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Sensors and Data-Driven Intelligent Transportation Systems

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 1831

Special Issue Editors


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Guest Editor
Department of Civil Engineering, Ariel University, Ariel, Israel and UMass Lowell, Lowell, MA, USA
Interests: Transportation Engineering; Transportation Systems Analysis; Intelligent Transportation Systems; Optimization and Simulation Methods
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Massachusetts (UMass) Lowell, Lowell, MA 01854, USA
Interests: Intelligent Transportation Systems; Transportation Safety; Traffic Control and Simulation; Data Analytics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Intelligent Transportation Research Center, Southeast University, Nanjing, 210096, China
Interests: transportation safety and security; intelligent transportation systems; traffic simulation; big data and data mining
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors are essential components of Intelligent Transportation Systems (ITS), such as connected vehicles, automated vehicles, traveler information systems, and advanced traffic control systems. They include loop detectors, mobile devices, traffic cameras, radar and lidar sensors, drones, etc.  These sensors generate an enormous amount of data that are important for guiding decision making in transportation and for efficient operation of the transportation system.

Numerous critical issues can be addressed by the wide range of the sensor applications in ITS.  Some examples of such issues are: how to optimally place sensors and quantify their benefits, how to effectively visualize, analyze and integrate data from various sources using advanced models, and how nontraditional sensor data can be used to develop innovative solutions to traffic operations problems (e.g., incident detection, traffic re-routing, etc.) and traffic safety applications (e.g., hotspot identification).

This Special Joint Issue focuses on innovative ITS solutions enabled by both traditional and nontraditional sensors. Submissions related to all aspects of sensor-enabled innovative ITS applications are encouraged. Specific topics of interest include, but are not limited to:

  • Optimal placement of sensors
  • Development and evaluation of new sensor applications for ITS problems
  • Innovative traffic safety solutions based on advanced sensors, such as Surrogate Safety Measures (SSM) derived from sensor data
  • Crash count and hotspot modeling based on emerging data sources
  • Development of advanced statistical and Artificial Intelligence (AI) models using ITS sensor data (e.g., asset conditions, traffic videos, telemetry data)
  • Advanced transportation decision making models based on sensor data
  • Deriving critical transportation planning data such as travel demands, Origin-Destination (OD) information, travel times, traffic volumes from data collected using cameras, loop detectors, smartphones, microwave detectors, Bluetooth, etc.
  • Using sensor data for real-time route guidance and parking information
  • Development of innovative traffic signal control strategies based on sensor information (e.g., adaptive signal control,transit signal priority, perimeter gating control, connected vehicles, Automated Traffic Signal Performance Measures)
  • Incident detection from multi-sourced data
  • Sensors and highway operations (e.g., work zone operations, queue warning, distracted and fatigued drivers, occupancy detection for High-Occupancy Vehicle Lane operations)
  • Wireless sensor networks and Internet of Things (IoT) for ITS (e.g., traffic monitoring, smart parking, traffic controller status monitoring)
  • Real-time traveler information system such as roadway weather systems (e.g., black ice and flooding detection)
  • Structural and vehicle health monitoring (e.g., bridge, pavement, rail track, rolling stock)
  • Mobile sensor networks (e.g., data mining using smartphone data, connected vehicles, commercial fleets, buses, GPS)

You may choose our Joint Special Issue in Systems.

Prof. Dr. Nathan Gartner
Prof. Dr. Yuanchang Xie
Prof. Dr. Chen Wang
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. Sensors 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 2600 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.

Published Papers (1 paper)

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Research

21 pages, 2095 KiB  
Article
Drivers’ Subjective Assessment of the Ease of Finding a Vacant Parking Space in an Area Equipped with Vehicle Detection Devices
by Agata Kurek and Elżbieta Macioszek
Sensors 2022, 22(18), 6734; https://doi.org/10.3390/s22186734 - 6 Sep 2022
Cited by 2 | Viewed by 1256
Abstract
The growing traffic on city streets leads to traffic disruptions, lowering the level of road safety, as well as the problem of finding a vacant parking space. Drivers looking for a vacant parking space on the street generate so-called search traffic. Paid parking [...] Read more.
The growing traffic on city streets leads to traffic disruptions, lowering the level of road safety, as well as the problem of finding a vacant parking space. Drivers looking for a vacant parking space on the street generate so-called search traffic. Paid parking zones are introduced to increase the availability of parking spaces for more drivers in many cities around the world. The development in the technology and information sector has contributed to the development of systems guiding drivers to vacant parking spaces. This article aims to analyze drivers’ subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. Data from the Municipal Roads Authority in Gliwice (Poland) were obtained for the study, covering the use of parking spaces in the paid parking zone covered by dynamic parking information. Moreover, a survey was conducted among users of the paid parking zone in Gliwice. The answers of the respondents were used to build a logit model that allows determining the probability of a driver’s positive subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. The results from the model allow the characterization of drivers who positively assess the ease of finding a vacant parking space in the area equipped with vehicle detection devices. In addition, it is possible to reach a group of drivers who negatively assessed the ease of finding a vacant parking space to learn about the factors that may cause them to change their assessment to a positive one. The research results allow city authorities to better manage parking spaces equipped with vehicle detection devices in the paid parking zone. This may change the negative assessment of the ease of finding a vacant parking space into a positive one. Full article
(This article belongs to the Special Issue Sensors and Data-Driven Intelligent Transportation Systems)
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