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.
Rapid urban growth puts pressure on local governments to rethink how they manage street curb parking. Competition for space among road users and lack of adequate infrastructure force delivery drivers either to search for vacant spaces or to park in unsuitable areas, which negatively impacts road capacity and causes inconvenience to other users of the road.
The purpose of this paper is to advance research by providing data-based insight into what is actually happening at the curb. To achieve this objective, the research team developed and implemented a data collection method to quantify the usage of curb space in the densest urban area of Seattle, Center City.
This study captures the parking behavior of commercial vehicles everywhere along the block face as well as the parking activities of all vehicles (including passenger vehicles) in commercial vehicle loading zones. Based on the empirical findings, important characteristics of Seattle’s urban freight parking operations are described, including a detailed classification of vehicle types, dwell time distribution, and choice of curb use for parking (e.g., authorized and unauthorized spaces). The relationship between land use and commercial vehicle parking operations at the curb is discussed. Seattle’s parking management initiatives will benefit from the insights into current behavior gained from this research.
Rapid urban growth, increasing demand, and higher customer expectations have amplified the challenges of urban freight movement. Finding an adequate space to park can be a major challenge in urban areas. For commercial vehicles used for freight transportation and provision of services, the lack of parking spaces and parking policies that recognize those vehicles’ unique needs can have negative impacts that affect all users of the road, particularly the drivers of these commercial vehicles (1–4).
The curb is an important part of the public right-of-way. It provides a space for vehicles to park on-street; for delivery vehicles (i.e., cargo bikes, cargo vans, and trucks), in particular, it also provides a dedicated space for the loading and unloading of goods close to destinations. Hence it is a key asset for urban freight transportation planning which local governments can administer to support delivery and collection of goods.
According to Marcucci et al. (5), the development of sustainable management policies for urban logistics should be based on site-specific data given the heterogeneity and complexity of urban freight systems. Current loading/unloading parking policies include time restrictions, duration, pricing, space management, and enforcement (6, 7). However, as Marcucci et al. pointed out after an extensive review of the literature on freight parking policy, the quantification of commercial vehicle operations on the curb to inform policy decision making is nonexistent (5). Therefore, local governments often lack data about the current usage of the curb and parking infrastructure, which is necessary to evaluate and establish these policies and therefore make well-informed decisions regarding freight planning, especially in dense, constrained urban areas.
Given the importance of the curb as an essential piece of the load/unload infrastructure, this paper investigates what is actually happening at the curb, developing an evidence-based understanding of the current use of this infrastructure. The research team developed and applied a systematic data collection method resulting in empirical findings about the usage of public parking for loading and unloading operations in the Seattle downtown area.
This research documents and analyzes the parking patterns of commercial vehicles (i.e., delivery, service, waste management, and construction vehicles) in the area around five prototype buildings located in the Center City area. The results of this research will help to develop and inform parking management initiatives.
The paper includes four sections in addition to this introduction. The second section discusses previous freight parking studies and the existing freight parking policies in cities, and explores which of these approaches are being used in Seattle. The third section proposes a data collection method to document freight-related parking operations at the curb though direct observations. The fourth section provides empirical findings from data collection in Seattle. The fifth and last section includes a discussion of the findings and concluding remarks.
Community resilience depends on the resilience of the lifeline infrastructure and the performance of the disaster-related functions of local governments. State and federal resilience plans and guidelines acknowledge the importance of the transportation system as a critical lifeline in planning for community resilience and in helping local governments to set recovery goals. However, a widely accepted definition of the resilience of the transportation system and a structure for its measurement are not available. This paper provides a literature review that summarizes the metrics used to assess the resilience of the transportation system and a categorization of the assessment approaches at three levels of analysis (the asset, network, and systems levels). Furthermore, this paper ties these metrics to relevant dimensions of community resilience. This work addresses a key first step required to enhance the efficiency of planning related to transportation system resilience by providing (a) a standard terminology with which efforts to enhance the resilience of the transportation system can be developed, (b) an approach to organize planning and research efforts related to the resilience of the transportation system, and (c) identification of the gaps in measurement of the performance of the resilience of the transportation system.
This paper quantifies the benefits to drayage trucks and container terminals from a data-sharing strategy designed to improve operations at the drayage truck-container terminal interface. This paper proposes a simple rule for using truck information to reduce container rehandling work and suggests a method for evaluating yard crane productivity and truck transaction time. Various scenarios with different levels of information quality are considered to explore how information quality affects system efficiency (i.e., truck wait time and yard crane productivity). Different block configurations and truck arrival rates are also investigated to evaluate the effectiveness of truck information under various system configurations. The research demonstrates that a small amount of truck information can significantly improve crane productivity and reduce truck delay, especially for those terminals operating near capacity or using intensive container stacking, and that complete truck arrival sequence information is not necessary for system improvement.
A number of trucking companies use Global Positioning System (GPS) devices for fleet management. Data extracted from these devices can provide valuable traffic information such as spot (instantaneous) speeds and vehicle trajectory. However, the accuracy of GPS spot speeds has not been fully explored, and there is concern about their use for estimating truck travel speed. This concern was addressed by initially comparing GPS spot speeds with speeds estimated from dual-loop detectors. A simple speed estimation method based on GPS spot speeds was devised to estimate link travel speed, and that method was compared with space mean speed estimation based on GPS vehicle location and time data. The analysis demonstrated that aggregated GPS spot speeds generally matched loop detector speeds and captured travel conditions over time and space. Speed estimation based on GPS spot speeds was sufficiently accurate in comparison with space mean speeds, with a mean absolute difference of less than 6%. It is concluded that GPS spot speed data provide an alternative for measuring freight corridor performance and truck travel characteristics.
Variable service times at vehicle processing facilities (borders, weigh stations, landside marine port gates) cause transportation planning challenges for companies that regularly visit them. Companies must either build more time into their schedules than is necessary, and therefore underutilize their equipment, or risk missing delivery windows or exceeding hours of service regulations, actions that can result in fines, lost business opportunities, or other logistical costs. Border crossing times are examined at Blaine, Washington, between Whatcom County, Washington, and the Lower Mainland of British Columbia, Canada, to assess the variability in crossing times at this border crossing and the impact of this variability on regional supply chains. Variability data collected for bidirectional trade are presented. Directional, daily, hourly, and seasonal variations are examined, and interviews are conducted with regional carriers to better understand the current response to variability, the benefit of a reduction in variability, and how that is related to the goods moved or to other business operating characteristics. This paper describes the level of variability in border crossing times and carriers’ responses to this variability and shows that the primary strategy used, increasing buffer times, reduces carrier productivity. However, this cost is negligible because of the current nature of the industry.
We utilize an unsupervised learning algorithm called-modes clustering (Huang 1998), which is similar to the better-known-means method (Hartigan and Wong 1979), but with a dissimilarity measure designed for categorical variables (Cao et al. 2012), originally developed for analyzing sequential categorical data such as gene sequences (Goodall 1966), but also amenable to curb zoning types. For a specified, the-modes algorithm finds the top vectors that minimize a distance to all sample vectors in the training dataset. The resulting top modes are representative of distinct clusters of sample vectors, with cluster membership determined by the closest mode. The parameter is chosen through cross-validation by holding out portions of the available training data and finding the smallest that largely minimizes the within-cluster variation in this hold-out set (also called the “elbow method”). We utilize basic matching dissimilarity, as implemented in (Vos 2015). For two vectors and of length, where each element attains categorical values, matching dissimilarity is defined as, where denotes the indicator vector, with value 1 where the bracketed condition is true and 0 otherwise. We’ve chosen this measure of dissimilarity between two sets of categorical variables for a number of reasons: 1) its simplicity, 2) successful use in categorical data clustering (Goodall 1966), and 3) its sensitivity to the ordering of values when vectors and are ordered, specific to how we have chosen to represent curb zoning data.
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.
Delivery options have become very diverse with online shoppers demanding faster delivery options (e.g, 2-day delivery, same day delivery options) and more personalized services. For this reason, transportation planners, retailers, and delivery companies are seeking ways to better understand how best to deliver goods and services in urban areas while minimizing disruption to traffic, parking, and building operations. This includes understanding vertical and horizontal goods movements within urban areas.
The goal of this project is to capture the delivery processes within urban buildings in order to minimize these disruptions. This is achieved using a systems approach to understanding the flow of activities and workers as they deliver goods within urban buildings. A mobile application was designed to collect the start and stop times for each task within the delivery process for 31 carriers as they deliver goods within a 62-story office building.
The process flow map helped identify bottlenecks and areas for improvements in the final segment of the delivery operations: the final 50 feet. It also highlighted consistent tasks conducted by all carriers as well as differences with given carrier type. This information is useful to help decision-makers plan appropriately for the design of future cities that encompass a variety of delivery processes.