Non-Stationary Time Series Model for Station-Based Subway Ridership During COVID-19 Pandemic: Case Study of New York City.

The COVID-19 pandemic in 2020 has caused sudden shocks in transportation systems, specifically the subway ridership patterns in New York City (NYC), U.S. Understanding the temporal pattern of subway ridership through statistical models is crucial during such shocks. However, many existing statistical frameworks may not be a good fit to analyze the ridership data sets during the pandemic, since some of the modeling assumptions might be violated during this time. In this paper, utilizing change point detection procedures, a piecewise stationary time series model is proposed to capture the nonstationary structure of subway ridership. Specifically, the model consists of several independent station based autoregressive integrated moving average (ARIMA) models concatenated together at certain time points. Further, data-driven algorithms are utilized to detect the changes of ridership patterns as well as to estimate the model parameters before and during the COVID-19 pandemic. The data sets of focus are daily ridership of subway stations in NYC for randomly selected stations. Fitting the proposed model to these data sets enhances understanding of ridership changes during external shocks, both in relation to mean (average) changes and the temporal correlations.

An estimation of the effects of social distancing measures on transit vehicle capacity and operations.

The COVID-19 pandemic has a direct impact on public transport operations. In this paper, impacts on transit operations of the physical distancing measures deployed to slow the spread of the virus are analyzed and recommendations are provided. At first, two social distancing optimization solutions are provided in order to keep riders at a safe distance. The first is a discrete optimization that can be used in buses with fixed seats, while the second is a continuous optimization that can be used to distribute riders on a grid and be applied on a bus or subway platform. Assuming that the ridership will eventually go back to its level before the pandemic, the second objective of this research is to address the transit operation parameters that need to be changed in order to serve the pre-COVID ridership level, while respecting the social distancing measures. An O-D distribution has been developed in this paper for New York City (NYC) subway line 1, based on the 2018 NYC Travel Survey conducted by the Metropolitan Transportation Authority. Five scenarios of physical distancing are simulated and analyzed in this paper: 3ft, 4ft, 5ft, 5.4ft, and 6ft of separation between passengers. The results show the number of additional trains required to accommodate the hypothetical pre-COVID ridership demand while maintaining social distancing. An interesting key finding is that, by decreasing the minimum distance from 6ft to 5.4ft, the number of additional trains required to serve the transit demand drastically decreases and hence more resources are saved.

Slowing the spread of COVID-19: Review of "Social distancing" interventions deployed by public transit in the United States and Canada.

This paper presents a review of social distancing measures deployed by transit agencies in the United States and Canada during the COVID-19 pandemic and discusses how specific operators across the two countries have implemented changes. Challenges and impacts on their operations are also provided. Social distancing is one of the community mitigation measures traditionally implemented during influenza pandemics and the novel coronavirus pandemic. Research has shown that social distancing is effective in containing the spread of disease. This is applicable to the current situation with the novel coronavirus, given the lack of effective vaccines and treatments in the United States and Canada in the first eight months of the pandemic. Moreover, social distancing is particularly useful in settings where community transmission is substantial. Directives for social distancing were issued in several states and public transit operators were charged with how to provide for physical distance of six feet between passengers on their property including physical infrastructure such as station buildings and rolling infrastructure (rolling stock) including trains, subway cars and buses. Operational changes were also required due to physical distancing, e.g. adding train cars to provide for opportunities to physically distance on the train. Examples of some measures discussed in this research includes taping off every other seat on buses, increasing the total length of trains by adding cars, separating bus drivers from passengers with plastic sheeting, rear door boarding, etc. This research also analyzes long-term impacts for transit operators and challenges to encourage passengers to return to public transit after lockdown requirements ordered by government officials are lifted. A section on the policies that are being explored by government to continue to sustain public transportation is also included.

Difference in rural and urban driver-injury severities in highway-rail grade crossing accidents.

Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive research, analysis results showed that there were substantial differences between rural and urban areas at highway-rail grade crossings. However, there is no published study specific on driver's injury severity at highway-rail grade crossings classified by area types. Using an ordered probit modelling approach, the study explores the determinants of driver-injury severity at rural highway-rail grade crossings compared with urban highway-rail grade crossings. The analysis found that motor vehicle driver's injury level at rural highway-rail grade crossing is extremely higher than urban area. Compared to collisions at urban area, collisions happened at rural area tend to result in more severe injuries. These crashes were more prevalent if vehicle drivers are driving at a high speed or the oncoming trains are high-speed. Moreover, highway-rail grade crossing accidents were more likely to occur at rural area without pavement and lighting.

The effect of age and gender on motor vehicle driver injury severity at highway-rail grade crossings in the United States.

INTRODUCTION: Based on the Federal Railway Administration (FRA) database, there were 25,945 highway-rail crossing accidents in the United States between 2002 and 2011. With an extensive database of highway-rail grade crossing accidents in the United States from 2002 to 2011, estimation results showed that there were substantial differences across age/gender groups for driver's injury severity. METHOD: The study applied an ordered probit model to explore the determinants of driver injury severity for motor vehicle drivers at highway-rail grade crossings. RESULTS: The analysis found that there are important behavioral and physical differences between male and female drivers given a highway-rail grade crossing accident happened. PRACTICAL APPLICATIONS: Older drivers have higher fatality probabilities when driving in open space under passive control especially during bad weather condition. Younger male drivers are found to be more likely to have severe injuries at rush hour with high vehicle speed passing unpaved highway-rail grade crossings under passive control. Synthesizing these results led to the conclusion that the primary problem with young is risk-taking and lack of vehicle handling skills. The strength of older drivers lies in their aversion to risk, but physical degradation issues which result in longer reaction/perception times and degradation in vision and hearing often counterbalance this attribute.

Costs and benefits of pneumatic collection in three specific New York City cases.

Truck-based collection of municipal solid waste imposes significant negative externalities on cities and constrains the efficiency of separate collection of recyclables and organics and of unit-price-based waste-reduction systems. In recent decades, hundreds of municipal-scale pneumatic collection systems have been installed in Europe and Asia. Relatively few prior studies have compared the economic or environmental impacts of these systems to those of truck collection. A critical factor to consider when making this comparison is the extent to which the findings reflect the specific geographic, demographic, and operational characteristics of the systems considered. This paper is based on three case studies that consider the specific characteristics of three locations, comparing pneumatic systems with conventional collection on the basis of actual waste tonnages, composition, sources, collection routes, truck trips, and facility locations. In one case, alternative upgrades to an existing pneumatic system are compared to a potential truck-collection operation. In the other cases, existing truck operations are compared to proposed pneumatic systems which, to reduce capital costs, would be installed without new trenching or tunneling through the use of existing linear infrastructure. For the two proposed retrofit pneumatic systems, up to 48,000 truck kilometers travelled would be avoided and energy use would be reduced by up to 60% at an incremental cost of up to $400,000 USD per year over the total operating-plus-capital cost of conventional collection. In the location where a greenfield pneumatic system is already in operation, truck collection would be both less expensive and more energy-efficient than pneumatic collection. The results demonstrate that local geographic, demographic, and operational conditions play a decisive role in determining whether pneumatic collection will reduce energy requirements, produce more or fewer greenhouse gas emissions, and cost more or less over the long-term. These findings point to the local factors that will determine the relative economic and environmental costs and benefits in specific situations.