Impact of COVID-19 on paratransit operators and riders: A case study of central Alabama

Nie, Qifan; Qian, Xinwu; Guo, Shuocheng; Jones, Steven; Doustmohammadi, Mehrnaz; Anderson, Michael

doi:10.1016/j.tra.2022.04.016

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…Although the outbreak related to the Omicron variant briefly stagnated the process, policymakers, public health professionals, and most of the general public all learned from the outbreak that a “New Normal” of living with COVID-19 is inches away ( [1] , Two Years Into the Pandemic, Americans Inch Closer to a New Normal | Pew Research Center. https://www.pewresearch.org/, 2022 , Emanuel et al, 2022 , Nie et al, 2022 ). As government policies, public perceptions, and even the virus changed dramatically during the later stage of the pandemic, factors contributing to the crash frequency and crash severity, such as traffic volume and drivers’ behavior, are likely to change as well.…”

Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 on traffic safety from the “Lockdown” to the “New Normal”: A case study of Utah

Gong

Yang

2023

Accident Analysis & Prevention

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Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 on traffic safety from the “Lockdown” to the “New Normal”: A case study of Utah

Gong

Yang

2023

Accident Analysis & Prevention

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“…Assessing the implications of the COVID-19 pandemic for different regions and identification of measures or actions that help policymakers and traffic planners to better develop sustainable strategies to improve transport system efficiency [31][32][33][34] Internet of Things and Big Data Evaluation of Internet of Things concepts and the 5v's of big data for leveraging the sustainability and resilience of urban mobility systems and providing directions to future research agendas [35][36][37] Given the above-mentioned challenges to traffic flow, city authorities during the COVID-19 pandemic shifted to measures that reduced the need for travel as a response to reduce transmission [38]. This had an impact on how people conduct their work, with more people working from home as compared to the office.…”

Section: Machine Learning and Deep Learningmentioning

confidence: 99%

Assessing Spatial Variations of Traffic Congestion Using Traffic Index Data in a Developing City: Lessons from Johannesburg, South Africa

et al. 2022

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The COVID-19 pandemic has created unforeseen effects in public transport and the mobility of people in cities globally. Johannesburg, being a developing city in one of the most affected countries in Africa during the pandemic, has experienced severe changes in traffic management and travel patterns as a result of the restrictions imposed on movement. Hence, this study examined the spatial variations in traffic during the pandemic. The study utilized data obtained from the TomTom Traffic Index for the city of Johannesburg from 2019 to 2021, with 2019 representing the period pre-COVID-19 with no lockdown restrictions, 2020 representing the period with restricted movement to limit spread of COVID-19, and 2021 representing a period of relaxed and minimized restrictions on movement. Our findings revealed that there was a variation in congestion levels between 2019–2021 with year 2020 having the least congestion from the beginning of the COVID-19 restrictions due to regulations enforced in movement and reduced travel. Our findings further revealed that traffic congestion was higher during weekdays than weekends during the three periods, with mini-bus taxis as the major contributors to congestion. Consequently, there is a need to discourage the use of single occupancy vehicles and invest in more sustainable means of transportation to ease the mobility of people and reduce traffic on major roads.

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“…The paratransit service is operated by Central Alabama's Specialized Transit (ClasTran), a non-profit corporation that provides specialized mobility services to people with disabilities and limited mobility, seniors, and people who reside in and travel to or from rural areas (Clastran 2021). We refer the readers to our previous study (Nie et al 2022) for more details on the data set. The trip records provided by ClasTran includes the exact information of the passengers (i.e., age, travel purpose) and trips (i.e., trip date, coordinates of the origin and destination, and the scheduled and reported pick-up and drop-off time).…”

Section: Real-world Paratransit Trip Datamentioning

confidence: 99%

A branch-cut-and-price algorithm for a dial-a-ride problem with minimum disease-transmission risk

Guo¹,

Dayarian²,

Qian³

et al. 2022

Preprint

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This paper investigates a variant of the dial-a-ride problem (DARP), namely Risk-aware DARP (RDARP). Our RDARP extends the DARP by (1) minimizing a weighted sum of travel cost and disease-transmission risk exposure for onboard passengers and (2) introducing a maximum cumulative exposure risk constraint for each vehicle to ensure a trip with lower external exposure. Both extensions require that the risk exposure of each onboard passenger is propagated in a minimized fashion while satisfying other existing constraints of the DARP. To fully describe the RDARP, we first provide a three-index arc-based formulation and reformulate the RDARP into an equivalent min-max trip-based formulation, which is solved by an exact Branch-Cut-and-Price (BCP) algorithm. For each node in the branching tree, we adopt the column generation method by decomposing the problem into a master problem and a subproblem. The latter takes the form of an elementary shortest path problem with resource constraints and minimized maximum risk (ESPPRCMMR). To solve the ESPPRCMMR efficiently, we develop a new labeling algorithm and establish families of resource extension functions in compliance with the risk-related resources. We adopt a real-world paratransit trip dataset to generate the RDARP instances ranging from 17 to 55 heterogeneous passengers with 3 to 13 vehicles during the morning and afternoon periods. Computational results show that our BCP algorithm can optimally solve all small-and medium-sized instances (32 or fewer passengers) within 5 minutes. For the large instances (39 to 55 passengers), our BCP algorithm can solve 23 of 30 instances optimally within a time limit of one hour.

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Impact of COVID-19 on paratransit operators and riders: A case study of central Alabama

Cited by 8 publications

References 22 publications

Impact of COVID-19 on traffic safety from the “Lockdown” to the “New Normal”: A case study of Utah

Impact of COVID-19 on traffic safety from the “Lockdown” to the “New Normal”: A case study of Utah

Assessing Spatial Variations of Traffic Congestion Using Traffic Index Data in a Developing City: Lessons from Johannesburg, South Africa

A branch-cut-and-price algorithm for a dial-a-ride problem with minimum disease-transmission risk

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