Skip to content
Paper

Commercial Vehicle Driver Behaviors and Decision Making: Lessons Learned from Urban Ridealongs

 
Download PDF  (0.79 MB)
Publication:  Transportation Research Record: Journal of the Transportation Research Board
Volume: 2675 (9)
Pages: 608-619
Publication Date: 2021
Summary:

As ecommerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliveries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experience in making deliveries.

In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles with global positioning system devices.

The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times.

We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other commercial drivers.

The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

In recent years, cities have changed their approach toward managing urban freight vehicles. Passive regulations, such as limiting delivery vehicles’ road and curb use to given time windows or areas have been replaced by active management through designing policies for deploying more commercial vehicle (CV) load zones, pay-per-use load zone pricing, curb reservations, and parking information systems. The goal is to reduce the negative externalities produced by urban freight vehicles, such as noise and emissions, traffic congestion, and unauthorized parking, while guaranteeing goods flow in dense urban areas. To accomplish this goal, planners need to have an understanding of the fundamental parking decision-making process and behaviors of CV drivers.

Two main difficulties are encountered when CV driver behaviors are analyzed. First, freight movement in urban areas is a very heterogeneous phenomenon. Drivers face numerous challenges and have to adopt different travel and parking behaviors to navigate the complex urban network and perform deliveries and pick-ups. Therefore, researchers and policy makers find it harder to identify common behaviors and responses to policy actions for freight vehicles than for passenger vehicles. Second, there is a lack of available data. Most data on CV movements are collected by private carriers, who use them to make business decisions and therefore rarely release them to the public. Lack of data results in a lack of fundamental knowledge of the urban freight system, inhibiting policy makers’ ability to make data-driven decisions.

The urban freight literature discusses research that has employed various data collection techniques to study CV driver behaviors. Cherrett et al. reviewed 30 UK surveys on urban delivery activity and performed empirical analyses on delivery rates, time-of-day choice, types of vehicles used to perform deliveries, and dwell time distribution, among others. The surveys reviewed were mostly establishment-based, capturing driver behaviors at specific locations and times of the day. Allen et al. performed a more comprehensive investigation, reviewing different survey techniques used to study urban freight activities, including driver surveys, field observations, vehicle trip diaries, and global positioning system (GPS) traces. Driver surveys collect data on driver activities and are usually performed through in-person interviews with drivers outside their working hours or at roadside at specific locations. In-person interviews provide valuable insights into driver choices and decisions but are often limited by the locations at which the interviews occur or might not reflect actual choices because they are done outside the driver work context. Vehicle trip diaries involve drivers recording their daily activities while field observations entail observing driver activities at specific locations and establishments; neither collects insights into the challenges that drivers face during their trips and how they make certain decisions. The same limitations hold true for data collected through GPS traces. Allen et al. mentioned the collection of travel diaries by surveyors traveling in vehicles with drivers performing deliveries and pick-ups as another data collection technique that could provide useful insights into how deliveries/pick-ups are performed. However, they acknowledged that collecting this type of data is cumbersome because of the difficulty of obtaining permission from carriers and the large effort needed to coordinate data collection.

This study aims to fill that gap by collecting data on driver decision-making behaviors through observations made while riding along with CV drivers. A systematic approach was taken to observe and collect data on last-mile deliveries, combining both qualitative observations and quantitative data from GPS traces. The ridealongs were performed with various delivery companies in Seattle, Washington, covering a range of vehicle types (cars, vans, and trucks), goods types (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail).

The data collected will not only add to the existing literature by providing estimates of trip times, parking choice types, time and distance spent cruising for parking, and parking dwell times but will also provide insights into why those decisions are made and the factors affecting driver choices.

The objectives of this study are to provide a better understanding of CV driver behaviors and to identify common and unique challenges they experience in performing the last mile. These findings will help city planners, policy makers, and delivery companies work together better to address those challenges and improve urban delivery efficiency.

The next section of this paper describes the relevant literature on empirical urban freight behavior studies. The following section then introduces the ridealongs performed and the data collection methods employed. Next, analysis of the data and qualitative observations from the ridealongs are described, and the results are discussed in five overarching categories: the time spent in and out of the vehicle, parking location choice, the reasons behind those choices, parking cruising time, and factors affecting dwell time.

Recommended Citation:
Chiara, Giacomo Dalla, Krutein, Klaas Fiete, Ranjbari, Andisheh, & Goodchild, Anne. (2021). Understanding Urban Commercial Vehicle Driver Behaviors and Decision Making. Transportation Research Record, 2675(9), 608-619. https://doi.org/10.1177/03611981211003575
Paper

Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China

 
Download PDF  (0.94 MB)
Publication: Sustainability
Volume: 12(23)
Publication Date: 2020
Summary:

This paper discusses how to promote high-speed rail (HSR) freight business by solving the congestion problem. First, we define the existing operation modes in China and propose the idea of relieving congestion by reserving more carriages of HSR passenger trains for freight between cities with large potential volume or small capacity. Second, we take one HSR corridor as a case to study, and use predictive regression and integrated time series methods to forecast the growth of HSR freight volume along the corridor. Finally, combined with forecast results and available capacity during the peak month of 2018, we offer suggestions on the mode adoption in each segment during the peak month from 2019 to 2022. Results demonstrate: (1) Among all 84 Origin-Destination (OD) city flows, the percentage of those monthly volumes over 1 ton increases from 17.9% in 2018 to 84.6% in 2022, and those over 30 tons rise from 3.6% to 26.2%. (2) Among the segments between seven main cities in the HSR corridor, T-J should be given priority to operate trains with reserved mode; the segment between X and J deserves to reserve most carriages during the peak month in the future. Specifically, our model suggests reserving 5.3–10.1 carriages/day for J-X, and 4.8–16.3 carriages/day for X-J during the peak month from 2019 to 2022.

Authors: Hanlin GaoDr. Anne Goodchild, Meiqing Zhang
Recommended Citation:
Hanlin Gao, Meiqing Zhang, & Anne Goodchild. (2020). Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China. Sustainability (Basel, Switzerland), 12(23). https://doi.org/10.3390/su12239918 

Shipping Resilience: Strategic Planning for Coastal Community Resilience to Marine Transportation Risk (SIREN)

Many coastal communities across Canada are highly dependent upon maritime transportation systems that are vulnerable in natural disasters. This project aims to improve understanding of how coastal maritime transportation systems would be disrupted in natural hazard events, how such disruption would impact coastal communities, and what strategies could effectively address this risk.

Ports across Canada are vulnerable in natural disasters, and their disruption can pose severe consequences for marine transportation systems and the coastal communities that rely on them. This project aims to improve understanding of how different types of ports may be affected in hazard events, with focus on catastrophic earthquake risk in coastal British Columbia, and consideration of severe hurricane damage to ports in Eastern Canada.

Focusing on the movement of people and goods in the emergency response phase of a disaster, the research team develops new tools, information, and risk assessments to support preparedness planning by local and provincial governments and the transportation sector. Through iterative engagement with stakeholders, the research is also intended to foster dialogue and shared understandings of risk that are necessary for resilience planning.

The research consists of an interrelated set of activities:

  • Organization of workshops for engaging government and transport sector stakeholders.
  • Development of a framework for assessing community resilience to shipping and port disruption.
  • Development of a model and simulation tool for the coastal maritime transportation system and regional multimodal logistics system.
  • Development of a simulation model for port operations and vulnerabilities to natural hazards.
  • Development of an approach for evaluating the effectiveness of the modelling approach.

Research questions:

  1. How would a major disaster likely affect marine transportation routes?
  2. How would this marine transportation disruption affect the movement of people and resources in the emergency response phase?
  3. What strategies (e.g., alternate routes and/or transport modes) would be effective for different types of communities in alleviating the potential consequences?
  4. Will a port be available, and in what state, after a natural hazard event, considering its own vulnerability and the vulnerability of interdependent infrastructure (e.g., road access, electric power)?
  5. Based on expected states, what ports could be used for ingress and egress of populations and resources during the immediate and sustained response phases of a catastrophic disaster?
  6. What strategies would be effective for different types of ports to reduce failure risk or improve functional resilience?
Student Thesis and Dissertations

Ridehail and Commercial Vehicles Access in Urban Areas: Implications for Public Infrastructure Management

 
Download PDF  (2.99 MB)
Publication Date: 2022
Summary:

As urbanized populations and concentrations of activities increase, there is growing pressure in dense and constrained urban areas to unlock the potential of every public infrastructure element to address the increasing demand for public space. Specifically, there is a growing demand for space for parking operations related to the access to land use by people and goods. On one side, ridehailing services, such as those provided by Uber and Lyft, are on the rise and with them the associated passenger pick-up/drop-off (PUDOs) operations. On the other side, freight and servicing trips require a supply of adequate infrastructure to support vehicle access and load/unload activities and final delivery/service to customers. This dissertation aims to provide insights based on real-world datasets and tests to support the management of two key public infrastructure that provides access to land uses: alleys and curb lanes. To achieve this goal, first, this dissertation will investigate what roles alleys play in cities and inspect alleys’ physical characteristics and vehicle parking operations in these spaces. Secondly, this research will examine factors of PUDO dwell time and evaluate the impact of adding curb lane PUDO zones and geofencing ridehailing vehicles to these zones using a hazard-based duration modeling approach. Finally, this dissertation will analyze the impact of different ridehailing curb management strategies on curb lane utilization based on simulation.

Recommended Citation:
León, J., Luis Machado. (2022). Ridehail and Commercial Vehicles Access in Urban Areas: Implications for Public Infrastructure Management (Order No. 10827973). University of Washington Doctoral Dissertation.
Technical Report

Urban Goods Delivery Toolkit

Publication Date: 2020
Summary:

This Toolkit is designed to help transportation professionals and researchers gather key data needed to make the Final 50 Feet segment function as efficiently as possible, reducing both the time trucks park in load/unload spaces and the number of failed first delivery attempts.

In addition, the toolkit can help transportation planners, traffic engineers, freight system managers, parking and operations strategists, and researchers build a fundamental knowledge base for planning; managing parking operations; managing emergency management and response; updating traffic, land use and building codes; and modeling future scenarios and needs.

In short, the toolkit can be used to help cities meet the ever-increasing demand for trucks and other load/unload activities.

Recommended Citation:
Urban Freight Lab. (2020) Urban Goods Delivery Toolkit. https://depts.washington.edu/toolkit
Paper

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

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

The Isolated Community Evacuation Problem with Mixed Integer Programming

 
Download PDF  (0.78 MB)
Publication: Transportation Research Part E: Logistics and Transportation Review
Volume: 161
Pages: 102710
Publication Date: 2022
Summary:

As awareness of the vulnerability of isolated regions to natural disasters grows, the demand for efficient evacuation plans is increasing. However, isolated areas, such as islands, often have characteristics that make conventional methods, such as evacuation by private vehicle, impractical to infeasible. Mathematical models are conventional tools for evacuation planning. Most previous models have focused on densely populated areas, and are inapplicable to isolated communities that are dependent on marine vessels or aircraft to evacuate. This paper introduces the Isolated Community Evacuation Problem (ICEP) and a corresponding mixed integer programming formulation that aims to minimize the evacuation time of an isolated community through optimally routing a coordinated fleet of heterogeneous recovery resources. ICEP differs from previous models on resource-based evacuation in that it is highly asymmetric and incorporates compatibility issues between resources and access points. The formulation is expanded to a two-stage stochastic problem that allows scenario-based optimal resource planning while also ensuring minimal evacuation time. In addition, objective functions with a varying degree of risk are provided, and the sensitivity of the model to different objective functions and problem sizes is presented through numerical experiments. To increase efficiency, structure-based heuristics to solve the deterministic and stochastic problems are introduced and evaluated through computational experiments. The results give researchers and emergency planners in remote areas a tool to build optimal evacuation plans given the heterogeneous resource fleets available, which is something they have not been previously able to do and to take actions to improve the resilience of their communities accordingly.

Recommended Citation:
Krutein, K. F., & Goodchild, A. (2022). The isolated community evacuation problem with mixed integer programming. In Transportation Research Part E: Logistics and Transportation Review (Vol. 161, p. 102710). Elsevier BV. https://doi.org/10.1016/j.tre.2022.10271
Paper

Testing Curbside Management Strategies to Mitigate the Impacts of Ridesourcing Services on Traffic

 
Download PDF  (2.01 MB)
Publication:  Transportation Research Record: Journal of the Transportation Research Board
Publication Date: 2020
Summary:

Increased use of ridehailing leads to increased pick-up and drop-off activity. This may slow traffic or cause delays as vehicles increase curb use, conduct pick-up and drop-off activity directly in the travel lane, or slow to find and connect with passengers. How should cities respond to this change in an effort to keep travel lanes operating smoothly and efficiently? This research evaluates two strategies in Seattle, WA, in an area where large numbers of workers commute using ridesourcing services: (i) a change of curb allocation from paid parking to passenger load zone (PLZ), and (ii) a geofencing approach by transportation network companies (TNCs) which directs their drivers and passengers to designated pick-up and drop-off locations on a block. An array of data on street and curb activity along three study blockfaces was collected, using video and sensor technology as well as in-person observations. Data were collected in three phases: (i) the baseline, (ii) after the new PLZs were added, expanding total PLZ curb length from 20 ft to 274 ft, and (iii) after geofencing was added to the expanded PLZs. The added PLZs were open to any passenger vehicle (not just TNC vehicles), weekdays 7:00–10:00 a.m. and 2:00–7:00 p.m. The results showed that the increased PLZ allocation and geofencing strategy reduced the number of pick-ups/drop-offs in the travel lane, reduced dwell times, increased curb use compliance, and increased TNC passenger satisfaction. The two strategies, however, had no observable effect on travel speeds or traffic safety in the selected study area.

Recommended Citation:
Ranjbari, Andisheh, Jose Luis Machado-León, Giacomo Dalla Chiara, Don MacKenzie, and Anne Goodchild. “Testing Curbside Management Strategies to Mitigate the Impacts of Ridesourcing Services on Traffic.” Transportation Research Record, (October 2020). https://doi.org/10.1177/0361198120957314.
Paper

Estimating Intermodal Transfer Barriers to Light Rail using Smartcard Data in Seattle, WA

 
Download PDF  (2.90 MB)
Publication:  Transportation Research Record: Journal of the Transportation Research Board
Publication Date: 2022
Summary:

Transit transfers are a necessary inconvenience to riders. They support strong hierarchical networks by connecting various local, regional, and express lines through a variety of modes. This is true in Seattle, where many lines were redrawn to feed into the Link Light Rail network. Previous transfer studies, using surveys, found that perceived safety, distance, and personal health were significant predictors of transfers. This study aims to use smartcard data and generalized linear modeling to estimate which elements of transfers are commonly overcome—and which are not—among riders boarding the Link Light Rail in Seattle and its suburbs. The aims of this research are twofold: (1) critical analysis of attributes of transfer barriers so that the future station area could serve improved riders’ accessibility; (2) equity of transfer barriers among the users by analyzing the user breakdown of the origin lines and the destination. We use Seattle’s One Regional Card for All smartcard data among the Link Light Rail riders in the Seattle metropolitan area in 2019, and applied a negative binomial generalized linear model. The model suggests that walking distance and walking grade have significant effects on transfers. For the users’ equity analysis, the disabled population tends to transfer less, while the low-income and youth riders populations tend to transfer more often. Future research could incorporate a more mixed-methods approach to confirm some of these findings or include station amenities, such as live schedule updates for common transfer lines.

Authors: Dr. Ed McCormack, James Eager (University of Washington Department of Urban Design and Planning), Chang-Hee Christine Bae (University of Washington Department of Urban Design and Planning)
Recommended Citation:
Eager, J., Bae, C.-H. C., & McCormack, E. D. (2022). Estimating Intermodal Transfer Barriers to Light Rail using Smartcard Data in Seattle, WA. Transportation Research Record. https://doi.org/10.1177/03611981221119190.
Paper

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

 
Download PDF  (0.42 MB)
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.

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.