Search results for: traffic accidents

Authors: A. Das, L. Hitihamillage, S. Moridpour

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Natural disasters are inevitable to the biodiversity. Disasters such as flood, tsunami and tornadoes could be brutal, harsh and devastating. In Australia, flooding is a major issue experienced by different parts of the country. In such crisis, delays in evacuation could decide the life and death of the people living in those regions. Congestion management could become a mammoth task if there are no steps taken before such situations. In the past to manage congestion in such circumstances, many strategies were utilised such as converting the road shoulders to extra lanes or changing the road geometry by adding more lanes. However, expansion of road to resolving congestion problems is not considered a viable option nowadays. The authorities avoid this option due to many reasons, such as lack of financial support and land space. They tend to focus their attention on optimising the current resources they possess and use traffic signals to overcome congestion problems. Traffic Signal Management strategy was considered a viable option, to alleviate congestion problems in the City of Geelong, Victoria. Arterial road with signalised intersections considered in this paper and the traffic data required for modelling collected from VicRoads. Traffic signalling software SIDRA used to model the roads, and the information gathered from VicRoads. In this paper, various signal parameters utilised to assess and improve the corridor performance to achieve the best possible Level of Services (LOS) for the arterial road.

Keywords: congestion, constraints, management, LOS

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Authors: Guneet Saini, Shahrukh, Sunil Sharma

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Traffic congestion is the most critical issue faced by those in the transportation profession today. Over the past few years, roundabouts have been recognized as a measure to promote efficiency at intersections globally. In developing countries like India, this type of intersection still faces a lot of issues, such as bottleneck situations, long queues and increased waiting times, due to increasing traffic which in turn affect the performance of the entire urban network. This research is a case study of a non-conventional roundabout, in terms of geometric design, in a small town in India. These types of roundabouts should be analyzed for their functionality in mixed traffic conditions, prevalent in many developing countries. Microscopic traffic simulation is an effective tool to analyze traffic conditions and estimate various measures of operational performance of intersections such as capacity, vehicle delay, queue length and Level of Service (LOS) of urban roadway network. This study involves analyzation of an unsymmetrical non-circular 6-legged roundabout known as “Kala Aam Chauraha” in a small town Bulandshahr in Uttar Pradesh, India using VISSIM simulation package which is the most widely used software for microscopic traffic simulation. For coding in VISSIM, data are collected from the site during morning and evening peak hours of a weekday and then analyzed for base model building. The model is calibrated on driving behavior and vehicle parameters and an optimal set of calibrated parameters is obtained followed by validation of the model to obtain the base model which can replicate the real field conditions. This calibrated and validated model is then used to analyze the prevailing operational traffic performance of the roundabout which is then compared with a proposed alternative to improve efficiency of roundabout network and to accommodate pedestrians in the geometry. The study results show that the alternative proposed is an advantage over the present roundabout as it considerably reduces congestion, vehicle delay and queue length and hence, successfully improves roundabout performance without compromising on pedestrian safety. The study proposes similar designs for modification of existing non-conventional roundabouts experiencing excessive delays and queues in order to improve their efficiency especially in the case of developing countries. From this study, it can be concluded that there is a need to improve the current geometry of such roundabouts to ensure better traffic performance and safety of drivers and pedestrians negotiating the intersection and hence this proposal may be considered as a best fit.

Keywords: operational performance, roundabout, simulation, VISSIM

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Authors: Mozhgan Aliakbari, Sara Moridpour

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In recent years, much attention has been given to truck drivers’ fatigue management. Long working hours negatively influence truck drivers’ physiology, health, and safety. However, there is little empirical research in the heavy vehicle transport sector in Australia to identify the influence of working hours’ management on drivers’ fatigue and consequently, on the risk of crashes and injuries. There is no national legislation regulating the number of hours or kilometres travelled by truck drivers. Consequently, it is almost impossible to define a standard number of hours or kilometres for truck drivers in a safety management system. This paper reviews the existing studies concerning safe system interventions such as tachographs in relation to fatigue caused by long working hours. This paper also reviews the literature to identify the influence of frequency of rest breaks on the reduction of work-related road transport accidents involving trucks. A framework is presented to manage truck drivers’ fatigue, which may result in the reduction of injuries and fatalities involving heavy vehicles.

Keywords: fatigue, time management, trucks, traffic safety

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Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

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Intelligent Transportation System is an integrated application of communication, control and monitoring and display process technologies for developing a user–friendly transportation system for urban areas in developing countries. In fact, the development of a country and the progress of its transportation system are complementary to each other. Urban traffic has been growing vigorously due to population growth as well as escalation of vehicle ownership causing congestion, delays, pollution, accidents, high-energy consumption and low productivity of resources. The development and management of urban transport in developing countries like India however, is at tryout stage with very few accumulations. Under the umbrella of ITS, urban corridor management strategy have proven to be one of the most successful system in accomplishing these objectives. The present study interprets and figures out the performance of the 27.4 km long Urban Bus route having six intersections, five flyovers and 29 bus stops that covers significant area of the city by causality analysis. Performance interpretations incorporate Passenger Boarding and Alighting, Dwell time, Distance between Bus Stops and Total trip time taken by bus on selected urban route.

Keywords: congestion, dwell time, passengers boarding alighting, travel time

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: parameter calibration, sequential quadratic programming, stochastic user equilibrium, traffic assignment, transportation planning

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Authors: Kankrong Suangka

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This research explored behaviors of toll way users that impact their decision to use the Electronic Toll Collection System (ETC). It also went on to explore and evaluated the efficiency of toll plaza in terms of number of ETC booths in toll plaza and its lane location. The two main parameters selected for the scenarios analyzed were (1) the varying ration of ETC enabled users (2) the varying locations of the dedicated ETC lane. There were a total of 42 scenarios analyzed. Researched data indicated that in A.D.2013, the percentage of ETC user from the total toll user is 22%. It was found that the delay at the payment booth was reduced by increasing the ETC booth by 1 more lane under the condition that the volume of ETC users passing through the plaza less than 1,200 vehicles/hour. Meanwhile, increasing the ETC lanes by 2 lanes can accommodate an increased traffic volume to around 1,200 to 1,800 vehicles/hour. Other than that, in terms of the location of ETC lane, it was found that if for one ETC lane-plazas, installing the ETC lane at the far right are the best alternative. For toll plazas with 2 ETC lanes, the best layout is to have 1 lane in the middle and 1 lane at the far right. This layout shows the least delay when compared to other layouts. Furthermore, the results from this research showed that micro-simulator traffic models have potential for further applications and use in designing toll plaza lanes. Other than that, the results can also be used to analyze the system of the nearby area with similar traffic volume and can be used for further design improvements.

Keywords: the electronic toll collection system, average queuing delay, toll plaza configuration, bioinformatics, biomedicine

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Authors: Zainuddin Zakaria, Sun Woh Lye

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Despite the continuous advancements in automated conflict resolution tools, there is still a low rate of adoption of automation from Air Traffic Control Officers (ATCOs). Trust or acceptance in these tools and conformance to the individual ATCO preferences in strategy execution for conflict resolution are two key factors that impact their use. This paper proposes a methodology to unearth and classify ATCO conflict resolution strategies from simulator data of trained and qualified ATCOs. The methodology involves the extraction of ATCO executive control actions and the establishment of a system of strategy resolution classification based on ATCO radar commands and prevailing flight parameters in deconflicting a pair of aircraft. Six main strategies used to handle various categories of conflict were identified and discussed. It was found that ATCOs were about twice more likely to choose only vertical maneuvers in conflict resolution compared to horizontal maneuvers or a combination of both vertical and horizontal maneuvers.

Keywords: air traffic control strategies, conflict resolution, simulator data, strategy classification system

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Authors: Umut Tac, Leyla Tavacioglu, Pelin Bolat

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Human factor has been one of the elements that cause vulnerabilities which can be resulted with accidents in maritime transportation. When the roots of human factor based accidents are analyzed, gaps in performing cognitive abilities (reaction time, attention, memory…) are faced as the main reasons for the vulnerabilities in complex environment of maritime systems. Thus cognitive processes in maritime systems have arisen important subject that should be investigated comprehensively. At this point, neurocognitive tests such as reaction time analysis tests have been used as coherent tools that enable us to make valid assessments for cognitive status. In this respect, the aim of this study is to evaluate the reaction time (response time or latency) of seafarers due to their occupational experience and age. For this study, reaction time for different maneuverers has been taken while the participants were performing a sea voyage through a simulator which was run up with a certain scenario. After collecting the data for reaction time, a statistical analyze has been done to understand the relation between occupational experience and cognitive abilities.

Keywords: cognitive abilities, human factor, neurocognitive test battery, reaction time

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Authors: Avi Harel

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Most accidents are commonly attributed in hindsight to human errors, yet most methodologies for safety focus on technical issues. According to the Black Swan theory, this paradox is due to insufficient data about the ways systems fail. The article presents a study of the sources of errors, and proposes a methodology for utility-oriented design, comprising methods for coping with each of the sources identified. Accident analysis indicates that errors typically result from difficulties of operating in exceptional conditions. Therefore, following STAMP, the focus should be on preventing exceptions. Exception analysis indicates that typically they involve an improper account of the operational scenario, due to deficiencies in the system integration. The methodology proposes a model, which is a formal definition of the system operation, as well as principles and guidelines for safety-oriented system integration. The article calls to develop and integrate tools for recording and analysis of the system activity during the operation, required to implement validate the model.

Keywords: accidents, complexity, errors, exceptions, interaction, modeling, resilience, risks

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Authors: Saifullah Khalid

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Governance and good governance are among the main topics in international discussions about the success factors for social and economic development. The image of developing countries as for example Pakistan in this respect is bad (in TI Corruption Index nr. among countries). Additionally, the police are among the sectors and organizations which are seen as most corrupt in many countries. However, in case of Pakistan there seem to be exceptions to the rule, and improvement can be brought in specific police departments. This paper represents the findings of Islamabad traffic police (ITP). In Pakistan, the police, in general, have been stigmatized for being the most corrupt department in the country. However, the few recent examples of Motorway police and its replicated model of Islamabad traffic police changed the perception about police and policing. These police forces have shown that Policing in Pakistan can be changed for better. In this paper, the research question that is addressed is: How corrupt are (traffic) police forces in Pakistan and what factors influence corruption within that police force? And What lessons can be learned from that to improve police integrity? Both qualitative and quantitative tools are utilized for data collection. The overall picture of the factors is not so easy to interpret and summarise. Nevertheless paying a better salary does not seem to limit integrity violations, neither does recruitment and selection and leadership, while supervision and control, training and stimulating the positive and limiting the negative elements of culture appear to be important in curbing (sometimes specific) integrity violations in the context of Pakistani police forces. The study also leads to a number of suggestions for curbing corruption and other integrity violations in the Pakistan police.

Keywords: corruption control, governance, integrity violations, Islamabad traffic police, Pakistan

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Authors: Melissa Hachem, Lynda Bensefa-Colas, Isabelle Momas

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We evaluated the impact of the first lockdown restriction measures (March-May 2020) in the Paris area on (1) the variation of in-vehicle ultrafine particle (UFP) and black carbon (BC) concentrations between pre-and post-lockdown period and (2) the professional drivers working conditions and practices. The study was conducted on 33 Parisian taxi drivers. UFP and BC were measured inside their vehicles with DiSCmini® and microAeth®, respectively, on two typical working days before and after the first lockdown. The job-related characteristics were self-reported. Our results showed that after the first lockdown, the number of clients significantly decreased as well as the taxi driver's journey duration. Taxi drivers significantly opened their windows more and reduced the use of air recirculation. UFP decreased significantly by 32% and BC by 31% after the first lockdown, with a weaker positive correlation compared to before the lockdown. The reduction of in-vehicle UFP was explained mainly by the reduction of traffic flow and ventilation settings, though the latter probably varied according to the traffic condition. No predictor explained the variation of in-vehicle BC concentration between pre-and post-lockdown periods, suggesting different sources of UFP and BC. The road traffic was not anymore the dominant source of BC post-lockdown. We emphasize the role of traffic emissions on in-vehicle air pollution and that preventive measures such as ventilation settings will help to better manage air quality inside a vehicle in order to minimize exposure of professional drivers, as well as passengers, to air pollutants.

Keywords: black carbon, COVID-19, France, lockdown, taxis, ultrafine particles

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Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

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Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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Authors: Ren Moses, Jaqueline Masaki

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This paper addresses the need for accurate and updated vehicle classification system through a thorough evaluation of vehicle class categories to identify errors arising from the existing system and proposing modifications. The data collected from two permanent traffic monitoring sites in Florida were used to evaluate the performance of the existing vehicle classification table. The vehicle data were collected and classified by the automatic vehicle classifier (AVC), and a video camera was used to obtain ground truth data. The Federal Highway Administration (FHWA) vehicle classification definitions were used to define vehicle classes from the video and compare them to the data generated by AVC in order to identify the sources of misclassification. Six types of errors were identified. Modifications were made in the classification table to improve the classification accuracy. The results of this study include the development of updated vehicle classification table with a reduction in total error by 5.1%, a step by step procedure to use for evaluation of vehicle classification studies and recommendations to improve FHWA 13-category rule set. The recommendations for the FHWA 13-category rule set indicate the need for the vehicle classification definitions in this scheme to be updated to reflect the distribution of current traffic. The presented results will be of interest to States’ transportation departments and consultants, researchers, engineers, designers, and planners who require accurate vehicle classification information for planning, designing and maintenance of transportation infrastructures.

Keywords: vehicle classification, traffic monitoring, pavement design, highway traffic

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Authors: Ruchi Sharma, Rajasekhar Balasubramanian

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Motor vehicles emit a number of air pollutants, among which fine particulate matter (PM₂.₅) is of major concern in cities with high population density due to its negative impacts on air quality and human health. Typically, people spend more than 80% of their time indoors. Consequently, human exposure to traffic-related PM₂.₅ in indoor environments has received considerable attention. Most of the public residential buildings in tropical countries are designed for natural ventilation where indoor air quality tends to be strongly affected by the migration of air pollutants of outdoor origin. However, most of the previously reported traffic-related PM₂.₅ exposure assessment studies relied on ambient PM₂.₅ concentrations and thus, the health impact of traffic-related PM₂.₅ on occupants in naturally ventilated buildings remains largely unknown. Therefore, a systematic field study was conducted to assess indoor human exposure to traffic-related PM₂.₅ with and without mitigation measures in a typical naturally ventilated residential apartment situated near a road carrying a large volume of traffic. Three PM₂.₅ exposure scenarios were simulated in this study, i.e., Case 1: keeping all windows open with a ceiling fan on as per the usual practice, Case 2: keeping all windows fully closed as a mitigation measure, and Case 3: keeping all windows fully closed with the operation of a portable indoor air cleaner as an additional mitigation measure. The indoor to outdoor (I/O) ratios for PM₂.₅ mass concentrations were assessed and the effectiveness of using the indoor air cleaner was quantified. Additionally, potential human health risk based on the bioavailable fraction of toxic trace elements was also estimated for the three cases in order to identify a suitable mitigation measure for reducing PM₂.₅ exposure indoors. Traffic-related PM₂.₅ levels indoors exceeded the air quality guidelines (12 µg/m³) in Case 1, i.e., under natural ventilation conditions due to advective flow of outdoor air into the indoor environment. However, while using the indoor air cleaner, a significant reduction (p < 0.05) in the PM₂.₅ exposure levels was noticed indoors. Specifically, the effectiveness of the air cleaner in terms of reducing indoor PM₂.₅ exposure was estimated to be about 74%. Moreover, potential human health risk assessment also indicated a substantial reduction in potential health risk while using the air cleaner. This is the first study of its kind that evaluated the indoor human exposure to traffic-related PM₂.₅ and identified a suitable exposure mitigation measure that can be implemented in densely populated cities to realize health benefits.

Keywords: fine particulate matter, indoor air cleaner, potential human health risk, vehicular emissions

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: accident analysis, multi-factorial error modeling, risk, systemic methods

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Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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Authors: Huey-Kuo Chen

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Travel demand forecasting including four travel choices, i.e., trip generation, trip distribution, modal split and traffic assignment constructs the core of transportation planning. In its current application, travel demand forecasting has associated with three important issues, i.e., interface inconsistencies among four travel choices, inefficiency of commonly used solution algorithms, and undesirable multiple path solutions. In this paper, each of the three issues is extensively elaborated. An ideal unified framework for the combined model consisting of the four travel choices and variable demand functions is also suggested. Then, a few remarks are provided in the end of the paper.

Keywords: travel choices, B algorithm, entropy maximization, dynamic traffic assignment

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Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

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Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

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Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.

Keywords: mechanistic-empirical pavement design guide (MEPDG), traffic characteristics, materials properties, climate, Riyadh

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Authors: M. Sadique, S. Ainane, Y. F. Yap, P. Rostron, E. Al Hajri

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The presence of sand in production lines in the oil and gas industries causes material degradation due to erosion-corrosion. The material degradation caused by erosion-corrosion in pipelines can result in a high cost of monitoring and maintenance and in major accidents. The process of erosion-corrosion consists of erosion, corrosion, and their interactions. Investigating and understanding how the erosion-corrosion process affects the degradation process in certain materials will allow for a reduction in economic loss and help prevent accidents. In this study, material loss due to erosion-corrosion of mild steel under impingement of sand-laden water at 90˚ impingement angle is investigated using a submerged impingement jet (SIJ) test. In particular, effects of jet velocity and sand loading on TWL due to erosion-corrosion, weight loss due to pure erosion and erosion-corrosion interactions, at a temperature of 29-33 °C in sea water environment (3.5% NaCl), are analyzed. The results show that the velocity and sand loading have a great influence on the removal of materials, and erosion is more dominant under all conditions studied. Changes in the surface characteristics of the specimen after impingement test are also discussed.

Keywords: erosion-corrosion, flow velocity, jet impingement, sand loading

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Authors: Prajamitra Bhuyan

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Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

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Authors: Amin Hamrahi, Niloofar Moghaddam

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Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

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Authors: Qiang Zhang, Xiaojian Hu1

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Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.

Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Yaser Miaji, Mohammed Aloryani

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The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

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Authors: Myoung-Jin Lee, Sung-Jin Lee, Young-Kon Park, Jin-Wook Kim, Bo-Kyoung Kim, Song-Hun Chong, Sun-Il Kim

Abstract:

Currently, sinkholes may occur due to natural or unknown causes. When the sinkhole is an instantaneous phenomenon, most accidents occur because of significant damage. Thus, methods of monitoring are being actively researched, such that the impact of the accident can be mitigated. A sinkhole can severely affect and wreak havoc in community-based facilities such as a city railway construction. Therefore, the development of a laser / scanning system and an image-based tunnel is one method of pre-monitoring that it stops the accidents. The laser scanning is being used but this has shortcomings as it involves the development of expensive equipment. A laser / videobased scanning tunnel is being developed at Korea Railroad Research Institute. This is designed to automatically operate the railway. The purpose of the scanning is to obtain an image of the city such as of railway structures (stations, tunnel). At the railway structures, it has developed 3D laser scanning that can find a micro-crack can not be distinguished by the eye. An additional aim is to develop technology to monitor the status of the railway structure without the need for expensive post-processing of 3D laser scanning equipment, by developing corresponding software.

Keywords: 3D laser scanning, sinkhole, tunnel, city railway construction

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Authors: P. N. Salini, B. Anish Kini, R. Ashalatha

Abstract:

At signalized intersections with heterogeneous traffic, the percentage share of different vehicle categories have a bearing on the inter-vehicle space utilization, which eventually impacts the saturation flow. This paper analyzed the impact of the percentage share of various vehicle categories in the traffic stream on the saturation flow at signalized intersections by video graphing major intersections with varying geometry in Kerala, India. It was found that as the percentage share of two-wheelers increases, the saturation flow at signalized intersections increases and vice-versa for the percentage share of cars. The effect of bus blockage and parking maneuvers on the saturation flow were also studied. As the distance of bus blockage increases from the stop line, the effect on the saturation flow decreases, while with more buses stopping at the same bus stop, the saturation flow reduces further. The study revealed that with higher kerbside parking maneuvers on the upstream, the saturation flow reduces, and with an increase in the distance of the parking maneuver from the stop line, the effect on the saturation flow decreases. The adjustment factors for bus blockage due to bus stops within 75m downstream and parking maneuvers within 75m upstream of the intersection have been established for mixed traffic conditions. These adjustment factors could empower the urban planners, enforcement personnel and decision-makers to estimate the reduction in the capacity of signalized intersections for suggesting improvements in the form of parking restrictions/ bus stop relocation for existing intersections or make design changes for planned intersections.

Keywords: signalized intersection, saturation flow, adjustment factors, capacity

Procedia PDF Downloads 91

Authors: Ren Moses

Abstract:

The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: A. C. Dey, H. M. Ahsan

Abstract:

Heterogeneous traffic composed of both motorized and non-motorized vehicles that are a common feature of urban Bangladeshi roads. Popular non-motorized vehicles include rickshaws, rickshaw-van, and bicycle. These modes performed an important role in moving people and goods in the absence of a dependable mass transport system. However, rickshaws play a major role in meeting the demand for door-to-door public transport services to the city dwellers. But there is no separate lane for non-motorized vehicles in this city. Non-motorized vehicles generally occupy the outermost or curb-side lanes, however, at intersections non-motorized vehicles get mixed with the motorized vehicles. That’s why the conventional models fail to analyze the situation completely. Microscopic traffic simulation software VISSIM 5.3, itself a lane base software but default behavioral parameters [such as driving behavior, lateral distances, overtaking tendency, CCO=0.4m, CC1=1.5s] are modified for calibrating a model to analyze the effects of non-motorized traffic at an intersection (Mirpur-10) in a non-lane based mixed traffic condition. It is seen from field data that NMV occupies an average 20% of the total number of vehicles almost all the link roads. Due to the large share of non-motorized vehicles, capacity significantly drop. After analyzing simulation raw data, significant variation is noticed. Such as the average vehicular speed is reduced by 25% and the number of vehicles decreased by 30% only for the presence of NMV. Also the variation of lateral occupancy and queue delay time increase by 2.37% and 33.75% respectively. Thus results clearly show the negative effects of non-motorized vehicles on capacity at an intersection. So special management technics or restriction of NMV at major intersections may be an effective solution to improve this existing critical condition.

Keywords: lateral occupancy, non lane based intersection, nmv, queue delay time, VISSIM 5.3

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Authors: Yoshitaka Ooya, Daishuke Furuya, Manabu Nemoto

Abstract:

Some countries such as Canada and Australia have mandatory bicycle helmet laws for all citizens and age groups. As of 2008 Japan has also adopted a helmet law but it is restricted to people 13 years old and under. People over 13 years of age are not required to wear helmets in Japan. Currently, the rate that people 0-13 years old actually wear helmets is low. In 2013 a number of patients came to Saitama University Hospital International Medical Center for treatment due to bicycle-related trauma. The total number of patients was 89 (55 male and 34 female). The average age of the patients was 40.9 years old (eldest; 83 y/o, median; 40 y/o, youngest; 1 y/o with a standard deviation ± 2.8). 54 of these patients (61%) experienced head trauma as well as some experiencing multiple injuries associated with their accident. 13 patients were wearing helmets, 50 patients were not wearing helmets and it is unknown if the remaining 26 patients were wearing helmets. This information was acquired from the patient`s medical charts. Only one patient who was wearing a helmet had a severe head injury, and this patient also experienced other multiple injuries. 17 patients who were not wearing helmets had severe head injuries and out of the 17, two had multiple injuries. The mechanism for injury varied. 12 patients were injured in an accident with a vehicle, only one of which was wearing a helmet. This patient also had multiple injuries. Of the other 11 patients, two had multiple injuries. The remaining patient`s injuries were caused by other accidents (3; fell over while riding, 2; crashed into an inanimate object, 1; collided with a motorcycle). The ladder of which had a severe head injury. All of these patients had light energy accidents and were all over 13 years of age. In Japan it is not mandatory for people over the age of 13 years to wear a bicycle helmet. Research shows that light energy accidents were mostly present in people over the age of 13, to which the law does not require the wearing of helmets. It is important that all people in all age groups be required to wear helmets when operating a bicycle to reduce the rate of light energy severe head injuries.

Keywords: bicycle helmet, head trauma, hospital, traumatic situation

Procedia PDF Downloads 339