by analyzing real-time toll data; finally, in order to improve the accuracy of evaluation, have an optimization of traffic safety index definition. Application on the Beijing-Hong Kong-Macao freeway shows that traffic safety index can be combined with monitoring data to evaluate the condition of road sections and the road network, and its historical data can be used to predict the road traffic conditions, and provide effective guidance for freeway traffic safety operation.

Research on Second Ring Expressway Traffic Congestion in Beijing

According to the urban expressway traffic congestion of Beijing, from the perspective of traffic flow, the study makes a calculation and analysis on road network congestion rate, load of road network and traffic operation index. Training the traffic congestion and load of road network by using the BP neutral network in MATLAB, and put forward some countermeasures to solve the problem of traffic congestion. Through analyzing the load of different section and congestion rate, we can obtain the spatial distribution of the traffic flow and grasp the overall traffic on the Ring Road running load, develop appropriate management control programs for traffic managers, provide service and travel mode for travelers at the same time, so that balance the overall network load tends.

Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference

Traffic congestion detection is the basis of dynamic traffic control and real time guidance. This study proposes a fuzzy logic based traffic congestion identification method. The components of a fuzzy logic inference are firstly formulated. According to such information as the speed and occupancy of freeway traffic flow, and the weather conditions on the freeway, a congestion identification method based on fuzzy logic inference is then designed. Gauss curves are assumed for the membership functions of the input and output variables, and 45 fuzzy rules are also established. Finally, the congestion identification method is simulated. Simulation results verify the effectiveness of the above method. Fuzzy logic inference is suitable for estimating the traffic congestion index.

A link traffic model by incorporating both merits of vertical and Horizontal Queue Concept

With the development of traffic flow theory and practice, traffic models at different levels of analysis are expected to provide comprehensive outputs with satisfactory efficiency. Accordingly, this research proposes an Equivalent Link traffic State Model (ELSM) to meet this requirement. ELSM combines both advantages of Vertical Queue Model (VQ) and Horizontal Queue Model (HQ). On one hand, the structure of ELSM is similar to VQ; on the other hand, queue dynamics at any moment along the link can be available through deriving three “characteristic points” of each cycle based on shock wave theory. Thus spatial variation of vehicle queue can be obtained. As a result, common traffic performance indexes such as delay, stops and queue length can be directly obtained in addition to the microscopic level variables such as vehicle trajectories and travel time. It is shown that with the increasing of numerical resolution, the results of CTM (Cell Transmission Model) gradually converge to ELSM.

Evaluation on Public Bicycle Traffic System

First, the public bicycle traffic evaluation index system is established by six indicators measured, including system characteristics, environmental pollution and service levels. Further, the function models are established. Last, comparing comprehensive evaluation index value of bicycle, bus and motor vehicle three traffic kinds of transportation by a case, the result shows that public bicycle traffic has an absolute advantage among them within 3 kilometers.

Data Imputation for Regional Traffic Index Based on GSO-NN

The incomplete traffic data in urban road networks greatly affect the quality and performance of traffic information platform. The importance of effectively imputing the missing values emerges. The paper introduces a three-layer feed-forward neural network to missing traffic index prediction, where the group search optimization (GSO) is proposed to optimize the connection weights and thresholds to solve the problem of falling into the local optima. It is the first time to apply the technique to missing data imputation. Simulations are presented to demonstrate the accuracies and effectiveness of the proposed methodologies. This reveals that it is a promising approach in missing data prediction.

Study on the Environmental Impact Assessment Index of Traffic Engineering Based on the Low Carbon Economy Perspective

The traffic engineering environment impact assessment generally considered the influence on environment of traffic engineering operation stage only, relatively ignored the influence on environment of traffic engineering construction stage and demolition stage. This paper gives comprehensive analysis on the influence on environment of traffic engineering at the view of the whole life cycle of traffic engineering. That is considering the influence on environment of materiel production stage, processing stage, engineering construction stage and demolition stage. The traffic engineering environment impact assessment index is established by considering a low carbon economy connotation and with the use of total life cycle analysis method, and the evaluation index of each specific quantitative index is given.

INVESTIGATION OF THE EFFECT OF TRAFFIC PARAMETERS ON ROAD HAZARD USING CLASSIFICATION TREE MODEL

This paper presents a method for the identification of hazardous situations on the freeways. For this study, about 18 km long section of Eastern Freeway in Melbourne, Australia was selected as a test bed. Three categories of data i.e. traffic, weather and accident record data were used for the analysis and modelling. In developing the crash risk probability model, classification tree based model was developed in this study. In formulating the models, it was found that weather conditions did not have significant impact on accident occurrence so the classification tree was built using two traffic indices; traffic flow and vehicle speed only. The formulated classification tree is able to identify the possible hazard and non-hazard situations on freeway. The outcome of the study will aid the hazard mitigation strategies.

Lifetime Highway Bridge Traffic Load Effect from a Combination of Traffic States Allowing for Dynamic Amplification

Recent research has shown that the dynamic amplification factor (DAF) to be applied to free-flowing traffic-induced load effect may not be as high as previously thought. Therefore, congested traffic states may govern extreme load effect at lower bridge lengths than currently assumed. Thus, there is a need for a methodology that incorporates both free-flowing and congested traffic states in the calculation of lifetime load effect. It should allow for the relative frequency of occurrence of the different forms of traffic and any form of DAF function that may arise. This paper presents such an approach and also presents a general probabilistic DAF formulation for inclusion. Using measured traffic, the approach is applied to a range of bridge lengths and load effects employing a variety of DAF approaches from the literature, in addition to the new DAF formulation. Using a critical traffic index, it is shown that the governing form of traffic is very sensitive to the dynamic amplification model used. Further, depending on this model, congested traffic can govern short spans, and for other spans, a combination of free- and congested-flow traffic states must be considered.

Study on Evaluation Index System of Traffic Simulation under the Concept of Low-Carbon

Evaluation index system of traffic simulation is very important to compare the difference of several cases, which contributes to the advance of traffic simulation models and technologies. Under the concept of low-carbon, the paper establishes evaluation index system of traffic simulation. Firstly, the paper analyzes the requirements of the evaluation index system of traffic simulation from two aspects which are the application characteristics and the application under the concept of low-carbon of traffic simulation models and technologies. On the basis of analysis above, it establishes the evaluation index system of traffic simulation which concludes road network structure index, traffic operation state index, traffic environment index and traffic safety index. It proposes the application rules of evaluation index system. Then, it proposes the two-level combined evaluation method for calculating weights on the basis of comparative analysis about two methods, which are the analytic hierarchy process (AHP) method and entropy method. Finally, it applies the proposed evaluation system to calculate the comprehensive index values of two transit operation cases of Beijing Olympic Games Opening Ceremony audience evacuation. It is shown that evaluation index system of traffic simulation is practicable and effective.

Urban Environment-Oriented Traffic Zoning Based on Spatial Cluster Analysis

Environment-oriented traffic management zoning (TMZ) provides an important way to study spatial variation of urban traffic environment. The TMZ can be used to manage the urban traffic environment and establish regional improvement strategies. In this study, a spatial immune cluster method based on aiNet (Artificial Immune Network) is designed to facilitate the traffic environment zoning. Spatial coordinates are employed to measure the spatial correlation of the traffic system, and the weightings of different indices are calculated with the use of PCA (principle component analysis). For the case of Beijing, the whole city area is divided into evenly distributed grid cells. An urban traffic environment index system is developed to measure the traffic environment condition of different grids based on the concept of traffic sustainability. The GIS (Geographical information System) software of ArcGIS and database programming are used to calculate the indexical values of each grid. In order to classify the grid data set, we use two analysis methods, i.e. immune cluster algorithm and K-mean algorithm, and it is found that the immune cluster algorithm has better performance for the classification. With the use of this method, the study area is divided into 4 zones.

Spatial analysis of bioavailable soil lead concentrations in Los Angeles, California

Lead (Pb) poisoning causes permanent neurologic and developmental disorders and remains an important environmental health problem for US children, despite removal of Pb from gasoline and household paints. To better understand the contribution of Pb from historical traffic and residential Pb based paint to soil Pb concentrations in Los Angeles, we analyzed 550 soil Pb samples from south central Los Angeles County, CA, in relation to land-use patterns (commercial, industrial, residential, and parks and open areas) and proximity to freeways, highways, and major arterials. House age variables (surrogates of historical Pb-based paint) and traffic index variables (surrogates of historical traffic) were created at different buffer distances (10-5000m). Total and bioavailable Pb concentrations near freeways and major arterials were significantly higher than those collected elsewhere. Total and bioavailable Pb concentrations were highly correlated (r=0.96) after the removal of one outlier. Both parcel-age related variables and traffic variables were important predictors of current soil bioavailable Pb concentrations. Average age of parcels within 30m and length of small streets within 3000m explained 57% and 38% of the variance, respectively, in soil bioavailable Pb concentrations in residential areas away from freeways and major arterials (N=44). Road length of freeways within 750m explained 28% of bioavailable Pb concentrations in parks and open areas (N=26). Multi-variable regression models predicted 16-61% of the variances in bioavailable Pb concentrations, depending on land-use type and spatial relationship to roadways. Based on these models a map of spatial distributions of soil Pb concentrations was created for the Los Angeles area that shows promise as a screening tool to evaluate continued Pb poisoning in children.

Residential Traffic Exposure, Pulse Pressure, and C-reactive Protein: Consistency and Contrast among Exposure Characterization Methods

BackgroundTraffic exposure may increase cardiovascular disease (CVD) risk via systemic inflammation and elevated blood pressure, two important clinical markers for managing disease progression.ObjectivesWe assessed degree and consistency of association between traffic exposure indicators as predictors of C-reactive protein (CRP) and pulse pressure (PP) in an adult U.S. Puerto Rican population (n = 1,017).MethodsCross-sectional information on health and demographics and blood data was collected. Using multiple linear regression, we tested for associations between CRP, PP, and six traffic exposure indicators including residential proximity to roads with > 20,000 vehicles/day and traffic density [vehicle miles traveled per square mile (VMT/mi2)]. Diabetes and obesity [body mass index (BMI) ≥ 30 kg/m2] were tested as effect modifiers.ResultsCRP was positively associated with traffic density in the total population [36% CRP difference with 95% confidence interval (CI) 2.5–81%] for residence within the highest versus lowest VMT/mi2 level. With BMI ≥ 30, CRP showed significant positive associations with five of six traffic indices including residence ≤ 200 m versus > 200 m of a roadway [22.7% CRP difference (95% CI, 3.15–46.1)] and traffic density in the third highest versus lowest VMT/mi2 level [28.1% difference (95% CI, 1.0–62.6)]. PP was positively associated with residence within ≤ 100 m of a roadway for the total population [2.2 mmHg (95% CI, 0.13–4.3 mmHg)] and persons with BMI ≥ 30 [3.8 mmHg (95% CI, 0.88–6.8)]. Effect estimates approximately doubled for residence within ≤ 200 m of two or more roadways, particularly in persons with diabetes [8.1 mmHg (95% CI, 2.2–14.1)].ConclusionsTraffic exposure at roadway volumes as low as 20,000–40,000 vehicles/day may increase CVD risk through adverse effects on blood pressure and inflammation. Individuals with elevated inflammation profiles, that is, BMI ≥ 30, may be more susceptible to the effects of traffic exposure.