Paper

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

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

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).

Paper

Evaluation of Emissions Reduction in Urban Pickup Systems Heterogeneous Fleet Case Study

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URL: https://doi.org/10.3141/2224-02

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

Volume: 2224

Pages: 8-16

Publication Date: 2011

Summary:

A case study of the University of Washington Mailing Services, which operates a heterogeneous fleet of vehicles, provides insight into the impact of operational changes on cost, service quality, and emissions. An emissions minimization problem was formulated and solutions were identified with a creation and local search algorithm based on the I1 and 2-opts heuristics.

The algorithm could be used to find many solutions that could improve existing routing on both cost and emissions metrics, reduce emissions by an average of almost 6%, and reduce costs by an average of 9%. More significant cost and emissions savings could be found with service quality reductions. For example, reducing delivery frequency to once a day could lead to emissions and cost savings of close to 35% and 3%, respectively.

Rules of thumb for vehicle assignment within heterogeneous fleets were explored to gain an understanding of simple implementations, such as assigning cleaner vehicles to routes with more customers and longer travel distances.

This case study identified significant emissions reductions that could be obtained with minimal effects on cost and service and that offered new, practical applications that could be used by fleet managers interested in reducing their carbon footprint.

Authors: Dr. Anne Goodchild, Kelly Pitera, Felipe Sandoval

Recommended Citation:
Pitera, Kelly, Felipe Sandoval, and Anne Goodchild. "Evaluation of Emissions Reduction in Urban Pickup Systems: Heterogeneous Fleet Case Study." Transportation Research Record 2224, no. 1 (2011): 8-16.

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

Data Stories from Urban Loading Bays

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URL: https://doi.org/10.1007/s12544-017-0267-3

Publication: European Transport Research Review

Volume: 9

Publication Date: 2017

Summary:

Freight vehicle parking facilities at large urban freight traffic generators, such as urban retail malls, are often characterized by a high volume of vehicle arrivals and a poor parking supply infrastructure. Recurrent congestion of freight parking facilities generates environmental (e.g. pollution), economic (e.g. delays in deliveries), and freight and social (e.g. traffic) negative externalities. Solutions aimed at either improving or better managing the existing parking infrastructure rely heavily on data and data-driven models to predict their impact and guide their implementation. In the current work, we provide a quantitative study of the parking supply and freight vehicle drivers’ parking behavior at urban retail malls.

We use as case studies two typical urban retail malls located in Singapore, and collect detailed data on freight vehicles delivering or picking up goods at these malls. Insights from this data collection effort are relayed as data stories. We first describe the parking facility at a mall as a queueing system, where freight vehicles are the agents and their decisions are the parking location choice and the parking duration.

Using the data collected, we analyze (i) the arrival rates of vehicles at the observed malls, (ii) the empirical distribution of parking durations at the loading bays, (iii) the factors that influence the parking duration, (iv) the empirical distribution of waiting times spent by freight vehicle queueing to access the loading bay, and (v) the driver parking location choices and how this choice is influenced by system congestion.

This characterization of freight driver behavior and parking facility system performance enables one to understand current challenges, and begin to explore the feasibility of freight parking and loading bay management solutions.

Authors: Dr. Giacomo Dalla Chiara, Lynette Cheah

Recommended Citation:
Dalla Chiara, G., Cheah, L. Data stories from urban loading bays. Eur. Transp. Res. Rev. 9, 50 (2017). https://doi.org/10.1007/s12544-017-0267-3