Chapter

Are Cities’ Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations

URL: https://doi.org/10.1002/9781119425526.ch21

Publication: City Logistics 2: Modeling and Planning Initiatives (Proceedings of the 2017 International Conference on City Logistics)

Volume: 2

Pages: 351-368

Publication Date: 2018

Summary:

Two converging trends – the rise of e‐commerce and urban population growth – challenge cities facing competing uses for road, curb and alley space. The University of Washington has formed a living Urban Freight Lab to solve city logistics problems that cross private and public sector boundaries. To assess the capacity of the city’s truck load/unload spaces, the lab collected GIS coordinates for private truck loading bays, and combined them with public GIS layers to create a comprehensive map of the city’s truck parking infrastructure. The chapter offers a practical approach to identify useful existent urban GIS data for little or no cost; collect original granular urban truck data for private freight bays and loading docks; and overlay the existing GIS layers and a new layer to study city‐wide truck parking capacity. The Urban Freight Lab’s first research project is addressing the “Final 50 Feet” of the urban delivery system.

Authors: Barbara IvanovDr. Ed McCormackDr. Anne GoodchildJosé Luis Machado LeónGabriela Girón-Valderrama, Anne Moudon, Jason Scully

Recommended Citation:
Goodchild, Anne, Barb Ivanov, Ed McCormack, Anne Moudon, Jason Scully, José Machado Leon, and Gabriela Giron Valderrama. Are Cities' Delivery Spaces in the Right Places? Mapping Truck Load/Unload Locations: Modeling and Planning Initiatives. City Logistics 2: Modeling and Planning Initiatives (2018): 351-368. 10.1002/9781119425526.ch21

The Final 50 Feet of the Urban Goods Delivery System: Documenting Loading Bays, Demonstrating Parcel Lockers’ Proof of Concept & Tracking Curb Use in Seattle’s Interconnected Load/Unload Network (Task Order 2)

Part of the Final 50 Feet Research Program, this project contains: a curb occupancy study, a survey of First and Capitol Hill Loading Bays, a pilot test at Seattle Municipal Tower, and the development of a toolkit.

Private Loading Bays and Docks Inventory Study

Taken together with the Urban Freight Lab’s earlier private infrastructure inventory (Seattle Center City Alley Infrastructure Inventory and Occupancy Study 2018) in Downtown Seattle, Uptown, and South Lake Union, this report finalizes the creation of a comprehensive Center City inventory of private loading/unloading infrastructure.

To the research team’s knowledge, Seattle is the first city to maintain a database with the location and features of private loading/unloading infrastructure (meaning, out of the public right of way). This matters because these facilities are privately owned and managed, cities lack information about them—information critical to urban planning. The private infrastructure has been a missing piece of the urban freight management puzzle. The work in this report helps complete that puzzle and advance efforts to make urban freight delivery more efficient in increasingly dense, constrained cities, such as Seattle.

Key Findings from Private Loading Bays and Docks Inventory

Data collectors in this study identified, examined, and collected key data on 92 private loading docks, bays and areas across 421 city blocks in the neighborhoods of Capitol Hill, First Hill, and a small segment of the International District east of I-5. The earlier inventory in Downtown Seattle, Uptown, and South Lake Union had proportionally more than twice the density of private infrastructure of Capitol Hill and First Hill documented in this report. This finding is unsurprising. While all the inventoried neighborhoods are in the broad Center City area, they are fundamentally different neighborhoods with different built environments, land use, and density. Variable demand for private infrastructure—and the resulting supply—stems from those differences.

Researchers found that a trust relationship with the private sector is essential to reduce uncertainty in this type of work. UPS’ collaboration helped reduce uncertainty in the total inventory from 33% to less than 1%.

Curb Occupancy Study

This study gives the city on-the-ground data on the current use and operational capacity of the curb for commercial vehicles, documenting vehicle parking behavior in a three-by-three city block grid around each of five prototype Center City buildings: a hotel, a high-rise office building, an historical building, a retail center, and a residential tower. These buildings were intentionally chosen to deepen the city’s understanding of the Center City; they were part of UFL’s earlier SDOT-sponsored research tracking how goods move vertically within a building in the Final 50 Feet of the goods delivery system.

Significantly, this study captured the parking behavior of commercial vehicles everywhere along the curb as well as the parking activities of all vehicles (including passenger vehicles) in commercial vehicle loading zones (CVLZs.) The research team documented: (1) which types of vehicles parked in CVLZs and for how long, and; (2) how long commercial vehicles (CVs) parked in CVLZs, in metered parking, and in passenger load zones (PLZ) and other unauthorized spaces. (Passenger vehicles in this study were not treated as commercial vehicles, due to challenges in systematically identifying whether passenger vehicles were making deliveries or otherwise carrying a commercial permit.)

Key Findings from Curb Occupancy Study

Commercial and passenger vehicle drivers use CVLZs and PLZs fluidly: commercial vehicles are parking in PLZs and passenger vehicles are parking in CVLZs.
Most commercial vehicle (CV) demand is for short-term parking: 15 or 30 minutes.
Thirty-six percent of the total CVs parked along the curb were service CVs, showing the importance of factoring their behavior and future demand into urban parking schemes.
Forty-one percent of commercial vehicles parked in unauthorized locations. But a much higher percentage parked in unauthorized areas near the two retail centers (55% – 65%) when compared to the predominantly office and residential areas (27% – 30%). The research team found that curb parking behavior is associated with granular, building-level urban land use. This occurred even as other factors such as the total number, length and ratio of CVLZs versus PLZs varied widely across the five study areas.

Seattle Municipal Tower Common Carrier Locker Pilot

The UFL’s 2017 research (The Final 50 Feet Urban Goods Delivery System Research Scan and Data Collection Project) documented that of the 20 total minutes delivery drivers spent on average in the 62-story Seattle Municipal Tower, 12.2 of those minutes were spent going floor-to-floor in freight elevators and door-to-door to tenants on multiple floors. The UFL recognized that cutting those two steps from the delivery process could slash delivery time in the Tower by more than half—which would translate into a substantial reduction in truck dwell time.

This report provides compelling evidence of the effectiveness of a new urban goods delivery system strategy: common carrier lockers that create parcel delivery density and provide secure delivery locations in public spaces. Parcel lockers are widely available secure, automated, self-service storage systems that are typically owned by a single retailer or delivery firm and placed inside private property. In contrast, common carrier lockers are open to multiple retailers and delivery carriers. This pilot, which placed a common carrier locker system in the 62-floor Seattle Municipal Tower for ten days in spring 2018, was intentionally carried out in a public space.

Key Findings from Seattle Municipal Tower Common Carrier Locker Pilot

The common carrier locker both reduced total delivery time by 78% when compared to traditional floor-to-floor, door-to-door delivery method and cut the number of failed first parcel deliveries to zero.

Paper

Urban Delivery Company Needs and Preferences for Green Loading Zones Implementation: A Case Study of NYC

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URL: https://doi.org/10.1061/9780784484340.030

Publication: Proceedings of American Society of Civil Engineers (ASCE) Transportation and Development Conference 2022: Transportation Planning and Workforce Development

Publication Date: 2022

Summary:

(This project is part of the Urban Freight Lab’s Technical Assistance Program, where UFL contributes to the project by providing 1:1 match funds in terms of staff and/or research assistants to complete project tasks.)

Green Loading Zones (GLZs) are curb spaces dedicated to the use of electric or alternative fuel (“green”) delivery vehicles. Some U.S. cities have begun piloting GLZs to incentivize companies to purchase and operate more green vehicles. However, there are several questions to be answered prior to a GLZ implementation, including siting, potential users and their willingness to pay. We reviewed best practices for GLZs around the world, and surveyed goods delivery companies operating in New York City to collect such information for a future GLZ pilot. The findings suggest the best candidate locations are areas where companies are currently subject to the most parking fines and double parking. Companies expressed willingness to pay for GLZs, as long as deploying green vehicles in the city can offset other cost exposures. Respondents also selected several single-space GLZs spread throughout a neighborhood as the preferred layout.

Authors: Thomas MaxnerNota GoulianouDr. Andisheh RanjbariDr. Anne Goodchild

Recommended Citation:
Maxner, T., Goulianou, P., Ranjbari, A., and Goodchild, A. (2022). "Studying Urban Delivery Company Needs and Preferences for Green Loading Zones Implementation: A Case Study of NYC", In Proceedings of ASCE Transportation and Development Conference (Forthcoming), Seattle, WA.

Dynamically Managed Curb Space Pilot

Transportation Network Company (TNC) usage in Seattle has been increasing every quarter since 2015 when the City of Seattle Department of Transportation (SDOT) began collecting data. TNC trips exceeded 20 million in 2017, a 46% increase from total reported trips in 2016. This has led to concerns about congestion and pedestrian safety as cars and people take risks to connect at the curb and in the right-of-way. By providing additional curb capacity through increased passenger loading zones and directing customers via in-app messaging, the City may be able to reduce congestion and unsafe vehicle/people movements during peak traffic and late-night hours.

Other cities have attempted to study the impacts of increased usage of passenger loading zones (e.g., San Francisco, Washington D.C.), with varying success, but no standard methodology exists for cities to assess the potential for reallocated curb space and the subsequent impacts of those changes. SDOT is taking a data-driven approach to curb reallocation and traffic network impacts, modeling the work SDOT has done to quantify demand in paid parking areas and set rates accordingly. The main goals of this pilot are three-fold: increase pedestrian safety, minimize congestion impacts on the larger transportation network, and build a scalable methodology for assessment and implementation of curb allocation to accommodate this new mobility service.

The Supply Chain Transportation & Logistics Center and SDOT will work in collaboration with employers, transit operators, and TNCs to test a variety of strategies to mitigate the traffic impacts of TNC pick-ups on the greater transportation network and improve safety for passengers and drivers. Strategies include increasing the number of passenger loading zones in high-traffic pick-up areas and geofenced pick-up or black-out areas. Curb and street use data will be collected under each alternative and compared to baseline data.

Report

NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research

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Publication Date: 2022

Summary:

In an effort to reduce emissions from last-mile deliveries and incentivize green vehicle adoption, The New York City Department of Transportation (NYC DOT) is seeking to implement a Green Loading Zone (GLZ) pilot program. A Green Loading Zone is curb space designated for the sole use of “green” vehicles, which could include electric and alternative fuel vehicles as well as other zero-emission delivery modes like electric-assist cargo bikes. To inform decisions about the program’s siting and regulations, this study was conducted by the University of Washington’s Urban Freight Lab (UFL) in collaboration with NYC DOT under the UFL’s Technical Assistance Program.

The study consists of three sources of information, focusing primarily on input from potential GLZ users, i.e., delivery companies. An online survey of these stakeholders was conducted, garnering 13 responses from 8 types of companies. Interviews were conducted with a parcel carrier and an electric vehicle manufacturer. Additionally, similar programs from around the world were researched to help identify current practices. The major findings are summarized below, followed by recommendations for siting, usage restriction and pricing of GLZs. It is important to note that these recommendations are based on the survey and interview findings and thus on benefits to delivery companies. However, other important factors such as environmental justice, land use patterns, and budgetary constraints should be considered when implementing GLZs.

Literature Review Findings

Green Loading Zones are a relatively novel approach to incentivizing electric vehicle (EV) adoption. Two relevant pilot programs exist in the United States, one in Santa Monica, CA and the other one in Los Angeles, CA. Both are “zero-emission” delivery programs, meaning alternative fuel vehicles that reduce emissions (compared to fossil fuel vehicles) are not included in the pilot’s parking benefits (dedicated spaces and free parking). Other cities including Washington, DC and Vancouver, Canada are also creating truck-only zones and dedicating parking to EVs in their efforts to reduce emissions. Bremen, Germany also has a similar program called an Environmental Loading Point.

Many cities in Europe are implementing low- or zero-emission zones. These are different than GLZs in that entire cities or sections of cities are restricted to vehicles that meet certain emissions criteria. London, Paris, and 13 Dutch municipalities are all implementing low-emission zones. These zones have achieved some success in reducing greenhouse gas emissions: in London, CO2 from vehicles has been reduced by 13 percent. Companies operating in those cities have opted to purchase cleaner vehicles or to replace trucks with alternative modes like cargo bikes. In addition to demonstrating similar goals as NYC DOT, these programs provide insights to the siting and structure of GLZs. Loading zones have been selected based on equity concerns, delivery demand, and commercial density. Every city in the literature review has installed specific signage for the programs to clearly convey the regulations involved.

Survey and interview Findings

A range of company types replied to the survey: parcel carriers (large shippers), small shippers, e-commerce and retail companies, freight distributors, a truck dealer, a liquid fuel delivery company, and a logistics NYC association (answering on behalf of members). The majority of these companies will be increasing their fleet sizes over the next ten years, and most plan to increase the share of EVs in their fleets while doing so. A smaller share (4 of 13) also plans to increase their share of alternative fuel vehicles. The most cited reasons for increasing fleet size and green vehicle share are: 1) internal sustainability goals, 2) social responsibility, and 3) new vehicles/models coming to the market.

Green vehicle adoption is not without its challenges. For EV adoption specifically, companies identified three major barriers: 1) competition in the EV market, 2) electric grid requirements upstream of company-owned facilities, and 3) lack of adequate government-supported purchasing subsidies. To overcome these barriers, respondents would like larger or more government purchasing incentives and reduced toll or parking rates for EVs. However, the majority of companies also expressed a willingness to pay for GLZs at similar rates to other commercial loading zones.

As for area coverage, all respondents deliver to Manhattan, Queens, and Brooklyn. 11 of 13 deliver to Staten Island and the Bronx as well. All EV and cargo bike operators deliver to Manhattan, whereas only one EV operator and one cargo bike operator deliver to all five boroughs of NYC. Respondents deliver at all times of day, but the busiest times are between 9:00AM and 4:00PM (stated by 8 of 13 respondents). Peak periods are busiest for four companies in the morning (6:00AM-9:00AM) and six companies in the evening (4:00PM-9:00PM).

The interviews supported findings from the survey. Both interviewed companies have a vested interest in reducing their environmental footprint and plan to use or produce exclusively zero-emission vehicles by 2050 (carrier) or 2035 (manufacturer). However, they noted challenges to electrifying entire fleets for cities. Charging infrastructure needs to be expanded, but incentives are also needed (parking benefits, subsidies, expedited permitting) to make the market viable for many delivery companies.

Recommendations

The preceding findings informed four key recommendations:

GLZs should be made available to multiple modes: green vehicles and cargo bikes. Adequate curb space might be needed to accommodate multiple step-side vans plus a small vehicle and cargo bikes, but this should be balanced against curb utilization rates and anticipated dwell times to maximize curb use.
Explore piloting GLZs in Lower Manhattan and commercial areas of Midtown Manhattan; they could be the most beneficial locations for the pilot according to survey respondents.
The preferred layout for GLZs is several spaces distributed across multiple blocks.
DOT can charge for the GLZ use. It is recommended that rates not exceed current parking prices in the selected neighborhood, but some companies are willing to pay a modest increase over that rate to avoid parking tickets.

Authors: Thomas MaxnerNota GoulianouDr. Andisheh RanjbariDr. Anne Goodchild

Recommended Citation:
Urban Freight Lab (2022). NYC Zero-Emissions Urban Freight and Green Loading Zones Market Research.

Technology Integration to Gain Commercial Efficiency for the Urban Goods Delivery System, Meet Future Demand for City Passenger and Delivery Load/Unload Spaces, and Reduce Energy Consumption

The Urban Freight Lab (UFL) received $1.5 million in funding from the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (DOE EERE) to undertake work to help goods delivery drivers find a place to park without driving around the block in crowded cities for hours, wasting time and fuel and adding to congestion. The project partners will integrate sensor technologies, develop data platforms to process large data streams, and publish a prototype app to let delivery drivers know when a parking space is open – and when it’s predicted to be open so they can plan to arrive when another truck is leaving.

The UFL will also pilot test common carrier locker systems in public and private load/unload spaces near transit stops. Transit riders, downtown workers, and residents will be able to pick up packages they ordered online from any retailer in a convenient and secure locker in a public plaza or outside their office. The benefits don’t stop there. Common carrier lockers create delivery density that increases the productivity of parking spaces and provides significant commercial efficiencies. They do this by reducing the amount of time it takes delivery people to complete their work. The driver parks next to the locker system, loads packages into it, and returns to the truck. When delivery people spend less time going door-to-door, it decreases the time their truck needs to be parked, increasing turnover and adding parking capacity in crowded cities.

This is a timely project as cities are looking for new strategies to accommodate the rapid growth of e-commerce. Online shopping has grown by 15% annually for the past 11 years, and is now 9% of total retail sales in the U.S., with $453.5 billion in revenue in 2017. Many online shoppers want the goods delivery system to bring them whatever they want, where they want it, in one to two hours. At the same time, many cities are replacing goods delivery load/unload spaces with transit and bike lanes. Cities need new load/unload space concepts supported by technology to make the leap to autonomous cars and trucks in the street, and autonomous freight vehicles in the Final 50 Feet of the goods delivery system. The Final 50 feet segment starts when a truck parks in a load/unload space, and includes delivery persons’ activities as they maneuver goods along sidewalks and into urban towers to make their deliveries.

The goals of this project are to:

Reduce parking seeking behavior by 20% in the pilot test area by returning current and predicted load/unload space occupancy information to users on a web-based and/or mobile platform to inform real-time parking decisions.
Reduce parcel truck dwell time in pilot test area locations by 30%, thereby increasing productivity of load/unload spaces near common carrier locker systems.
Increase network and commercial firms’ efficiency by increasing curb and alley space occupancy rates, and underutilized private loading bay occupancy in the p.m. peak, in the pilot test area.

Cost-share partnering organizations are:

Seattle Department of Transportation
Bellevue Department of Transportation
CBRE Seattle
King County Metro Transit
Kroger Company
Puget Sound Clean Air Agency
Sound Transit

Members of the UFL are also participating in the project. Pacific National National Laboratory (PNNL) is a partner, completing several of the project tasks.

Technical Report

Transit Corridor Study

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URL: https://mic.comotion.uw.edu/wp-content/uploads/2021/07/TransitCorridorStudy_InterimReport_June2021.pdf

Publication Date: 2021

Summary:

This study is sponsored by Amazon, Bellevue Transportation department, Challenge Seattle, King County Metro, Seattle Department of Transportation, Sound Transit, and Uber, with support from the Mobility Innovation Center at UW CoMotion.

Population and extended economic growth in many Seattle neighborhoods are driving increased demand for private car travel along with transportation services such as ridehailing and on-demand delivery. Together, these trends are adding to existing demand for loading and unloading operations throughout the city, and exacerbating traffic congestion. Anecdotal evidence indicates that passenger/delivery vehicle stops at or next to transit stops can interfere with bus operations, causing longer or more volatile delays. The increased travel times and reduced reliability further erode the attractiveness of transit to travelers. Thus, it is important to understand how transit, ridehailing, and goods delivery vehicles interact in terms of both operations and travel demand.

This project focuses on the analysis of open-source transit data to screen for locations with slow and/or unreliable bus travel times, and couple that data with interference observation, environmental, and traffic-related data to potentially predict the likely causes. We have developed tools to identify transit corridors with high levels of interference from other road users, including passenger cars, ridehailing vehicles and goods delivery vehicles. These tools are applied to transit corridors in Seattle and Bellevue, and methods have been developed to identify likely sources of interference from available data.

We drew on multiple data sources for identifying high-interference corridors in the region, including:

a virtual workshop with participants from beneficiary agencies and stakeholders to solicit input;
an online crowdsourcing survey to engage the community and gather feedback from all road users;
route-level ridership data from King County Metro; and
aggregated pick-up/drop-off data on ridehailing activities from SharedStreets.

Data was consolidated and 10 corridors were selected based on their likelihood of containing interference between buses and other road users, transit ridership levels, and stakeholder and community feedback.

In addition, we have developed a tool for identifying corridors with slow and/or unreliable bus travel times from open-source real-time transit data. We implemented a pipeline for ingesting and analyzing King County Metro’s real-time Generalized Transit Feed Specification data (GTFS-RT) at 10-second intervals. Using this pipeline, active bus coordinate and schedule adherence data has been scraped and stored to an Amazon Web Services (AWS) server since September 2020. We developed efficient methods to aggregate tracked bus locations and assign them to roadway segments, and quantified delays in terms of schedule deviation and ratio of median to free-flow speeds, among other metrics. We have developed a web based visualization tool to display this data, and it is being updated daily with aggregated performance metrics from our database.

To collect ground truth validation data along selected corridors, we implemented an online data collection tool for field observations, and recruited research assistants to observe bus operations along the study corridors and record information on bus traversals and instances of interference. This dataset is analyzed alongside the GTFS-RT data, environmental, and traffic related data to identify instances of delay and predict the likely causes.

Field data was collected for three weeks along eight of the selected corridors in March 2021, but was later paused due to depressed levels of transportation activity during the COVID-19 pandemic and the current unstable condition of travel choices and city traffic (and thus interferences). Preliminary analysis on the collected data revealed that there is not a substantial effect shown in the GTFS-RT data when a bus is interfered with; however, there were not a lot of interference observations in the collected field data. So, it remains to be seen whether the lack of an identifiable effect is due to the lack of ground truth data, lack of precision in the automatic vehicle location system, or the relatively low impact of an interference when compared to the effects of general traffic congestion, signals, and other roadway conditions. A linear regression model was also generated to determine the extent to which roadway characteristics can predict segment performance, which produced mildly predictive results.

As businesses and transit services continue to reopen, there will likely be an increase in the amount of transit interference experienced between buses and other roadway users, which will potentially allow for the gathering of more ground truth validation data. Field observations will resume in late Summer/early Fall 2021 and will continue until enough data is collected to either (1) model connections between observed interference and bus delays in the GTFS-RT data; or (2) determine whether significant delays cannot be linked to observed instances of interference in the study corridors. The GTFS-RT data scraping will continue daily, and summarized in the developed interactive visualization tool.

The major anticipated benefits of the project can be summarized as follows:

This work will help identify network-wide road and route segments with slow and/or unreliable bus travel times. We may also be able to identify main causes of delay in the study corridors.
Moreover, we expect that this work will generate reusable analytical tools that can be applied by local agencies on an ongoing basis, and by other researchers and transportation agencies in their own jurisdictions.
The outcomes of this work will enable identifying corridors with slow and/or unreliable bus travel times as candidates for specific countermeasures to increase transit performance, such as increased enforcement, modified curb use rules, or preferential bus or street use treatments. Targeting such countermeasures towards priority locations will result in faster and more reliable bus operations, and a more efficient transportation network at a lower cost to transit agencies.

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

Paper

An Empirical Analysis of Passenger Vehicle Dwell Time and Curb Management Strategies for Ride-Hailing Pick-Up/Drop-Off Operations

URL: https://doi.org/10.1007/s11116-023-10380-6

Publication: Transportation

Publication Date: 2023

Summary:

With the dramatic and recent growth in demand for curbside pick-up and drop-off by ride-hailing services, as well as online shopping and associated deliveries, balancing the needs of roadway users is increasingly critical. Local governments lack tools to evaluate the impacts of curb management strategies that prioritize different users’ needs. The dwell time of passenger vehicles picking up/dropping off (PUDO) passengers, including ride-hailing vehicles, taxis, and other cars, is a vital metric for curb management, but little is understood about the key factors that affect it. This research used a hazard-based duration modeling approach to describe the PUDO dwell times of over 6,000 passenger vehicles conducted in Seattle, Wash. Additionally, a before-after study approach was used to assess the effects of two curb management strategies: adding PUDO zones and geofencing. Results showed that the number of passenger maneuvers, location and time of day, and traffic and operation management factors significantly affected PUDO dwell times. PUDO operations took longer with more passengers, pick-ups (as opposed to drop-offs), vehicle´s trunk access, curbside stops, and in the afternoon. More vehicles at the curb and in adjacent travel lanes were found to be related to shorter PUDO dwell times but with a less practical significance. Ride-hailing vehicles tended to spend less time conducting PUDOs than other passenger vehicles and taxis. Adding PUDO zones, together with geofencing, was found to be related to faster PUDO operations at the curb. Suggestions are made for the future design of curb management strategies to accommodate ride-hailing operations.

Authors: José Luis Machado LeónDr. Anne Goodchild, Don MacKenzie (University of Washington College of Engineering)

Recommended Citation:
Machado-León, J.L., MacKenzie, D. & Goodchild, A. An Empirical Analysis of Passenger Vehicle Dwell Time and Curb Management Strategies for Ride-Hailing Pick-Up/Drop-Off Operations. Transportation (2023). https://doi.org/10.1007/s11116-023-10380-6

Paper

Curbspace Management Challenges and Opportunities from Public and Private Sector Perspectives

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URL: https://journals.sagepub.com/doi/10.1177/03611981211027156

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

Publication Date: 2021

Summary:

Through structured interviews with public agency and private company staff and a review of existing pilot project evaluations and curb management guidelines, this study surveys contemporary approaches to curb space management in 14 U.S. cities and documents the challenges and opportunities associated with them. A total of 17 public agencies (including public works departments, transportation agencies, and metropolitan planning organizations) in every census region of the U.S. and 10 technology companies were interviewed.

The results show that the top curb management concerns among public officials are enforcement and communication, data collection and management, and interagency coordination. Interviewees reported success with policies such as allocating zones for passenger pick-ups and drop-offs, incentives for off-peak delivery, and requiring data sharing in exchange for reservable or additional curb spaces. Technology company representatives discussed new tools and technologies for curb management, including smart parking reservation systems, occupancy sensors and cameras, and automated enforcement. Both public and private sector staff expressed a desire for citywide policy goals around curb management, more consistent curb regulations across jurisdictions, and a common data standard for encoding curb information.

Authors: Caleb DiehlDr. Andisheh RanjbariDr. Anne Goodchild

Recommended Citation:
Diehl, C., Ranjbari, A., & Goodchild, A. (2021). Curbspace Management Challenges and Opportunities from Public and Private Sector Perspectives. Transportation Research Record. https://doi.org/10.1177/03611981211027156

Special Issue

The Curb Lane

URL: https://www.sciencedirect.com/journal/transportation-research-part-a-policy-and-practice/special-issue/10F7Q5183NN

Publication: Transportation Research Part A: Policy and Practice

Publication Date: 2021

Summary:

Efforts to regulate the curb also suffer from a lack of publicly accessible data on both the demand and supply of curb space. Cities often do not have the technical expertise to develop a curb data collection and data-sharing strategy. In addition, the private individuals and companies that generate most of the curb-use data often withhold them from public use to protect proprietary information and personal user data.

However, new uses of data sources, such as the Global Positioning System (GPS) and cellular networks, as well as the implementation of wide networks of IoT devices, are enabling the “digitization” of the curb, allowing cities to gain a better understanding of curb use as well as ways to change their approach toward curb space management.

In a way, the revolution in curb space management has already started. Many cities are re-inventing their role from passively regulating on-street parking to dynamically allocating and managing the curb, both physically and digitally, to serve many different users. Geofencing and time-dependent allocation of curb space facilitate efficient passenger pickup and drop off. Parking information systems and pay-for-parking apps enable dynamic parking allocation and pricing. We believe this is the right time for scientific research to “catch up” with current changes and to develop new analytical tools for curb space management. Such efforts are the focus of this special issue on curb lane analysis and policy.

Authors: Dr. Anne GoodchildDr. Giacomo Dalla ChiaraDr. Andisheh Ranjbari, Susan Shaheen (University of California, Berkeley), Donald Shoup (UCLA)

Recommended Citation:
Special Issue: The Curb Lane. Transportation Research Part A: Policy and Practice | ScienceDirect.com by Elsevier.