An Innovative Heuristic for Planning-based Urban Traffic Control

Santiago Franco Aixela; Alan Lindsay; Mauro Vallati; Thomas McCluskey

doi:10.1007/978-3-319-93698-7_14

An Innovative Heuristic for Planning-based Urban Traffic Control

Santiago Franco Aixela, Alan Lindsay, Mauro Vallati, Thomas McCluskey

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

5 Citations (Scopus)

Abstract

The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. In this scenario, optimising the exploitation of urban road network is a pivotal challenge, particularly in the case of unexpected situations. In order to tackle this challenge, approaches based on mixed discrete-continuous planning have been recently proposed and although their feasibility has been demonstrated, there is a lack of informative heuristics for this class of applications. Therefore, existing approaches tend to provide low-quality solutions, leading to a limited impact of generated plans on the actual urban infrastructure. In this work, we introduce the Time-Based heuristic: a highly informative heuristic for PDDL+ planning-based urban traffic control. The heuristic, which has an admissible and an inadmissible variant, has been evaluated considering scenarios that use real-world data.

Original language	English
Title of host publication	Computational Science – ICCS 2018
Subtitle of host publication	18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I
Editors	Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack Dongarra, Peter M. A. Sloot
Place of Publication	Cham
Publisher	Springer Verlag
Pages	181-193
Number of pages	13
ISBN (Electronic)	9783319936987
ISBN (Print)	9783319936970
DOIs	https://doi.org/10.1007/978-3-319-93698-7_14
Publication status	Published - 13 Jun 2018
Event	International Conference on Computational Science: Science at the Intersection of Data, Modelling and Computation - Wuxi, China Duration: 11 Jun 2018 → 13 Jun 2018 https://www.iccs-meeting.org/iccs2018/ (Link to Conference Website )

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10860 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Science
Abbreviated title	ICCS 2018
Country/Territory	China
City	Wuxi
Period	11/06/18 → 13/06/18
Internet address	https://www.iccs-meeting.org/iccs2018/ (Link to Conference Website )

UN SDGs

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

Access to Document

10.1007/978-3-319-93698-7_14Licence: Unspecified

time-h-iccsAccepted author manuscript, 362 KBLicence: Unspecified

Cite this

Franco Aixela, S., Lindsay, A., Vallati, M., & McCluskey, T. (2018). An Innovative Heuristic for Planning-based Urban Traffic Control. In Y. Shi, H. Fu, Y. Tian, V. V. Krzhizhanovskaya, M. H. Lees, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I (pp. 181-193). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10860 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-93698-7_14

Franco Aixela, Santiago ; Lindsay, Alan ; Vallati, Mauro et al. / An Innovative Heuristic for Planning-based Urban Traffic Control. Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I. editor / Yong Shi ; Haohuan Fu ; Yingjie Tian ; Valeria V. Krzhizhanovskaya ; Michael Harold Lees ; Jack Dongarra ; Peter M. A. Sloot. Cham : Springer Verlag, 2018. pp. 181-193 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An Innovative Heuristic for Planning-based Urban Traffic Control",

abstract = "The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. In this scenario, optimising the exploitation of urban road network is a pivotal challenge, particularly in the case of unexpected situations. In order to tackle this challenge, approaches based on mixed discrete-continuous planning have been recently proposed and although their feasibility has been demonstrated, there is a lack of informative heuristics for this class of applications. Therefore, existing approaches tend to provide low-quality solutions, leading to a limited impact of generated plans on the actual urban infrastructure. In this work, we introduce the Time-Based heuristic: a highly informative heuristic for PDDL+ planning-based urban traffic control. The heuristic, which has an admissible and an inadmissible variant, has been evaluated considering scenarios that use real-world data.",

keywords = "Automated planning, Heuristic for planning, Urban traffic control",

author = "{Franco Aixela}, Santiago and Alan Lindsay and Mauro Vallati and Thomas McCluskey",

note = "The final authenticated version is available online at https://doi.org/10.1007/978-3-319-93698-7_14.; International Conference on Computational Science : Science at the Intersection of Data, Modelling and Computation, ICCS 2018 ; Conference date: 11-06-2018 Through 13-06-2018",

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Franco Aixela, S, Lindsay, A, Vallati, M & McCluskey, T 2018, An Innovative Heuristic for Planning-based Urban Traffic Control. in Y Shi, H Fu, Y Tian, VV Krzhizhanovskaya, MH Lees, J Dongarra & PMA Sloot (eds), Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10860 LNCS, Springer Verlag, Cham, pp. 181-193, International Conference on Computational Science, Wuxi, China, 11/06/18. https://doi.org/10.1007/978-3-319-93698-7_14

An Innovative Heuristic for Planning-based Urban Traffic Control. / Franco Aixela, Santiago; Lindsay, Alan; Vallati, Mauro et al.

Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I. ed. / Yong Shi; Haohuan Fu; Yingjie Tian; Valeria V. Krzhizhanovskaya; Michael Harold Lees; Jack Dongarra; Peter M. A. Sloot. Cham : Springer Verlag, 2018. p. 181-193 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10860 LNCS).

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

TY - GEN

T1 - An Innovative Heuristic for Planning-based Urban Traffic Control

AU - Franco Aixela, Santiago

AU - Lindsay, Alan

AU - Vallati, Mauro

AU - McCluskey, Thomas

N1 - The final authenticated version is available online at https://doi.org/10.1007/978-3-319-93698-7_14.

PY - 2018/6/13

Y1 - 2018/6/13

N2 - The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. In this scenario, optimising the exploitation of urban road network is a pivotal challenge, particularly in the case of unexpected situations. In order to tackle this challenge, approaches based on mixed discrete-continuous planning have been recently proposed and although their feasibility has been demonstrated, there is a lack of informative heuristics for this class of applications. Therefore, existing approaches tend to provide low-quality solutions, leading to a limited impact of generated plans on the actual urban infrastructure. In this work, we introduce the Time-Based heuristic: a highly informative heuristic for PDDL+ planning-based urban traffic control. The heuristic, which has an admissible and an inadmissible variant, has been evaluated considering scenarios that use real-world data.

AB - The global growth in urbanisation increases the demand for services including road transport infrastructure, presenting challenges in terms of mobility. In this scenario, optimising the exploitation of urban road network is a pivotal challenge, particularly in the case of unexpected situations. In order to tackle this challenge, approaches based on mixed discrete-continuous planning have been recently proposed and although their feasibility has been demonstrated, there is a lack of informative heuristics for this class of applications. Therefore, existing approaches tend to provide low-quality solutions, leading to a limited impact of generated plans on the actual urban infrastructure. In this work, we introduce the Time-Based heuristic: a highly informative heuristic for PDDL+ planning-based urban traffic control. The heuristic, which has an admissible and an inadmissible variant, has been evaluated considering scenarios that use real-world data.

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KW - Heuristic for planning

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SN - 9783319936970

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

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BT - Computational Science – ICCS 2018

A2 - Shi, Yong

A2 - Fu, Haohuan

A2 - Tian, Yingjie

A2 - Krzhizhanovskaya, Valeria V.

A2 - Lees, Michael Harold

A2 - Dongarra, Jack

A2 - Sloot, Peter M. A.

PB - Springer Verlag

CY - Cham

T2 - International Conference on Computational Science

Y2 - 11 June 2018 through 13 June 2018

ER -

Franco Aixela S, Lindsay A, Vallati M , McCluskey T. An Innovative Heuristic for Planning-based Urban Traffic Control. In Shi Y, Fu H, Tian Y, Krzhizhanovskaya VV, Lees MH, Dongarra J, Sloot PMA, editors, Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018, Proceedings, Part I. Cham: Springer Verlag. 2018. p. 181-193. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2018 Jun 12. doi: 10.1007/978-3-319-93698-7_14

An Innovative Heuristic for Planning-based Urban Traffic Control

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