Article A COVID-19 Public Transport Frequency Setting Model That Includes Short-Turning Options Yoran de Weert † and Konstantinos Gkiotsalitis * ,†   Citation: de Weert, Y.; Gkiotsalitis, K. A COVID-19 Public Transport Frequency Setting Model That Includes Short-Turning Options. Future Transp. 2021, 1, 3–20. https://doi.org/10.3390/ futuretransp1010002 Academic Editor: Laura Eboli Received: 19 February 2021 Accepted: 16 March 2021 Published: 29 March 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Department of Civil Engineering, University of Twente, Enschede, 7500 AE Enschede, The Netherlands; y.r.deweert@student.utwente.nl * Correspondence: k.gkiotsalitis@utwente.nl; Tel.: +31-5348-91-870 † These authors contributed equally to this work. Abstract: The COVID-19 pandemic has had an enormous impact on the public transport sector. After the start of the pandemic, passenger demand dropped significantly for public transport services. In addition, social distancing measures have resulted in introducing pandemic-imposed capacity limitations to public transport vehicles. Consequently, public transport operators should adjust their planning to minimize the impact of the COVID-19 pandemic. This study introduces a mixed-integer quadratic program that sets the optimal frequencies of public transport lines and sublines in order to conform with the pandemic-imposed capacity. The focus is on cases where the public transport demand is high, but the crowding levels inside public transport vehicles should remain below the pandemic-imposed capacities. Of particular interest are public transport lines with skewed demand profiles that can benefit from the introduction of short-turning sublines that serve the high-demand line segments. The frequency setting model is tested on a network containing two high-demand bus lines in the Twente region in the Netherlands, and it demonstrates that the revenue losses due to social distancing can be reduced when implementing short-turning service patterns. Keywords: COVID-19; public transport; short-turning; frequency setting; revenue losses; pandemic- imposed capacity 1. Introduction During the year 2020, COVID-19 spread rapidly around the world and evolved into a worldwide pandemic. The impact of COVID-19 is nowadays visible in many business sectors. Governments implemented measures to reduce the risk of contamination by, for example, shutting down business sectors, implementing travel restrictions, or supporting home offices [1,2]. This change in the world heavily affects public transport services. Due to regulations and changes in travel habits, the number of weekly household trips was reduced by 50%, and the mode share of public transport was reduced from 15% to 7% during the lockdown period in Australia [3]. The demand reduction in Colombia was around 80% to 90%, with the highest demand loss of 96% observed in Cartagena during their mandatory quarantine period [4]. This demand reduction was also around 90% in the Netherlands [5], and the same trend has been observed in major cities in China, Iran, and the U.S. [6]. Some public transport operators in the United Kingdom also reported a decrease of as much as 70% [7]. Public transport operators are not only affected by the lower travel demand; their operations should also conform with the government regulations relating to COVID-19 [8]. These regulations consist mostly of wearing a face mask and physical distancing [9–11]. The latter regulation implies that in-vehicle capacities are reduced to pandemic-imposed capacities. In a post-lockdown period, some activities will resume and will result in an increase in passenger demand. This will force public transport operators to apply physical distancing measures to reduce the virus transmission risk. Tirachini and Cats [12] stated that there are some options to avoid exceeding the pandemic-imposed capacity of vehicles. These Future Transp. 2021, 1, 3–20. https://doi.org/10.3390/futuretransp1010002 https://www.mdpi.com/journal/futuretransp