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Paper

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

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

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

Measuring Delivery Route Cost Trade-Offs Between Electric-Assist Cargo Bicycles and Delivery Trucks in Dense Urban Areas

 
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Publication: European Transport Research Review
Volume: 11
Publication Date: 2019
Summary:

Introduction

Completing urban freight deliveries is increasingly a challenge in congested urban areas, particularly when delivery trucks are required to meet time windows. Depending on the route characteristics, Electric Assist (EA) cargo bicycles may serve as an economically viable alternative to delivery trucks. The purpose of this paper is to compare the delivery route cost trade-offs between box delivery trucks and EA cargo bicycles that have the same route and delivery characteristics, and to explore the question, under what conditions do EA cargo bikes perform at a lower cost than typical delivery trucks?

Methods

The independent variables, constant variables, and assumptions used for the cost function comparison model were gathered through data collection and a literature review. A delivery route in Seattle was observed and used as the base case; the same route was then modeled using EA cargo bicycles.

Four separate delivery scenarios were modeled to evaluate how the following independent route characteristics would impact delivery route cost – distance between a distribution center (DC) and a neighborhood, number of stops, distance between each stop, and number of parcels per stop.

Results

The analysis shows that three of the four modeled route characteristics affect the cost trade-offs between delivery trucks and EA cargo bikes. EA cargo bikes are more cost effective than delivery trucks for deliveries in close proximity to the DC (less than 2 miles for the observed delivery route with 50 parcels per stop and less than 6 miles for the hypothetical delivery route with 10 parcels per stop) and at which there is a high density of residential units and low delivery volumes per stop.

Conclusion

Delivery trucks are more cost effective for greater distances from the DC and for large volume deliveries to one stop.

 

Recommended Citation:
Sheth, Manali, Polina Butrina, Anne Goodchild, and Edward McCormack. "Measuring delivery route cost trade-offs between electric-assist cargo bicycles and delivery trucks in dense urban areas." European Transport Research Review 11, no. 1 (2019): 11.
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

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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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.