Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

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The Feasibility of Opening Communities -- Based on the Wiedemann Car-Following Model

Computer and Information Science ◽

10.5539/cis.v11n3p57 ◽

2018 ◽

Vol 11 (3) ◽

pp. 57

Author(s):

Xiao-Yan Cao ◽

Bing-Qian Liu ◽

Bao-Ru Pan ◽

Yuan-Biao Zhang

Keyword(s):

Traffic Congestion ◽

Large Scale ◽

Gated Communities ◽

Urban Traffic ◽

Average Delay ◽

Traffic Demand ◽

Car Following ◽

Car Following Model ◽

Urbanization In China ◽

The Impact

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.

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Characteristic Parameters Identification of Macro Traffic Flow on Urban Expressway

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.409-410.1209 ◽

2013 ◽

Vol 409-410 ◽

pp. 1209-1212

Author(s):

Da Shan Chen

Keyword(s):

Traffic Flow ◽

Traffic Congestion ◽

Traffic Management ◽

Road Network ◽

Large Scale ◽

Characteristic Parameters ◽

Traffic Demand ◽

Urban Expressway ◽

Back Ground ◽

Control And Management

The macroscopic traffic flow parameters characteristic is an important research content in traffic flow theory. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. With the growing of traffic demand and much more traffic congestion and accidents, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. As the backbone road network, traffic flow characteristic parameters have great value for the control and management of urban expressway. Then the characteristic variables of the expressway traffic flow were identified which support meticulous management for urban expressway.

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A novel cooperative model in the collection of infectious waste in COVID-19 pandemic

Journal of Modelling in Management ◽

10.1108/jm2-07-2020-0189 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Jaber Valizadeh ◽

Peyman Mozafari

Keyword(s):

Large Scale ◽

Cost Savings ◽

Municipal Waste ◽

Scale Model ◽

Future Research ◽

Content Type ◽

Large Scale Model ◽

Solution Methods ◽

Infectious Waste ◽

Additional Value

Purpose Production of waste has been increased exponentially due to world industrialization and urban and machine life expansion. On the other hand, the outbreak of the COVID-19 coronavirus quickly became a global crisis. This crisis has added a large amount of waste to urban waste. The purpose of this study is to create cooperation between municipal waste collector contractors. Design/methodology/approach Thus, a mathematical model is proposed under uncertain conditions, which includes the volume of municipal waste and infectious waste including personal protective equipment and used equipment for patients. To reduce total costs, the results are evaluated with four cooperative game theory methods such as Shapley value, t value, core center and least core. Ultimately, the saved cost by cooperation in each coalition is allocated fairly among the contractors. Finally, a comparison was made between the solution methods based on the value of the objective function and the solution time. Findings The results indicate that the proposed cooperative method increases cost savings and reduces the fine of residual waste. Therefore, it can be mentioned that this kind of cooperation would finally result in more incentives for contractors to form larger coalitions. Genetic algorithms were used to solve the large-scale model. Originality/value The proposed model boosts the current understanding of waste management in the COVID-19 pandemic. The paper adds additional value by unveiling some key future research directions. This guidance may demonstrate possible existing and unexplored gaps so that researchers can direct future research to develop new processes.

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The Potential of Blockchain in Building Construction

Buildings ◽

10.3390/buildings9040077 ◽

2019 ◽

Vol 9 (4) ◽

pp. 77 ◽

Cited By ~ 7

Author(s):

Zakaria Dakhli ◽

Zoubeir Lafhaj ◽

Alan Mossman

Keyword(s):

Transaction Costs ◽

No Value ◽

Significant Proportion ◽

Cost Savings ◽

Future Research ◽

Potential Cost ◽

Client Group ◽

Blockchain Technology ◽

The Uk ◽

Real Estate Company

Construction customers want more complex facilities delivered faster and at a lower cost. Transaction costs account for a significant proportion of each new or refurbished facility (a 2017 report from the Infrastructure Client Group in the UK suggests as high as 50%), yet they contribute no value to the customer. Blockchain is being suggested as a way to reduce transaction costs by eliminating the need for intermediaries to build trust as a prerequisite for successfully executed agreements. This study first describes the thinking that underpins blockchain technology, outlining how it works, and the potential limitations of the technology. Second, using a case study, reviews the potential cost savings from the use of blockchain for a real estate company. The results reveal a potential cost savings from blockchain deployment at 8.3% of the total cost of residential construction, with a standard deviation of 1.26%. Third, we explore the implications, risks and applications of blockchain technology for improving flow in the end-to-end design and construction process and we identify opportunities for future research on blockchain applications in construction.

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Pilot Implementation of Public Transport Priority in the City of Zagreb

PROMET - Traffic&Transportation ◽

10.7307/ptt.v27i3.1735 ◽

2015 ◽

Vol 27 (3) ◽

pp. 257-265 ◽

Cited By ~ 9

Author(s):

Miroslav Vujić ◽

Sadko Mandzuka ◽

Martin Greguric

Keyword(s):

Public Transport ◽

Traffic Control ◽

Traffic Congestion ◽

Urban Areas ◽

Urban Traffic ◽

Control Measures ◽

Traffic Demand ◽

Public Transport System ◽

Adaptive Traffic Control ◽

The City

The problem with traffic congestion is particularly expressed in urban areas where possibilities for physical increment of capacity are limited or impossible. Significant in the approach to solving this problem is the usage of Public Transport (PT) and the implementation of various advanced control measures that can improve the quality of overall public transport system. The main objective of this research is to explore the possibilities of implementation of adaptive traffic control on signalized intersections giving priority to public transport vehicles through urban traffic network in the city of Zagreb. The possibilities of implementing public transport priority (PTP) technique in the city of Zagreb are analyzed because of specific traffic situations on defined corridors (location of stops, distance between intersections, etc.). With proper usage of PTP techniques (e.g. adequate detector positions, good estimation of PT vehicle arrival time at intersection) the total tram travel time can be significantly reduced. The Level of Service at intersection may be approximately retained because cross-street traffic demand was not ignored. According to technological level of traffic control system in the city of Zagreb, global implementation of PTP is not possible. So, for each intersection the PTP algorithm was developed separately, but mutual traffic influence of all intersections on the corridor was considered. The cooperative concept application within urban traffic control is considered as well.

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A Survey of Methods and Technologies for Congestion Estimation Based on Multisource Data Fusion

Applied Sciences ◽

10.3390/app11052306 ◽

2021 ◽

Vol 11 (5) ◽

pp. 2306

Author(s):

Dominik Cvetek ◽

Mario Muštra ◽

Niko Jelušić ◽

Leo Tišljarić

Keyword(s):

Data Fusion ◽

Traffic Flow ◽

Traffic Congestion ◽

Urban Areas ◽

Negative Impact ◽

Network Capacity ◽

Multiple Sources ◽

Traffic Demand ◽

Advantages And Disadvantages ◽

Fusion Methods

Traffic congestion occurs when traffic demand is greater than the available network capacity. It is characterized by lower vehicle speeds, increased travel times, arrival unreliability, and longer vehicular queueing. Congestion can also impose a negative impact on the society by decreasing the quality of life with increased pollution, especially in urban areas. To mitigate the congestion problem, traffic engineers and scientists need quality, comprehensive, and accurate data to estimate the state of traffic flow. Various types of data collection technologies have different advantages and disadvantages as well as data characteristics, such as accuracy, sampling frequency, and geospatial coverage. Multisource data fusion increases the accuracy and provides a comprehensive estimation of the performance of traffic flow on a road network. This paper presents a literature overview related to the estimation of congestion and prediction based on the data collected from multiple sources. An overview of data fusion methods and congestion indicators used in the literature for traffic state and congestion estimation is given. Results of these methods are analyzed, and a disseminative analysis of the advantages and disadvantages of surveyed methods is presented.

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Web-Face-to-Face Mixed-Mode Design in a Longitudinal Survey: Effects on Participation Rates, Sample Composition, and Costs

Journal of Official Statistics ◽

10.1515/jos-2017-0019 ◽

2017 ◽

Vol 33 (2) ◽

pp. 385-408 ◽

Cited By ~ 8

Author(s):

Annamaria Bianchi ◽

Silvia Biffignandi ◽

Peter Lynn

Keyword(s):

Mixed Mode ◽

Large Scale ◽

Cost Savings ◽

Longitudinal Survey ◽

Potential Cost ◽

Face To Face ◽

Mode Design ◽

Cumulative Response ◽

Sample Composition ◽

The Uk

AbstractSequential mixed-mode designs are increasingly considered as an alternative to interviewer-administered data collection, allowing researchers to take advantage of the benefits of each mode. We assess the effects of the introduction of a sequential web-face-to-face mixed-mode design over three waves of a longitudinal survey in which members were previously interviewed face-to-face. Findings are reported from a large-scale randomised experiment carried out on the UK Household Longitudinal Study. No differences are found between the mixed-mode design and face-to-face design in terms of cumulative response rates and only minimal differences in terms of sample composition. On the other hand, potential cost savings are evident.

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Improving the Performance of Cloud-based Scientific Services

10.26686/wgtn.17019068.v1 ◽

2021 ◽

Author(s):

◽

Ryan Chard

Keyword(s):

Large Scale ◽

Network Performance ◽

Cost Model ◽

Cost Savings ◽

Search Space ◽

Management Service ◽

Cloud Infrastructure ◽

Potential Cost ◽

Application Performance ◽

Trade Offs

Cloud computing provides access to a large scale set of readily available computing resources at the click of a button. The cloud paradigm has commoditised computing capacity and is often touted as a low-cost model for executing and scaling applications. However, there are significant technical challenges associated with selecting, acquiring, configuring, and managing cloud resources which can restrict the efficient utilisation of cloud capabilities. Scientific computing is increasingly hosted on cloud infrastructure—in which scientific capabilities are delivered to the broad scientific community via Internet-accessible services. This migration from on-premise to on-demand cloud infrastructure is motivated by the sporadic usage patterns of scientific workloads and the associated potential cost savings without the need to purchase, operate, and manage compute infrastructure—a task that few scientific users are trained to perform. However, cloud platforms are not an automatic solution. Their flexibility is derived from an enormous number of services and configuration options, which in turn result in significant complexity for the user. In fact, naïve cloud usage can result in poor performance and excessive costs, which are then directly passed on to researchers. This thesis presents methods for developing efficient cloud-based scientific services. Three real-world scientific services are analysed and a set of common requirements are derived. To address these requirements, this thesis explores automated and scalable methods for inferring network performance, considers various trade-offs (e.g., cost and performance) when provisioning instances, and profiles application performance, all in heterogeneous and dynamic cloud environments. Specifically, network tomography provides the mechanisms to infer network performance in dynamic and opaque cloud networks; cost-aware automated provisioning approaches enable services to consider, in real-time, various trade-offs such as cost, performance, and reliability; and automated application profiling allows a huge search space of applications, instance types, and configurations to be analysed to determine resource requirements and application performance. Finally, these contributions are integrated into an extensible and modular cloud provisioning and resource management service called SCRIMP. Cloud-based scientific applications and services can subscribe to SCRIMP to outsource their provisioning, usage, and management of cloud infrastructures. Collectively, the approaches presented in this thesis are shown to provide order of magnitude cost savings and significant performance improvement when employed by production scientific services.

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Using Industry 4.0 Concept – Digital Twin – to Improve the Efficiency of Leather Cutting in Automotive Industry

Quality Innovation Prosperity ◽

10.12776/qip.v23i2.1211 ◽

2019 ◽

Vol 23 (2) ◽

pp. 01 ◽

Cited By ~ 2

Author(s):

Miroslava Horváthová ◽

Roman Lacko ◽

Zuzana Hajduová

Keyword(s):

Industry 4.0 ◽

Large Scale ◽

Material Selection ◽

Cost Savings ◽

Future Research ◽

Scale Production ◽

Data Set ◽

Digital Twin ◽

Business Entities ◽

Number Of Publications

Purpose: The aim of this study is to propose alternatives of increasing the efficiency of material selection and processing in the selected company and reduce costs and leather sustainability as a result.Methodology/Approach: In this case study, an automotive company processing a natural leather material that enters the process of a large-scale production was explored. For this purpose, the internal documents of the firm selected including its internal database and know-how of its employees were used. The ways of improving the efficiency of the material processing were proposed and tested in a digital environment. In the proposed solutions, Industry 4.0 principles were implemented.Findings: By the use of Digital twin and other Industry 4.0 principles and solutions in the process of material selection and processing in the company selected, the increased efficiency and cost savings were achieved.Research Limitation/implication: The solutions proposed in this paper were based on exploration of the chosen data set of the selected company. For the future research, testing of the given proposals in other companies should be conducted.Originality/Value of paper: Although there is an increasing number of publications describing the concept Industry 4.0, the research providing evidence of its benefits for business entities is still scarce. This paper offers such a research in the enterprise selected.

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A Large Scale, App-Based Behaviour Change Experiment Persuading Sustainable Mobility Patterns: Methods, Results and Lessons Learnt

Sustainability ◽

10.3390/su11092674 ◽

2019 ◽

Vol 11 (9) ◽

pp. 2674 ◽

Cited By ~ 5

Author(s):

Francesca Cellina ◽

Dominik Bucher ◽

Francesca Mangili ◽

José Veiga Simão ◽

Roman Rudel ◽

...

Keyword(s):

Energy Consumption ◽

Public Transportation ◽

Urban Areas ◽

Large Scale ◽

Controlled Trial ◽

Drop Out ◽

Future Research ◽

Sustainable Mobility ◽

Randomized Controlled ◽

Lessons Learnt

The present urban transportation system, mostly tailored for cars, has long shown its limitations. In many urban areas, public transportation and soft mobility would be able to effectively satisfy many travel needs. However, they tend to be neglected, due to a deep-rooted car dependency. How can we encourage people to make sustainable mobility choices, reducing car use and the related CO 2 emissions and energy consumption? Taking advantage of the wide availability of smartphone devices, we designed GoEco!, a smartphone application exploiting automatic mobility tracking, eco-feedback, social comparison and gamification elements to persuade individual modal change. We tested the effectiveness of GoEco! in two regions of Switzerland (Cantons Ticino and Zurich), in a large-scale, one year long randomized controlled trial. Notwithstanding a large drop-out rate experienced throughout the experiment, GoEco! was observed to produce a statistically significant impact (a decrease in CO 2 emissions and energy consumption per kilometer) for systematic routes in highly car-dependent urban areas, such as the Canton Ticino. In Zurich, instead, where high quality public transport is already available, no statistically significant effects were found. In this paper we present the GoEco! experiment and discuss its results and the lessons learnt, highlighting practical difficulties in performing randomized controlled trials in the field of mobility and providing recommendations for future research.

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