Search results for: multivariate road index

Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

Abstract:

With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering

Procedia PDF Downloads 125

Authors: Basavaraj Kabade, K. T. Nagaraja, Swathi Ramanathan, A. Veeraragavan, P. S. Reashma

Abstract:

Deteriorating quality of the pedestrian environment and the increasing risk of pedestrian crashes are major concerns for most of the cities in India. The recent shift in the priority to motorized transport and the abating condition of existing pedestrian facilities can be considered as prime reasons for the increasing pedestrian related crashes in India. Bengaluru City – the IT capital hub of the nation is not much different from this. The increase in number of pedestrian crashes in Bengaluru reflects the same. To resolve this issue and to ensure safe, sustainable and pedestrian friendly sidewalks, Govt. of Karnataka, India has implemented newfangled pedestrian sidewalks popularized programme named Tender S.U.R.E. (Specifications for Urban Road Execution) projects. Tender SURE adopts unique urban street design guidelines where the pedestrians are given prime preference. The present study presents an assessment of the quality and performance of the pedestrian side walk and the walkability index of the newly built pedestrian friendly sidewalks. Various physical and environmental factors affecting pedestrian safety are identified and studied in detail. The pedestrian mobility is quantified through Pedestrian Level of Service (PLoS) and the pedestrian walking comfort is measured by calculating the Walkability Index (WI). It is observed that the new initiatives taken in reference to improving pedestrian safety have succeeded in Bengaluru by attaining a level of Service of ‘A’ and with a good WI score.

Keywords: pedestrian safety, pedestrian level of service (PLoS), Right of Way (RoW), Tender S.U.R.E (Specifications for Urban Road Execution), walkability index (WI), walkway facilities

Procedia PDF Downloads 190

Authors: F. Ben Abdelghani, W. Maherezi

Abstract:

Dredging operations generate, each year, a great quantity of marine sediments. These raw materials can not be used in road construction without a specific treatment process. Sediments suitability tests has shown that most of studied sediments are not suitable to be used in road construction. In order to improve their compacity and their mechanical performance, addition of a granular material is recommended. The use of a dredged sand, to improve the granular mixture containing sediments, allows a better management of the two types of dredge materials (sand and sediment). In this study, a new road material containing dredged marine sediments and dredged sand is formulated and treated by adding various binders. Mechanical performance investigation of different mixtures by measuring Proctor-IPI values and simple compressive strengths is realized.

Keywords: dredged sediments, suitability tests, road construction, hydraulic binder, mechanical performance

Procedia PDF Downloads 359

Authors: Imèn Khanchouch, Malika Charrad, Mohamed Limam

Abstract:

The interpretation of the quality of clusters and the determination of the optimal number of clusters is still a crucial problem in clustering. We focus in this paper on multi-SOM clustering method which overcomes the problem of extracting the number of clusters from the SOM map through the use of a clustering validity index. We then tested multi-SOM using real and artificial data sets with different evaluation criteria not used previously such as Davies Bouldin index, Dunn index and silhouette index. The developed multi-SOM algorithm is compared to k-means and Birch methods. Results show that it is more efficient than classical clustering methods.

Keywords: clustering, SOM, multi-SOM, DB index, Dunn index, silhouette index

Procedia PDF Downloads 592

Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

Abstract:

There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

Procedia PDF Downloads 251

Authors: Francky Fouedjio

Abstract:

Multivariate geostatistical data have become omnipresent in the geosciences and pose substantial analysis challenges. One of them is the grouping of data locations into spatially contiguous clusters so that data locations within the same cluster are more similar while clusters are different from each other, in some sense. Spatially contiguous clusters can significantly improve the interpretation that turns the resulting clusters into meaningful geographical subregions. In this paper, we develop an agglomerative hierarchical clustering approach that takes into account the spatial dependency between observations. It relies on a dissimilarity matrix built from a non-parametric kernel estimator of the spatial dependence structure of data. It integrates existing methods to find the optimal cluster number and to evaluate the contribution of variables to the clustering. The capability of the proposed approach to provide spatially compact, connected and meaningful clusters is assessed using bivariate synthetic dataset and multivariate geochemical dataset. The proposed clustering method gives satisfactory results compared to other similar geostatistical clustering methods.

Keywords: clustering, geostatistics, multivariate data, non-parametric

Procedia PDF Downloads 474

Authors: Eric Mensah, Carlos Mensah

Abstract:

The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

Procedia PDF Downloads 368

Authors: O. Ikpotokin

Abstract:

In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.

Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics

Procedia PDF Downloads 343

Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

Abstract:

The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

Procedia PDF Downloads 142

Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

Abstract:

Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

Procedia PDF Downloads 565

Authors: Ebru Turgal, Beyza Doganay Erdogan

Abstract:

Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

Procedia PDF Downloads 200

Authors: David Nkurunziza, Rahman Tafahomi

Abstract:

The population growth rate of the city of Kigali is increasing annually. In 1960 the population was six thousand, in 1990 it became two hundred thousand and is supposed to be 4 to 5 million incoming twenty years. With the increase in the residents living in the city of Kigali, there is also a need for an increase in social and economic infrastructures connected by the road networks to serve the residents effectively. A road network is a route that connects people to their needs and has to facilitate people to reach the social and economic facilities easily. This research analyzed the social and economic aspects of three selected roads networks passing through all three districts of the city of Kigali, whose center is the city center roundabout, thorough evaluation of the proximity of the social and economic facilities to the road network. These road networks are the city center to nyabugogo to karuruma, city center to kanogo to Rwanda to kicukiro center to Nyanza taxi park, and city center to Yamaha to kinamba to gakinjiro to kagugu health center road network. This research used a methodology of identifying and quantifying the social and economic facilities within a limited distance of 300 meters along each side of the road networks. Social facilities evaluated are the health facilities, education facilities, institution facilities, and worship facilities, while the economic facilities accessed are the commercial zones, industries, banks, and hotels. These facilities were evaluated and graded based on their distance from the road and their value. The total scores of each road network per kilometer were calculated and finally, the road networks were ranked based on their percentage score per one kilometer—this research was based on field surveys and interviews to collect data with forms and questionnaires. The analysis of the data collected declared that the road network from the city center to Yamaha to kinamba to gakinjiro to the kagugu health center is the best performer, the second is the road network from the city center to nyabugogo to karuruma, while the third is the road network from the city center to kanogo to rwandex to kicukiro center to nyaza taxi park.

Keywords: social economical aspect, road network functionality, urban road network, economic and social facilities

Procedia PDF Downloads 149

Authors: Rania Alshikhe, Vinita Jindal

Abstract:

Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

Procedia PDF Downloads 153

Authors: Elbert S. Moyon, Edsel Matt O. Morales, Jaymer M. Jayoma, Kent C. Espejon, Jayson C. Dollete, Mark Phil B. Pacot

Abstract:

This research paper focuses on the potential of using Web-GIS technology in prioritizing farm-to-market road projects by the Philippines’ Department of Agriculture (DA). The study aimed to explore the benefits of Web-GIS in addressing the limitations faced by the DA in terms of Farm to Market Road profiling and project prioritization, which include a lack of access to updated data, limited spatial analysis capabilities, and difficulties in sharing information between stakeholders. The research methodology involves a comprehensive literature review and a case study of a Web-GIS application developed for the DA, which was used to profile and prioritize farm-to-market road projects in the Philippines. The results showed that the Web-GIS technology provides the DA with an effective tool for analyzing and visualizing data, which can help in profiling and prioritizing road projects based on various criteria such as economic, social, and environmental impacts. The study also showed that Web-GIS technology could help in reducing the time and effort required for road project prioritization and improve communication between stakeholders.

Keywords: GIS, web application, farm-to-market road, FMR prioritization, Django, GeoServer

Procedia PDF Downloads 78

Authors: Irfan Ahmad Afip

Abstract:

This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

Procedia PDF Downloads 110

Authors: Rosyidah, Permata Wulandari

Abstract:

We investigate the price effect of addition and deletions from the Indonesia Sharia Stock Index (ISSI) and Jakarta Islamic Index (JII). Using event study methodology, we measure abnormal returns for firms over the period June 2019 - to December 2021. Through the sample of 107 additions and 95 deletions, we find evidence to support the theory of Muslim country investment behavior. We find that additions to the Islamic index led to a significant positive stock market reaction and deletions to the Islamic index led to a negative stock market reaction on Jakarta Islamic Index (JII) and there is no significant reaction of addition and deletion on Indonesia Sharia Stock Index (ISSI).

Keywords: abnormal return, abnormal volume, event study, index changes, sharia index

Procedia PDF Downloads 124

Authors: Pedro Pablo Ramírez Sánchez, Alassane Ballé Ndiaye, Roberto Rendeiro Martín-Cejas

Abstract:

The aim of this paper is to analyse the different environmental policies adopted in Europe for car emissions, to comment on some of the possible perverse effects generated and point out these policies which are considered more efficient under the environmental perspective. This paper is focused on passenger cars as this category is the most significant in road transport. The utility of this research lies in this being the first step or basis to improve and optimise actual policies. The methodology applied in this paper refers to a comparative analysis from a practical and theoretical point of view of European environmental policies in road transport. This work describes an overview of the road transport industry in Europe pointing out some relevant aspects such as the contribution of road transport to total emissions and the vehicle fleet in Europe. Additionally, we propose a brief practice guide with the combined policies in order to optimise their aim.

Keywords: air quality, climate change, emission, environment, perverse effect, road transport, tax policy

Procedia PDF Downloads 154

Authors: Ami Nkumbuye

Abstract:

Background: Every year 1.3 million people die due to Road crashes, according to the Global status report. Road crashes remain the greatest killer aged between 15-29 years. Young people are paying an unacceptable price for their own safer mobility. 23,498 students attending class daily from home crossing the roads of 3 districts Kigali and Southern province is showing a similar trend with 40320 cross road daily. As most of them don't have any idea about the safety, they should have when they are crossing roads and traffic rules and signs as well. Despite the high number of mortality related to road crashes in Rwanda, we don't have any approved calendar to teach young people road safety as the most affected age group. Objective: The objective of this study was to identify the causes of road crashes and the outcome of victims after being involved in road crashes over a period of two years, from January 2020 to December 2021, in Huye district and Kigali City. Methods: A retrospective descriptive study with open questions and then data analysis, students were identified from 15 schools in Kigali City and Southern Province and through the Local Action Project supported by Global Youth Coalition for Road Safety and Youth for Road Safety (YOURS), students asked about the cause of road crashes through open and closed question and data analyzed. Result: There were 354 students from 15 schools: 198 males and 156 females. Their age ranged from 10 to 25 years. The commonest cause of road crashes among students attending schools daily was: high speed, lack of education on safe behavior on the road, drinking and driving, and poor road infrastructures, with 47%, 32%, 13% and 8 %, respectively. The hospital admission after road crashes for the victims was 32.3%. In most scenes where road crashes occur, students report that they didn't see any person who could provide post-crash care until the ambulance came, in some cases, resulted in bad outcomes for the victims after road crashes. Conclusion: This study revealed that high speed and lack of education n road safety are the major cause of road crashes among young people in Rwanda. If local Non-Governmental Organization and Decision makers work on these issues like never before, we can see a decrease in road crash among young people and adult as well. We would like to give a recommendation to two institutions: the first is the Rwanda National Police Traffic department to set 30km/m as the maximum speed limit in City and near schools. The second is for the Ministry of Education to put Road Safety and Post Crash Care curricula in both Primary and Secondary schools.

Keywords: road safety, post-crash care, young people, students

Procedia PDF Downloads 82

Authors: Han Bai, Tong Zhang, Lemei Yu, Doudou Xie, Liang Zhao

Abstract:

Road transition design on freeway tunnel entrance and exit is one vital factor in realizing smooth transition and improving traveling safety for vehicles. The goal of this research is to develop a horizontal road transition design tool that considers the transition technology of traffic capacity consistency to explore its accommodation mechanism. The influencing factors of capacity are synthesized and a modified capacity calculation model focusing on the influence of road width and lateral clearance is developed based on the VISSIM simulation to calculate the width of road transition sections. To keep the traffic capacity consistency, the right side of the transition section of the tunnel entrance and exit is divided into three parts: front arc, an intermediate transition section, and end arc; an optimization design on each transition part is conducted to improve the capacity stability and horizontal alignment transition. A case study on the Panlong Tunnel in Ji-Qing freeway illustrates the application of the tool.

Keywords: traffic safety, road transition, freeway tunnel, traffic capacity

Procedia PDF Downloads 319

Authors: Ayman Othman, Tallat Ali

Abstract:

A pavement maintenance management system (PMMS) was developed for the city of Aswan as a model of a small city to provide the road maintenance department in Aswan city with the capabilities for comprehensive planning of the maintenance activities needed to put the internal pavement network into desired physical condition in view of maintenance budget constraints. The developed system consists of three main stages. First is the inventory & condition survey stage where the internal pavement network of Aswan city was inventoried and its actual conditions were rated in segments of 100 meters length. Second is the analysis stage where pavement condition index (PCI) was calculated and the most appropriate maintenance actions were assigned for each segment. The total maintenance budget was also estimated and a parameter based ranking criteria were developed to prioritize maintenance activities when the available maintenance budget is not sufficient. Finally comes the packaging stage where approved maintenance budget is packed into maintenance projects for field implementation. System results indicate that, the system output maintenance budget is very reasonable and the system output maintenance programs agree to a great extent with the actual maintenance needs of the network. Condition survey of Aswan city road network showed that roughness is the most dominate distress. In general, the road network can be considered in a fairly reasonable condition, however, the developed PMMS needs to be officially adapted to maintain the road network in a desirable condition and to prevent further deterioration.

Keywords: pavement, maintenance, management, system, distresses, survey, ranking

Procedia PDF Downloads 241

Authors: Ouaaz Oum Essaad, Melbouci Bachir

Abstract:

The experimental study conducted has a dual purpose: to valorize the clay material in the road domain and improve the lift of the shape layers by strengthening with plastic waste (in the form of aggregates). To do this, six mixtures of Clay and sand of different percentages were studied: 100% Clay, 95% Clay + 05% Sand, 90% Clay + 10% Sand, 85% Clay + 15% Sand, 80% Clay + 20% Sand, 75% Clay + 25% Sand. Proctor compaction and simple compression tests have been carried out on mixtures (sand + clay + plastic waste). The results obtained show a clear evolution of the characteristics of the Proctor test and the compressive strength of the mixtures according to the different types and percentages of the recycled plastic Plasticity and consistency index are important parameters that play a role in the toughness of plastic soil.

Keywords: valorization, recycling, soil mixture, mechanical tests

Procedia PDF Downloads 95

Authors: Patel Darshan Shaileshkumar, M. G. Vanza

Abstract:

Black cotton soil is problematic soil for any construction work. Black cotton soil contains montmorillonite in its structure. Due to this mineral, black cotton soil will attain maximum swelling and shrinkage. Due to these volume changes, it is necessary to stabilize black cotton soil before the construction of the road. For soil stabilization use of pozzolanic waste is found to be a good solution by some researchers. The palm kernel shell ash (PKSA) is a pozzolanic material that can be used for soil stabilization. Basically, PKSA is a waste material, and it is available at a cheap cost. Palm kernel shell is a waste material generated in palm oil mills. Then palm kernel shell is used in industries instead of coal for power generation. After the burning of a palm kernel shell, ash is formed; the ash is called palm kernel shell ash (PKSA). The PKSA contains a free lime content that will react chemically with the silicate and aluminate of black cotton soil and forms a C-S-H and C-A-H gel which will bines soil particles together and reduce the plasticity of the soil. In this study, the PKSA is added to the soil. It was found that with the addition of PKSA content in the soil, the liquid limit of the soil is decreased, the plastic limit of the soil is increased, and the plasticity of the soil is decreased. The group index value of the soil is evaluated, and it was found that with the addition of PKSA GI value of the soil is decreased, which indicates the strength of the soil is improved.

Keywords: palm kernel shell ash, black cotton soil, liquid limit, group index, plastic limit, plasticity index

Procedia PDF Downloads 102

Authors: Stanislovas Buteliauskas, Aušrius Juozapavičius

Abstract:

City road transport contributes significantly to climate change, and the ongoing world urbanization is only increasing the problem. The paper describes a city planning concept minimizing the number of vehicles on the roads while increasing overall mobility. This becomes possible by utilizing a recently invented two-level road junction with a unique property of serving both as an intersection of uninterrupted traffic and an easily accessible transport hub capable of accumulating private vehicles, and therefore becoming an especially effective park-and-ride solution, and a logistics or business center. Optimized layouts of city road infrastructure, living and work areas, and major roads are presented. The layouts are suitable both for the development of new cities as well as for the expansion of existing ones. Costs of the infrastructure and a positive impact on climate are evaluated in comparison to current city growth patterns.

Keywords: congestion, city infrastructure, park-and-ride, road junctions

Procedia PDF Downloads 299

Authors: Khalid A. Alsaif, Mosaad A. Foda

Abstract:

The primary objective of this study is to develop the first round of road traffic noise maps for Riyadh City using Geographical Information Systems (GIS) and software LimA 7810 predictor. The road traffic data were measured or estimated as accurate as possible in order to obtain reliable noise maps. Meanwhile, the attributes of the roads and buildings are automatically exported from GIS. The simulation results at some chosen locations are validated by actual field measurements, which are obtained by a system that consists of a sound level meter, a GPS receiver and a database to manage the measured data. The results show that the average error between the predicted and measured noise levels is below 3.0 dB.

Keywords: noise pollution, road traffic noise, LimA predictor, GIS

Procedia PDF Downloads 399

Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

Abstract:

This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

Procedia PDF Downloads 125

Authors: Thrivikraman Aswathi, S. Advaith

Abstract:

As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

Procedia PDF Downloads 123

Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

Abstract:

H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

Procedia PDF Downloads 265

Authors: Hamid Reza Behnood, Esmaeel Ayati, Tom Brijs, Mohammadali Pirayesh Neghab

Abstract:

Investment projects in road safety planning can benefit from an effectiveness evaluation regarding their expected safety outcomes. The objective of this study is to develop a decision support system (DSS) to support policymakers in taking the right choice in road safety planning based on the efficiency of previously implemented safety measures in a set of regions in Iran. The measures considered for each region in the study include performance indicators about (1) police operations, (2) treated black spots, (3) freeway and highway facility supplies, (4) speed control cameras, (5) emergency medical services, and (6) road lighting projects. To this end, inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators (i.e., road safety measures) which should be minimized. The relative inefficiency for each region is modeled by the Data Envelopment Analysis (DEA) technique. In a next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA analysis into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety.

Keywords: performance indicators, road safety, decision support system, data envelopment analysis, fuzzy reasoning

Procedia PDF Downloads 344

Authors: P. Góes, J. Manzi

Abstract:

This paper focuses on the development of an energy efficiency index that will be applied to reactive systems, which is based in the First and Second Law of Thermodynamics, by giving particular consideration to the concept of maximum entropy. Among the requirements of such energy efficiency index, the practical feasibility must be essential. To illustrate the performance of the proposed index, such an index was used as decisive factor of evaluation for the optimization process of an industrial reactor. The results allow the conclusion to be drawn that the energy efficiency index applied to the reactive system is consistent because it extracts the information expected of an efficient indicator, and that it is useful as an analytical tool besides being feasible from a practical standpoint. Furthermore, it has proved to be much simpler to use than tools based on traditional methodologies.

Keywords: energy, efficiency, entropy, reactive

Procedia PDF Downloads 404

Authors: Yassine Jadi, Lin Jie

Abstract:

In order to serve the society in an electronic manner, many developing countries have launched tremendous e-government projects. The strategies of development and implementation e-government system have reached different levels, and to ensure consistency of development, the governments need to evaluate e-government performance. The United nation has design e-government development ranking index (EGDI) that rely on three indexes, Online service index (OSI), Telecommunication Infrastructure index (TII), and human capital index( HCI) which are not reflecting the interaction between a government and their citizens. Based on data envelopment analyses (DEA) technique, we are using E-participating index (EPI) as an output of government effort to evaluate the performance of e-government system. Therefore, the ranking index can be achieved in efficiency manner.

Keywords: e-government, DEA, efficiency measurement, EGDI

Procedia PDF Downloads 370