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

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.

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.

Technical Report

Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns

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URL: http://hdl.handle.net/1773/46655

Publication Date: 2020

Summary:

The rapid spread of COVID-19 pandemic in the U.S. spurred many state governments to take extensive actions for social distancing and issue stay-at-home orders to reduce the spread of the virus. Washington State and all other States in the PacTrans region have issued stay-at-home orders that include school closures, telecommuting, bars/restaurants closures, and group gathering bans, among others. These actions create significant changes to daily life and while some travel patterns will gradually restore by the end of outbreak, some may remain changed for a much longer period.

Behaviors that may see a lasting response include commuting, grocery shopping, business meetings, and even social interactions. Working from home for 2-3 months may change people’s attitudes toward telecommuting, and some may continue to do so a few days a week once the stay-at-home orders are lifted. Some employers may also shift their telecommute policies and provide/encourage working from home. In recent years, with the growth of e-commerce, many grocery stores had started to offer home deliveries; however, online grocery shopping experienced a fast and sudden boom during the pandemic. This has resulted in quick service adoption, and therefore some people may continue to do online grocery shopping once things go back to normal. Moreover, as people shift to online grocery shopping, they may proactively make a list and place orders less frequently compared to them going to store, resulting in fewer shopping trips. Some business meetings and even personal gatherings may also move online as people learn about and try alternate ways of communicating during the outbreak. Some may also consider enrolling in distant learning programs instead of attending in-person educational programs. There may also be significant changes in modes of travel. Some transit commuters may choose other modes of transportation for a while, and people may choose to drive or bike instead of taking a ride-hailing trip.

The goal of this research is to understand how COVID-19 disruption has affected people’s activity and travel patterns during the pandemic, and how these changes may persist in a post-pandemic era.

Authors: Dr. Andisheh Ranjbari, Parastoo Jabbari, Don MacKenzie

Recommended Citation:
Mackenzie D., Jabbari P., Ranjbari A. Analyzing the Long-Term Impacts of COVID-19 Disruption on Travel Patterns. Pacific Northwest Transportation Consortium (PacTrans). 2020. http://hdl.handle.net/1773/46655.

Paper

The Automated Driver as a New Road User

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URL: https://doi.org/10.1080/01441647.2020.1861124

Publication: Transport Reviews

Pages: 23-Jan

Publication Date: 2020

Summary:

Although road infrastructure has been designed to accommodate human drivers’ physiology and psychology for over a century, human error has always been the main cause of traffic accidents. Consequently, Advanced Driver Assistance Systems (ADAS) have been developed to mitigate human shortcomings. These automated functions are becoming more sophisticated allowing for Automated Driving Systems (ADS) to drive under an increasing number of road conditions. Due to this evolution, a new automated road user has become increasingly relevant for both road owners and the vehicle industry alike. While this automated driver is currently operating on roads designed for human drivers, in the future, infrastructure policies may be designed specifically to accommodate automated drivers. However, the current literature on ADSs does not cover all driving processes. A unified framework for human and automated driver, covering all driving processes, is therefore presented. The unified driving framework, based on theoretical models of human driving and robotics, highlights the importance of sensory input in all driving processes. How human and automated drivers sense their environment is therefore compared to uncover differences between the two road users relevant to adapt road design and maintenance to include the automated driver. The main differences identified between human and automated drivers are that (1) the automated driver has a much greater range of electromagnetic sensitivity and larger field of view, and (2) that the two road users interpret sensory input in different ways. Based on these findings, future research directions for road design and maintenance are suggested.

Authors: Dr. Ed McCormack, Ane Dalsnes Storsaeter, Kelly Pitera

Recommended Citation:
Storsæter, A. D., Pitera, K., & McCormack, E. D. (2020). The automated driver as a new road user. Transport Reviews, 1–23. https://doi.org/10.1080/01441647.2020.1861124

Paper

Bringing Alleys to Light: An Urban Freight Infrastructure Viewpoint

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URL: https://doi.org/10.1016/j.cities.2020.102847

Publication: Cities

Volume: 105

Publication Date: 2020

Summary:

There is growing pressure in cities to unlock the potential of every public infrastructure element as density and demand for urban resources increase. Despite their historical role as providing access to land uses for freight and servicing, alleys have not been studied as a resource in modern freight access planning.

The authors developed a replicable data collection method to build and maintain an alley inventory and operations study focused on commercial vehicles. A Seattle Case study showed that 40% of the urban center city blocks have an alley. 90% of those alleys are wide enough to accommodate only a single lane for commercial vehicles. 437 parking operations were recorded in seven alleys during business hours and found that all alleys were vacant 50% of the time.

This confirms that, in its alleys, Seattle has a valuable resource as both space for freight load/unload; and direct access to parking facilities and business entrances for commercial, private, and emergency response vehicles.

However, alley design features and the prevalence of parking facilities accessed through the alley may restrict the freight load/unload space in the alley. Future efforts should investigate how to better manage these infrastructures.

Authors: Dr. Anne GoodchildJosé Luis Machado LeónGabriela Girón-Valderrama

Recommended Citation:
Machado-León, Girón-Valderrama, G. del C., & Goodchild, A. (2020). Bringing Alleys to Light: An Urban Freight Infrastructure Viewpoint. Cities, 105. https://doi.org/10.1016/j.cities.2020.102847

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.

Paper

Analyzing the Effect of Autonomous Ridehailing on Transit Ridership: Competitor or Desirable First-/Last-Mile Connection?

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URL: https://doi.org/10.1177/03611981211025278

Publication: Transportation Research Record

Volume: 2675 (11)

Pages: 1154-1167

Publication Date: 2021

Summary:

Ridehailing services (e.g., Uber or Lyft) may serve as a substitute or a complement—or some combination thereof—to transit. Automation as an emerging technology is expected to further complicate the current complex relationship between transit and ridehailing. This paper aims to explore how US commuters’ stated willingness to ride transit is influenced by the price of ridehailing services and whether the service is provided by an autonomous vehicle. To that end, a stated preference survey was launched around the US to ask 1,500 commuters how they would choose their commute mode from among choices including their current mode and other conventional modes as well as asking them to choose between their current mode and an autonomous mode. Using a joint stated and revealed preference dataset, a mixed logit model was developed and analyzed.

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

Recommended Citation:
Khaloei, M., Ranjbari, A., Laberteaux, K., & MacKenzie, D. (2021). Analyzing the Effect of Autonomous Ridehailing on Transit Ridership: Competitor or Desirable First-/Last-Mile Connection? Transportation Research Record, 2675(11), 1154–1167. https://doi.org/10.1177/03611981211025278