2020

Jiawen Yang, Peking University
Xiongbin Lin, Ningbo University

Urban China is experiencing substantial growth of metropolitan passenger trips, particularly in developed coastal areas. However, China lacks specific regional institutions to plan and fund inter-city transportation infrastructure and service. How China’s governments have managed to fund regional inter-city rail which is facilitating passenger movement in high-density urbanized areas is not well understood. Using the Pearl River Delta as the study case, this research studies a variety of regional rail investments and policy arrangements, ranging from inter-city metro systems, to provincial government-led inter-city passenger rail, and to regional express services on the national high-speed rail track. The pros and cons of each of these rail options are assessed.

Jacob Thompson, Tennessee State University
Kimberly Triplett, Tennessee State University

This research study includes an in-depth case study on why the city of Nashville, Tennessee’s “Transit for Nashville” referendum did not pass. Nashville is growing by almost 100 people every day and the roadways are gridlocked. With years of planning and public participation, Nashville’s city planners and officials developed the “Transit for Nashville” plan to reduce traffic congestion. Although there are many reasons why the “Transit for Nashville” referendum did not pass, this study identifies and focuses on three reasons: cost/benefit, car dependency, and politics. The research study also presents recommendations to improve traffic congestion issues as the city of Nashville moves forward with capacity.

Yi He, Utah State University
Zhaocai Liu, National Renewable Energy Laboratory (NREL)
Ziqi Song, Utah State University

Shared transportation has grown tremendously as a sustainable alternative to tackle the increasingly severe transportation problems (e.g., traffic congestions), energy issues, and environmental problems in recent years. The public bike system, also known as bike share system, is one of the most popular shared transportation systems and has recently gained prominence. It can either serve as an individual mobility for short trips or integrate with other public transportation systems to provide more convenient and efficient mode of transportation. The deployment of the bike share system in a transportation network is an important factor for the success of the bike share program. However, most previous literature that dealt with the strategic planning of bike share systems only considered the bike system itself or the integration of the bike system and public transit system, but ignored the potential influence of the bike share system on other modes in the transportation network. This study aims to fill this gap in the literature. A mathematical program with complementarity constraints (MPCC) is formulated to find the optimal locations and inventory levels of bike stations in a multimodal transportation network as well as the optimal subsidy for specific users. An active-set algorithm is developed to solve the model. To illustrate the effectiveness and efficiency of the proposed model and the algorithm, a numerical example the computational results are provided.

Rick Grahn, Carnegie Mellon University
Sean Qian, Carnegie Mellon University
Chris Hendrickson, Carnegie Mellon University
H. Scott Matthews, Carnegie Mellon University

Transportation network companies (TNC) provide mobility services that are influencing travel behavior in ways largely unknown due to limited TNC trip-level data. How they interact with other modes of transportation can have direct societal impacts, prompting appropriate policy intervention. This paper outlines a methodology to inform such policies through a data-driven approach that specifically analyzes the interaction between TNCs and bus services in Pittsburgh, PA. Surge multiplier data from Uber is used over a six month time period to approximate TNC usage (i.e., demand over supply ratio) for ten predefined points of interest throughout the city. Bus boarding data for each bus stop near each point of interest is used to relate TNC usage. Data from multiple sources (weather, traffic speed data, bus levels of service) are used to control for conditions that influence bus ridership. We find significant but mixed changes in bus boardings during periods of unusually high TNC usage at three locations during the evening hours (weekday evening peak for a residential location, weekday late night for a mixed-use location, and weekend evening for a university location). The remaining seven locations observe no significant change in bus boardings. The results also indicate that ad-hoc substitutional behavior varies by location and time of day. This dynamic interaction highlights the importance of data-informed policy making.

Jacob Wasserman, University of California, Los Angeles
Brian Taylor, University of California, Los Angeles

Peaking on transit—the overconcentration of ridership at peak times, in commute directions, and in central areas—has developed over the past century, as transit has lost mode share unevenly across times of day and trip types. The latest manifestation of this chronic problem is on Bay Area Rapid Transit, the San Francisco Bay Area’s regional heavy rail system. While BART staved off an absolute ridership decline longer than most American operators, its current patronage slump, due almost entirely to off-peak losses, has brought to light peaking issues dating back earlier.   To examine the changing demand for and use of BART, we model BART trips as a function of both temporal and spatial characteristics. We uniquely use origin-destination pairs as the unit of analysis in order to separately measure influences at either end of the trip.   We find that station-area jobs are, by far, the most important factor explaining BART ridership in 2011 and 2015. Moreover, their influence has grown over time. The same holds true in a number of alternative model specifications that consider only off-peak times or only trips outside of downtown San Francisco.   The peaking problem plaguing public transit systems for decades appears to be worsening—on this one nationally significant transit system, at least—up to the present day. The consequences for agency finances, passenger subsidies, and rider satisfaction are far from abstract, though efforts to identify and remediate the causes of off-peak ridership losses may ameliorate the worst of them.

Ting Zuo, University of Cincinnati
Heng Wei, University of Cincinnati
Na Chen, University of Cincinnati

The speed advantage in bicycling over walking has been believed to ease the first-and-last mile (F&LM), expand transit service coverage area, and allow more people to have access to transit service. To quantify those potentials of bicycle as the F&LM connector, the paper attempts to measure transit service coverage accessed by walking and bicycling with the GPS trajectory data collected from Cincinnati GPS-based Household Travel Survey in Hamilton County, Ohio. The transit service coverage is measured by transit catchment areas and number of service population. Distance decay functions representing the attractiveness of public transit that decreases with increasing walking/biking time to access transit facilities and the spatial boundaries of catchment areas are developed. Bicycle Level of Traffic Stress is used to evaluate the bicycle suitability of streets and bike network connectivity. Based on the distance decay functions and bike network connectivity, the transit service coverage area as well as the transit service population and employment are estimated. The results show that more population and employment can reach transit service by bicycling than walking. Meanwhile, disadvantaged groups, i.e., low-income and zero-car population, can be better covered by transit if using bicycle as the F&LM connector. In addition, the low-stress bicycling connectivity is a significant factor determining the bicycle-transit service coverage, and a well-connected low-stress bike network with more bikeways, especially protected bike lanes, is crucial to guaranteeing that. These findings can be used as references to assist planners in their decision-making process to achieve better mobility and accessibility.

Sajeeb Kirtonia, Florida State University
Yanshuo Sun, Florida State University

This paper presents a comparative analysis of rail transit and taxi by travel cost and time based on the large-scale taxi trip data and public transit schedule information in Washington, D.C. and Chicago, IL. To quantify the relative advantage of one mode over the other, we introduce the notion of travel gradient, which is calculated as the travel cost difference divided by the travel time difference. Based on the signs of the travel cost and travel time differences, we classify all trips into four quadrants. Quadrant II trips are selected for further analysis because rail transit is identified to be competitive with taxi for such trips. A multiple linear regression model is used to understand the relation between various trip characteristics and rail transit’s comparative advantage, quantified by the travel gradient. Main findings from the numerical analyses include: (1) around 70% of the trips in the datasets can be substituted with rail transit trips if the maximum walking time is 0.5 mile on each trip end in both cities; (2) for around 10% of trips with both rail transit and taxi as viable modes, rail transit dominates taxi in both travel cost and travel time; (3) for the rest of trips, rail transit is competitive with taxi. Moreover, on average if a traveler accepts a prolonged trip by one hour, a travel cost reduction of about $70 can be expected by switching from taxi to rail transit, exceeding the value of travel time for most travelers.

Duy Nguyen-Phuoc, Danang University
Diem-Trinh Le, Singapore-MIT Alliance for Research and Technology
Zhou Meng, Singapore-MIT Alliance for Research and Technology
Simon Oh, Singapore-MIT Alliance for Research and Technology

The operation of buses plays an important role in an urban transport system. A well-designed bus system can contribute to alleviate traffic congestion, air pollution and accidents, thus promotes urban sustainability. Previous studies have investigated the relief impacts of bus services on congestion using ‘vehicle-based’ measurements. However, it is limited to capture the congestion level at disaggregate levels. This study estimates the congestion level at the individual level using ‘person-based’ measures to assess the overall impact of bus on urban transport. Using SimMobility, an agent-based microsimulation platform, this paper aims to achieve a better understanding of the impacts of bus operations on reducing the congestion level of urban transport systems, with a focus on train systems and road networks. The results indicate that Singapore’s bus services contribute to reduce passenger kilometers travelled and total travel time of train passengers by approximately 40-45% and of car users by 16-18% in peak hours. The spatial effect of bus operations is also investigated, which shows that during morning peak hours, train passengers and car users living in outer areas are most affected. Findings from this study emphasizes bus operation’s contribution to achieving transport policies’ objectives and wider urban sustainability goals.

Danique Ton, Delft University of Technology
Sanmay Shelat, Delft University of Technology
Sandra Nijenstein, HTM Personenvervoer
Lotte Rijsman, royal HaskoningDHV
Niels van Oort, Technische Universiteit Delft
Serge Hoogendoorn, Technische Universiteit Delft

Governments worldwide are aiming for an increase in sustainable mode use to increase sustainability, livability and accessibility. Integration of bicycle and transit can increase catchment areas of transit compared to walking and thus provide better competition to non-sustainable modes. To achieve this, effective measures have to be designed that require a better understanding of the factors influencing access mode and station choice. At the national/regional level this has been thoroughly studied. However, at the urban level knowledge is missing. This study aims to investigate which factors influence the joint decision for tram access mode and tram station choice. The joint investigation can identify trade-offs between the access and transit journey. Furthermore, the effect of each factor on the bicycle catchment area is investigated. Using data from tram travelers in The Hague, Netherlands, a joint simultaneous discrete choice model is estimated. Generally, walking is preferred over cycling. Our findings suggest that access distance is one of the main factors for explaining the choice, where walking distance is weighted 2.1 times cycling distance. Frequent cyclists are more likely to also cycle to the tram station, whereas frequent tram users are less inclined to do so. Bicycle parking facilities increase the cycling catchment area by 234m. The transit journey time has the largest impact on the catchment area of cyclists. Improvements to the system, such as less stops and/or higher frequency (like LRT) result with a much higher accepted cycling distance.

Jueyu Wang, University of Minnesota
Eric Lind, Metro Transit, Minneapolis-St. Paul
Anna Flintoft, Washington Metropolitan Area Transit Authority
Greg Lindsey, University of Minnesota

The increasing interest in multi-mode development has aroused attention on the integration of bicycle and transit. However, the relevant empirical studies of evaluating the integration of the bicycle and transit are limited in the US context. The study explores the relationship between the built environment and bike on bus demand along the BRT A Line in the Minneapolis-St. Paul Metropolitan Area. We use a detailed bike rack sensor data in 2018 and estimate three models to examine three different spatial zones of built environment variables, including the built environment around origin and destination stops, and along the route. The estimation results are consistent across the three models with minor differences. The number of connecting transit service around the origin stop and whether the stop is connecting to regional light rail service have positive associations with the number of bikes on at the stop. Connecting to regional light rail service at the destination stop also positively correlated with the number of bike off. The results also show that population density and job density at the stop level are positively correlated with the bike on bus trips, while population and job density along the route are negatively correlated. The paper ends with discussion and policy implications.

Laura Aston, Monash University
Graham Currie, Monash University
Md Kamruzzaman, Monash University
Alexa Delbosc, Monash University
Nicholas Fournier, Monash University
David Teller, State Government of Victoria

Many studies have identified links between the built environment and transit use. However, little is known about whether the built environment predictors of bus, train, tram and other transit services are different. Studies to date typically analyze modes in aggregate, by combining bus, train, and tram; or analyze each mode separately. Findings from these studies demonstrate the built environment attributes that are relevant for apportioning trips to transit. However, they do not differentiate demand for competing modes. This study aims to investigate if built environment impacts on transit ridership vary according to mode, by analyzing two types of co-located (matched) transit modes (train-bus and tram-bus) in Melbourne. Multivariate multiple linear regression models were estimated to identify the relationships between different indicators of the built environment with patronage of each mode. This research indicates built environment impacts on ridership vary in type and relative importance according to mode. The strongest land use predictor of train ridership was proximity to the CBD, while bus ridership was most closely associated with the presence of Activity Centres in the catchment. Tram and bus ridership shared no built environment predictors, with land use diversity the strongest predictor for tram use, compared to intersection density for bus. These differences provide evidence that built environment impacts on transit cannot be generalized for all modes. The study’s findings suggest that strategies to encourage transit use could be made more effective if they are differentiated by mode.