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Social cost guarantees in smart route guidance

Social cost guarantees in smart route guidance
Social cost guarantees in smart route guidance
We model and study the problem of assigning traffic in an urban road network infrastructure. In our model, each driver submits their intended destination and is assigned a route to follow that minimizes the social cost (i.e., travel distance of all the drivers). We assume drivers are strategic and try to manipulate the system (i.e., misreport their intended destination and/or deviate from the assigned route) if they can reduce their travel distance by doing so. Such strategic behavior is highly undesirable as it can lead to an overall suboptimal traffic assignment and cause congestion. To alleviate this problem, we develop moneyless mechanisms that are resilient to manipulation by the agents and offer provable approximation guarantees on the social cost obtained by the solution. We then empirically test the mechanisms studied in the paper, showing that they can be effectively used in practice in order to compute manipulation resistant traffic allocations.
482-495
Springer, Cham
Serafino, Paolo
e0138324-dca1-4577-9af2-80583b80e1f4
Ventre, Carmine
9abfa84f-266a-4296-82f1-ae3bdecaea38
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
An, Bo
4b0743f9-91c9-4452-868c-1d12b4e9f456
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Nayak, A.
Sharma, A.
Serafino, Paolo
e0138324-dca1-4577-9af2-80583b80e1f4
Ventre, Carmine
9abfa84f-266a-4296-82f1-ae3bdecaea38
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Zhang, Jie
6bad4e75-40e0-4ea3-866d-58c8018b225a
An, Bo
4b0743f9-91c9-4452-868c-1d12b4e9f456
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Nayak, A.
Sharma, A.

Serafino, Paolo, Ventre, Carmine, Tran-Thanh, Long, Zhang, Jie, An, Bo and Jennings, Nick (2019) Social cost guarantees in smart route guidance. Nayak, A. and Sharma, A. (eds.) In PRICAI 2019: Trends in Artificial Intelligence. PRICAI 2019. vol. 11671, Springer, Cham. pp. 482-495 . (doi:10.1007/978-3-030-29911-8_37).

Record type: Conference or Workshop Item (Paper)

Abstract

We model and study the problem of assigning traffic in an urban road network infrastructure. In our model, each driver submits their intended destination and is assigned a route to follow that minimizes the social cost (i.e., travel distance of all the drivers). We assume drivers are strategic and try to manipulate the system (i.e., misreport their intended destination and/or deviate from the assigned route) if they can reduce their travel distance by doing so. Such strategic behavior is highly undesirable as it can lead to an overall suboptimal traffic assignment and cause congestion. To alleviate this problem, we develop moneyless mechanisms that are resilient to manipulation by the agents and offer provable approximation guarantees on the social cost obtained by the solution. We then empirically test the mechanisms studied in the paper, showing that they can be effectively used in practice in order to compute manipulation resistant traffic allocations.

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Social Cost Guarantees in Smart Route Guidance - Accepted Manuscript
Restricted to Repository staff only until 23 August 2020.
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Accepted/In Press date: 3 June 2019
e-pub ahead of print date: 23 August 2019
Venue - Dates: The 16th Pacific Rim International Conference on Artificial Intelligence, Yanuca Island, Fiji, 2019-08-26 - 2019-08-30

Identifiers

Local EPrints ID: 435348
URI: https://eprints.soton.ac.uk/id/eprint/435348
PURE UUID: 2b7e637b-d62c-41ab-965e-dba490e0fcdb
ORCID for Paolo Serafino: ORCID iD orcid.org/0000-0002-5366-3153
ORCID for Long Tran-Thanh: ORCID iD orcid.org/0000-0003-1617-8316
ORCID for Jie Zhang: ORCID iD orcid.org/0000-0003-1380-9952

Catalogue record

Date deposited: 31 Oct 2019 17:30
Last modified: 30 Nov 2019 01:34

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Contributors

Author: Paolo Serafino ORCID iD
Author: Carmine Ventre
Author: Long Tran-Thanh ORCID iD
Author: Jie Zhang ORCID iD
Author: Bo An
Author: Nick Jennings
Editor: A. Nayak
Editor: A. Sharma

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