Search results for: Subsetsplit method and Traffic Engineering.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9295

Search results for: Subsetsplit method and Traffic Engineering.

9175 Predicting Application Layer DDoS Attacks Using Machine Learning Algorithms

Authors: S. Umarani, D. Sharmila

Abstract:

A Distributed Denial of Service (DDoS) attack is a major threat to cyber security. It originates from the network layer or the application layer of compromised/attacker systems which are connected to the network. The impact of this attack ranges from the simple inconvenience to use a particular service to causing major failures at the targeted server. When there is heavy traffic flow to a target server, it is necessary to classify the legitimate access and attacks. In this paper, a novel method is proposed to detect DDoS attacks from the traces of traffic flow. An access matrix is created from the traces. As the access matrix is multi dimensional, Principle Component Analysis (PCA) is used to reduce the attributes used for detection. Two classifiers Naive Bayes and K-Nearest neighborhood are used to classify the traffic as normal or abnormal. The performance of the classifier with PCA selected attributes and actual attributes of access matrix is compared by the detection rate and False Positive Rate (FPR).

Keywords: Distributed Denial of Service (DDoS) attack, Application layer DDoS, DDoS Detection, K- Nearest neighborhood classifier, Naive Bayes Classifier, Principle Component Analysis.

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9174 Spatial Clustering Model of Vessel Trajectory to Extract Sailing Routes Based on AIS Data

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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9173 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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9172 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.

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9171 Improvement of the Quality of Internet Service Based On an Internet Exchange Point (IXP)

Authors: Souleymane Oumtanaga, Falilu Abudul Kadiri

Abstract:

Internet is without any doubt the fastest and effective mean of communication making it possible to reach a great number of people in the world. It draws its base from exchange points. Indeed exchange points are used to inter-connect various Internet suppliers and operators in order to allow them to exchange traffic and it is with these interconnections that Internet made its great strides. They thus make it possible to limit the traffic delivered via the operators of transits. This limitation allows a significant improvement of the quality of service, a reduction in the latency time just as a reduction of the cost of connection for the final subscriber. Through this article we will show how the installation of an IXP allows an improvement and a diversification of the services just as a reduction of the Internet connection costs.

Keywords: Quality of service, Exchange point, interconnection, Service providers, bandwidth, traffic, routers, routing table.

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9170 Energy Detection Based Sensing and Primary User Traffic Classification for Cognitive Radio

Authors: Urvee B. Trivedi, U. D. Dalal

Abstract:

As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: Cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary User (PU), secondary user (SU), Fast Fourier transform (FFT), signal to noise ratio (SNR).

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9169 Incorporating Multiple Supervised Learning Algorithms for Effective Intrusion Detection

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

Abstract:

As internet continues to expand its usage with an  enormous number of applications, cyber-threats have significantly  increased accordingly. Thus, accurate detection of malicious traffic in  a timely manner is a critical concern in today’s Internet for security.  One approach for intrusion detection is to use Machine Learning (ML)  techniques. Several methods based on ML algorithms have been  introduced over the past years, but they are largely limited in terms of  detection accuracy and/or time and space complexity to run. In this  work, we present a novel method for intrusion detection that  incorporates a set of supervised learning algorithms. The proposed  technique provides high accuracy and outperforms existing techniques  that simply utilizes a single learning method. In addition, our  technique relies on partial flow information (rather than full  information) for detection, and thus, it is light-weight and desirable for  online operations with the property of early identification. With the  mid-Atlantic CCDC intrusion dataset publicly available, we show that  our proposed technique yields a high degree of detection rate over 99%  with a very low false alarm rate (0.4%). 

 

Keywords: Intrusion Detection, Supervised Learning, Traffic Classification.

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9168 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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9167 Analysis and Evaluation of the Public Responses to Traffic Congestion Pricing Schemes in Urban Streets

Authors: Saeed Sayyad Hagh Shomar

Abstract:

Traffic congestion pricing in urban streets is one of the most suitable options for solving the traffic problems and environment pollutions in the cities of the country. Unlike its acceptable outcomes, there are problems concerning the necessity to pay by the mass. Regarding the fact that public response in order to succeed in this strategy is so influential, studying their response and behavior to get the feedback and improve the strategies is of great importance. In this study, a questionnaire was used to examine the public reactions to the traffic congestion pricing schemes at the center of Tehran metropolis and the factors involved in people’s decision making in accepting or rejecting the congestion pricing schemes were assessed based on the data obtained from the questionnaire as well as the international experiences. Then, by analyzing and comparing the schemes, guidelines to reduce public objections to them are discussed. The results of reviewing and evaluating the public reactions show that all the pros and cons must be considered to guarantee the success of these projects. Consequently, with targeted public education and consciousness-raising advertisements, prior to initiating a scheme and ensuring the mechanism of the implementation after the start of the project, the initial opposition is reduced and, with the gradual emergence of the real and tangible benefits of its implementation, users’ satisfaction will increase.

Keywords: Demand management, international experiences, traffic congestion pricing, public acceptance, public objection.

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9166 The Role of Driving Experience in Hazard Perception and Categorization: A Traffic-Scene Paradigm

Authors: Avinoam Borowsky, Tal Oron-Gilad, Yisrael Parmet

Abstract:

This study examined the role of driving experience in hazard perception and categorization using traffic scene pictures. Specifically, young-inexperienced, moderately experienced and very experienced (taxi) drivers observed traffic scene pictures while connected to an eye tracking system and were asked to rate the level of hazardousness of each picture and to mention the three most prominent hazards in it. Target pictures included nine, nearly identical, pairs of pictures where one picture in each pair included an actual hazard as an additional element. Altogether, 22 areas of interest (AOIs) were predefined and included 13 potential hazards and 9 actual hazards. Data analysis included both verbal reports and eye scanning patterns of these AOIs. Generally, both experienced and taxi drivers noted a relatively larger number of potential hazards than young inexperienced drivers Thus, by relating to less salient potential hazards, experienced drivers have demonstrated a better situation model of the traffic environment.

Keywords: Concept Construction, Hazard Perception, EyeMovements, Driving Experience.

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9165 WiFi Data Offloading: Bundling Method in a Canvas Business Model

Authors: Majid Mokhtarnia, Alireza Amini

Abstract:

Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one.

Keywords: Bundling, canvas business model, telecommunication, WiFi Data Offloading.

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9164 Optical Flow Based System for Cross Traffic Alert

Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

Abstract:

This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: Clustering, cross traffic alert, optical flow, real time, vanishing point.

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9163 A New Approach of Wireless Network Traffic on VPN

Authors: Amir Rashid, M. Saleem Khan, Freeha Zafar

Abstract:

This work presents a new approach of securing a wireless network. The configuration is focused on securing & Protecting wireless network traffic for a small network such as a home or dorm room. The security Mechanism provided both authentication, allowing only known authorized users access to the wireless network, and encryption, preventing anyone from reading the wireless traffic. The mentioned solution utilizes the open source free S/WAN software which implements the Internet Protocol Security –IPSEC. In addition to wireless components, wireless NIC in PC and wireless access point needs a machine running Linux to act as security gateway. While the current configuration assumes that the wireless PC clients are running Linux, Windows XP/VISTA/7 based machines equipped with VPN software which will allow to interface with this configuration.

Keywords: Wireless network security, security network, authentication, encryption and internet protocol security.

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9162 Rescue Emergency Drone for Fast Response to Medical Emergencies Due to Traffic Accidents

Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

Abstract:

Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: Automated external defibrillator, medical emergency, fire and rescue services, response time, unmanned aerial system.

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9161 A Fast Sign Localization System Using Discriminative Color Invariant Segmentation

Authors: G.P. Nguyen, H.J. Andersen

Abstract:

Building intelligent traffic guide systems has been an interesting subject recently. A good system should be able to observe all important visual information to be able to analyze the context of the scene. To do so, signs in general, and traffic signs in particular, are usually taken into account as they contain rich information to these systems. Therefore, many researchers have put an effort on sign recognition field. Sign localization or sign detection is the most important step in the sign recognition process. This step filters out non informative area in the scene, and locates candidates in later steps. In this paper, we apply a new approach in detecting sign locations using a new color invariant model. Experiments are carried out with different datasets introduced in other works where authors claimed the difficulty in detecting signs under unfavorable imaging conditions. Our method is simple, fast and most importantly it gives a high detection rate in locating signs.

Keywords: Sign localization, color-based segmentation.

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9160 On the Analysis of Bandwidth Management for Hybrid Load Balancing Scheme in WLANs

Authors: Chutima Prommak, Airisa Jantaweetip

Abstract:

In wireless networks, bandwidth is scare resource and it is essential to utilize it effectively. This paper analyses effects of using different bandwidth management techniques on the network performances of the Wireless Local Area Networks (WLANs) that use hybrid load balancing scheme. In particular, we study three bandwidth management schemes, namely Complete Sharing (CS), Complete Partitioning (CP), and Partial Sharing (PS). Performances of these schemes are evaluated by simulation experiments in term of percentage of network association blocking. Our results show that the CS scheme can provide relatively low blocking percentage in various network traffic scenarios whereas the PS scheme can enhance quality of services of the multimedia traffic with rather small expenses on the blocking percentage of the best effort traffic.

Keywords: Bandwidth management, Load Balancing, WLANs.

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9159 Optimizing Mobile Agents Migration Based on Decision Tree Learning

Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

Abstract:

Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

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9158 Traffic Noise under Stop and Go Conditions in Intersections – A Case Study

Authors: Nima Jahandar, Amin Hosseinpour, Mohammad Ali Sahraei

Abstract:

Whit the increasing of traffic, noise emanated from motor vehicles increases as well, which subsequently causes adding to the stress of modern city. Thus, it is needed to look for most critical areas in terms of environmental and social impact of noise. There are several critical situations for noise emanated from motor vehicles such as stop and go situation which usually occurs near junctions or at-grade intersections. This study was conducted in two locations, most common types of intersections, crossroads and Tjunctions. The highest average noise levels are recorded during Go phase for T-junction, 64.4 dB, and Drive phase for crossroad, 64 dB. It implies that the existence of intersection caused the noise level to increase. The vehicles starting to move produce more sound than when they travel at a constant speed along the intersection. It is suggested that special considerations and priority of allocating funds should be given to these critical spots.

Keywords: Crossroad, T-junction, Traffic Noise, Stop and Go, Urban noise

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9157 Optimization and GIS-Based Intelligent Decision Support System for Urban Transportation Systems Analysis

Authors: Mohamad K. Hasan, Hameed Al-Qaheri

Abstract:

Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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9156 Evaluating Emission Reduction Due to a Proposed Light Rail Service: A Micro-Level Analysis

Authors: Saeid Eshghi, Neeraj Saxena, Abdulmajeed Alsultan

Abstract:

Carbon dioxide (CO2) alongside other gas emissions in the atmosphere cause a greenhouse effect, resulting in an increase of the average temperature of the planet. Transportation vehicles are among the main contributors of CO2 emission. Stationary vehicles with initiated motors produce more emissions than mobile ones. Intersections with traffic lights that force the vehicles to become stationary for a period of time produce more CO2 pollution than other parts of the road. This paper focuses on analyzing the CO2 produced by the traffic flow at Anzac Parade Road - Barker Street intersection in Sydney, Australia, before and after the implementation of Light rail transport (LRT). The data are gathered during the construction phase of the LRT by collecting the number of vehicles on each path of the intersection for 15 minutes during the evening rush hour of 1 week (6-7 pm, July 04-31, 2018) and then multiplied by 4 to calculate the flow of vehicles in 1 hour. For analyzing the data, the microscopic simulation software “VISSIM” has been used. Through the analysis, the traffic flow was processed in three stages: before and after implementation of light rail train, and one during the construction phase. Finally, the traffic results were input into another software called “EnViVer”, to calculate the amount of CO2 during 1 h. The results showed that after the implementation of the light rail, CO2 will drop by a minimum of 13%. This finding provides an evidence that light rail is a sustainable mode of transport.

Keywords: Carbon dioxide, emission modeling, light rail, microscopic model, traffic flow.

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9155 Investigating the Pedestrian Willingness to Pay to Choose Appropriate Policies for Improving the Safety of Pedestrian Facilities

Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Fatemeh Mohajeri

Abstract:

Road traffic accidents lead to a higher rate of death and injury, especially in vulnerable road users such as pedestrians. Improving the safety of facilities for pedestrians is a major concern for policymakers because of the high number of pedestrian fatalities and direct and indirect costs which are imposed to the society. This study focuses on the idea of determining the willingness to pay of pedestrians for increasing their safety while crossing the street. In this study, three different scenarios including crossing the street with zebra crossing facilities, crossing the street with zebra crossing facilities and installing a pedestrian traffic light and constructing a pedestrian bridge with escalator are presented. The research was conducted based on stated preferences method. The required data were collected from a questionnaire that consisted of three parts: pedestrian’s demographic characteristics, travel characteristics and scenarios. Four different payment amounts are presented for each scenario and a logit model has been built for each proposed payment. The results show that sex, age, education, average household income and individual salary have significant effect on choosing a scenario. Among the policies that have been mentioned through the questionnaire scenarios, the scenario of crossing the street with zebra crossing facilities and installing a traffic lights is the most frequent, with willingness to pay 10,000 Rials and the scenario of crossing the street with a zebra crossing with a willingness to pay 100,000 Rials having the least frequency. For all scenarios, as the payment is increasing, the willingness to pay decreases.

Keywords: Pedestrians, willingness to pay, safety, immunization.

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9154 Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: Automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA.

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9153 Impact of Ship Traffic to PM2.5 and Particle Number Concentrations in Three Port-Cities of the Adriatic/Ionian Area

Authors: Daniele Contini, Antonio Donateo, Andrea Gambaro, Athanasios Argiriou, Dimitrios Melas, Daniela Cesari, Anastasia Poupkou, Athanasios Karagiannidis, Apostolos Tsakis, Eva Merico, Rita Cesari, Adelaide Dinoi

Abstract:

Emissions of atmospheric pollutants from ships and harbour activities are a growing concern at international level given their potential impacts on air quality and climate. These close-to-land emissions have potential impact on local communities in terms of air quality and health. Recent studies show that the impact of maritime traffic to atmospheric particulate matter concentrations in several coastal urban areas is comparable with the impact of road traffic of a medium size town. However, several different approaches have been used for these estimates making difficult a direct comparison of results. In this work, an integrated approach based on emission inventories and dedicated measurement campaigns has been applied to give a comparable estimate of the impact of maritime traffic to PM2.5 and particle number concentrations in three major harbours of the Adriatic/Ionian Seas. The influences of local meteorology and of the logistic layout of the harbours are discussed.

Keywords: Ship emissions, PM2.5, particle number concentrations, impact of shipping to atmospheric aerosol.

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9152 Road Accidents Bigdata Mining and Visualization Using Support Vector Machines

Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

Abstract:

Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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9151 Impact of Vehicle Travel Characteristics on Level of Service: A Comparative Analysis of Rural and Urban Freeways

Authors: Anwaar Ahmed, Muhammad Bilal Khurshid, Samuel Labi

Abstract:

The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The current version of Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore, a single PCE value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, present study developed separate PCE values for single-unit and combination trucks to replace the single value provided in the HCM on different freeways. Site specific PCE values, were developed using concept of spatial lagging headways (that is the distance between rear bumpers of two vehicles in a traffic stream) measured from field traffic data. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-leastsquares (3SLS) regression techniques were used to generate models that predicted lagging headways for passenger cars, single unit trucks (SUT), and combination trucks (CT). The estimated PCE values for single-unit and combination truck for basic urban freeways (level terrain) were: 1.35 and 1.60, respectively. For rural freeways the estimated PCE values for single-unit and combination truck were: 1.30 and 1.45, respectively. As expected, traffic variables such as vehicle flow rates and speed have significant impacts on vehicle headways. Study results revealed that the use of separate PCE values for different truck classes can have significant influence on the LOS estimation.

Keywords: Level of Service, Capacity Analysis, Lagging Headway.

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9150 Distributed Coordination of Connected and Automated Vehicles at Multiple Interconnected Intersections

Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu

Abstract:

In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.

Keywords: Connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control.

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9149 Rear Seat Belt Use in Developing Countries: A Case Study from the United Arab Emirates

Authors: Salaheddine Bendak, Sara S. Alnaqbi

Abstract:

The seat belt is a vital tool in improving traffic safety conditions and minimising injuries due to traffic accidents. Most developing countries are facing a big problems associated with the human and financial losses due to traffic accidents. One way to minimise these losses is the use of seat belts by passengers both in the front and rear seats of a vehicle; however, at the same time, close to nothing is known about the rates of seat belt utilisation among rear seat passengers in many developing countries. Therefore, there is a need to estimate these rates in order to know the extent of this problem and how people interact with traffic safety measures like seat belts and find demographic characteristics that contribute to wearing or non-wearing of seat belts with the aim of finding solutions to improve wearing rates. In this paper, an observational study was done to gather data on restraints use in motor vehicle rear seats in eight observational stations in a rapidly developing country, the United Arab Emirates (UAE), and estimate a use rate for the whole country. Also, a questionnaire was used in order to study demographic characteristics affecting the wearing of seatbelts in rear seats. Results of the observational study showed that the overall wearing/usage rate was 12.3%, which is considered very low when compared to other countries. Survey results show that single, male, less educated passengers from Arab and South Asian backgrounds use seat belts reportedly less than others. Finally, solutions are put forward to improve this wearing rate based on the results of this study.

Keywords: Seat belts, traffic crashes, United Arab Emirates, rear seats.

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9148 Classification System for a Collaborative Urban Retail Logistics

Authors: Volker Lange, Stephanie Moede, Christiane Auffermann

Abstract:

From an economic standpoint the current and future road traffic situation in urban areas is a cost factor. Traffic jams and congestion prolong journey times and tie up resources in trucks and personnel. Many discussions about imposing charges or tolls for cities in Europe in order to reduce traffic congestion are currently in progress. Both of these effects lead – directly or indirectly - to additional costs for the urban distribution systems in retail companies. One approach towards improving the efficiency of retail distribution systems, and thus towards avoiding negative environmental factors in urban areas, is horizontal collaboration for deliveries to retail outlets – Urban Retail Logistics. This paper presents a classification system to help reveal where cooperation between retail companies is possible and makes sense for deliveries to retail outlets in urban areas.

Keywords: City Logistics, Horizontal Collaboration, Urban Freight Transport, Urban Retail Logistics.

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9147 Research on the Public Policy of Vehicle Restriction under Traffic Control

Authors: Wang Qian, Bian Cheng Xiang

Abstract:

In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve the related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: Carbon emission, traffic jam, vehicle restriction, policy evaluation.

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9146 Analysis of Non-Conventional Roundabout Performance in Mixed Traffic Conditions

Authors: Guneet Saini, Shahrukh, Sunil Sharma

Abstract:

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, traffic.

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