Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Variable Speed Limit Strategies to Reduce the Impacts of Traffic Flow Breakdown at Recurrent Freeway Bottlenecks

Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

The economic costs of road traffic crashes: Australia, states and territories

In this paper, we obtain detailed data on road traffic crash (RTC) casualties, by severity, for each of the eight state and territory jurisdictions for Australia and use these to estimate and compare the economic impact of RTCs across these regions. We show that the annual cost of RTCs in Australia, in 2003, was approximately $17b, which is approximately 2.3% of the Gross Domestic Product (GDP). Importantly, though, there is remarkable intra-national variation in the incident rates of RTCs in Australia and costs range from approximately 0.62 to 3.63% of Gross State Product (GSP). The paper makes two fundamental contributions: (i) it provides a detailed breakdown of estimated RTC casualties, by state and territory regions in Australia, and (ii) it presents the first sub-national breakdown of RTC costs for Australia. We trust that these contributions will assist policy-makers to understand sub-national variations in the road toll better and will encourage further research on the causes of the marked differences between RTC outcomes across the states and territories of Australia. (c) 2006 Elsevier Ltd. All rights reserved.

Air pollution levels measured at traffic hot spots : Brisbane urban corridor study

Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.

Long-term trends in fine particle number concentrations in the urban atmosphere of Brisbane : the relevance of traffic emissions and new particle formation

The measurement of submicrometre (< 1.0 m) and ultrafine particles (diameter < 0.1 m) number concentration have attracted attention since the last decade because the potential health impacts associated with exposure to these particles can be more significant than those due to exposure to larger particles. At present, ultrafine particles are not regularly monitored and they are yet to be incorporated into air quality monitoring programs. As a result, very few studies have analysed their long-term and spatial variations in ultrafine particle concentration, and none have been in Australia. To address this gap in scientific knowledge, the aim of this research was to investigate the long-term trends and seasonal variations in particle number concentrations in Brisbane, Australia. Data collected over a five-year period were analysed using weighted regression models. Monthly mean concentrations in the morning (6:00-10:00) and the afternoon (16:00-19:00) were plotted against time in months, using the monthly variance as the weights. During the five-year period, submicrometre and ultrafine particle concentrations increased in the morning by 105.7% and 81.5% respectively whereas in the afternoon there was no significant trend. The morning concentrations were associated with fresh traffic emissions and the afternoon concentrations with the background. The statistical tests applied to the seasonal models, on the other hand, indicated that there was no seasonal component. The spatial variation in size distribution in a large urban area was investigated using particle number size distribution data collected at nine different locations during different campaigns. The size distributions were represented by the modal structures and cumulative size distributions. Particle number peaked at around 30 nm, except at an isolated site dominated by diesel trucks, where the particle number peaked at around 60 nm. It was found that ultrafine particles contributed to 82%-90% of the total particle number. At the sites dominated by petrol vehicles, nanoparticles (< 50 nm) contributed 60%-70% of the total particle number, and at the site dominated by diesel trucks they contributed 50%. Although the sampling campaigns took place during different seasons and were of varying duration these variations did not have an effect on the particle size distributions. The results suggested that the distributions were rather affected by differences in traffic composition and distance to the road. To investigate the occurrence of nucleation events, that is, secondary particle formation from gaseous precursors, particle size distribution data collected over a 13 month period during 5 different campaigns were analysed. The study area was a complex urban environment influenced by anthropogenic and natural sources. The study introduced a new application of time series differencing for the identification of nucleation events. To evaluate the conditions favourable to nucleation, the meteorological conditions and gaseous concentrations prior to and during nucleation events were recorded. Gaseous concentrations did not exhibit a clear pattern of change in concentration. It was also found that nucleation was associated with sea breeze and long-range transport. The implications of this finding are that whilst vehicles are the most important source of ultrafine particles, sea breeze and aged gaseous emissions play a more important role in secondary particle formation in the study area.

Creating a proactive decision-support environment in managing road traffic noise

Properly designed decision support environments encourage proactive and objective decision making. The work presented in this paper inquires into developing a decision support environment and a tool to facilitate objective decision making in dealing with road traffic noise. The decision support methodology incorporates traffic amelioration strategies both within and outside the road reserve. The project is funded by the CRC for Construction Innovation and conducted jointly by the RMIT University and the Queensland Department of Main Roads (MR) in collaboration with the Queensland Department of Public Works, Arup Pty Ltd., and the Queensland University of Technology. In this paper, the proposed decision support framework is presented in the way of a flowchart which enabled the development of the decision support tool (DST). The underpinning concept is to establish and retain an information warehouse for each critical road segment (noise corridor) for a given planning horizon. It is understood that, in current practice, some components of the approach described are already in place but not fully integrated and supported. It provides an integrated user-friendly interface between traffic noise modeling software, noise management criteria and cost databases.

Comparative study : health research on traffic noise pollution vs. Technical research on traffic noise mitigation

Community awareness and the perception on the traffic noise related health impacts have increased significantly over the last decade resulting in a large volume of public inquiries flowing to Road Authorities for planning advice. Traffic noise management in the urban environment is therefore becoming a “social obligation”, essentially due to noise related health concerns. Although various aspects of urban noise pollution and mitigation have been researched independently, an integrated approach by stakeholders has not been attempted. Although the current treatment and mitigation strategies are predominantly handled by the Road Agencies, a concerted effort by all stakeholders is becoming mandatory for effective and tangible outcomes in the future. A research project is underway a RMIT University, Australia, led by the second author to consider the use of “hedonic pricing” for alternative noise amelioration treatments within the road reserve and outside the road reserve. The project aims to foster a full range noise abatement strategy encompassing source, path and noise receiver. The benefit of such a study would be to mitigate the problem where it is most effective and would defuse traditional “authority” boundaries to produce the optimum outcome. The project is conducted in collaboration with the Department of Main Roads Queensland, Australia and funded by the CRC for Construction Innovation. As part of this study, a comprehensive literature search is currently underway to investigate the advancements in community health research, related to environmental noise pollution, and the advancements in technical and engineering research in mitigating the issue. This paper presents the outcomes of this work outlining state of the art, national and international good practices and gap analysis to identify major anomalies and developments.

Increase in particle number emissions from motor vehicles due to interruption of steady traffic flow

We assess the increase in particle number emissions from motor vehicles driving at steady speed when forced to stop and accelerate from rest. Considering the example of a signalized pedestrian crossing on a two-way single-lane urban road, we use a complex line source method to calculate the total emissions produced by a specific number and mix of light petrol cars and diesel passenger buses and show that the total emissions during a red light is significantly higher than during the time when the light remains green. Replacing two cars with one bus increased the emissions by over an order of magnitude. Considering these large differences, we conclude that the importance attached to particle number emissions in traffic management policies be reassessed in the future.

Modelling ideal turbulent vortex breakdown

In this computational study we investigate the role of turbulence in ideal axisymmetric vortex breakdown. A pipe geometry with a slight constriction near the inlet is used to stabilise the location of the breakdown within the computed domain. Eddy-viscosity and differential Reynolds stress models are used to model the turbulence. Changes in upstream turbulence levels, flow Reynolds and Swirl numbers are considered. The different computed solutions are monitored for indications of different breakdown flow configurations. Trends in vortex breakdown due to turbulent flow conditions are identified and discussed.

Characterising anomalous events using change point correlation on unsolicited network traffic

Monitoring unused or dark IP addresses offers opportunities to extract useful information about both on-going and new attack patterns. In recent years, different techniques have been used to analyze such traffic including sequential analysis where a change in traffic behavior, for example change in mean, is used as an indication of malicious activity. Change points themselves say little about detected change; further data processing is necessary for the extraction of useful information and to identify the exact cause of the detected change which is limited due to the size and nature of observed traffic. In this paper, we address the problem of analyzing a large volume of such traffic by correlating change points identified in different traffic parameters. The significance of the proposed technique is two-fold. Firstly, automatic extraction of information related to change points by correlating change points detected across multiple traffic parameters. Secondly, validation of the detected change point by the simultaneous presence of another change point in a different parameter. Using a real network trace collected from unused IP addresses, we demonstrate that the proposed technique enables us to not only validate the change point but also extract useful information about the causes of change points.

Use of Probe Vehicles to Increase Traffic Estimation Accuracy in Brisbane

Traffic congestion is an increasing problem with high costs in financial, social and personal terms. These costs include psychological and physiological stress, aggressivity and fatigue caused by lengthy delays, and increased likelihood of road crashes. Reliable and accurate traffic information is essential for the development of traffic control and management strategies. Traffic information is mostly gathered from in-road vehicle detectors such as induction loops. Traffic Message Chanel (TMC) service is popular service which wirelessly send traffic information to drivers. Traffic probes have been used in many cities to increase traffic information accuracy. A simulation to estimate the number of probe vehicles required to increase the accuracy of traffic information in Brisbane is proposed. A meso level traffic simulator has been developed to facilitate the identification of the optimal number of probe vehicles required to achieve an acceptable level of traffic reporting accuracy. Our approach to determine the optimal number of probe vehicles required to meet quality of service requirements, is to simulate runs with varying numbers of traffic probes. The simulated traffic represents Brisbane’s typical morning traffic. The road maps used in simulation are Brisbane’s TMC maps complete with speed limits and traffic lights. Experimental results show that that the optimal number of probe vehicles required for providing a useful supplement to TMC (induction loop) data lies between 0.5% and 2.5% of vehicles on the road. With less probes than 0.25%, little additional information is provided, while for more probes than 5%, there is only a negligible affect on accuracy for increasingly many probes on the road. Our findings are consistent with on-going research work on traffic probes, and show the effectiveness of using probe vehicles to supplement induction loops for accurate and timely traffic information.

Sunglasses, traffic signals, and color vision deficiencies

Purpose: To determine (a) the effect of different sunglass tint colorations on traffic signal detection and recognition for color normal and color deficient observers, and (b) the adequacy of coloration requirements in current sunglass standards. Methods: Twenty color-normals and 49 color-deficient males performed a tracking task while wearing sunglasses of different colorations (clear, gray, green, yellow-green, yellow-brown, red-brown). At random intervals, simulated traffic light signals were presented against a white background at 5° to the right or left and observers were instructed to identify signal color (red/yellow/green) by pressing a response button as quickly as possible; response times and response errors were recorded. Results: Signal color and sunglass tint had significant effects on response times and error rates (p < 0.05), with significant between-color group differences and interaction effects. Response times for color deficient people were considerably slower than color normals for both red and yellow signals for all sunglass tints, but for green signals they were only noticeably slower with the green and yellow-green lenses. For most of the color deficient groups, there were recognition errors for yellow signals combined with the yellow-green and green tints. In addition, deuteranopes had problems for red signals combined with red-brown and yellow-brown tints, and protanopes had problems for green signals combined with the green tint and for red signals combined with the red-brown tint. Conclusions: Many sunglass tints currently permitted for drivers and riders cause a measurable decrement in the ability of color deficient observers to detect and recognize traffic signals. In general, combinations of signals and sunglasses of similar colors are of particular concern. This is prima facie evidence of a risk in the use of these tints for driving and cautions against the relaxation of coloration limits in sunglasses beyond those represented in the study.