Evaluating Traffic Impacts of Permitting Trucks in Transit-Only Lanes

2021 ◽  
pp. 036119812110318
Author(s):  
Seyma Gunes ◽  
Anne Goodchild ◽  
Chelsea Greene ◽  
Venu Nemani
Keyword(s):  
Management Strategy ◽  
Choice Model ◽  
Rapid Development ◽  
Video Data ◽  
Urban Setting ◽  
Passenger Cars ◽  
Goods And Services ◽  
Drastic Increase ◽  
Traffic Impacts ◽  
Unused Capacity

With ongoing population growth and rapid development in cities, the demand for goods and services has seen a drastic increase. Consequently, transportation planners are searching for new ways to better manage the flow of traffic on existing facilities, and more efficiently utilize available and unused capacity. In this research, a lane management strategy that allows freight vehicles to use bus-only lanes is empirically evaluated in an urban setting. This paper presents an analysis of data that was collected to evaluate the operational impacts of the implementation of a freight and transit (FAT) lane, and to guide the development of future FAT lane projects by learning from the case study in Seattle, U.S. The video data was converted to vehicle counts, which were analyzed to understand the traffic impacts and used to construct a discrete choice model. The analysis shows that transit buses used the FAT lane 96% of the time, and authorizing trucks to use the lane did not affect that lane choice. Trucks used the FAT lane, but their utilization decreased with increasing numbers of buses in the FAT lane. Instead of higher rates of trucks, unauthorized vehicles, such as passenger cars and work vans, increasingly used the FAT lane during congestion. As a result of their differing schedule patterns, trucks and buses used the FAT lane at complementary times and trucks showed relatively low volumes in the FAT lane. Overall, the results are promising for a lane management strategy that may improve freight system performance without reducing transit service quality.

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

scholarly journals Comparative analysis of the stock quotes dynamics for IT-sector and the entertainment industry companies based on the characteristics of memory depth

2021 ◽  
Vol 107 ◽  
pp. 01003
Author(s):  
Nataliia Maksyshko ◽  
Oksana Vasylieva
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Rapid Development ◽  
Entertainment Industry ◽  
Long Term Memory ◽  
Range Analysis ◽  
Goods And Services ◽  
Rescaled Range Analysis ◽  
Persistence Property ◽  
The Impact

The article is devoted to the study and comparative analysis of the stock quotes dynamics for the world’s leading companies in the IT sector and the entertainment industry. Today, these areas are developing the fastest and most powerful, which attracts the attention of investors around the world. This is due to the rapid development of digital communication technologies, the growth of intellectualization and individualization of goods and services, and so on. These spheres have strong development potential, but the question to how their companies’ stock quotes respond to the impact of such a natural but crisis phenomenon as the COVID-19 pandemic remains open. Based on the nonlinear paradigm of the financial markets dynamics, the paper considers and conducts a comprehensive fractal analysis of the quotations dynamics for six leading companies (Apple Inc., Tesla Inc., Alphabet Inc., The Walt Disney Company, Sony Corporation, Netflix) in this area before and during the COVID-19 pandemic. As a result of the application of the rescaled range analysis (R/S analysis), the presence of the persistence property and long-term memory in the stock quotes dynamics for all companies and its absence in their time series of profitability was confirmed. The application of the method of sequential R/S analysis made it possible to construct fuzzy sets of memory depths for the considered time series and to deepen the analysis of the dynamics due to the quantitative characteristics calculated on their basis. Taking into account the characteristics of memory depth in the dynamics of quotations made it possible to conduct a comparative analysis of the dynamics, both under the influence of the natural crisis situation and in terms of investing in different terms. The peculiarities of the delayed profitability dynamics of quotations for each of the companies are also taken into consideration and compared. The developed recommendations can be used in investment activities in the stock market.

A Modeling Analysis of Impact from E-Hailing Service on Non-Work Travel Mode in Shanghai, China

2018 ◽  
Vol 2672 (47) ◽  
pp. 125-134 ◽  
Author(s):  
Jiayu Zhong ◽  
Xin Ye ◽  
Ke Wang ◽  
Dongjin Li
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Choice Model ◽  
Mode Choice ◽  
Rapid Development ◽  
Influential Factors ◽  
Travel Mode ◽  
Explanatory Variables ◽  
Bus Travel Time ◽  
Vehicle Travel Time

With the rapid development of mobility services, e-hailing service have been highly prevalent and e-hailing travel has become a part of daily life in many cities in China. At the same time, travelers’ mode choice behaviors have been influenced to some degree by different factors, and in this paper, a web-based retrospective survey initially conducted in Shanghai, China is used to analyze the extent to which various factors are influencing mode choice behaviors. Then, a multinomial-logit-based mode choice model is developed to incorporate the e-hailing auto mode as a new travel mode for non-work trips. The developed model can help to identify influential factors and quantify their impact on mode choice probabilities. The developed model involves a variety of explanatory variables including e-hailing/taxi fare, bus travel time, rail station access/egress distance, trip distance, car in-vehicle travel time as well as travelers’ socioeconomic and demographic characteristics, etc. The model indicates that the e-hailing fare, travel companions and some travelers’ characteristics (e.g., age, income, etc.) are significant factors influencing the choice of e-hailing mode. The alternative-specific constant in the e-hailing utility equation is adjusted to match the observed market share of the e-hailing mode. Based on the developed model, elasticities of LOS attributes are computed and discussed. The research methods used in this paper have the potential to be applied to investigate travel behavior changes under the influence of emerging travel modes. The research findings can aid in evaluating policies to manage e-hailing services and improve their levels of services.

scholarly journals Grassmann Manifold Based State Analysis Method of Traffic Surveillance Video

2019 ◽  
Vol 9 (7) ◽  
pp. 1319 ◽  
Author(s):  
Peng Qin ◽  
Yong Zhang ◽  
Boyue Wang ◽  
Yongli Hu
Keyword(s):  
Euclidean Space ◽  
Grassmann Manifold ◽  
Rapid Development ◽  
Video Data ◽  
High Dimensional ◽  
Intelligent Transport System ◽  
Surveillance Video ◽  
Traffic Surveillance ◽  
Traditional Methods ◽  
State Analysis

For a contemporary intelligent transport system, congestion state analysis of traffic surveillance video (TSV) is one of the most crucial and intricate research topics because of the rapid development of transportation systems, the sustained growth of surveillance facilities on road, which lead to massive traffic flow data, and the inherent characteristics of our analysis target. Traditional methods on feature extractions are usually operated on Euclidean space in general, which are not accurate for high-dimensional TSV data analysis. This paper proposes a Grassmann manifold based neural network model to analysis TSV data , by mapping the video data from high dimensional Euclidean space to Grassmann manifold space, and considering the inner relation among adjacent cameras. The accuracy of the traffic congestion is improved, compared with several traditional methods. Experimental results are conducted to validate the accuracy of our method and to investigate the effects of different factors on performance.

scholarly journals Mode choice model for public transport (ferry, fast ship and aircraft) study case: Kupang - Rote Route

2019 ◽  
Vol 270 ◽  
pp. 03011
Author(s):  
Margareth E. Bolla ◽  
Rossy A. Bella ◽  
Aprianto Nomleni ◽  
Desy Yuliaty Tungga
Keyword(s):  
Choice Model ◽  
Multinomial Logistic Regression ◽  
Air Transportation ◽  
Transportation Services ◽  
Multinomial Logistic Regression Analysis ◽  
Goods And Services ◽  
Sea Transportation ◽  
Mode Of Transportation ◽  
Study Case ◽  
Aircraft Study

The mode of transportation that travels from Kupang City to Rote Ndao Regency is currently a mode of sea transportation and air transportation. This study aims to find out user information based on its mode choices and model it in the multinomial log function, besides that it's hoped that this result can be used as a reference in determining policies that improve functions and facilities for mobilizing people, goods and services carried out on the Kupang to Rote.Data analysis was carried out in two ways, namely with descriptive statistical analysis techniques to explain the characteristics of respondents and multinomial logistic regression analysis to create a model of mode transportation selection for Kupang-Rote service. The results of the study showed that users of transportation services from Kupang to Rote, generally men prefer to use ferry boats while women prefer to use fast boats. The characteristics of respondents is age 20-39 years. While the factors that influence the choice of transportation are the influence of luggage, weather and comfort. For the selection model, the probability of a speedboat is 34.65%,the probability of choosing a ferry is 42.96%, and the probability of choosing an aircraft is 22.3%.

Applied Research of Assessment Methods on Video Quality

2012 ◽  
Vol 262 ◽  
pp. 157-162
Author(s):  
Chong Gu ◽  
Zhan Jun Si
Keyword(s):  
Video Processing ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Rapid Development ◽  
Video Quality ◽  
Objective Evaluation ◽  
Video Data ◽  
Assessment System ◽  
Video Encoding ◽  
High Definition

With the rapid development of modern video technology, the range of video applications is increasing, such as online video conferencing, online classroom, online medical, etc. However, due to the quantity of video data is large, video has to be compressed and encoded appropriately, but the encoding process may cause some distortions on video quality. Therefore, how to evaluate the video quality efficiently and accurately is essential in the fields of video processing, video quality monitoring and multimedia video applications. In this article, subjective, and comprehensive evaluation method of video quality were introduced, a video quality assessment system was completed, four ITU recommended videos were encoded and evaluated by Degradation Category Rating (DCR) and Structural Similarity (SSIM) methods using five different formats. After that, comprehensive evaluations with weights were applied. Results show that data of all three evaluations have good consistency; H.264 is the best encoding method, followed by Xvid and wmv8; the higher the encoding bit rate is, the better the evaluations are, but comparing to 1000kbps, the subjective and objective evaluation scores of 1400kbps couldn’t improve obviously. The whole process could also evaluate new encodings methods, and is applicable for high-definition video, finally plays a significant role in promoting the video quality evaluation and video encoding.

scholarly journals Disaggregating Ecosystem Benefits: An Integrated Environmental-Deprivation Index

2020 ◽  
Vol 12 (18) ◽  
pp. 7589 ◽  
Author(s):  
Emily C. Hazell
Keyword(s):  
Ecosystem Services ◽  
Composite Index ◽  
Principal Component ◽  
Well Being ◽  
Urban Ecosystem ◽  
Urban Setting ◽  
Measurement Scale ◽  
Policy Outcomes ◽  
Goods And Services ◽  
Environmental Deprivation

The valuation of ecosystem services has become an integral part of smart urban planning practices. Traditionally designed to bridge ecology and economy through economic language and logic (e.g., goods and services), this conceptual framework has developed into an effective tool for interdisciplinary work. The concept of ecosystem services is used to improve the management of ecosystems for human well-being. However, gaps in how to govern ecological benefits remain. Specifically, identifying which stakeholders benefit the most from the provision of ecosystem services remains largely unaddressed. This study examines the spatial discordance between ecosystem services and the residential stakeholders who may benefit. Using a landscape approach to quantify urban ecosystem services, an area-based composite index was developed for the City of Toronto, Canada, based on the three pillars of sustainability in order to identify potentially vulnerable populations. This method combines the use of principal component analysis (PCA) and spatial multicriteria decision analysis (GIS-MCDA) to combine and weight a select grouping of socioeconomic and ecological indicators. In addition, two sets of enumeration units (i.e., dissemination areas and census tracts) were evaluated to assess the potential impact of measurement scale on subsequent decision or policy outcomes. Results indicate the spatial interdependencies between ecological and socioeconomic processes in an urban setting, offering a unique framework for novel planning and policy intervention strategies. The influence of measurement scale was demonstrated, creating an opportunity to assess an appropriate policy scale by which to measure and evaluate trends over time and space. This approach seeks to provide a flexible and intuitive planning tool that can help to achieve goals relating to urban sustainability, resiliency and equity.

Fulminant diabetes mellitus and concomitant enterovirus infection: a clinical case

2020 ◽  
Vol 26 (2) ◽  
pp. 125-132
Author(s):  
T. V. Saprina ◽  
N. N. Musina ◽  
S. V. Vtorushin ◽  
N. V. Krakhmal’ ◽  
Yu. V. Rogovskaya
Keyword(s):  
Diabetes Mellitus ◽  
Management Strategy ◽  
Clinical Case ◽  
Rapid Development ◽  
Fulminant Type 1 Diabetes ◽  
Pancreatic Cells ◽  
Total Destruction ◽  
Fulminant Diabetes ◽  
Fulminant Type

Fulminant type 1 diabetes mellitus is a subtype of diabetes mellitus. It is characterized by the extremely rapid development of hyperglycemia and ketoacidosis because of the near-total destruction of pancreatic -cells. A clinical case of lethal, type 1, fulminant diabetes mellitus is presented. The patient management strategy and possible causes of the adverse course and outcome of the disease are analyzed.

Research on Key Technologies of Massive Videos Management Under the Background of Cloud Platform

2019 ◽  
Vol 23 (1) ◽  
pp. 72-77
Author(s):  
Lin Jin ◽  
◽  
Changhong Yan
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Management System ◽  
Rapid Development ◽  
Mobile Internet ◽  
Video Data ◽  
Cloud Platform ◽  
Module Design ◽  
Management Platform ◽  
Key Technologies

With the rapid development of mobile internet and smart city, video surveillance is popular in areas such as transportation, schools, homes, and shopping malls. It is important subject to manage the massive videos quickly and accurately. This paper tries to use Hadoop cloud platform for massive video data storage, transcoding and retrieval. The key technologies of cloud computing and Hadoop are introduced firstly in the paper. Then, we analyze the functions of video management platform, such as user management, videos storage, videos transcoding, and videos retrieval. According to the basic functions and cloud computing, each module design process and figure are provided in the paper. The massive videos management system based on cloud platform will be better than the traditional videos management system in the aspects of storage capacity, transcoding performance and retrieval speed.

scholarly journals Direct and cross price elasticities of demand for gasoline, diesel, hybrid and battery electric cars: the case of Norway

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Lasse Fridstrøm ◽  
Vegard Østli
Keyword(s):  
Choice Model ◽  
Market Response ◽  
Energy Prices ◽  
Market Demand ◽  
Passenger Cars ◽  
Data Set ◽  
Electric Cars ◽  
Price Elasticities ◽  
Approval Rate ◽  
The Cross

Abstract Aim The primary goals of this research is (i) to derive direct and cross demand market response functions for automobile powertrains and their energy carriers and (ii) to assess how CO2 emissions from automobiles depend on vehicle and energy prices Methods The market demand for automobiles with differing powertrains is studied by means of a discrete choice model. Statistically precise coefficient estimates are calculated by means of a highly disaggregate data set consisting of virtually all 1.8 million new passenger car transactions in Norway during 2002–2016. Having estimated the model, we derive market response parameters in the form of direct and cross price elasticities of demand for gasoline, diesel, ordinary hybrid, plug-in hybrid and battery electric cars. Results The own-price elasticity of gasoline driven cars is estimated at −1.08, and those of diesel driven, battery electric and plug-in hybrid electric cars at –0.99, −1.27 and −1.72, respectively, as of 2016 in Norway. The cross price elasticities of demand for gasoline cars with respect to the price of diesel cars, and vice versa, are estimated at 0.64 and 0.51, while the cross price elasticities of demand for battery electric cars with respect to the prices of gasoline and diesel driven cars come out at 0.36 and 0.48, respectively. A 1 % increase in the price of liquid fuel in general is found to reduce the average type approval rate of CO2 emission from new passenger cars by an estimated 0.19%. Conclusion Fiscal policy measures affecting the prices of vehicles and fuel have a considerable potential for changing the long term composition of the vehicle fleet and its energy consumption, climate footprint and general environmental impact.

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