Special Issue "Smart Mobility"

A special issue of Infrastructures (ISSN 2412-3811). This special issue belongs to the section "Smart Infrastructures".

Deadline for manuscript submissions: 31 January 2022.

Special Issue Editors

Dr. Said M. Easa
E-Mail Website
Guest Editor
Department of Civil Engineering, Ryerson University, 350 Victoria St., Toronto, ON M5B 2K3, Canada
Interests: intelligent transportation systems; highway geometric design and safety; human factors in transportation; traffic operations and management; engineering education
Special Issues, Collections and Topics in MDPI journals
Dr. Jianchuan Cheng
E-Mail Website
Guest Editor
School of Transportation, Southeast University, 2 Southeast University Rd., Nanjing 211189, Jiangsu, China
Interests: road safety and geometric design; integrated roadway surveying and design; intelligent transportation systems
Dr. Yunlong Zhang
E-Mail Website
Guest Editor
Zachry Deprtment of Civil & Environmental Engineering, Texas A&M University, 3136 TAMU, College Station, TX 77843, USA
Interests: intelligent transportation systems; connected and autonomous vehicle applications; AI applications; traffic signal and control; transportation data and modeling; traffic safety
Dr. Xiaobo Qu
E-Mail Website
Guest Editor
Department of Architecture and Civil Engineering, Chalmers University of Technology, Gothenburg, Sweden
Interests: traffic operations; connected and automated vehicles; electric transportation

Special Issue Information

Dear Colleagues,

This Special Issue focuses on “Smart Mobility”, which represents the world of tomorrow. The concept has received increasing attention as an ideal tool for addressing issues in current transportation systems, such as congestion, traffic collisions, and pollution. Smart mobility aims at reducing congestion and fostering greener, faster, and cheaper transportation options. Transportation systems will become more intelligent and more flexible using Information and Communication Technologies (ICT) that are carried out with fully integrated and intelligent infrastructures. Specifically, the goals of smart mobility are to improve the quality of life of citizens, to reduce the environmental impacts, and to increase the connectivity and operational efficiency of multimodal transportation. By 2025, the annual addressable market of smart mobility themes is estimated to be around US$400 billion, or about eight times the size of today.

Among the components that can substantially help to achieve smart mobility, the infrastructure plays a fundamental role. Integrated and intelligent infrastructures can perform numerous functions, including data collection, data transmission and communication, and data interactions and exchanges with other intelligent components of the transportation systems (e.g., autonomous vehicles). To realize these functions, a variety of digital devices (e.g., sensors) are supposed to be installed in different parts of the existing infrastructure and integrated with advanced ICT. Only when all sensors are interconnected and work properly can intelligent recognition, location, tracking, monitoring, and management, which are all crucial to smart mobility, be achieved.

However, with the explosive growth of smart mobility service and applications, many scientific and engineering challenges to intelligent infrastructures are inevitably emerging and need ingenious research efforts from both academia and industry. For instance, many questions remain, such as: How can we optimize the deployment of smart sensors for better mobility? Is it possible for the infrastructures to provide more functions in the coming transportation resolution? How can we estimate and tackle the issues of cybersecurity, privacy, and social trust? How do we prepare the infrastructures for gradual change in the emerging and future modes of urban mobility? These challenges represent great opportunities to shape the intelligent transportation system of the future.

Researchers from academia and industry are invited to submit papers in the following areas:

  • Big data in smart mobility
  • Artificial Intelligence and machine learning applications
  • Intelligent infrastructure (e.g., traffic signals, parking, camera systems)
  • Infrastructure-related data processing and management
  • Infrastructure-cooperative algorithms
  • Innovative safety solutions (e.g., in-vehicle systems, LiDAR implementation)
  • Facilities for alternative travel modes
  • Smart vehicles (e.g., connected, autonomous, and disruptive)
  • Transportation electrification (e.g., electric vehicles, charging infrastructure, modeling)
  • Infrastructure adaptation to emergency vehicles
  • Smart use (e.g., ride-sharing and flexible mobility)
  • Mobility as a service (e.g., payment, online journey planning)
  • Smart infrastructure maintenance scheduling
  • Sustainable mobility
  • Public transportation
  • Smart powertrains
  • Eco-driving methods
  • Cyber security, privacy, and social issues
  • Other relevant areas to smart mobility

The Special Issue aims at publishing high-quality papers, particularly those that address engineering and scientific aspects related to the above topics.

Dr. Said M. Easa
Dr. Jianchuan Cheng
Dr. Yunlong Zhang
Dr. Xiaobo Qu
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 papers will be 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. Infrastructures is an international peer-reviewed open access monthly 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 1400 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 (4 papers)

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Research

Article
Optimal Speed Plan for the Overtaking of Autonomous Vehicles on Two-Lane Highways
Infrastructures 2020, 5(5), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5050044 - 18 May 2020
Cited by 2 | Viewed by 1853
Abstract
In passing maneuvers on two-lane highways, assessing the needed distance and the potential power reserve to ensure the required speed mode of the passing vehicle is a critical task of speed planning. This task must meet several mutually exclusive conditions that lead to [...] Read more.
In passing maneuvers on two-lane highways, assessing the needed distance and the potential power reserve to ensure the required speed mode of the passing vehicle is a critical task of speed planning. This task must meet several mutually exclusive conditions that lead to successful maneuvers. This paper addresses three main aspects. First, the issues associated with a rational distribution of the speed of the passing vehicle for overtaking a long commercial vehicle on two-lane highways are discussed. The factors that affect the maneuver effectiveness are analyzed, considering the safety and cost. Second, a heuristic algorithm is proposed based on the rationale for choosing the necessary space and time for overtaking. The initial prediction’s sensitivity to fluctuations of the current measurements of the position and speed of the overtaking participants is examined. Third, an optimization technique for the passing vehicle speed distribution during the overtaking time using the finite element method is presented. Adaptive model predictive control is applied for tracking the references being generated. The presented model is illustrated using a simulation. Full article
(This article belongs to the Special Issue Smart Mobility)
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Article
Path and Control Planning for Autonomous Vehicles in Restricted Space and Low Speed
Infrastructures 2020, 5(5), 42; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5050042 - 12 May 2020
Cited by 2 | Viewed by 2274
Abstract
This paper presents models of path and control planning for the parking, docking, and movement of autonomous vehicles at low speeds, considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models [...] Read more.
This paper presents models of path and control planning for the parking, docking, and movement of autonomous vehicles at low speeds, considering space constraints. Given the low speed of motion, and in order to test and approve the proposed algorithms, vehicle kinematic models are used. Recent works on the development of parking algorithms for autonomous vehicles are reviewed. Bicycle kinematic models for vehicle motion are considered for three basic types of vehicles: passenger car, long wheelbase truck, and articulated vehicles with and without steered semitrailer axes. Mathematical descriptions of systems of differential equations in matrix form and expressions for determining the linearization elements of nonlinear motion equations that increase the speed of finding the optimal solution are presented. Options are proposed for describing the interaction of vehicle overall dimensions with the space boundaries, within which a maneuver should be performed. An original algorithm that considers numerous constraints is developed for determining vehicle permissible positions within the closed boundaries of the parking area, which are directly used in the iterative process of searching for the optimal plan solution using nonlinear model predictive control (NMPC). The process of using NMPC to find the best trajectories and control laws while moving in a semi-limited space of constant curvature (turnabouts, roundabouts) are described. Simulation tests were used to validate the proposed models for both constrained and unconstrained conditions and the output (state-space) and control parameters’ dependencies are shown. The proposed models represent an initial effort to model the movement of autonomous vehicles for parking and have the potential for other highway applications. Full article
(This article belongs to the Special Issue Smart Mobility)
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Article
Competing Risks Models for the Assessment of Intelligent Transportation Systems Devices: A Case Study for Connected and Autonomous Vehicle Applications
Infrastructures 2020, 5(3), 30; https://0-doi-org.brum.beds.ac.uk/10.3390/infrastructures5030030 - 15 Mar 2020
Cited by 3 | Viewed by 2289
Abstract
Intelligent transportation system (ITS) has become a crucial section of transportation and traffic management systems in the past decades. As a result, transportation agencies keep improving the quality of transportation infrastructure management information for accessibility and security of transportation networks. The goal of [...] Read more.
Intelligent transportation system (ITS) has become a crucial section of transportation and traffic management systems in the past decades. As a result, transportation agencies keep improving the quality of transportation infrastructure management information for accessibility and security of transportation networks. The goal of this paper is to evaluate the impact of two competing risks: “natural deterioration” of ITS devices and hurricane-induced failure of the same components. The major devices employed in the architecture of this paper include closed circuit television (CCTV) cameras, automatic vehicle identification (AVI) systems, dynamic message signals (DMS), wireless communication systems and DMS towers. From the findings, it was evident that as ITS infrastructure devices age, the contribution of Hurricane Category 3 as a competing failure risk is higher and significant compared to the natural deterioration of devices. Hurricane Category 3 failure vs. natural deterioration indicated an average hazard ratio of 1.5 for CCTV, AVI and wireless communications systems and an average hazard ratio of 2.3 for DMS, DMS towers and portable DMS. The proportional hazard ratios of the Hurricane Category 1 compared to the devices was estimated as <0.001 and that of Hurricane Category 2 < 0.5, demonstrating the lesser impact of the Hurricane Categories 1 and 2. It is expedient to envisage and forecast the impact of hurricanes on the failure of wireless communication networks, vehicle detection systems and other message signals, in order to prevent vehicle to infrastructure connection disruption, especially for autonomous and connected vehicle systems. Full article
(This article belongs to the Special Issue Smart Mobility)
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Article
Roadworks Warning—Closure of a Lane, the Impact of C-ITS Messages
Infrastructures 2020, 5(3), 27; https://doi.org/10.3390/infrastructures5030027 - 06 Mar 2020
Cited by 3 | Viewed by 2283
Abstract
By now, it is widely acknowledged among stakeholders and academia that infrastructures will have to be composed both by a physical component and a digital one. The deployment of technologies exploiting dedicated short-range communications is viewed as the most cost-effective solution to face [...] Read more.
By now, it is widely acknowledged among stakeholders and academia that infrastructures will have to be composed both by a physical component and a digital one. The deployment of technologies exploiting dedicated short-range communications is viewed as the most cost-effective solution to face the foreseen growth of mobility. Still, little has been done to define the best implementation logic of DSRC. Aim of this paper is to frame the possible impacts arising by the implementation of a cooperative intelligent transport system (C-ITS)-use case: roadworks warning—closure of a lane, and, in order to achieve this result, microsimulations are exploited. The results are intended to support both road operators and car-makers in defining the best operational logics and the possible benefits achievable by presenting the cooperative message at a certain distance for certain market penetrations. Moreover, if the C-ITS message actually entails benefits or simply disrupts the upstream traffic should be assessed in advance, before implementing the system. The obtained results show that the risk of disruption and of reduction in traffic efficiency arises at lower market penetration levels. Nevertheless, a consistent trend in delay reduction is recorded upstream the roadworks, the highest reduction being equal to 8.66%. Moreover, the average speed at the roadworks entrance on the closing lane increases by a difference equal to around 10 km/h, while the average time in the queue at the highest market penetration reduces by 60 s on the open lane and 25 s on the closing one. These presented results reflect the way the traffic shifts from the slow to the fast lane thanks to the C-ITS system and effectively frames both the potentialities and the risks of the system. Full article
(This article belongs to the Special Issue Smart Mobility)
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