A Survey of Parking Solutions for Smart Cities

Aljohani, Meshari; Olariu, Stephan; Alali, Abrar; Jain, Shubham

doi:10.1109/tits.2021.3112825

Cited by 21 publications

(18 citation statements)

References 106 publications

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“…As a matter of fact, a high percentage of the travel time spent by the travellers in metropolitan areas is due to cruising for finding an available parking spot, with relevant impacts on traffic congestion, emissions, and fuel consumption. The most recent parking solutions are market-oriented and include pricing to incentivise socially desirable driver behaviours, as deeply discussed in the survey paper (Aljohani, Olariu, Alali, & Jain, 2021).…”

Section: Parking Management Policiesmentioning

confidence: 99%

Control for smart systems: Challenges and trends in smart cities

Jia

Panetto

Macchi

et al. 2022

Annual Reviews in Control

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Section: Parking Management Policiesmentioning

confidence: 99%

Control for smart systems: Challenges and trends in smart cities

Jia

Panetto

Macchi

et al. 2022

Annual Reviews in Control

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Section: Smart Mobility-a Key Service In Smart Cities and Smart Communitiesmentioning

confidence: 99%

“…Smart Transportation has two key components, namely Smart Mobility [6] and Smart Parking [33,34]. In a very recent paper, Aljohani et al [33] devoted their attention to Smart Parking solutions in Smart Cities. Their goal was to identify, among the many published papers dealing with parking, innovative solutions for parking-related problems that can be employed in the Smart Cities of the near future.…”

Section: Smart Mobility-a Key Service In Smart Cities and Smart Communitiesmentioning

confidence: 99%

SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities

Olariu

Popescu

2021

Sensors

Self Cite

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It has been widely recognized that one of the critical services provided by Smart Cities and Smart Communities is Smart Mobility. This paper lays the theoretical foundations of SEE-TREND, a system for Secure Early Traffic-Related EveNt Detection in Smart Cities and Smart Communities. SEE-TREND promotes Smart Mobility by implementing an anonymous, probabilistic collection of traffic-related data from passing vehicles. The collected data are then aggregated and used by its inference engine to build beliefs about the state of the traffic, to detect traffic trends, and to disseminate relevant traffic-related information along the roadway to help the driving public make informed decisions about their travel plans, thereby preventing congestion altogether or mitigating its nefarious effects.

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“…Hence, reasonable parking space layout planning is of vital importance in the field of NDP. Up till now, various possible measures have been provided in an attempt to solve the parking issue for non‐AV scenarios (Aljohani et al., 2021; Ferguson et al., 2012; Ni et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

Zhang,

Waller,

Lin

2023

Computer aided Civil Eng

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This study is the first in the literature to examine the Braess paradox considering parking behavior in the autonomous vehicle (AV) environment, based on which the network design problem for the autonomous transportation system (NDP‐ATS) is modeled. First, we introduce the AV commuting pattern considering the self‐driving process for the parking purpose. We then illustrate the existence of two distinct Braess paradoxes that can occur in AV traffic networks with regards to parking space addition and network capacity expansion. They show that these two types of “improvement” measures might deteriorate the network system performance in an AV situation. Second, motivated to avoid the deterioration due to the introduced Braess paradoxes, we develop a bi‐level programming model for NDP‐ATS. The lower‐level program addresses the network‐equilibrium traffic assignment for AVs. The upper‐level program aims to minimize the network‐wide travel cost considering both occupied and empty AV trips by selecting the optimal design option accounting for road capacity enhancement and parking facility deployment simultaneously. To solve the developed bi‐level model, the simplicial homology global optimization algorithm is employed along with the Frank–Wolfe algorithm and the CPLEX. Finally, the efficacy of the modeling framework is validated through case studies on the Sioux Falls city network and the Anaheim network. The results show that the developed methodology is capable of producing high‐quality solutions with respect to savings in system‐level travel costs for AV traffic. The results also highlight the impacts of parking fees on the system performance for the optimized network. Additionally, it is found that the two objectives, which minimize the total system travel cost and minimize that for empty AV trips only, are conflicting for certain scenarios. The methodological approach introduced in this work serves as a critical modeling device for infrastructure development and policy assessment for AV traffic.

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A Survey of Parking Solutions for Smart Cities

Cited by 21 publications

References 106 publications

Control for smart systems: Challenges and trends in smart cities

Control for smart systems: Challenges and trends in smart cities

SEE-TREND: SEcurE Traffic-Related EveNt Detection in Smart Communities

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

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