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Applied Sciences
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Transport Mobility in a Changing Word: Survey Applications, Sensors and...
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Transport Mobility in a Changing Word: Survey Applications, Sensors and Automatic Data Collection Methods

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 11020

Special Issue Editors

Dr. Vicenza Torrisi

E-Mail Website
Guest Editor
DICAR, Department of Civil Engineering and Architecture, University of Catania, Via S. Sofia 64, 95125 Catania, Italy
Interests: sustainable mobility; transport planning and management; Smart mobility and MaaS; Intelligent Transport Systems; dynamic traffic assignment and real-time network analysis; shared mobility; accessibility; vulnerable users; microsimulation; traffic data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Tiziana Campisi

E-Mail Website
Guest Editor
Faculty of Engineering and Architecture, University of Enna Kore, 94100 Enna, Italy
Interests: sustainable urban mobility; mobility management; first last mile logistics
Special Issues, Collections and Topics in MDPI journals
Dr. Rosalia Camporeale

E-Mail Website
Guest Editor
Department of Technology and Society, Lund University, 22100 Lund, Sweden
Interests: bike-sharing systems; public transport systems; sustainable mobility; transportation network design; equity; accessibility; vulnerable groups; transport planning
Special Issues, Collections and Topics in MDPI journals
Dr. Sarbast Moslem

E-Mail Website
Guest Editor
School of Architecture Planning and Environmental Policy, University College Dublin, Richview Sch of Architecture Belfield Dublin 4, Dublin, Ireland
Interests: multi criteria decision making (MCDM); sustainable transport planning; public transport; mobility choice; driver behavior; road safety
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Transport mobility is one of the key issues of the historical period that we are witnessing. This need for mobility is determined by a lifestyle that implies trips for work, study, leisure, etc. Likewise or maybe even more than other sectors, the transportation sector is characterized by a deep transformation, boosted by a variety of technological innovations that, especially during this COVID-19 emergency, are deeply affecting the mobility habits, needs, and preferences of passengers and businesses. Our main area of interest is the description and analysis of strategies, initiatives, and actions identified and implemented through the acquisition, elaboration, and interpretation of data from different sources, aimed at the possibility of promoting, disseminating, and undertaking the change towards sustainable mobility. Through an adequate survey policy (both online and paper-based) it can possible to acquire, in a simple way, timely information about transport modes, mobility needs, characterization of different user classes and about the triggers that can encourage and accompany this change.

Furthermore, the evolution of people's travel behavior must be supported by adequate technological solutions, such as sensors for interacting with vehicles and passengers (e.g., VMS for infomobility services, route planner, driver assistance, traffic lights, bus poles) and data collection for flow monitoring (cameras, radar sensors, tubes, bluetooth), for the detection of emissions (e.g., pollution and weather sensors), real-time localization of public transport (e.g., on-board GPS control units) and infrastructure status (e.g., to schedule any maintenance). This Special Issue aims to collect high-quality articles focused on describing the conception, direction, and coordination of survey applications for exploring user needs and their attitudes towards mobility; and on describing sensors and automatic data collection methods (such as the acquisition of data from fixed equipment or public and private floating vehicles, and up to the monitoring of the cyclists and pedestrians). This is the attempt to shape a comprehensive knowledge of the phenomenon and to foster sustainable mobility in view of social inclusion, environmental mitigation risks, and innovation. This topic can be interesting for scientists who deal with sustainable mobility and innovative transport planning and management, as well as sustainable and smart cities, and/or emerging technologies to identify, implement and monitor actions that aim (in a global vision of economic, social, and environmental sustainability) to improve the mobility and the quality of life. Other important areas of concern regarding transport mobility data acquisition include but are not limited to:

  • Smart and sustainable mobility
  • Transport needs and choice of transport modes
  • Information and communication technologies and Intelligent Transport Systems
  • Urban planning, management and decision support
  • Mixed survey data
  • Fixed and mobile sensors and actuators
  • Transport network analysis and optimization
  • Traffic simulation, monitoring and forecasting
  • Different data sources and database management
  • Traffic data elaboration and technologically integrated dashboards
  • Network modelling and server infrastructure
  • Travel information systems (travel times, costs, presence of parking, route planner, infomobility services)
  • Systems for monitoring and reduction of emissions
  • Electric and autonomous vehicles
  • Smart cities
  • Transport and land use

Dr. Vicenza Torrisi
Prof. Dr. Tiziana Campisi
Dr. Rosalia Camporeale
Dr. Sarbast Moslem
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sustainable and smart mobility
  • Sustainable transport planning and management
  • Smart cities
  • Sustainable urban planning and management
  • Transport modelling and analysis
  • Resilient cities
  • Big data and IoT
  • Shared mobility, MaaS
  • Fixed and mobile sensors and actuators
  • Electric and autonomous vehicles
  • Intelligent Transport Systems (ITS) and Information and Communication Technologies (ICT)
  • Cyber security
  • Infrastructures plan, design, and maintenance
  • Vulnerable users
  • Disabilities and architectural barriers
  • Pollutant emissions
  • Mixed survey data and questionnaires
  • GPS and FCD data
  • Public transport
  • Driver behavior
  • Road safety

Published Papers (4 papers)

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Research

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14 pages, 7285 KiB  
Article
Exploring Space Syntax Integration at Public Transport Hubs and Public Squares Using Drone Footage
by Carl Johnsson and Rosalia Camporeale
Appl. Sci. 2022, 12(13), 6515; https://0-doi-org.brum.beds.ac.uk/10.3390/app12136515 - 27 Jun 2022
Cited by 1 | Viewed by 1844
Abstract
Space Syntax theory is a methodological framework for describing and analysing the relationships between spaces and buildings. The fundamental building blocks of Space Syntax are called axial lines, which represent lines of sight from a specific point in space. These lines can then [...] Read more.
Space Syntax theory is a methodological framework for describing and analysing the relationships between spaces and buildings. The fundamental building blocks of Space Syntax are called axial lines, which represent lines of sight from a specific point in space. These lines can then be used to quantitatively analyse the integration (or attractiveness) of an area. However, many public squares and transport hubs are crossed by roads which prove a hinderance when walking although not impairing the sightlines of pedestrians. The aim of this paper is to test how this limitation affects the concept and whether Space Syntax is still useful to understand how people move in such areas. Seven public squares and transport hubs in Malmö (Sweden) were selected and their Space Syntax integration was calculated. These values were compared with pedestrian detections from the same areas based on video recordings from a drone. When aggregating the areas into several levels based on their integration value, the result shows a clear link between Space Syntax integration and the number of pedestrian detections made at each location, demonstrating how this measure could be useful for understanding micromobility usage on a small scale. Full article
(This article belongs to the Special Issue Transport Mobility in a Changing Word: Survey Applications, Sensors and Automatic Data Collection Methods)
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26 pages, 10127 KiB  
Article
Discovering Intra-Urban Population Movement Pattern Using Taxis’ Origin and Destination Data and Modeling the Parameters Affecting Population Distribution
by Fatema Rahimi, Abolghasem Sadeghi-Niaraki, Mostafa Ghodousi and Soo-Mi Choi
Appl. Sci. 2021, 11(13), 5987; https://0-doi-org.brum.beds.ac.uk/10.3390/app11135987 - 27 Jun 2021
Viewed by 1391
Abstract
GPS-equipped vehicles are an effective approach for acquiring urban population movement patterns. Attempts have been made in the present study in order to identify the population displacement pattern of the study region using taxis’ origin and destination data, and then model the parameters [...] Read more.
GPS-equipped vehicles are an effective approach for acquiring urban population movement patterns. Attempts have been made in the present study in order to identify the population displacement pattern of the study region using taxis’ origin and destination data, and then model the parameters affecting the population displacement pattern and provide an ultimate model in order to predict pick-up and drop-off locations. In this way, the passenger pick-up and drop-off locations have been identified in order to obtain the population movement pattern. In this study, Moran’s I index was used to measure the spatial autocorrelation, and hot spot analysis was used to analyze spatial patterns of pick-up and drop-off locations. Effective parameters modeling was performed using the Poisson regression. The results of the spatiotemporal distribution map for pick-up and drop-off locations indicated a similarity in patterns and equal results for some locations. Results also indicated different features of spatial distribution during different hours of the day. Spatial autocorrelation analysis results indicated a low probability of randomness in the general spatial distribution of the locations. The result of modeling the parameters shows the positive effect of the parameters on the pattern of population movement, and according to the p-value of 0.000, Poisson regression is significant for the pick-up and drop-off locations. The modeling results also highlighted the importance of movement patterns in recognizing urban hot spots, which is valuable for policymakers and urban planners. Full article
(This article belongs to the Special Issue Transport Mobility in a Changing Word: Survey Applications, Sensors and Automatic Data Collection Methods)
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17 pages, 1097 KiB  
Article
Mobility Patterns of Students: Evidence from Tricity Area, Poland
by Agnieszka Szmelter-Jarosz and Michał Suchanek
Appl. Sci. 2021, 11(2), 522; https://0-doi-org.brum.beds.ac.uk/10.3390/app11020522 - 07 Jan 2021
Cited by 15 | Viewed by 2191
Abstract
Generational change is one of the vital socioeconomic forces affecting the global economic environment. In many studies, the youngest generations are presented as the ones changing the market trends. This can also be observed in areas of travel demand and mobility patterns. However, [...] Read more.
Generational change is one of the vital socioeconomic forces affecting the global economic environment. In many studies, the youngest generations are presented as the ones changing the market trends. This can also be observed in areas of travel demand and mobility patterns. However, research on those topics in many countries, for many societies, is scarce. This study aimed to examine the travel behavior of Polish young adults, namely students living in the Tricity area. Factor analysis and ANOVA were used to analyze the data gathered via an online survey assessing the characteristics of mobility patterns of students born between 1981 and 1999. Factor analysis allowed grouping the attitudes towards traveling among those young adults (Y Generation, Y’s, Y Gen). Three factors were identified, and they were associated with luxury and self-expression, freedom and comfort, safety and environmental friendliness. The driver’s characteristics were the least consistent with the classic image of typical Y’s, and those using the active commute—the most. In turn, the largest group were people using public transport, which partially presented convergent opinions with drivers and users of the active commute. It turned out that the car drivers, active commuters and respondents utilizing public transport differed not only in their behavior and presentation of Y Gen characteristics but also in their attitude towards categories such as comfort, desire for luxury, economy or ecology. This study is a complex analysis of the mobility patterns of students in the Tricity area. It presents the set of variables influencing the travel demand of the chosen age group. The study also compares the presented travel choices with those declared by representatives of other nations. Finally, it indicates the next research problems to be addressed in future research. Full article
(This article belongs to the Special Issue Transport Mobility in a Changing Word: Survey Applications, Sensors and Automatic Data Collection Methods)
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Review

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20 pages, 344 KiB  
Review
A Survey of Methods and Technologies for Congestion Estimation Based on Multisource Data Fusion
by Dominik Cvetek, Mario Muštra, Niko Jelušić and Leo Tišljarić
Appl. Sci. 2021, 11(5), 2306; https://0-doi-org.brum.beds.ac.uk/10.3390/app11052306 - 05 Mar 2021
Cited by 21 | Viewed by 3986
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Transport Mobility in a Changing Word: Survey Applications, Sensors and Automatic Data Collection Methods)
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