The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles

Max van der Tholen; Breno A. Beirigo; Jovana Jovanova; Frederik Schulte

doi:10.1007/978-3-030-87672-2_23

The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles

Max van der Tholen
, Breno A. Beirigo
, Jovana Jovanova
, Frederik Schulte^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

12 Citations (Scopus)

Abstract

The shared autonomous vehicle (SAV) is a new concept that meets the upcoming trends of autonomous driving and changing demands in urban transportation. SAVs can carry passengers and parcels simultaneously, making use of dedicated passenger and parcel modules on board. A fleet of SAVs could partly take over private transport, taxi, and last-mile delivery services. A reduced fleet size compared to conventional transportation modes would lead to less traffic congestion in urban centres. This paper presents a method to estimate the optimal capacity for the passenger and parcel compartments of SAVs. The problem is presented as a vehicle routing problem and is named variable capacity share-a-ride-problem (VCSARP). The model has a MILP formulation and is solved using a commercial solver. It seeks to create the optimal routing schedule between a randomly generated set of pick-up and drop-off requests of passengers and parcels. The objective function aims to minimize the total energy costs of each schedule, which is a trade-off between travelled distance and vehicle capacity. Different scenarios are composed by altering parameters, representing travel demand at different times of the day. The model results show the optimized cost of each simulation along with associated routes and vehicle capacities.

Original language	English
Title of host publication	Computational Logistics
Subtitle of host publication	12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings
Editors	Martijn Mes, Eduardo Lalla-Ruiz, Stefan Voß
Place of Publication	Cham
Publisher	Springer
Pages	347-361
Number of pages	15
ISBN (Electronic)	978-3-030-87672-2
ISBN (Print)	978-3-030-87671-5
DOIs	https://doi.org/10.1007/978-3-030-87672-2_23
Publication status	Published - 2021
Externally published	Yes
Event	12th International Conference on Computational Logistics, ICCL 2021 - University of Twente (online), Enschede, Netherlands Duration: 27 Sept 2021 → 29 Sept 2021 Conference number: 12 https://iccl2021.nl/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI))
Volume	13004
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Computational Logistics, ICCL 2021
Abbreviated title	ICCL 2021
Country/Territory	Netherlands
City	Enschede
Period	27/09/21 → 29/09/21
Internet address	https://iccl2021.nl/

Keywords

n/a OA procedure
Shared autonomous vehicles
Vehicle routing problem
Capacity optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-87672-2_23

Cite this

van der Tholen, M., Beirigo, B. A., Jovanova, J., & Schulte, F. (2021). The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles. In M. Mes, E. Lalla-Ruiz, & S. Voß (Eds.), Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings (pp. 347-361). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI)); Vol. 13004). Springer. https://doi.org/10.1007/978-3-030-87672-2_23

van der Tholen, Max ; Beirigo, Breno A. ; Jovanova, Jovana et al. / The Share-A-Ride Problem with Integrated Routing and Design Decisions : The Case of Mixed-Purpose Shared Autonomous Vehicles. Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings. editor / Martijn Mes ; Eduardo Lalla-Ruiz ; Stefan Voß. Cham : Springer, 2021. pp. 347-361 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI))).

@inproceedings{5503389cff01436dae4718ea22f020ad,

title = "The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles",

abstract = "The shared autonomous vehicle (SAV) is a new concept that meets the upcoming trends of autonomous driving and changing demands in urban transportation. SAVs can carry passengers and parcels simultaneously, making use of dedicated passenger and parcel modules on board. A fleet of SAVs could partly take over private transport, taxi, and last-mile delivery services. A reduced fleet size compared to conventional transportation modes would lead to less traffic congestion in urban centres. This paper presents a method to estimate the optimal capacity for the passenger and parcel compartments of SAVs. The problem is presented as a vehicle routing problem and is named variable capacity share-a-ride-problem (VCSARP). The model has a MILP formulation and is solved using a commercial solver. It seeks to create the optimal routing schedule between a randomly generated set of pick-up and drop-off requests of passengers and parcels. The objective function aims to minimize the total energy costs of each schedule, which is a trade-off between travelled distance and vehicle capacity. Different scenarios are composed by altering parameters, representing travel demand at different times of the day. The model results show the optimized cost of each simulation along with associated routes and vehicle capacities.",

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author = "\{van der Tholen\}, Max and Beirigo, \{Breno A.\} and Jovana Jovanova and Frederik Schulte",

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van der Tholen, M, Beirigo, BA, Jovanova, J & Schulte, F 2021, The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles. in M Mes, E Lalla-Ruiz & S Voß (eds), Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI)), vol. 13004, Springer, Cham, pp. 347-361, 12th International Conference on Computational Logistics, ICCL 2021, Enschede, Netherlands, 27/09/21. https://doi.org/10.1007/978-3-030-87672-2_23

The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles. / van der Tholen, Max; Beirigo, Breno A.; Jovanova, Jovana et al.
Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings. ed. / Martijn Mes; Eduardo Lalla-Ruiz; Stefan Voß. Cham: Springer, 2021. p. 347-361 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI)); Vol. 13004).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - The Share-A-Ride Problem with Integrated Routing and Design Decisions

T2 - 12th International Conference on Computational Logistics, ICCL 2021

AU - van der Tholen, Max

AU - Beirigo, Breno A.

AU - Jovanova, Jovana

AU - Schulte, Frederik

N1 - Conference code: 12

PY - 2021

Y1 - 2021

N2 - The shared autonomous vehicle (SAV) is a new concept that meets the upcoming trends of autonomous driving and changing demands in urban transportation. SAVs can carry passengers and parcels simultaneously, making use of dedicated passenger and parcel modules on board. A fleet of SAVs could partly take over private transport, taxi, and last-mile delivery services. A reduced fleet size compared to conventional transportation modes would lead to less traffic congestion in urban centres. This paper presents a method to estimate the optimal capacity for the passenger and parcel compartments of SAVs. The problem is presented as a vehicle routing problem and is named variable capacity share-a-ride-problem (VCSARP). The model has a MILP formulation and is solved using a commercial solver. It seeks to create the optimal routing schedule between a randomly generated set of pick-up and drop-off requests of passengers and parcels. The objective function aims to minimize the total energy costs of each schedule, which is a trade-off between travelled distance and vehicle capacity. Different scenarios are composed by altering parameters, representing travel demand at different times of the day. The model results show the optimized cost of each simulation along with associated routes and vehicle capacities.

AB - The shared autonomous vehicle (SAV) is a new concept that meets the upcoming trends of autonomous driving and changing demands in urban transportation. SAVs can carry passengers and parcels simultaneously, making use of dedicated passenger and parcel modules on board. A fleet of SAVs could partly take over private transport, taxi, and last-mile delivery services. A reduced fleet size compared to conventional transportation modes would lead to less traffic congestion in urban centres. This paper presents a method to estimate the optimal capacity for the passenger and parcel compartments of SAVs. The problem is presented as a vehicle routing problem and is named variable capacity share-a-ride-problem (VCSARP). The model has a MILP formulation and is solved using a commercial solver. It seeks to create the optimal routing schedule between a randomly generated set of pick-up and drop-off requests of passengers and parcels. The objective function aims to minimize the total energy costs of each schedule, which is a trade-off between travelled distance and vehicle capacity. Different scenarios are composed by altering parameters, representing travel demand at different times of the day. The model results show the optimized cost of each simulation along with associated routes and vehicle capacities.

KW - n/a OA procedure

KW - Shared autonomous vehicles

KW - Vehicle routing problem

KW - Capacity optimization

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DO - 10.1007/978-3-030-87672-2_23

M3 - Conference contribution

AN - SCOPUS:85116351263

SN - 978-3-030-87671-5

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI))

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PB - Springer

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ER -

van der Tholen M, Beirigo BA, Jovanova J, Schulte F. The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles. In Mes M, Lalla-Ruiz E, Voß S, editors, Computational Logistics: 12th International Conference, ICCL 2021, Enschede, The Netherlands, September 27–29, 2021, Proceedings. Cham: Springer. 2021. p. 347-361. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI))). Epub 2021 Sept 22. doi: 10.1007/978-3-030-87672-2_23

The Share-A-Ride Problem with Integrated Routing and Design Decisions: The Case of Mixed-Purpose Shared Autonomous Vehicles

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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