Replication code for: Performance evaluation of stochastic systems with dedicated delivery bays and general on-street parking

DOI

Matlab code to replicate the study.

Study abstract: As freight deliveries in cities increase due to retail fragmentation and e-commerce, parking is becoming a more and more relevant part of transportation. In fact, many freight vehicles in cities spend more time parked than they are moving. Moreover, part of the public parking space is shared with passenger vehicles, especially cars. Both arrival processes and parking and delivery processes are stochastic in nature. In order to develop a framework for analysis, we propose a queueing model for an urban parking system consisting of delivery bays and general on-street parking spaces. Freight vehicles may park both in the dedicated bays and in general on-street parking, while passenger vehicles only make use of general on-street parking. Our model allows us to create parsimonious insights into the behavior of a delivery bay parking stretch as part of a limited length of curbside. We are able to find explicit expressions for the relevant performance measures, and formally prove a number of monotonicity results. We further conduct a series of numerical experiments to show more intricate properties that cannot be shown analytically. The model helps us shed light onto the effects of allocating scarce urban curb space to dedicated unloading bays at the expense of general on-street parking. In particular, we show that allocating more space to dedicated delivery bays can also make passenger cars better off.

This dataset contains code and no data. The authors make use of a publicly accessible database. The description of the database is included in the attached files.

Identifier
DOI https://doi.org/10.34894/W3E0SF
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/W3E0SF
Provenance
Creator Abhishek; Legros, Benjamin; Fransoo, Jan C. ORCID logo
Publisher DataverseNL
Contributor Fransoo, Jan; DataverseNL
Publication Year 2021
Rights This work is licensed under a CC BY-NC license. For more information see https://creativecommons.org/licenses/by-nc/4.0/; info:eu-repo/semantics/openAccess
OpenAccess true
Contact Fransoo, Jan (Tilburg University, Tilburg School of Economics and Management)
Representation
Resource Type Matlab code; Dataset
Format text/x-matlab; application/pdf
Size 14479; 17062; 14723; 300254; 9043
Version 1.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Economics; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences