TRB Annual Meeting 2019

2019 Paper Award Winner:

• "Spatio-Temporal Analysis of Routes and Timetable Change: the impact on Users' Level of Service" by Duval Hadas. (19-02708)

2019 Poster Award winners:

• • Raphael Hörler, (Zhaw Zurich University of Applied Sciences) FOR: Socioeconomic & Attitudinal Factors in Sustainable Commuting: A Swiss Case Study

  • Amy Smith, (Uber Technologies) & Eric Womeldorff, (Fehr & Peers) FOR: Data-Driven Approach to Understanding and Planning for Curb Space Utility

  • Anahita Jami, (University of Toronto) FOR: Greenhouse Gas Emission Modeling for the Transit Sector

  • Yuval Hadas, (Bar Ilan University) FOR: Spatio-Temporal Analysis of Routes and Timetables Change: The Impact on Users’ Level of Service

LECTERN ABSTRACTS 

"Trends in Public transportation Ridership and Demand"

New York City Subway Ridership: Regional Variation Across Land Use and Socioeconomic Settings 

Matthew Volovski, Manhattan College

Nicola Grillo, Manhattan College

Conor Varga, Manhattan College

Tariq Usman Saeed, Purdue University

Mohab El-Hakim, Manhattan College

Accurate forecasts of public transportation ridership are key components to a transit agency’s management program. These forecasts are used to develop revenue projections that are then imputed into short-term and long-term maintenance, rehabilitation, and capital investment programming. The forecasts are complicated by the fact that many of the causes of the underlying variability, such as socioeconomic and land use factors, are not constant over the network. Failure to account for these spatial processes will yield biased, inefficient, and inconsistent demand estimates. To overcome these challenges, the current paper presents a Spatial Durbin model for analyzing the change in the New York City subway station ridership between 2011 and 2016. The results indicate that subway stations experienced a greater increase in ridership over the study period when station; served more train lines, were located in areas comprised of census tracts with a greater number of tax units (residential, commercial, etc.), or served lower mean household incomes. Furthermore, the subway stations located in areas surrounded by census tracts with more commercial property or higher median family income are also expected to have a greater increase in ridership. Lastly, ridership at a given station decreases due to an increase in ridership at neighboring stations. This may indicate that a change in ridership at a station is due, in part, to riders in a region changing which station they use instead of riders shifting from alternative modes of transportation.

Estimating the Impacts of Capital Bikeshare on Metrorail Ridership in the Washington Metropolitan Area 

Ting Ma, District Department of Transportation

Gerrit Jan Knaap, University of Maryland, College Park

Bikeshare programs have transformed our urban transportation systems. However, their impacts on rail transit have not been carefully examined. Some find bikes help reduce the first-mile/last-mile gaps and boost transit ridership, while some see bikeshare as an alternative transportation option which competes for riders. Previous studies have mostly relied on surveys of bikeshare program users, and few have addressed the question using more rigorous methods. In this paper, the authors take the Capital Bikeshare (CaBi) program and the Metrorail system in the Washington metropolitan area as an example to quantify the bikeshare program’s impacts on rail transit ridership. Statistical analysis is conducted using monthly ridership data between 2010 and 2015. Metrorail ridership data is broken down by type (entries vs. exits) and time of the day (AM peak vs. PM peak) to analyze in detail how CaBi interacts with Metrorail. Stations located in downtown D.C. and peripheral neighborhoods are studied separately for comparison. Regression results show that CaBi’s impacts vary by location. For core Metrorail stations, CaBi competes with Metrorail for riders. Having CaBi docking stations within a ¼ mile distance of a Metrorail station reduces both AM- and PM-peak entries and exits of that Metrorail station. In particular, CaBi would reduce the number of AM-peak entries by 4,738 per month. However, CaBi complements Metrorail in peripheral neighborhoods. Having CaBi installed nearby would increase monthly Metrorail ridership by 1,175 AM-peak exits, 1,417 PM-peak entries, 2,284 AM-entries, and 2,422 PM-peak exits. Planning suggestions are made based on statistical analysis results.

Modeling the Effect of New Commuter Bus Service on Demand and the Impact on Greenhouse Gas Emissions: Application to Greater Boston 

Christopher Lyman, University of Massachusetts, Amherst

Nicholas Campbell, University of Massachusetts, Amherst

Eric J. Gonzales, University of Massachusetts, Amherst

Eleni Christofa, University of Massachusetts, Amherst

The transportation sector is considered one of the major contributors to greenhouse gas (GHG) emissions in metropolitan areas, and any efforts to reduce these emissions requires strategic management of multiple transportation modes. This paper presents a method to identify opportunities to reduce GHG emissions by expanding commuter bus services and incentives to shift commuters from private cars to transit. The approach uses a nested multinomial logit model for mode choice in a region that includes driving alone, carpooling, walking, cycling, and using four possible transit modes (ferry, commuter rail, rapid transit, bus) by walk access or driving access. A model of existing conditions was calibrated with data Boston metropolitan area. Using an emission factor model based on average speeds from the California Air Resources Board (CARB), the net effect of new commuter bus service on GHG emissions from transportation is estimated. Potential GHG reductions are weighed against the capital and operating costs of new transit services to quantify the cost-effectiveness of new commuter bus service for isolated origin-destination pairs. This modeling framework is used to optimize fares and bus frequency in order to identify the corridors with the most cost-effective potential for GHG reduction. Results are presented for the Boston region, demonstrating the feasibility of implementation and the potential magnitude of benefits for cost-effectively reducing GHG emissions associated with transportation. The method is general and can be applied in other cities around the world.

Current State of Practice in Transit Ridership Prediction: Results from a Survey of Canadian Transit Agencies 

Ehab Diab, University of Saskatchewan

Dena Kasraian, University of Toronto

Eric Miller, University of Toronto

Amer Shalaby, University of Toronto

With the emergence of new technologies, new data sources and software, it is important to understand the current approaches used by transit agencies in ridership prediction. This study reports the results of a recent web-based survey conducted in 2018 among 36 Canadian transit agencies to understand their current state of ridership prediction practice. The study presents a wide range of results starting from agencies’ used prediction methods to the challenges faced by transit agencies due to the observed changes in ridership estimates after the introduction of new automated data collection systems. The study also discusses the transit agencies’ level of satisfaction with the current used methods and data inputs and factors that are incorporated in their methods. In addition, it develops a better understanding of the requirements of robust ridership prediction models from the transit agencies’ perspective. This paper provides planners and researchers with a comprehensive examination of the different aspects and issues that are related to the current state of transit agencies’ ridership prediction practices.

Integration of an Urban Ropeway into Munich's Transit System Demand Modeling 

Michaela Tießler, Bundeswehr University, Munich

Roman Engelhardt, Bundeswehr University, Munich

Klaus Bogenberger, Bundeswehr University, Munich

Christoph Hessel, gevas humberg & partner

Magdalena Serwa-Klamouri, gevas humberg & partner

While in some cities ropeways already belong to the transit system, in Germany, they are rather known from skiing in the alps or as tourist attractions that were implemented in relation to expositions as in Koblenz or Berlin. Nonetheless, a ropeway system has several advantages, which make it an interesting alternative in urban public transportation. In this paper, we investigate the varying attitude of residents and commuters towards a ropeway system and its potential on a route in the north of Munich. To get an impression on their opinion, we conducted an online survey focusing on route choice depending on the transit mode and travel times. In general, the respondents had a positive attitude towards this novel option and rate it with similar attractiveness as subway. In order to investigate the demand for the ropeway, the results of the survey were used to add a new transportation mode in the VISUM model for transit in Munich.