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Effectiveness of automated connected shuttles (ACS) during COVID-19 pandemic

Authors:

Shanjeeda Akter,

H M Abdul AzizAuthors Info & Claims

IWCTS '21: Proceedings of the 14th ACM SIGSPATIAL International Workshop on Computational Transportation Science

Article No.: 6, Pages 1 - 9

https://doi.org/10.1145/3486629.3490694

Published: 18 November 2021 Publication History

Abstract

The COVID-19 pandemic had significantly impacted the public transit system in most cities across the world. Factors including physical distancing, remote working, distance education, and COVID-risk perception due to exposure have contributed to reducing public transport ridership. Automated Connected shuttles (ACS) services can be an effective alternative to regular buses with substantially reduced break-out risks and efficient operations. Our goal is to assess the mobility and energy impacts of ACS deployments when deployed as a replacement of standard (human-driven) buses within the context of the COVID-19 pandemic accounting for adjustment in passenger demand and capacity. To accomplish this purpose, we used a traffic microsimulation tool---PTV VISSIM---to simulate the behavior of buses and ACS units. We designed and simulated hypothetical scenarios in a New York City, NY, network. The scenarios are designed based on different COVID-19 restrictions, and the performances are compared to measure ACS effectiveness over regular buses. The results showed that ACS units are more effective than regular buses when they operate at business-as-usual capacity. Further, ACS services are more energy-efficient during physical distancing restrictions than bus services based on the emissions and energy estimates using the EPA-MOVES tool.

References

[1]

Hafiz Usman Ahmed, Ying Huang, and Pan Lu. 2021. A Review of Car-Following Models and Modeling Tools for Human and Autonomous-Ready Driving Behaviors in Micro-Simulation. Smart Cities 4, 1 (March 2021), 314--335.

[2]

Jaagup Ainsalu, Ville Arffman, Mauro Bellone, Maximilian Ellner, Taina Haapamäki, Noora Haavisto, Ebba Josefson, Azat Ismailogullari, Bob Lee, Olav Madland, Raitis Madžulis, Jaanus Müür, Sami Mäkinen, Ville Nousiainen, Eetu Pilli-Sihvola, Eetu Rutanen, Sami Sahala, Boris Schønfeldt, Piotr Marek Smolnicki, Ralf-Martin Soe, Juha Sääski, Magdalena Szymańska, Ingar Vaskinn, and Milla Åman. 2018. State of the Art of Automated Buses. Sustain. 2018, Vol. 10, Page 3118 10, 9 (August 2018), 3118.

[3]

American Public Transportation Association. 2021. Impact of COVID-19 Pandemic on Public Transit Funding Needs.

[4]

H. M. Abdul Aziz, Venu Garikapati, Tony K. Rodriguez, Lei Zhu, Bingrong Sun, Stanley E. Young, and Yuche Chen. 2020. An optimization-based planning tool for on-demand mobility service operations. Int. J. Sustain. Transp. 0, 0 (2020), 1--12.

[5]

H.M.A. Aziz. 2019. Energy and Mobility Impacts of System Optimal Dynamic Traffic Assignment for a Mixed Traffic of Legacy and Automated Vehicles.

[6]

Rounaq Basu, Andrea Araldo, Arun Prakash Akkinepally, Bat Hen Nahmias Biran, Kalaki Basak, Ravi Seshadri, Neeraj Deshmukh, Nishant Kumar, Carlos Lima Azevedo, and Moshe Ben-Akiva. 2018. Automated Mobility-on-Demand vs. Mass Transit: A Multi-Modal Activity-Driven Agent-Based Simulation Approach. Transp. Res. Rec. 2672, 8 (December 2018), 608--618.

[7]

Zhichao Cao and Avishai (Avi) Ceder. 2019. Autonomous shuttle bus service timetabling and vehicle scheduling using skip-stop tactic. Transp. Res. Part C Emerg. Technol. 102, (May 2019), 370--395.

[8]

Zhuang Dai, Xiaoyue Cathy Liu, Xi Chen, and Xiaolei Ma. 2020. Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: A dynamic programming approach. Transp. Res. Part C Emerg. Technol. 114, March (May 2020), 598--619.

[9]

Skip Descant. 2021. Self-Driving Shuttles Find New Uses During Pandemic.

[10]

Alastair Evanson. 2017. CONNECTED AUTONOMOUS VEHICLE (CAV) SIMULATION USING PTV VISSIM. In Proceedings of the 2017 Winter Simulation Conference.

[11]

Eva Fraedrich, Dirk Heinrichs, Francisco J. Bahamonde-Birke, and Rita Cyganski. 2019. Autonomous driving, the built environment and policy implications. Transp. Res. Part A Policy Pract. 122, (April 2019), 162--172.

[12]

Antora Mohsena Haque and Candace Brakewood. 2020. A synthesis and comparison of American automated shuttle pilot projects. Case Stud. Transp. Policy 8, 3 (September 2020), 928--937.

[13]

Saskia Hausler, Kersten Heineke, Russell Hensley, Timo Möller, Dennis Schwedhelm, and Pei Shen. 2020. The impact of COVID-19 on future mobility solutions.

[14]

Michael Hyland and Hani S. Mahmassani. 2018. Dynamic autonomous vehicle fleet operations: Optimization-based strategies to assign AVs to immediate traveler demand requests. Transp. Res. Part C Emerg. Technol. 92, April (2018), 278--297.

[15]

Alejandro De La Garza. 2021. COVID-19 Has Been "Apocalyptic" for Public Transit | Time.

[16]

Gregor Leich and Joschka Bischoff. 2019. Should autonomous shared taxis replace buses? A simulation study. Transp. Res. Procedia 41, (January 2019), 450--460.

[17]

Michael W. Levin, Kara M. Kockelman, Stephen D. Boyles, and Tianxin Li. 2017. A general framework for modeling shared autonomous vehicles with dynamic network-loading and dynamic ride-sharing application. Comput. Environ. Urban Syst. 64, (2017), 373--383.

[18]

Todd Litman. 2014. Autonomous Vehicle Implementation Predictions: Implications for Transport Planning. Transp. Res. Board Annu. Meet. 42, 2014 (2014), 36--42.

[19]

Mahmood Mahmoodi Nesheli, Lisa Li, Matthew Palm, and Amer Shalaby. 2021. Driverless shuttle pilots: Lessons for automated transit technology deployment. Case Stud. Transp. Policy 9, 2 (June 2021), 723--742.

[20]

Mark Mario Morando, Qingyun Tian, Long T. Truong, and Hai L. Vu. 2018. Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures. J. Adv. Transp. 2018, (April 2018).

[21]

Kostas Mouratidis and Victoria Cobeña Serrano. 2021. Autonomous buses: Intentions to use, passenger experiences, and suggestions for improvement. Transp. Res. Part F Traffic Psychol. Behav. 76, (January 2021), 321--335.

[22]

Tanveer Muhammad, Faizan Ahmad Kashmiri, Hassan Naeem, Xin Qi, Hsu Chia-Chun, and Huapu Lu. 2020. Simulation Study of Autonomous Vehicles' Effect on Traffic Flow Characteristics including Autonomous Buses. J. Adv. Transp. 2020, (2020).

[23]

Vibeke Nenseth, Alice Ciccone, and Niels Buus Kristensen. 2019. Societal consequences of automated vehicles - Norwegian scenarios.

[24]

NYC OpenData. 2020. Traffic Volume Counts (2014--2019). NYC Department of Transportation (DOT).

[25]

NYC OpenData. 2020. Vehicle Classification Counts (2014--2019). NYC Department of Transportation (DOT).

[26]

Sean O'Kane. Supervised self-driving shuttles are moving COVID-19 tests in Florida - The Verge. 2020.

[27]

Kelsey Oldbury and Karolina Isaksson. 2021. Governance arrangements shaping driverless shuttles in public transport: The case of Barkarbystaden, Stockholm. Cities 113, (June 2021), 103146.

[28]

PTV. 2021. PTV VISSIM 2021 User Manual. (2021).

[29]

Anna Schieben, Marc Wilbrink, Carmen Kettwich, Ruth Madigan, Tyron Louw, and Natasha Merat. 2018. Designing the interaction of automated vehicles with other traffic participants: design considerations based on human needs and expectations. Cogn. Technol. Work 21, 1 (September 2018), 69--85.

Digital Library

[30]

Yu Shen, Hongmou Zhang, and Jinhua Zhao. 2018. Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore. Transp. Res. Part A Policy Pract. 113, April (2018), 125--136.

[31]

Maryland DOT State Highway Administration. 2017. VISSIM Modeling Guidance.

[32]

Peter Sukennik. 18AD. Micro-simulation guide for automated vehicles.

[33]

Alejandro Tirachini and Oded Cats. 2020. COVID-19 and public transportation: Current assessment, prospects, and research needs. J. Public Transp. 22, 1 (2020), 1--34.

[34]

Alejandro Tirachini and Oded Cats. 2020. COVID-19 and Public Transportation: Current Assessment, Prospects, and Research Needs. J. Public Transp. 22, 1 (January 2020), 1--34.

[35]

S. Tsigdinos, C. Karolemeas, E. Bakogiannis, and A. Nikitas. 2021. Introducing autonomous buses into street functional classification systems: An exploratory spatial approach. Case Stud. Transp. Policy 9, 2 (June 2021), 813--822.

[36]

Desmond Yuen. 2021. Making Roads Safer with Self-Driving Cars and 5G.

[37]

Lei Zhu, Venu Garikapati, Yuche Chen, Yi Hou, H. M. Abdul Aziz, and Stanley Young. 2018. Quantifying the mobility and energy benefits of automated mobility districts using microscopic traffic simulation. Int. Conf. Transp. Dev. 2018 Connect. Auton. Veh. Transp. Saf. - Sel. Pap. from Int. Conf. Transp. Dev. 2018 (2018), 98--108.

[38]

Impact of COVID-19 on Adoption of Autonomous Vehicle Technology.

[39]

Self-Driving Shuttle for Passenger Transportation - NAVYA.

Cited By

Sobczuk SBorucka A(2024)Recent Advances for the Development of Sustainable Transport and Their Importance in Case of Global Crises: A Literature ReviewApplied Sciences10.3390/app14221065314:22(10653)Online publication date: 18-Nov-2024
https://doi.org/10.3390/app142210653
Berres AKurte KPaleti R(2022)The 14th ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS 2021), Beijing, ChinaSIGSPATIAL Special10.1145/3578484.357849013:3(15-20)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3578484.3578490

Index Terms

Effectiveness of automated connected shuttles (ACS) during COVID-19 pandemic
1. Applied computing
2. Computing methodologies

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Published In

cover image ACM Conferences

IWCTS '21: Proceedings of the 14th ACM SIGSPATIAL International Workshop on Computational Transportation Science

November 2021

75 pages

ISBN:9781450391177

DOI:10.1145/3486629

Editors:
Kuldeep Kurte
Oak Ridge National Laboratory, Oak Ridge, TN
,
Andy Berres
Oak Ridge National Laboratory, Oak Ridge, TN
,
Rajesh Paleti
Oak Ridge National Laboratory, Oak Ridge, TN

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 November 2021

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SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems

November 2, 2021

Beijing, China

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Cited By

Sobczuk SBorucka A(2024)Recent Advances for the Development of Sustainable Transport and Their Importance in Case of Global Crises: A Literature ReviewApplied Sciences10.3390/app14221065314:22(10653)Online publication date: 18-Nov-2024
https://doi.org/10.3390/app142210653
Berres AKurte KPaleti R(2022)The 14th ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS 2021), Beijing, ChinaSIGSPATIAL Special10.1145/3578484.357849013:3(15-20)Online publication date: 23-Dec-2022
https://dl.acm.org/doi/10.1145/3578484.3578490

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