MDLF: A Multi-View-Based Deep Learning Framework for Individual Trip Destination Prediction in Public Transportation Systems

2021 ◽  
pp. 1-14
Author(s):  
Juanjuan Zhao ◽  
Liutao Zhang ◽  
Jiexia Ye ◽  
Chengzhong Xu
Keyword(s):  
Deep Learning ◽  
Public Transportation ◽  
Transportation Systems ◽  
Learning Framework ◽  
Public Transportation Systems

scholarly journals Virus Transmission Risk in Urban Rail Systems: Microscopic Simulation-Based Analysis of Spatio-Temporal Characteristics

2021 ◽  
pp. 036119812110101
Author(s):  
Jiali Zhou ◽  
Haris N. Koutsopoulos
Keyword(s):  
Public Transportation ◽  
Virus Transmission ◽  
Flow Characteristics ◽  
Transportation Systems ◽  
Transmission Risk ◽  
Microscopic Simulation ◽  
Spatial And Temporal Patterns ◽  
Subway System ◽  
Public Transportation Systems ◽  
The Impact

The transmission risk of airborne diseases in public transportation systems is a concern. This paper proposes a modified Wells-Riley model for risk analysis in public transportation systems to capture the passenger flow characteristics, including spatial and temporal patterns, in the number of boarding and alighting passengers, and in number of infectors. The model is used to assess overall risk as a function of origin–destination flows, actual operations, and factors such as mask-wearing and ventilation. The model is integrated with a microscopic simulation model of subway operations (SimMETRO). Using actual data from a subway system, a case study explores the impact of different factors on transmission risk, including mask-wearing, ventilation rates, infectiousness levels of disease, and carrier rates. In general, mask-wearing and ventilation are effective under various demand levels, infectiousness levels, and carrier rates. Mask-wearing is more effective in mitigating risks. Impacts from operations and service frequency are also evaluated, emphasizing the importance of maintaining reliable, frequent operations in lowering transmission risks. Risk spatial patterns are also explored, highlighting locations of higher risk.

scholarly journals Light Field Image Quality Enhancement by a Lightweight Deformable Deep Learning Framework for Intelligent Transportation Systems

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1136
Author(s):  
David Augusto Ribeiro ◽  
Juan Casavílca Silva ◽  
Renata Lopes Rosa ◽  
Muhammad Saadi ◽  
Shahid Mumtaz ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Intelligent Transportation Systems ◽  
Light Field ◽  
State Of The Art ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Machine Learning Algorithms ◽  
Learning Framework ◽  
Reconstruction Methods

Light field (LF) imaging has multi-view properties that help to create many applications that include auto-refocusing, depth estimation and 3D reconstruction of images, which are required particularly for intelligent transportation systems (ITSs). However, cameras can present a limited angular resolution, becoming a bottleneck in vision applications. Thus, there is a challenge to incorporate angular data due to disparities in the LF images. In recent years, different machine learning algorithms have been applied to both image processing and ITS research areas for different purposes. In this work, a Lightweight Deformable Deep Learning Framework is implemented, in which the problem of disparity into LF images is treated. To this end, an angular alignment module and a soft activation function into the Convolutional Neural Network (CNN) are implemented. For performance assessment, the proposed solution is compared with recent state-of-the-art methods using different LF datasets, each one with specific characteristics. Experimental results demonstrated that the proposed solution achieved a better performance than the other methods. The image quality results obtained outperform state-of-the-art LF image reconstruction methods. Furthermore, our model presents a lower computational complexity, decreasing the execution time.

scholarly journals Design of a Hybrid Storage for Road Public Transportation Systems

2018 ◽  
pp. 149-157 ◽  
Author(s):  
Adriano Alessandrini ◽  
Riccardo Barbieri ◽  
Lorenzo Berzi ◽  
Fabio Cignini ◽  
Antonino Genovese ◽  
...  
Keyword(s):  
Public Transportation ◽  
Transportation Systems ◽  
Hybrid Storage ◽  
Public Transportation Systems

scholarly journals LISP Optimisation of Mobile Data Streaming in Connected Societies

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
T. Balan ◽  
D. Robu ◽  
F. Sandu
Keyword(s):  
Public Transportation ◽  
Network Architecture ◽  
Virtual Machines ◽  
Transportation Systems ◽  
Urban Environments ◽  
Data Streaming ◽  
Host Mobility ◽  
And Migration ◽  
Public Transportation Systems ◽  
Load Balanced

Mobility mechanisms are key elements of “always connected” smart environments. Since the first mobile IPv4 protocols, the IP mobility solutions have evolved from host mobility to network mobility and migration to IPv6, but there are still use-cases to be covered, especially for redundant multihomed scenarios. Also mobility does not refer only to hosts or individuals, but also to code/applications and to virtual machines. LISP (Locator/Identifier Separation Protocol) can contribute to new solutions for both host mobility and virtual machine mobility (e.g., inside enterprise data centers) by the separation of the identifier and location of a network endpoint. The aim of this paper is to propose a LISP based multihome and load-balanced network architecture for urban environments. Validation is done in an emulated environment for the case of an enterprise with distributed locations, but, furthermore, we extrapolate to other mobile urban scenarios, like the case of providing reliable load-balanced and secured Internet in Public Transportation Systems, with a proposal for an open-source implementation.

scholarly journals A NOVEL APPROACH TO OPTIMIZE THE RIDESHARING PROBLEM USING GENETIC ALGORITHM

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 875-878
Author(s):  
S. Rangriz ◽  
M. Davoodi ◽  
J. Saberian
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Public Transportation ◽  
Noise Pollution ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Jam ◽  
Novel Approach ◽  
Proposed Model ◽  
Public Transportation Systems

Abstract. The enormous increase in the number of vehicles in the cities makes plenty of problems including air pollution, noise pollution, and traffic jam. Overcoming these annoying issues needs a significant plan in urban management such as using modern techniques in public transportation systems. Sharing either cars or taxies is one of the most interesting ways that has been used in some countries recently. In this phenomenon, 2 or 3 people use other’s car or taxi. In this article, an innovative approach to share taxies is proposed, and it uses a Genetic Algorithm to determine the placement of travelers in taxies. Therefore, some taxis will be switched off, and this helps to decrease urban traffic jam in cities. The results present that the proposed model turns off 69.8 % of taxies, and also 27.8 % of them carry more than one passenger; hence, this confirms the performance of the proposed model.

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