Paper

A Description of Fatal Bicycle Truck Accidents in the United States: 2000 to 2010

Publication: Transportation Research Board 95th Annual Meeting

Volume: 16-5911

Publication Date: 2016

Summary:

Bicycling is being encouraged across the US and the world as a low-impact, environmentally friendly mode of transportation. In the US, many states and cities, especially cities facing congestion issues, are encouraging cycling as an alternative to automobiles. However, as cities grow and consumption increases, freight traffic in cities will increase as well, leading to higher amounts of interactions between cyclists and trucks. This paper will describe where and how accidents between cyclists and trucks occur. From 2000 to 2010, 807 bicyclists were killed the United States in accidents involving trucks. In 2009, trucks accounted for 9.5% of fatal bicycle accidents, despite trucks only accounting for 4.5% of registered vehicles. The typical fatal bike-truck accident happens in an urban area on an arterial street with a speed limit of 35 or 45 mph. It is about equally likely to occur mid-block or at an intersection. Most accidents involved trucks going straight (56%), and right-turning trucks were involved in a much larger number of accidents (24%) than left turning trucks (7%). Methods such as providing bicycle lanes, or even physically separated bicycle tracks, will not be sufficient to address bicycle-truck collisions, as a significant number of accidents (49%) occur in intersections or are intersection related. Cities with a higher mode-share of bicycling had a lower rate of bicycle-truck fatality accidents.

Authors: Dr. Anne Goodchild, Jerome Drescher

Recommended Citation:
Drescher, Jerome and Anne Goodchild. (2016), "A Description of Fatal Bicycle Truck Accidents in the United States: 2000 to 2010," Accepted for presentation at the 95th Transportation Research Board Annual Meeting, Washington DC, January 10-14. [Paper # 16-5911]

Paper

Examining the Differential Responses of Shippers and Motor Carriers to Travel Time Variability

URL: http://dx.doi.org/10.4018/jal.2012010103

Publication: International Journal of Applied Logistics

Volume: 3 (1)

Pages: 39-53

Publication Date: 2012

Summary:

Shippers and motor carriers are impacted by and react differently to travel time variability due to their positions within the supply chain and end goals. Through interviews and focus groups these differences have been further examined. Shippers, defined here as entities that send or receive goods, but do not provide the transportation themselves, are most often concerned with longer-term disruptions, which are typically considered within the context of transportation system resilience. Motor carriers, defined here as entities engaged in transporting goods for shippers, are most often concerned with daily travel time variability from events such as congestion. This paper describes the disparity in concerns and the strategies shippers and motor carriers are likely to engage in to address time travel variability. This knowledge allows for a better understanding of how investments to mitigate travel time variability will impact shippers and motor carriers.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Kelly Pitera

Recommended Citation:
Goodchild, Anne V., Kelly Pitera, and Edward McCormack. "Examining the differential responses of shippers and motor carriers to travel time variability." International Journal of Applied Logistics (IJAL) 3, no. 1 (2012): 39-53.

Paper

Understanding Freight Trip Chaining Behavior Using Spatial Data Mining Approach with GPS Data

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URL: http://dx.doi.org/10.3141/2596-06

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

Volume: 2596

Pages: 44-54

Publication Date: 2016

Summary:

Freight systems are a critical yet complex component of the transportation domain. Understanding the dynamic of freight movements will help in better management of freight demand and eventually improve freight system efficiency. This paper presents a series of data-mining algorithms to extract an individual truck’s trip-chaining information from multi-day GPS data. Individual trucks’ anchor points were identified with the spatial clustering algorithm for density-based spatial clustering of applications with noise. The anchor points were linked to construct individual trucks’ trip chains with 3-day GPS data, which showed that 51% of the trucks in the data set had at least one trip chain. A partitioning around medoids nonhierarchical clustering algorithm was applied to group trucks with similar trip-chaining characteristics. Four clusters were generated and validated by visual inspection when the trip-chaining statistics were distinct from each other. This study sheds light on modeling freight-chaining behavior in the context of massive freight GPS data sets. The proposed trip chain extraction and behavior classification algorithms can be readily implemented by transportation researchers and practitioners to facilitate the development of activity-based freight demand models.

Authors: Dr. Ed McCormack, X. Ma, W. Yong, and Yinhai Wang

Recommended Citation:
Ma, Xiaolei & Wang, Yong & McCormack, Edward & Wang, Yinhai. (2016). Understanding Freight Trip-Chaining Behavior Using a Spatial Data-Mining Approach with GPS Data. Transportation Research Record: Journal of the Transportation Research Board. 2596. 44-54. 10.3141/2596-06.

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

Estimating Truck Trips with Product Specific Data: A Disruption Case Study in Washington Potatoes

URL: https://doi.org/10.3328/TL.2012.04.03.153-166

Publication: Transportation Letters: The International Journal of Transportation Research

Volume: 4 (3)

Publication Date: 2013

Summary:

Currently, knowledge of actual freight flows in the US is insufficient at a level of geographic resolution that permits corridor-level freight transportation analysis and planning. Commodity specific origins, destinations, and routes are typically estimated from four-step models or commodity flow models. At a sub-regional level, both of these families of models are built on important assumptions driven by the limited availability of data. This study was motivated by a desire to determine whether efforts to gather corridor-level freight movement data will bring significant new insights over current approaches to freight transportation modeling. Through a case study of Washington State’s potato and value added potato products industry, we show that significant insight can be gained by collecting commodity-specific truck trip generation and destination data: the approach allows product specific truck trips to be estimated for each roadway link. When considering a network change, the number of affected trips can be identified, and their re-route distance quantified.

Authors: Dr. Anne Goodchild, Derik Andreoli, Eric Jessup

Recommended Citation:
Derik Andreoli, Anne Goodchild & Eric Jessup (2012) Estimating truck trips with product specific data: a disruption case study in Washington potatoes, Transportation Letters, 4:3, 153-166, https://doi.org/10.3328/TL.2012.04.03.153-166

Paper

SimMobility Freight: An Agent-Based Urban Freight Simulator for Evaluating Logistics Solutions

URL: https://doi.org/10.1016/j.tre.2020.102017

Publication: Transportation Research Part E: Logistics and Transportation Review

Volume: 141

Publication Date: 2020

Summary:

Despite significant advances in freight transport modeling in recent years, there is still lack of available tools for evaluating novel logistics solutions. We introduce the framework of SimMobility Freight, which is part of SimMobility, a multi-scale agent-based urban transportation simulation platform. SimMobility Freight is capable of simulating commodity contracts, logistics and vehicle operation planning and parking decisions in a fully-disaggregate manner. This allows us to evaluate alternative logistics solutions and measure their impacts. To illustrate its capability, we conduct an analysis of delivery time window regulations, assessing the policy impacts.

Authors: Dr. Giacomo Dalla Chiara, Takanori Sakai, André Romano Alho, B.K. Bhavathrathan, Raja Gopalakrish, Peiyu Jinge, Tetsuro Hyodo, Lynette Cheah, Moshe Ben-Akivae

Recommended Citation:
Sakai, T., Romano Alho, A., Bhavathrathan, B., Chiara, G. D., Gopalakrishnan, R., Jing, P., Hyodo, T., Cheah, L., & Ben-Akiva, M. (2020). SimMobility Freight: An Agent-Based Urban Freight Simulator for Evaluating Logistics Solutions. Transportation Research Part E: Logistics and Transportation Review, 141, 102017. https://doi.org/10.1016/j.tre.2020.102017

Paper

GPS Tracking of Freight Vehicles to Identify and Classify Bottlenecks

URL: https://ieeexplore.ieee.org/abstract/document/6338666

Publication: Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference

Publication Date: 2012

Summary:

This paper presents a systematic methodology for identifying and ranking bottlenecks using probe data collected by commercial GPS fleet management devices. This methodology is based on the hypotheses that truck speed distributions can be represented by either a unimodal or bimodal probability density function, and it proposes a new reliability measure for evaluating roadway performance.

Authors: Dr. Ed McCormack, Wenjuan Zhao, Daniel J. Dailey

Recommended Citation:
McCormack, E., Zhao, W., & Dailey, D. J. (2012, September). GPS Tracking of Freight Vehicles to Identify and Classify Bottlenecks. In 2012 15th International IEEE Conference on Intelligent Transportation Systems (pp. 1245-1249). IEEE.

Paper

Factors Impacting Bicyclist Lateral Position and Velocity in Proximity to Commercial Vehicle Loading Zones: Application of a Bicycling Simulator

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URL: https://doi.org/10.1016/j.aap.2019.01.024

Publication: Accident Analysis & Prevention

Volume: 125

Pages: 29-39

Publication Date: 2019

Summary:

There is little research on the behavioral interaction between bicycle lanes and commercial vehicle loading zones (CVLZ) in the United States. These interactions are important to understand, to preempt increasing conflicts between truckers and bicyclists. In this study, a bicycling simulator experiment examined bicycle and truck interactions. The experiment was successfully completed by 48 participants. The bicycling simulator collected data regarding a participant’s velocity and lateral position. Three independent variables reflecting common engineering approaches were included in this experiment: pavement marking (L1: white lane markings with no supplemental pavement color, termed white lane markings, L2: white lane markings with solid green pavement applied on the conflict area, termed solid green, and L3: white lane markings with dashed green pavement applied on the conflict area, termed dashed green), signage (L1: No sign and L2: a truck warning sign), and truck maneuver (L1: no truck in CVLZ, L2: truck parked in CVLZ, and L3: truck pulling out of CVLZ).

The results showed that truck presence does have an effect on bicyclist’s performance, and this effect varies based on the engineering and design treatments employed. Of the three independent variables, truck maneuvering had the greatest impact by decreasing mean bicyclist velocity and increasing mean lateral position. It was also observed that when a truck was present in a CVLZ, bicyclists had a lower velocity and lower divergence from right-edge of bike lane on solid green pavement, and a higher divergence from the right-edge of bike lane was observed when a warning sign was present.

Authors: Manali ShethDr. Anne GoodchildDr. Ed McCormack, Masoud Ghodrat Abadia, David S. Hurwitz

Recommended Citation:
Abadi, Masoud Ghodrat, David S. Hurwitz, Manali Sheth, Edward McCormack, and Anne Goodchild. (2019) Factors Impacting Bicyclist Lateral Position and Velocity in Proximity to Commercial Vehicle Loading Zones: Application of a Bicycling Simulator. Accident Analysis and Prevention, 125, 29–39. https://doi.org/10.1016/j.aap.2019.01.024

Paper

Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments

URL: https://trid.trb.org/view.aspx?id=1467189

Publication: NCFRP Research Report

Volume: Project NCFRP-46

Publication Date: 2017

Summary:

This report provides a guidebook for conducting benefit-cost analyses of proposed infrastructure investments on multimodal, multi-jurisdictional freight corridors for public and private decision-makers and other stakeholders at local, state, regional, and national levels to arrive at more informed investment decisions.

The guidebook is a resource and a reference for multimodal freight investment benefit-cost analysis, data sources, procedures, and tools for projects of different geographic scales.

To help practitioners get started, the guidebook is presented in a “how to” format relying on discrete steps that are accompanied with realistic and recent examples, a fully worked out case study, checklists of dos and don’ts, and supporting worksheets.

View TRB Webinar: Benefit Cost Methodologies for Evaluating Multimodal Freight Corridor Investments

Authors: Dr. Anne Goodchild, Sharada Vadali, C. James Kruse, Kenneth Kuhn

Recommended Citation:
Vadali, Sharada, C. James Kruse, Kenneth Kuhn, and Anne Goodchild. Guide for Conducting Benefit-Cost Analyses of Multimodal, Multijurisdictional Freight Corridor Investments. No. Project NCFRP-46. 2017.

Paper

Sustainable Urban Goods Movement: Emerging Research Agendas

URL: https://doi.org/10.1080/17549175.2013.875058

Publication: Journal of Urbanism

Volume: 8(20)

Pages: 115-132

Publication Date: 2014

Summary:

While recent urban planning efforts have focused on smart growth development and management of growth into developed areas, the research community has not examined the impacts of these development patterns on urban goods movement. Successful implementation of growth strategies has multiple environmental and social benefits, but it also raises the demand for intraurban goods movement, potentially increasing conflicts between modes of travel and worsening air quality. Because urban goods movement is critical for economic vitality, and as policies are developed to manage urban goods movement, understanding the relationship between smart growth and goods movement is necessary. This paper reviews the academic literature and summarizes the results of guided interviews to identify the existing gaps in the state of knowledge and suggest important future research topics. Little research exists that directly examines the relationship between smart growth and goods movement; therefore, smart growth is dissected into sub-areas that relate to goods movement, and these areas are individually examined. These five key sub-areas are 1) access, parking, and loading zones; 2) road channelization, bicycle, and pedestrian facilities; 3) land use; 4) logistics; and 5) network system management. The existing state of knowledge is discussed in each of these areas and identify specific areas of concern determined from guided interviews. With these inputs, important areas of future research are identified.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Erica Wygonik, Alon Bassok, Daniel Carlson

Recommended Citation:
Wygonik, Erica, Alon Bassok, Anne V. Goodchild, Edward McCormack and Daniel Fred Carlson. “Sustainable Urban Goods Movement: Emerging Research Agendas.” (2012).