Paper

The Impact of Weather on Bus Ridership in Pierce County, Washington

URL: http://doi.org/10.5038/2375-0901.15.1.6

Publication: Journal of Public Transportation

Publication Date: 2012

Summary:

A factor that influences transit ridership but has not received much attention from researchers is weather. This paper examines the effects of weather on bus ridership in Pierce County, Washington, for the years 2006–2008. Separate ordinary least squares regression models were estimated for each season, as weather conditions may have different effects depending on the time of year. Four weather variables were considered: wind, temperature, rain, and snow. High winds negatively affected ridership in winter, spring, and autumn. Cold temperatures led to decreases in ridership in winter. Rain negatively affected ridership in all four seasons, and snow was associated with lower ridership in autumn and winter. These results suggest that adverse weather conditions can have a negative effect on transit ridership.

Authors: Dr. Ed McCormack, Victor W. Stover

Recommended Citation:
Stover, V. W., & McCormack, E. D. (2012). The Impact of Weather on Bus Ridership in Pierce County, Washington. Journal of Public Transportation, 15(1), 6.

A Data-Driven Simulation Tool for Dynamic Curb Planning and Management

Project Budget: $2.9M (UW amount: $500k)

Lead Institution:

Pacific Northwest National Lab (PNNL)

Partner Institutions:

Urban Freight Lab (UFL), University of Washington
Lawrence Berkeley National Laboratory (LBNL)
Lacuna Technologies, Inc. (Lacuna)
National Renewable Energy Laboratory (NREL)

Summary:

Curbs are a critical interfacing layer between movement and arrival in urban areas—the layer at which people and goods transition from travel to arrival—representing a primary point of resistance when joining and leaving the transportation network. Traditionally, curb spaces are statically supplied, priced, and zoned for specific usage (e.g., paid parking, commercial/passenger loading, or bus stops). In response to the growing demand for curb space, some cities are starting to be more intentional about defining curb usage. Examples of curb demand include not only traditional parking and delivery needs, but today include things like curb access requirements generated by micro delivery services, active transportation modes, and transportation network companies. And now due to the pandemic, increased demand comes from food/grocery pick-up/drop-off activities, as well as outdoor business use of curb space (e.g., outdoor restaurant seating).

Heightened demand and changing expectations for finite curb resources necessitates the implementation of new and dynamic curb management capabilities so that local decision-makers have the tools needed to improve occupancy and throughput while reducing the types of traffic disruptions that result from parking search and space maneuvering activities.

However, municipalities and cities currently lack tools that allow them to simulate the effectiveness of potential dynamic curb management policies to understand how the available control variables (e.g. price or curb space supply) can be modified to influence curb usage outcomes. On the other hand, transportation authorities and fleet managers lack the needed signage or communication platforms to effectively communicate the availability of curb space for a specified use, price, and time at scales beyond centralized lots and garages.

This project aims to develop a city-scale dynamic curb use simulation tool and an open-source curb management platform. The envisioned simulation and management capabilities will include dynamically and concurrently controlling price, number of spaces, allowed parking duration, time of use or reservation, and curb space use type (e.g., dynamic curb space rezoning based on supply and demand).

Project Objectives:

Project objectives include the following:

Objective 1: The team will develop a microscale curb simulation tool to model behavior of individual vehicles with different purposes at the curb along a blockface over time of day, accounting for price, supply, function, and maximum parking time.
Objective 2: The team will integrate the microscale simulation tool with the LBNL’s mesoscale (city-scale) traffic simulation tool, BEAM, for simulating traffic impacts of alternative curb management strategies and their effects on citywide and regional traffic, in terms of (1) travel time, (2) throughput (people and goods) into and out of urban centers, (3) reduced energy use and emissions (from parking search and congestion), and (4) curb space utilization.
Objective 3: The team will develop a dynamic curbspace allocation controller for various curb users, either municipal or commercial, for the purpose of a demonstration and pilot.
Objective 4: The team will design, implement and test a curbside resource usage platform for fleet vehicles communications at commercial vehicle load zones (CVLZs), passenger load zones (PLZs), and transit stops.
Objective 5: The team will perform demonstrations with stakeholder agencies and provide pathways to practice for promising curb allocation policies.

Paper

Analyzing the Shift in Travel Modes’ Market Shares with the Deployment of Autonomous Vehicle Technology

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URL: http://hdl.handle.net/1773/45288

Publication Date: 2020

Summary:

It is generally accepted that automation as an emerging technology in transportation sector could have a potential huge effect on changing the way individuals travel. In this study, the impact of automation technology on the market share of current transportation modes has been examined. A stated preference (SP) survey was launched around the U.S. to ask 1500 commuters how they would choose their commute mode if they had the option to choose between their current mode and an autonomous mode. The survey included five transportation modes: car, transit, transit plus ride-sourcing for the first/last mile, solo ride-sourcing, and pooled ride-sourcing. Each of these modes could be presented as regular or autonomous in the choice scenarios. Then, a mixed logit model was developed using the collected data. Results from the analysis of the model showed that applying the automation in ride-sourcing services to decrease the fare, has the largest effect on the market share of transit ride-sourcing. Also, it was found that measures such as deploying more frequent services by ride-sourcing operators to minimize the waiting time of the services could lead to an increase in the market share of transit plus ride-sourcing but it might not improve the market share for solo and pooled ride-sourcing. Furthermore, it was concluded that if the ride-sourcing market share does not move toward the automation, the mode that will lose the market share is the transit plus ride-sourcing mode for which the market share will be decreased as a consequence of the high decrease in the cost of riding an autonomous private car.

Authors: Dr. Andisheh Ranjbari, Moein Khaloei, Don MacKenzie

Recommended Citation:
Khaloei, M., Ranjbari, A. and MacKenzie, D. (2020) Analyzing the Shift in Travel Modes’ Market Shares with the Deployment of Autonomous Vehicle Technology. Transportation

Student Thesis and Dissertations

EV Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities

URL: http://dx.doi.org/10.1016/j.scs.2018.10.024

Publication Date: 2021

Summary:

Electric vehicles, one of the emerging modes of transportation, are at the forefront of sustainable mobility. In the past years, there has been a rapid rise in EVs, both as private and public transportation modes. Private users are influenced by multiple factors while choosing electric cars as their travel modes. Among them, policy and infrastructure are deemed to be the main influencers globally. These policies and infrastructures vary in different cities. However, there is a lack of research dealing with what parts of the policy and infrastructure are actually most effective in EV adoption. This research presents a descriptive and quantitative evaluation as well as statistical analysis to identify the most effective policies and infrastructure components in electric car adoption as a personal transportation mode in sixteen selected cities; Seattle, Los Angeles, San Francisco, San Jose, New York, Oslo, Bergen, London, Amsterdam, Stockholm, Berlin, Munich, Paris, Shenzhen, Beijing and Tokyo. The cities are evaluated based on total electric vehicles on road, EVs on household level and electrification ratio of the registered cars in conjunction with household median income. Policy level incentives like electrification target, parking, toll, and lane access benefits along with tax rebates, subsidies and other monetary incentives as part of the total cost of ownership are also observed. Total number of public and residential charging points as well as the EV supply equipment program are analyzed as part of EV infrastructure preparedness on city level. Among the sample cities, Norway is the pioneer in the electric car integration into their passenger car market. All the sample cities have active Zero Energy Vehicle mandates and incentives for electric vehicles. Through secondary data collection via various online resources and statistical observation with help of the existing literature, this study found high correlation between EV ownership and incentives. Multilinear Regression Analysis model predicted 0.53% increase in passenger electrification with every $100 incentive increase. The environmental conditions of the sample cities are also evaluated to observe the impact of mass EV adoption in the overall improvement in CO2 emission reduction. At the end of this paper, this research proposes some policies to improve the EV adoption challenges present in the sample cities as well as the cities aiming to turn towards this sustainable mode in the future.

Authors: Romana Haque Suravi

Recommended Citation:
Suravi, Romana. (2021). EV Friendly Cities: A Comparison of Policy and Infrastructure in Sixteen Global Cities. 10.13140/RG.2.2.18239.02722. University of Washington Master's Thesis.

Thesis: Array

Student Thesis and Dissertations

Seattle Bicycle Share Feasibility Study

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URL: https://nacto.org/wp-content/uploads/2015/07/2011_McCormack-et-al_Seattle-Bicycle-Share-Feasibility-Study.pdf

Publication: University of Washington, College of Built Environment, Department of Urban Planning and Design

Publication Date: 2011

Summary:

This report assesses the feasibility of a public use bike-share system for Seattle, Washington. Colloquially referred to as “bike-share” or “bike-sharing,” such systems are considered a form of public transportation. Bike-share bicycles are intended for short-term use and are accessible via automated check-out systems. An important benefit of bike-share systems is the flexibility to return rented bicycles to any station within the system, thereby encouraging use for one-way travel and the “final mile” of a trip.

The four major chapters of this report represent the organization of our research and analysis. The topic areas are:

Introduction: Bike-share history and the structure of our study
Demand Analysis: Our analytic and forecast methodologies along with results of their application
Policy Framework: Consideration of governance institutions and their effects on system implementation
Bike-Share Program Recommendations: Summation of our findings and recommendations for how Seattle should proceed

During our analysis, we looked at demand for bike-share in Seattle. We have concluded that demand is sufficient to support a program. Our final recommendation includes three implementation phases, beginning with the downtown and surrounding neighborhoods.

However, despite anticipation of program demand, there are institutional policy challenges that must be addressed before successful implementation. Prominent among these are:

The King County helmet law
City of Seattle sign codes
Policies that affect station design and use of curbspace

In the case of the latter two, individual neighborhoods and districts may each have their own, unique impacts. Fortunately, Seattle has the flexibility to address these issues, and there are systems in place to overcome these challenges. Once addressed, we recommend the City move forward with implementing a bikeshare program.

Authors: Dr. Ed McCormack, Jennifer Gregerson, Max Hepp-Buchanan, Daniel Rowe, John Vander Sluis, Erica Wygonik, Michael Xenakis

Recommended Citation:
Gregerson, J., Hepp-Buchanan, M., Rowe, D., Vander Sluis, J., Wygonik, E., Xenakis, M., & McCormack, E. (2011). Seattle bicycle share feasibility study. University of Washington, College of Built Environment, Department of Urban Planning and Design.

West Seattle Bridge Case Study (Phase I)

Background
West Seattle is an area of the city of Seattle located on a peninsula west of the Duwamish waterway and east of the Puget Sound. In March 2020, the West Seattle High Bridge (WSHB), the main bridge connecting West Seattle to the rest of the city, was closed indefinitely to traffic due to its increasing rate of structural deterioration. Moreover, access to the Spokane Street Lower Bridge, a smaller bridge connecting West Seattle with Harbor Island and the rest of the city, was also restricted; prioritizing heavy freight, public transit, and emergency vehicles. After the bridge closure and restrictions, the total number of vehicle travel lanes crossing the Duwamish River was reduced from 21 to 12.

The unexpected closure of WSHB disrupted passenger and freight mobility to and from West Seattle, increasing travel times and generating bottlenecks on the remaining bridges, which can potentially negatively impact the livability of the peninsula as well as its economy and the environment. The situation might further deteriorate as traffic demand to and from West Seattle increases during recovery from the COVID-19 pandemic.

The Seattle Department of Transportation (SDOT) is taking actions to monitor changes in travel behavior to/from West Seattle and identify and implement strategies that could mitigate the negative impacts caused by the WSHB closure.

Goals
SDOT has engaged the Urban Freight Lab to conduct research to explore strategies to alleviate congestion impacts and minimize the disruption of goods and service delivery to West Seattle.

The purpose of this study is to support SDOT to:

understand current freight movements and freight demand in West Seattle;
identify a data-driven mitigation strategy for freight and service flow to and from West Seattle;
assess ex-ante the effectiveness of an implemented strategy.

The freight operations considered and analyzed within the scope of the project are consumer goods and services destined for West Seattle residents and businesses. Intermediate goods and raw materials destined for construction of production and other goods transiting through West Seattle but not destined for local residents or businesses will not be studied.

Continuation
This project continues with the West Seattle Bridge Case Study Phase II.

Paper

Would Being Driven by Others Affect the Value of Travel Time? Ridehailing as an Analogy for Automated Vehicles

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URL: https://doi.org/10.1007/s11116-019-10031-9

Publication: Transportation

Volume: 46

Pages: 2103–2116

Publication Date: 2019

Summary:

It is widely believed that vehicle automation will change how travelers perceive the value of travel time (VoTT), but the magnitude of this effect is still unknown. This study investigates how highly automated vehicles (AVs) may affect VoTT, using an existing mode—ridehailing services (RHS)—as an analogy for AVs.

Both AVs and RHS relieve travelers from the effort of driving and allow them to participate in other activities while traveling. In a stated choice experiment, respondents chose between driving a personal vehicle or taking an RHS, with each mode characterized by a cost and travel time.

Analysis results using a mixed logit model indicated that the VoTT was 13% lower when being driven in an RHS than when driving a personal car. We also told half the respondents (randomly selected) that the RHS was driverless; and for half (also randomly selected) we explicitly mentioned the ability to multitask while traveling in an RHS. Mentioning multitasking explicitly led to a much lower VoTT, approximately half that of driving oneself. However, the VoTT in a driverless RHS was 15% higher than when driving a personal car, which may reflect a lack of familiarity and comfort with driverless technology at present.

These results suggest sizable reductions in VoTT for travel in future AVs, and point to the need for caution in making forecasts based on consumers’ current perceptions of AV technology.

Authors: Dr. Andisheh Ranjbari, Jingya Gao, Don MacKenzie

Recommended Citation:
Gao, J., Ranjbari, A. & MacKenzie, D. Would being driven by others affect the value of travel time? Ridehailing as an analogy for automated vehicles. Transportation 46, 2103–2116 (2019). https://doi.org/10.1007/s11116-019-10031-9

Paper

Evaluating Traffic Impacts of Permitting Trucks in Transit-Only Lanes

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URL: https://doi.org/10.1177%2F03611981211031888

Publication: Transportation Research Record: Journal of the Transportation Research Board

Publication Date: 2021

Summary:

With ongoing population growth and rapid development in cities, the demand for goods and services has seen a drastic increase. Consequently, transportation planners are searching for new ways to better manage the flow of traffic on existing facilities, and more efficiently utilize available and unused capacity. In this research, a lane management strategy that allows freight vehicles to use bus-only lanes is empirically evaluated in an urban setting. This paper presents an analysis of data that was collected to evaluate the operational impacts of the implementation of a freight and transit (FAT) lane, and to guide the development of future FAT lane projects by learning from the case study in Seattle, U.S. The video data was converted to vehicle counts, which were analyzed to understand the traffic impacts and used to construct a discrete choice model. The analysis shows that transit buses used the FAT lane 96% of the time, and authorizing trucks to use the lane did not affect that lane choice. Trucks used the FAT lane, but their utilization decreased with increasing numbers of buses in the FAT lane. Instead of higher rates of trucks, unauthorized vehicles, such as passenger cars and work vans, increasingly used the FAT lane during congestion. As a result of their differing schedule patterns, trucks and buses used the FAT lane at complementary times and trucks showed relatively low volumes in the FAT lane. Overall, the results are promising for a lane management strategy that may improve freight system performance without reducing transit service quality.

Authors: Şeyma GüneşDr. Anne GoodchildChelsea Greene, Venu Nemani

Recommended Citation:
Gunes, S., Goodchild, A., Greene, C., & Nemani, V. (2021). Evaluating Traffic Impacts of Permitting Trucks in Transit-Only Lanes. Transportation Research Record. https://doi.org/10.1177/03611981211031888

Paper

Impact of Transit Network Layout on Resident Mode Choice

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Publication: Mathematical Problems in Engineering

Volume: 4

Publication Date: 2013

Summary:

This study reviews the impact of public transit network layout (TNL) on resident mode choice. The review of TNL as a factor uses variables divided into three groups: a variable set without considering the TNL, one considering TNL from the zone level, and one considering TNL from the individual level. Using Baoding’s travel survey data, a Multinomial Logit (MNL) model is used, and the parameter estimation result shows that TNL has significant effect on resident mode choice. Based on parameter estimation, the factors affecting mode choice are further screened. The screened variable set is regarded as the input data to the BP neural network’s training and forecasting. Both forecasting results indicate that introducing TNL can improve the performance of mode choice forecasting.

Authors: Dr. Ed McCormack, Jian Gao, Peng Zhao, Chengxiang Zhuge, Hui Zhang

Recommended Citation:
Gao, J., Zhao, P., Zhuge, C., Zhang, H., & McCormack, E. D. (2013). Impact of Transit Network Layout on Resident Mode Choice. Mathematical Problems in Engineering, 2013.

Managing Increasing Demand for Curb Space in the City of the Future

This research aims to develop innovative methods for managing curb lane function and curb access. The rapid rise of autonomous vehicles (AV), on-demand transportation, and e-commerce goods deliveries, as well as increased cycling rates and transit use, is increasing demand for curb space resulting in competition between modes, failed goods deliveries, roadway and curbside congestion, and illegal parking.

The research findings will improve mobility by increasing the understanding of existing curb usage and provide new solutions to city officials, planners, and engineers responsible for managing this scarce resource in the future.

The research team will work closely with several cities in the PacTrans region to ensure the study’s relevance to their needs, and that the results will be broadly applicable for other cities.

This research will allow for the development of innovative curb space designs and ensure that our urban street system may operate more efficiently, safely, and reliably for both goods and people.