Search results for: traffic volume
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3613

Search results for: traffic volume

3463 Driver Behavior Analysis and Inter-Vehicular Collision Simulation Approach

Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

Abstract:

The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

Procedia PDF Downloads 159
3462 Traffic Prediction with Raw Data Utilization and Context Building

Authors: Zhou Yang, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is essential in a multitude of ways in modern urban life. The researchers of earlier work in this domain carry out the investigation chiefly with two major focuses: (1) the accurate forecast of future values in multiple time series and (2) knowledge extraction from spatial-temporal correlations. However, two key considerations for traffic prediction are often missed: the completeness of raw data and the full context of the prediction timestamp. Concentrating on the two drawbacks of earlier work, we devise an approach that can address these issues in a two-phase framework. First, we utilize the raw trajectories to a greater extent through building a VLA table and data compression. We obtain the intra-trajectory features with graph-based encoding and the intertrajectory ones with a grid-based model and the technique of back projection that restore their surrounding high-resolution spatial-temporal environment. To the best of our knowledge, we are the first to study direct feature extraction from raw trajectories for traffic prediction and attempt the use of raw data with the least degree of reduction. In the prediction phase, we provide a broader context for the prediction timestamp by taking into account the information that are around it in the training dataset. Extensive experiments on several well-known datasets have verified the effectiveness of our solution that combines the strength of raw trajectory data and prediction context. In terms of performance, our approach surpasses several state-of-the-art methods for traffic prediction.

Keywords: traffic prediction, raw data utilization, context building, data reduction

Procedia PDF Downloads 104
3461 Development of Pothole Management Method Using Automated Equipment with Multi-Beam Sensor

Authors: Sungho Kim, Jaechoul Shin, Yujin Baek, Nakseok Kim, Kyungnam Kim, Shinhaeng Jo

Abstract:

The climate change and increase in heavy traffic have been accelerating damages that cause the problems such as pothole on asphalt pavement. Pothole causes traffic accidents, vehicle damages, road casualties and traffic congestion. A quick and efficient maintenance method is needed because pothole is caused by stripping and accelerates pavement distress. In this study, we propose a rapid and systematic pothole management by developing a pothole automated repairing equipment including a volume measurement system of pothole. Three kinds of cold mix asphalt mixture were investigated to select repair materials. The materials were evaluated for satisfaction with quality standard and applicability to automated equipment. The volume measurement system of potholes was composed of multi-sensor that are combined with laser sensor and ultrasonic sensor and installed in front and side of the automated repair equipment. An algorithm was proposed to calculate the amount of repair material according to the measured pothole volume, and the system for releasing the correct amount of material was developed. Field test results showed that the loss of repair material amount could be reduced from approximately 20% to 6% per one point of pothole. Pothole rapid automated repair equipment will contribute to improvement on quality and efficient and economical maintenance by not only reducing materials and resources but also calculating appropriate materials. Through field application, it is possible to improve the accuracy of pothole volume measurement, to correct the calculation of material amount, and to manage the pothole data of roads, thereby enabling more efficient pavement maintenance management. Acknowledgment: The author would like to thank the MOLIT(Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: automated equipment, management, multi-beam sensor, pothole

Procedia PDF Downloads 210
3460 A POX Controller Module to Collect Web Traffic Statistics in SDN Environment

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

Abstract:

Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

Procedia PDF Downloads 211
3459 Preparing Data for Calibration of Mechanistic-Empirical Pavement Design Guide in Central Saudi Arabia

Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman

Abstract:

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

Procedia PDF Downloads 210
3458 NO2 Exposure Effect on the Occurrence of Pulmonary Dysfunction the Police Traffic in Jakarta

Authors: Bambang Wispriyono, Satria Pratama, Haryoto Kusnoputranto, Faisal Yunus, Meliana Sari

Abstract:

Introduction/objective: The impact of the development of motor vehicles is increasing the number of pollutants in the air. One of the substances that cause serious health problems is NO2. The health impacts arising from exposure to NO2 include pulmonary function impairment. The purpose of this study was to determine the relationship of NO2 exposure on the incidence of pulmonary function impairment. Methods: We are using a cross-sectional study design with 110 traffic police who were divided into two groups: exposed (police officers working on the highway) and the unexposed group (police officers working in the office). Election subject convenient sampling carried out in each group to the minimum number of samples met. Results: The results showed that the average NO2 in the exposed group was 18.72 ppb and unexposed group is 4.14 ppb. Pulmonary dysfunction on exposed and unexposed groups showed that FVC (Forced Vital Capacity) value are 88.68 and 90.27. And FEV1 (Forced Expiratory Volume in One) value are 94.9 and 95.16. Some variables like waist circumference, Body Mass Index, Visceral Fat, and Fat has associated with the incidence of Pulmonary Dysfunction (p < 0.05). Conclusion: Health monitoring is needed to decreasing health risk in Policeman.

Keywords: NO2, pulmonary dysfunction, police traffic, Jakarta

Procedia PDF Downloads 238
3457 The Impact of Initiators on Fast Drying Traffic Marking Paint

Authors: Maryam Taheri, Mehdi Jahanfar, Kenji Ogino

Abstract:

Fast drying traffic marking paint comprising a solvent-borne resin, a filler, a pigment and a solvent that is especially suitable for colder ambient (temperatures near freezing) applications, where waterborne traffic paint cannot be used. Acrylic resins based on methyl methacrylate, butyl acrylate, acrylic acid, and styrene were synthesized in different solvents using organic peroxide initiators such as peroxyester, peroxyketal, dialkylperoxide and azo. After polymerization, the molecular weight (Mw), polydispersity index= PDI (Mw/Mn), viscosity, total residual monomer and APHA color were evaluated and results of organic peroxide initiators (t- butyl and t-amyl derivatives) were also compared with the azo initiator. The Mw, PDI, viscosity, mass conversation and APHA color of resins with t-amyl derivatives of organic peroxide initiators are very proper. The results of the traffic marking paints test such as non-volatile matter, no- pick- up time, hiding power, resistance to wear and water resistance study that produced with these resins also confirm this.

Keywords: fast drying traffic marking paint, acrylic resin, organic peroxide initiator, peroxyester, peroxyketal, dialkylperoxide and azo initiator

Procedia PDF Downloads 185
3456 Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow

Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

Abstract:

The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

Procedia PDF Downloads 131
3455 A New Car-Following Model with Consideration of the Brake Light

Authors: Zhiyuan Tang, Ju Zhang, Wenyuan Wu

Abstract:

In this research, a car-following model with consideration of the status of the brake light is proposed. The numerical results show that the stability of the traffic flow is improved. The ability of the brake light to reduce car accident is also showed.

Keywords: brake light, car-following model, traffic flow, regional planning, transportation

Procedia PDF Downloads 559
3454 A Study of Cloud Computing Solution for Transportation Big Data Processing

Authors: Ilgin Gökaşar, Saman Ghaffarian

Abstract:

The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

Procedia PDF Downloads 434
3453 Real Time Traffic Performance Study over MPLS VPNs with DiffServ

Authors: Naveed Ghani

Abstract:

With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

Procedia PDF Downloads 407
3452 Mobile Traffic Management in Congested Cells using Fuzzy Logic

Authors: A. A. Balkhi, G. M. Mir, Javid A. Sheikh

Abstract:

To cater the demands of increasing traffic with new applications the cellular mobile networks face new changes in deployment in infrastructure for making cellular networks heterogeneous. To reduce overhead processing the densely deployed cells require smart behavior with self-organizing capabilities with high adaptation to the neighborhood. We propose self-organization of unused resources usually excessive unused channels of neighbouring cells with densely populated cells to reduce handover failure rates. The neighboring cells share unused channels after fulfilling some conditional candidature criterion using threshold values so that they are not suffered themselves for starvation of channels in case of any abrupt change in traffic pattern. The cells are classified as ‘red’, ‘yellow’, or ‘green’, as per the available channels in cell which is governed by traffic pattern and thresholds. To combat the deficiency of channels in red cell, migration of unused channels from under-loaded cells, hierarchically from the qualified candidate neighboring cells is explored. The resources are returned back when the congested cell is capable of self-contained traffic management. In either of the cases conditional sharing of resources is executed for enhanced traffic management so that User Equipment (UE) is provided uninterrupted services with high Quality of Service (QoS). The fuzzy logic-based simulation results show that the proposed algorithm is efficiently in coincidence with improved successful handoffs.

Keywords: candidate cell, channel sharing, fuzzy logic, handover, small cells

Procedia PDF Downloads 103
3451 Evaluation of the Impact of Pavement Roughness on Vehicle Emissions by HDM-4

Authors: Muhammad Azhar, Arshad Hussain

Abstract:

Vehicular emissions have increased in recent years due to rapid growth in world traffic resulting in an increase in associated problems such as air pollution and climate change, therefore it’s necessary to control vehicle emissions. This study looks at the effect of road maintenance on vehicle emissions. The Highway Development and Management Tool (HDM-4) was used to find the effect of road maintenance on vehicle emissions. Key data collected were traffic volume and composition, vehicle characteristics, pavement characteristics and climate data of the study area. Two options were analysed using the HDM-4 software; the base case or do nothing while the second is overlay maintenance. The study also showed a strong correlation between average roughness and yearly emission levels in both the alternatives. Finally, the study showed that proper maintenance reduces the roughness and emissions.

Keywords: vehicle emissions, road roughness, IRI, maintenance, HDM-4, CO2

Procedia PDF Downloads 244
3450 Measuring and Evaluating the Effectiveness of Mobile High Efficiency Particulate Air Filtering on Particulate Matter within the Road Traffic Network of a Sample of Non-Sparse and Sparse Urban Environments in the UK

Authors: Richard Maguire

Abstract:

This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

Procedia PDF Downloads 109
3449 Traffic Safety and Risk Assessment Model by Analysis of Questionnaire Survey: A Case Study of S. G. Highway, Ahmedabad, India

Authors: Abhijitsinh Gohil, Kaushal Wadhvaniya, Kuldipsinh Jadeja

Abstract:

Road Safety is a multi-sectoral and multi-dimensional issue. An effective model can assess the risk associated with highway safety. A questionnaire survey is very essential to identify the events or activities which are causing unsafe condition for traffic on an urban highway. A questionnaire of standard questions including vehicular, human and infrastructure characteristics can be made. Responses from the age wise group of road users can be taken on field. Each question or an event holds a specific risk weightage, which contributes in creating an inappropriate and unsafe flow of traffic. The probability of occurrence of an event can be calculated from the data collected from the road users. Finally, the risk score can be calculated by considering the risk factor and the probability of occurrence of individual event and addition of all risk score for the individual event will give the total risk score of a particular road. Standards for risk score can be made and total risk score can be compared with the standards. Thus road can be categorized based on risk associated and traffic safety on it. With this model, one can assess the need for traffic safety improvement on a given road, and qualitative data can be analysed.

Keywords: probability of occurrence, questionnaire, risk factor, risk score

Procedia PDF Downloads 324
3448 Mining Riding Patterns in Bike-Sharing System Connecting with Public Transportation

Authors: Chong Zhang, Guoming Tang, Bin Ge, Jiuyang Tang

Abstract:

With the fast growing road traffic and increasingly severe traffic congestion, more and more citizens choose to use the public transportation for daily travelling. Meanwhile, the shared bike provides a convenient option for the first and last mile to the public transit. As of 2016, over one thousand cities around the world have deployed the bike-sharing system. The combination of these two transportations have stimulated the development of each other and made significant contribution to the reduction of carbon footprint. A lot of work has been done on mining the riding behaviors in various bike-sharing systems. Most of them, however, treated the bike-sharing system as an isolated system and thus their results provide little reference for the public transit construction and optimization. In this work, we treat the bike-sharing and public transit as a whole and investigate the customers’ bike-and-ride behaviors. Specifically, we develop a spatio-temporal traffic delivery model to study the riding patterns between the two transportation systems and explore the traffic characteristics (e.g., distributions of customer arrival/departure and traffic peak hours) from the time and space dimensions. During the model construction and evaluation, we make use of large open datasets from real-world bike-sharing systems (the CitiBike in New York, GoBike in San Francisco and BIXI in Montreal) along with corresponding public transit information. The developed two-dimension traffic model, as well as the mined bike-and-ride behaviors, can provide great help to the deployment of next-generation intelligent transportation systems.

Keywords: riding pattern mining, bike-sharing system, public transportation, bike-and-ride behavior

Procedia PDF Downloads 753
3447 Mitigation of Indoor Human Exposure to Traffic-Related Fine Particulate Matter (PM₂.₅)

Authors: Ruchi Sharma, Rajasekhar Balasubramanian

Abstract:

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

Procedia PDF Downloads 107
3446 Research on Road Openness in the Old Urban Residential District Based on Space Syntax: A Case Study on Kunming within the First Loop Road

Authors: Haoyang Liang, Dandong Ge

Abstract:

With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

Procedia PDF Downloads 134
3445 VISSIM Modeling of Driver Behavior at Connecticut Roundabouts

Authors: F. Clara Fang, Hernan Castaneda

Abstract:

The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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3444 Activating Psychological Resources of DUI (Drivers under the Influence of Alcohol) Using the Traffic Psychology Intervention (IFT Course), Germany

Authors: Parichehr Sharifi, Konrad Reschke, Hans-Liudger Dienel

Abstract:

Psychological intervention generally targets changes in attitudes and behavior. Working with DUIs is part of traffic psychologists’ work. The primary goal of this field is to reduce the probability of re-conspicuous of the delinquent driver. One of these measurements in Germany is IFT courses for DUI s. The IFT course was designed by the Institute for Therapy Research. Participants are drivers who have fallen several times or once with a blood alcohol concentration of 1.6 per mill and who have completed a medical-psychological assessment (MPU) with the result of the course recommendation. The course covers four sessions of 3.5 hours each (1 hour / 60 m) and in a period of 3 to 4 weeks in the group discussion. This work analyzes interventions for the rehabilitation of DUI (Drunk Drivers offenders) offenders in groups under the aspect of activating psychological resources. From the aspect of sustainability, they should also have long-term consequences for the maintenance of unproblematic driving behavior in terms of the activation of resources. It is also addressing a selected consistency-theory-based intervention effect, activating psychological resources. So far, this has only been considered in the psychotherapeutic field but never in the field of traffic psychology. The methodology of this survey is one qualitative and three quantitative. In four sub-studies, it will be examined which measurements can determine the resources and how traffic psychological interventions can strengthen resources. The results of the studies have the following implications for traffic psychology research and practice: (1) In the field of traffic psychology intervention for the restoration of driving fitness, it can be stated that aspects of resource activation in this work have been investigated for the first time by qualitative and quantitative methods. (2) The resource activation could be confirmed based on the determined results as an effective factor of traffic psychological intervention. (3) Two sub-studies show a range of resources and resource activation options that must be given greater emphasis in traffic psychology interventions: - Social resource activation - improvement of the life skills of participants - Reactivation of existing social support options - Re-experiencing self-esteem, self-assurance, and acceptance of traffic-related behaviors. (4) In revising the IFT-§70 course, as well as other courses on recreating aptitude for DUI, new traffic-specific resource-enabling interventions against alcohol abuse should be developed to further enhance the courses through motivational, cognitive, and behavioral effects of resource activation, Resource-activating interventions can not only be integrated into behavioral group interventions but can also be applied in psychodynamic, psychodynamic (individual psychological) and other contexts of individual traffic psychology. The results are indicative but clearly show that personal resources can be strengthened through traffic psychology interventions. In the research, practice, training, and further education of traffic psychology, the aspect of primary resource activation (Grawe, 1999), therefore, always deserves the greatest attention for the rehabilitation of DUIs and Traffic safety.

Keywords: traffic safety, psychological resources, activating of resources, intervention programs for alcohol offenders, empowerment

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3443 Emergency Management and Patient Transportation of Road Traffic Accident Victims Admitted to the District General Hospital, Matale, Sri Lanka

Authors: Asanka U. K. Godamunne

Abstract:

Road traffic accidents (RTA) are a leading cause of death globally as well as in Sri Lanka and results in a large proportion of disability especially among young people. Ninety-percent of world’s road traffic deaths occur in low- and middle-income countries. The gross disparities in injury outcomes relate to immediate post-crash and hospital management. Emergency management, methods of patient transportation following road traffic accidents and safety measures are important factors to reduce mortality and morbidity. Studies in this area are limited in Sri Lanka. The main objective of this research was to assess the emergency management and proper method of transportation of road traffic accident victims. This offers the best way to explore the ways to reduce the mortality and morbidity and raise the public awareness. This study was conducted as a descriptive cross-sectional study. All the consecutive road traffic accident victims admitted to surgical wards at District General Hospital, Matale, Sri Lanka, over a period of three months were included in the study. Data from 387 victims were analyzed. The majority were in the 20-30 year age group. Seventy six percent of the patients were males. Motorcycles and trishaws were most affected. First-aid was given to only 2% of patients and it was given by non-medical persons. A significant proportion of patients (75%) were transported to the hospital by trishaws and only 1% transported by ambulance. About 86% of the patients were seated while transport and 14% were flat. Limbs and head were the most affected areas of the body. As per this study, immediate post-crash management and patient transportation were not satisfactory. There is a need to strengthen certain road safety laws and make sure people follow them.

Keywords: emergency management, patient transportation, road traffic accident victims, Sri Lanka

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3442 Algorithm Research on Traffic Sign Detection Based on Improved EfficientDet

Authors: Ma Lei-Lei, Zhou You

Abstract:

Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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3441 Injury Characteristics and Outcome of Road Traffic Accident among Victims at Adult Emergency Department of Tikur Anbesa Specialized Hospital, Addis Ababa, Ethiopia

Authors: Mohammed Seid, Aklilu Azazh, Fikre Enquselassie, Engida Yisma

Abstract:

Background: Road traffic injuries are the eighth leading cause of death globally, and the leading cause of death for young people. More than a million people die each year on the world’s roads, and the risk of dying as a result of a road traffic injury is highest in the Africa. Methods: A prospective hospital-based study was undertaken to assess injury characteristics and outcome of road traffic accident among victims at Adult Emergency Department of Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia. A structured pre-tested questionnaire was used to gather the required data. The collected data were analyzed using SPSS version 16.0. Results: A total of 230 road traffic accident victims were studied. The majority of the study subjects were men 165 (71.7%) and the male/female ratio was 2.6:1. The victims’ ages ranged from 14 to 80 years with the mean and standard deviations of 32.15 and ± 14.38 years respectively. Daily laborers (95 (41.3%)) and students (28 (12.2%)) were the majority of road traffic accident victims. Long-distance travelling Minibus (16.5%) was responsible for the majority of road traffic crash followed by followed by Taxi (14.8%) and pedestrians (62.6%) accounted for the majority of road traffic accident. Head (50.4%) and musculoskeletal (extremities) (47.0%) were the most common body region injured. Fractures (78.0%) and open wounds (56.5%) were the most common type of injuries sustained. Treatment of fracture was the most common procedure performed in 57.7 % of the victims. The overall length of hospital stay (LOS) ranged from 1 day to 61 days with mean (± standard deviation) of 7.12 ± 10.5 days and the mortality rate was 7.4 %. A significant higher proportion of victims aged 14-55 years were had less likelihood of death compared to those victims aged more than 55 years of age [Adjusted OR = 0.1 (95% CI: 0.01, 0.82)]. Conclusions: This study showed diverse injury characteristics and high morbidity and mortality among the victims attending Adult Emergency Department of Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia. The findings reflect that road traffic accident is a major public health problem. Urgent road traffic accident preventive measures and prompt treatment of the victims are warranted in order to reduce morbidity and mortality among the victims.

Keywords: road traffic accident, injury characteristics, outcome, Tikur Anbesa specialized hospital, Addis Ababa, Ethiopia

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3440 Smart Speed Bump

Authors: Mohammad Rahmani Rezaiyeh, Mojtaba Rahmani Rezaiyeh, Mehrdad Rahmani Rezaiyeh

Abstract:

Smart speed bump is a new invention and I am invented it. Smart speed bump is a system that can change the position of speed bumps either active or passive in necessary situations. The basic system of smart speed bumps is based on a robotic system which includes mechanic, electronic and artificial intelligence. The smart speed bump is capable of smart decision making and can change its position by anticipating the peak of terrific hours. It can be noted to the advantages of this system such as preventing the waste of petrol while crossing speed bumps, traffic management, accelerating, flowing and securing traffic, reducing accidents and judicial records.

Keywords: invention, smart, robotic system, speed bump, traffic, management

Procedia PDF Downloads 395
3439 Information Requirements for Vessel Traffic Service Operations

Authors: Fan Li, Chun-Hsien Chen, Li Pheng Khoo

Abstract:

Operators of vessel traffic service (VTS) center provides three different types of services; namely information service, navigational assistance and traffic organization to vessels. To provide these services, operators monitor vessel traffic through computer interface and provide navigational advice based on the information integrated from multiple sources, including automatic identification system (AIS), radar system, and closed circuit television (CCTV) system. Therefore, this information is crucial in VTS operation. However, what information the VTS operator actually need to efficiently and properly offer services is unclear. The aim of this study is to investigate into information requirements for VTS operation. To achieve this aim, field observation was carried out to elicit the information requirements for VTS operation. The study revealed that the most frequent and important tasks were handling arrival vessel report, potential conflict control and abeam vessel report. Current location and vessel name were used in all tasks. Hazard cargo information was particularly required when operators handle arrival vessel report. The speed, the course, and the distance of two or several vessels were only used in potential conflict control. The information requirements identified in this study can be utilized in designing a human-computer interface that takes into consideration what and when information should be displayed, and might be further used to build the foundation of a decision support system for VTS.

Keywords: vessel traffic service, information requirements, hierarchy task analysis, field observation

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3438 Measured versus Default Interstate Traffic Data in New Mexico, USA

Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

Abstract:

This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, traffic, weigh-in-motion, axle load distribution

Procedia PDF Downloads 325
3437 Performance Evaluation of Various Displaced Left Turn Intersection Designs

Authors: Hatem Abou-Senna, Essam Radwan

Abstract:

With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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3436 Characteristics of Speed Dispersion in Urban Expressway

Authors: Fujian Wang, Shubin Ruan, Meiwei Dai

Abstract:

Speed dispersion has tight relation to traffic safety. In this paper, several kinds of indicating parameters (the standard speed deviation, the coefficient of variation, the deviation of V85 and V15, the mean speed deviations, and the difference between adjacent car speeds) are applied to investigate the characteristics of speed dispersion, where V85 and V15 are 85th and 15th percentile speed, respectively. Their relationships are into full investigations and the results show that: there exists a positive relation (linear) between mean speed and the deviation of V85 and V15; while a negative relation (quadratic) between traffic flow and standard speed deviation. The mean speed deviation grows exponentially with mean speed while the absolute speed deviation between adjacent cars grows linearly with the headway. The results provide some basic information for traffic management.

Keywords: headway, indicating parameters, speed dispersion, urban expressway

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3435 Localized Variabilities in Traffic-related Air Pollutant Concentrations Revealed Using Compact Sensor Networks

Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

Abstract:

Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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3434 Leveraging the Power of Dual Spatial-Temporal Data Scheme for Traffic Prediction

Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

Procedia PDF Downloads 95