Paper

Measurement and Classification of Transit Delays Using GTFS-RT Data

URL: https://doi.org/10.1007/s12469-022-00291-7

Publication: Public Transport

Volume: 14

Pages: 263-285

Publication Date: 2022

Summary:

This paper presents a method for extracting transit performance metrics from a General Transit Feed Specification’s Real-Time (GTFS-RT) component and aggregating them to roadway segments. A framework is then used to analyze this data in terms of consistent, predictable delays (systematic delays) and random variation on a segment-by-segment basis (stochastic delays). All methods and datasets used are generalizable to transit systems which report vehicle locations in terms of GTFS-RT parameters. This provides a network-wide screening tool that can be used to determine locations where reactive treatments (e.g., schedule padding) or proactive infrastructural changes (e.g., bus-only lanes, transit signal priority) may be effective at improving efficiency and reliability. To demonstrate this framework, a case study is performed regarding one year of GTFS-RT data retrieved from the King County Metro bus network in Seattle, Washington. Stochastic and systematic delays were calculated and assigned to segments in the network, providing insight to spatial trends in reliability and efficiency. Findings for the study network suggest that high-pace segments create an opportunity for large, stochastic speedups, while the network as a whole may carry excessive schedule padding. In addition to the static analysis discussed in this paper, an online interactive visualization tool was developed to display ongoing performance measures in the case study region. All code is open-source to encourage additional generalizable work on the GTFS-RT standard.

Authors: Dr. Andisheh Ranjbari, Zack Aemmer, Don MacKenzie

Recommended Citation:
Aemmer, Z., Ranjbari, A. & MacKenzie, D. Measurement and classification of transit delays using GTFS-RT data. Public Transp 14, 263–285 (2022). https://doi.org/10.1007/s12469-022-00291-7.

Paper

Network Design with Elastic Demand and Dynamic Passenger Assignment to Assess the Performance of Transit Services

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URL: https://doi.org/10.1061/JTEPBS.0000326

Publication: Journal of Transportation Engineering, Part A: Systems

Volume: 146:05:00

Publication Date: 2020

Summary:

This study proposes a solution framework for operational analysis and financial assessment of transit services that considers the passenger behavior and the elasticity of transit demand to service characteristics. The proposed solution framework integrates a dynamic transit passenger assignment model (Fast-Trips) with a mode choice model and a service design module, and iterates these methods until an equilibrium between fares and frequencies is reached. The solution framework was implemented for a newly conceived intercity transit service in Arizona, and the system performance was studied for multiple fare policy and frequency design scenarios. The results showed that the scenarios with designed-oriented frequencies had lower ratios of revenue to operating cost (R/C) compared with those in which frequencies were set based on the passenger path-choice behaviors and route usage, which emphasizes the importance of considering elastic transit demand in network and service designs. The sensitivity analysis also indicated that there are multiple ways to achieve a certain R/C ratio, and therefore it is the other objectives and the operator’s priorities that define the final design and service characteristics.

Authors: Dr. Andisheh Ranjbari, Mark Hickman, Yi-Chang Chiu

Recommended Citation:
Ranjbari, A., Hickman, M., & Chiu, Y. C. (2020). Network Design with Elastic Demand and Dynamic Passenger Assignment to Assess the Performance of Transit Services. Journal of Transportation Engineering, Part A: Systems, 146(5), 04020030. https://doi.org/10.1061/jtepbs.0000326.

Paper

Developing Design Guidelines for Commercial Vehicle Envelopes on Urban Streets (Paper)

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URL: http://dx.doi.org/10.2495/TDI-V3-N2-132-143

Publication: International Journal of Transport Development and Integration

Volume: 3:02

Pages: 132 - 143

Publication Date: 2019

Summary:

Commercial heavy vehicles using urban curbside loading zones are not typically provided with an envelope, or space adjacent to the vehicle, allocated for loading and unloading activities. While completing loading and unloading activities, couriers are required to walk around the vehicle, extend ramps and handling equipment and maneuver goods; these activities require space around the vehicle. But the unique space needs of delivery trucks are not commonly acknowledged by or incorporated into current urban design practices in either North America or Europe. Because of this lack of a truck envelope, couriers of commercial vehicles are observed using pedestrian pathways and bicycling infrastructure for unloading activities, as well as walking in traffic lanes. These actions put them and other road users in direct conflict and potentially in harm’s way.

This article presents our research to improve our understanding of curb space and delivery needs in urban areas. The research approach involved the observation of delivery operations to determine vehicle type, loading actions, door locations and accessories used. Once common practices had been identified by observing 25 deliveries, simulated loading activities were measured to quantify different types of loading space requirements around commercial vehicles. This resulted in a robust measurement of the operating envelope required to reduce conflicts between truck loading and unloading activities with adjacent pedestrian, bicycle, and motor vehicle activities. From these results, commercial loading zone design recommendations can be developed that will allow our urban street system to operate more efficiently, safely and reliably for all users.

Authors: Dr. Ed McCormackDr. Anne GoodchildManali Sheth, David Hurwitz

Recommended Citation:
McCormack, Edward, Anne Goodchild, Manali Sheth, and David Hurwitz. Developing Design Guidelines for Commercial Vehicle Envelopes on Urban Streets. International Journal of Transport Development and Integration, 3(2), 132–143. https://doi.org/10.2495/TDI-V3-N2-132-143

Developing Design Guidelines for Commercial Vehicle Envelopes on Urban Streets

Commercial vehicles using loading zones are not typically provided with an envelope, or a space allocation adjacent to the vehicle for loading and unloading activities. While completing loading and unloading activities, drivers are required to walk around the vehicle, extend ramps and handling equipment, and maneuver goods; these activities require space around the vehicle. The unique needs of a delivery truck are not acknowledged by or incorporated in current design practices.

Due to lack of a truck envelope, drivers of commercial vehicles are observed using pedestrian pathways and bicycling infrastructure for unloading activities and the transport of goods by hand. These actions put themselves, and other road users in direct conflict and potentially in harm’s way. The purpose of this research is to improve our understanding of the interactions between heavy vehicles and other users in an urban environment, in particular, in cases where commercial vehicle activity disrupts the activity of pedestrians and bicyclists. The research approach includes both the observation of current practice and evaluation of infrastructure and simulation of roadway user behavior. This information will support better roadway and load zone design guidelines, which will allow our urban street system to operate more efficiently, safely, and reliably for all users.

Article

Physics-Informed Machine Learning of Parameterized Fundamental Diagrams

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URL: https://doi.org/10.48550/arXiv.2208.00880

Publication: arXiv

Volume: 2208.0088

Publication Date: 2022

Summary:

Fundamental diagrams describe the relationship between speed, flow, and density for some roadway (or set of roadway) configuration(s). These diagrams typically do not reflect, however, information on how speed-flow relationships change as a function of exogenous variables such as curb configuration, weather or other exogenous, contextual information. In this paper we present a machine learning methodology that respects known engineering constraints and physical laws of roadway flux–those that are captured in fundamental diagrams– and show how this can be used to introduce contextual information into the generation of these diagrams. The modeling task is formulated as a probe vehicle trajectory reconstruction problem with Neural Ordinary Differential Equations (Neural ODEs). With the presented methodology, we extend the fundamental diagram to non-idealized roadway segments with potentially obstructed traffic data. For simulated data, we generalize this relationship by introducing contextual information at the learning stage, i.e. vehicle composition, driver behavior, curb zoning configuration, etc, and show how the speed-flow relationship changes as a function of these exogenous factors independent of roadway design.

Authors: Thomas MaxnerDr. Andisheh Ranjbari, James Koch, Vinay Amatya, Chase Dowling

Recommended Citation:
Koch, J., Maxner, T., Amatya, V.C., Ranjbari, A., & Dowling, C.P. (2022). Physics-informed Machine Learning of Parameterized Fundamental Diagrams.

Paper

Challenges in Credibly Estimating the Travel Demand Effects of Mobility Services

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URL: https://doi.org/10.1016/j.tranpol.2021.02.001

Publication: Transport Policy

Volume: 103

Pages: 224-235

Publication Date: 2021

Summary:

Mobility services including carsharing and transportation network company (TNC) services have been growing rapidly in North America and around the world. Measuring the effects of these services on traveler behavior is challenging because the results of any such analysis are sensitive to how (1) outcomes are measured and (2) counterfactuals are constructed. The lack of good control groups or randomization of assignment leaves lingering uncertainty over the contributions of selection bias and treatment effects to reported differences in travel behavior between users and non-users of these services. This paper reports on two approaches for measuring the effects of mobility service adoption on travel rate and car ownership. We first tried a pretest-posttest randomized encouragement experiment to deal with the shortcomings of poor control groups. Then, we turned to the approach of self-reported effects based on hypothetical controls to investigate whether variations in survey question presentation could influence respondents’ answers and thus lead to changes in estimated effects. The data to conduct this study came from two sources: a panel survey administered by the authors at the University of Washington (UW), and a survey by Populus Technologies, Inc. (Populus). Various statistical tests were applied to analyze the data, and the results highlight the pivotal role that the research design plays in influencing the outcomes, and manifest the fundamental challenge of establishing credible estimates of the causal effects of adopting mobility services on travel behaviors.

Authors: Dr. Andisheh Ranjbari, Xiao Wen, Fan Qi, Regina R. Clewlow, Don MacKenzie

Recommended Citation:
Xiao Wen, Andisheh Ranjbari, Fan Qi, Regina R. Clewlow, Don MacKenzie. Challenges in credibly estimating the travel demand effects of mobility services. Transport Policy, (103:224-235) 2021. https://doi.org/10.1016/j.tranpol.2021.02.001.