Agent Negotiation for Different Needs in Smart Parking Allocation

Napoli, Claudia Di; Nocera, Dario Di; Rossi, Silvia

doi:10.1007/978-3-319-07551-8_9

Cited by 15 publications

(8 citation statements)

References 7 publications

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“…The drivers' perceived parking cost is described by a fuzzy set in order to present their imperfect knowledge on both parking and system status. Di Napoli et al [180] adopted a software agent negotiation mechanism, which establishes an agreement between drivers and parking manager considering drivers' preferences, e.g., location and cost.…”

Section: B Parking Competitionmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

421

185

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Section: B Parking Competitionmentioning

confidence: 99%

A Survey of Smart Parking Solutions

Lin

Rivano

Mouël

2017

IEEE Trans. Intell. Transport. Syst.

421

185

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“…In this sense, dynamic pricing is the most common approach to manage parking occupancy [14]. Prices are usually decided based on parking availability and demand ( [18][19][20][21][22]) or after multiagent negotiation processes ( [23][24][25]). In our parking management use case, we approach the problem at a different level.…”

Section: Related Workmentioning

confidence: 99%

Towards the Prioritised Use of Transportation Infrastructures: The Case of Vehicle-Specific Dynamic Access Restrictions in City Centres

et al. 2022

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One of the main problems that local authorities of large cities have to face is the regulation of urban mobility. They need to provide the means to allow for the efficient movement of people and distribution of goods. However, the provisioning of transportation services needs to take into account general global objectives, like reducing emissions and having more healthy living environments, which may not always be aligned with individual interests. Urban mobility is usually provided through a transport infrastructure that includes all the elements that support mobility. On many occasions, the capacity of the elements of this infrastructure is lower than the actual demand and thus different transportation activities compete for their use. In this paper, we argue that scarce transport infrastructure elements should be assigned dynamically and in a prioritised manner to transport activities that have a higher utility from the point of view of society; for example, activities that produce less pollution and provide more value to society. In this paper, we define a general model for prioritizing the use of a particular type of transportation infrastructure element called time-unlimited elements, whose usage time is unknown a priori, and illustrate its dynamics through two use cases: vehicle-specific dynamic access restriction in city centres (i) based on the usage levels of available parking spaces and (ii) to assure sustained admissible air quality levels in the city centre. We carry out several experiments using the SUMO traffic simulation tool to evaluate our proposal.

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“…Nevertheless, up to now extremely few investigations have been carried out on routing consisting of vehicle parking [19]. Park guidance and information (PGI) remedies are developed to increase the likelihood of finding a parking area [20], however without thinking about the opportunity to find a better remedy for the vehicle driver (e.g., a remedy that is not near the destination but less costly) [21], [22].…”

Section: Graph Modelmentioning

confidence: 99%

Mobile recommender system based on smart city graph

Khoshnaw

Shwany

Mustafa

et al. 2022

IJEECS

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<span>Mobile recommender systems have changed the way people find items, purposes of intrigue, administrations, or even new companions. The innovation behind mobile recommender systems has developed to give client inclinations and social impacts. This paper introduces a first way to build a mobile recommendation system based on smart city graphs that appear topic features, user profiles, and impacts acquired from social connections. It exploits graph centrality measures to expand customized recommendations from the semantic information represented in the graph. The graph shows and chooses graph algorithms for computing chart centrality that is the center of the mobile recommender system are exhibited. Semantic ideas, for example, semantic transcendence and likeness measures, are adjusted to the graph model. Usage challenges confronted to settle execution issues are additionally examined.</span>

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Agent Negotiation for Different Needs in Smart Parking Allocation

Cited by 15 publications

References 7 publications

A Survey of Smart Parking Solutions

A Survey of Smart Parking Solutions

Towards the Prioritised Use of Transportation Infrastructures: The Case of Vehicle-Specific Dynamic Access Restrictions in City Centres

Mobile recommender system based on smart city graph

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