scholarly journals Optimal Staffing for Vessel Traffic Service Operators: A Case Study of Yeosu VTS

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8004
Author(s):  
Sang-Lok Yoo ◽  
Kwang-Il Kim
Keyword(s):  
Statistical Data ◽  
Optimal Number ◽  
Traffic Volume ◽  
Near Miss ◽  
Trajectory Data ◽  
Staffing Level ◽  
Microscopic Approach ◽  
Marine Accidents ◽  
Traffic Organization

Vessel traffic volume and vessel traffic service (VTS) operator workloads are increasing with the expansion of global maritime trade, contributing to marine accidents by causing difficulties in providing timely services. Therefore, it is essential to have sufficient VTS operators considering the vessel traffic volume and near-miss cases. However, no quantitative method for determining the optimal number of workstations, which is necessary for calculating the VTS operator staffing level, has yet been proposed. This paper proposes a new, microscopic approach for calculating the number of workstations from vessel trajectories and voice recording communication data between VTS operators and navigators. The vessel trajectory data are preprocessed to interpolate different intervals. The proposed method consists of three modules: Information services, navigational assistance services, and traffic organization service. The developed model was applied to the Yeosu VTS in Korea. Another workstation should be added to the current workstation based on the proposed method. The results showed that even without annual statistical data, a reasonable VTS operator staffing level could be calculated. The proposed approach helps prevent vessel accidents by providing timely services even if the vessel traffic is congested if VTS operators are deployed to a sufficient number of workstations.

scholarly journals Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study using Floating Car Data in the Paris Region

2021 ◽  
pp. 036119812199550
Author(s):  
Danyang Sun ◽  
Fabien Leurent ◽  
Xiaoyan Xie
Keyword(s):  
Large Scale ◽  
City Planning ◽  
Human Mobility ◽  
Work Place ◽  
Trajectory Data ◽  
Floating Car Data ◽  
Vehicle Trajectories ◽  
Activity Types ◽  
Paris Region

In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.

Research on Ship Classification Based on Trajectory Features

2017 ◽  
Vol 71 (1) ◽  
pp. 100-116 ◽  
Author(s):  
Kai Sheng ◽  
Zhong Liu ◽  
Dechao Zhou ◽  
Ailin He ◽  
Chengxu Feng
Keyword(s):  
Pattern Mining ◽  
Extraction Methods ◽  
Behaviour Pattern ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Trajectory Features ◽  
Ship Classification ◽  
Historical Trajectory

It is important for maritime authorities to effectively classify and identify unknown types of ships in historical trajectory data. This paper uses a logistic regression model to construct a ship classifier by utilising the features extracted from ship trajectories. First of all, three basic movement patterns are proposed according to ship sailing characteristics, with related sub-trajectory partitioning algorithms. Subsequently, three categories of trajectory features with their extraction methods are presented. Finally, a case study on building a model for classifying fishing boats and cargo ships based on real Automatic Identification System (AIS) data is given. Experimental results indicate that the proposed classification method can meet the needs of recognising uncertain types of targets in historical trajectory data, laying a foundation for further research on camouflaged ship identification, behaviour pattern mining, outlier behaviour detection and other applications.

Value of Bootstrapping Staged Deployment of Infrastructure: Case Study in Space Infrastructure Deployment

2017 ◽  
Author(s):  
Koki Ho ◽  
Hao Chen ◽  
Harrison Kim
Keyword(s):  
Analytical Model ◽  
Analytical Method ◽  
Space Exploration ◽  
Optimal Number ◽  
Single Stage ◽  
Operational Planning ◽  
Uncertain Environment ◽  
Infrastructure System ◽  
Space Infrastructure

This paper analyzes the value of staged deployment for complex infrastructure system and propose a concept of bootstrapping staged deployment. Staged deployment has been well known for its advantage of providing flexibility in an uncertain environment. In contrast, this paper demonstrates that the proposed bootstrapping staged deployment can even add values in a deterministic environment. The key idea of bootstrapping staged deployment is to have the previously deployed stages support the subsequent deployment. We develop an analytical model to demonstrate the effects of bootstrapping staged deployment with a case study in space exploration. Our analysis results show that with a well-coordinated deployment plan, staged deployment can overperform single-stage deployment even in a deterministic environment, and that there is an optimal number of stages in terms of lifecycle cost under certain conditions. Our method can find the analytical expression for the optimal number of stages and its deployment strategies. The general findings from the proposed concept and analytical method can advance our knowledge about systems staged deployment, and make operational planning of resource generation infrastructure more efficient.

The influence of spatial design characteristics on low-rise residential neighbourhoods in Basra city

2014 ◽  
Vol 7 (4) ◽  
pp. 559-585
Author(s):  
Hani Alahmed ◽  
Wa’el Alaghbari ◽  
Rahinah Ibrahim ◽  
Azizah Salim
Keyword(s):  
Social Interaction ◽  
Social Interactions ◽  
Significant Influence ◽  
Statistical Data ◽  
Residential Building ◽  
Content Type ◽  
Spatial Design ◽  
Two Factors ◽  
Design Characteristics

Purpose – This paper aims to investigate the ways that could enhance residents’ social interaction in low-rise residential building neighbourhoods of Basra city in Iraq. The lack of social interaction among residents of Basra city prompted the authors to frame a strategy for this case study. Design/methodology/approach – The spatial design characteristics of low-rise residential building neighbourhoods implicated to support the residents in terms of social interactions in comparison to those exhibited by a single home and traditional neighbourhoods. The statistical data demonstrated that by using this strategy, several unique features of secured, collective, responsive and supportive spaces could enhance the residents’ social interaction. Findings – This study found that all collective space factors have a significant influence on social interaction. “Fostering proper proximity and accessibility” factor was ranked first and the most significant factor with an influence on social interaction. Secured spaces (hierarchical spatial structure, physical security supports and construct) have a significant influence on social interaction. The most interesting finding in this study is that all factors of the supportive spaces construct have a significant influence on social interaction. Finally, this study showed that two factors of the responsive spaces construct, increasing variety and increasing legibility, have an insignificant influence on social interaction. Originality/value – The design of low-rise residential building neighbourhoods in Basra city may be used to develop social interaction as the contributing factor for maintaining values of traditional neighbourhood communities. This study highlights certain recommendations for architects, especially urban designers, to reinforce residents’ social interaction in low-rise residential building neighbourhoods in Basra city.

scholarly journals Pengaruh Kualitas Produk dan Harga Terhadap Minat Beli Beras Selancar (Studi Kasus pada Ibu Rumah Tangga di Kota Baru Jalan Kapten Satar RT.10 RW.03 Kecamatan Lahat)

2020 ◽  
Vol 9 (2) ◽  
pp. 1-12
Author(s):  
Darwin Kesuma
Keyword(s):  
Product Quality ◽  
Purchase Intention ◽  
Statistical Data ◽  
Regression Coefficient ◽  
Coefficient Of Determination ◽  
Statistical Data Analysis ◽  
Joint Influence ◽  
The Individual

The Effect of Product Quality and Price on Purchase Intention for Selancar Rice (Case Study on Housewives in Kota Baru Jalan Kapten Satar RT. 10 RW. 03 Lahat). This research was conducted on housewives located at Jalan Kapten Satar RT 10 RW 03 No. 25 Kelurahan Kota Baru, Lahat District. The research objective was to see the effect of the product and price on buying interest in surfing rice. The regression equation Y = 10.588 + 0.453 X1 + 0.339 X2 + e. Based on statistical data analysis, the indicators in this study are valid and reliable. The individual order of each variable with the most influence is the product quality variable with a regression coefficient of 0.453 then the price variable with a regression coefficient of 0.339. Obtained t count variable product quality (X1) of 2.658> 2.011 and variable price (X2) obtained at 2.905> 2.011. This means that t is greater than t table, then H_0 is rejected and H1 is accepted. Obtained an F calculated value of 7.009> 3.20 so that it can be ignored that there is a simultaneous (joint) influence between product quality (X1) and price (X2) on buying interest (Y) of surfing rice. Analysis of the coefficient of determination of 23% means that there is a very weak relationship between the independent variables and the related variables and the rest is 77%. By other factors that are not discussed in this study.

scholarly journals Let Trajectories Speak Out the Traffic Bottlenecks

2022 ◽  
Vol 13 (1) ◽  
pp. 1-21
Author(s):  
Hui Luo ◽  
Zhifeng Bao ◽  
Gao Cong ◽  
J. Shane Culpepper ◽  
Nguyen Lu Dang Khoa
Keyword(s):  
Traffic Volume ◽  
Trajectory Data ◽  
Trade Offs ◽  
Bottleneck Identification ◽  
Spread Model ◽  
Efficiency And Effectiveness ◽  
Historical Trajectory ◽  
Algorithmic Approaches ◽  
Compare And Contrast ◽  
Road Segments

Traffic bottlenecks are a set of road segments that have an unacceptable level of traffic caused by a poor balance between road capacity and traffic volume. A huge volume of trajectory data which captures realtime traffic conditions in road networks provides promising new opportunities to identify the traffic bottlenecks. In this paper, we define this problem as trajectory-driven traffic bottleneck identification : Given a road network R , a trajectory database T , find a representative set of seed edges of size K of traffic bottlenecks that influence the highest number of road segments not in the seed set. We show that this problem is NP-hard and propose a framework to find the traffic bottlenecks as follows. First, a traffic spread model is defined which represents changes in traffic volume for each road segment over time. Then, the traffic diffusion probability between two connected segments and the residual ratio of traffic volume for each segment can be computed using historical trajectory data. We then propose two different algorithmic approaches to solve the problem. The first one is a best-first algorithm BF , with an approximation ratio of 1-1/ e . To further accelerate the identification process in larger datasets, we also propose a sampling-based greedy algorithm SG . Finally, comprehensive experiments using three different datasets compare and contrast various solutions, and provide insights into important efficiency and effectiveness trade-offs among the respective methods.

scholarly journals Optimization of the Mashaer Shuttle-Bus Service in Hajj: Arafat-Muzdalifah Case Study

Information ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 496
Author(s):  
Omar Hussain ◽  
Emad Felemban ◽  
Faizan Ur Rehman
Keyword(s):  
Optimal Number ◽  
Improve Performance ◽  
Large Numbers ◽  
Proposed Model ◽  
Holy Places ◽  
Essential Form ◽  
Service Delays ◽  
Customer Dissatisfaction ◽  
Bus Service

Hajj, the fifth pillar of Islam, is held annually in the month of Dhul Al-Hijjah, the twelfth month, in the Islamic calendar. Pilgrims travel to Makkah and its neighbouring areas—Mina, Muzdalifah, and Arafat. Annually, about 2.5 million pilgrims perform spatiotemporally restricted rituals in these holy places that they must execute to fulfil the pilgrimage. These restrictions make the task of transportation in Hajj a big challenge. The shuttle bus service is an essential form of transport during Hajj due to its easy availability at all stages and ability to transport large numbers. The current shuttle service suffers from operational problems; this can be deduced from the service delays and customer dissatisfaction with the service. This study provides a system to help in planning the operation of the service for one of the Hajj Establishments to improve performance by determining the optimal number of buses and cycles required for each office in the Establishment. We will also present a case study in which the proposed model was applied to the non-Arab Africa Establishment shuttle service. At the same time, we will include the mechanism for extracting the information required in the tested model from the considerably large GPS data of 20,000+ buses in Hajj 2018.

scholarly journals Regional Entrepreneurship Support Infrastructure: Volgograd Region Case Study

2020 ◽  
Vol 16 ◽  
Keyword(s):  
Complex Analysis ◽  
Statistical Data ◽  
High Tech ◽  
Volgograd Region ◽  
Technological Entrepreneurship ◽  
New Type ◽  
Knowledge Intensive

In the paper, the complex analysis of the regional infrastructure of support of technological entrepreneurship of the Volgograd region, based on the statistical data reflecting the activity of enterprise structures is carried out. The scientific relevance of this research is related to the fact that technological entrepreneurship is a new type of enterprise that meets the requirements of the postindustrial period. The functioning of this type of entrepreneurship is based on a high-tech or knowledge-intensive idea, which contributes to the development of the environment. According to the results of the analysis, the main drawbacks of the regional infrastructure of support of technological entrepreneurship of the Volgograd region, which create barriers in the development of technological entrepreneurship. Based on the identified problems, measures have been developed to overcome them.

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