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Urban Freight Lab

Publication Type: Paper

Paper

Rails-Next-to-Trails: A Methodology for Selecting Appropriate Safety Treatments at Complex Multimodal Intersections

 
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URL: https://journals.sagepub.com/doi/pdf/10.1177/0361198118792763
Publication: Transportation Research Record
Volume: 2672 (10)
Pages: 27-Dec
Publication Date: 2018
Summary:
There are more than 212,000 at-grade railroad crossings in the United States. Several feature paths running adjacent to the railroad tracks, and crossing a highway; they serve urban areas, recreational activities, light rail station access, and a variety of other purposes. Some of these crossings see a disproportionate number of violations and conflicts between rail, vehicles, and pedestrians and bikes. This research focuses on developing a methodology for appropriately addressing the question of treatments in these complex, multimodal intersections. The methodology is designed to be able to balance a predetermined, prescriptive approach with the professional judgment of the agency carrying out the investigation. Using knowledge and data from the literature, field studies, and video observations, a framework for selecting treatments based on primary issues at a given location is developed. Using such a framework allows the agency to streamline their crossing improvement efforts; to easily communicate and inform the public of the decisions made and their reasons for doing so; to secure stakeholder buy-in prior to starting a project or investigation; to make sure that approach and selected treatments are more standardized; and to ensure transparency in the organization to make at-grade crossings safer for pedestrians and bicyclists, without negatively impacting trains or vehicles.

 

Authors: Anna Bovbjerg AlligoodManali ShethDr. Anne GoodchildDr. Ed McCormackPolina Butrina
Paper

Delivery by Drone: An Evaluation of Unmanned Aerial Vehicle Technology in Reducing CO2 Emissions in the Delivery Service Industry

 
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URL: https://doi.org/10.1016/j.trd.2017.02.017
Publication: Transportation Research Part D: Transport and Environment
Volume: 61
Pages: 58-67
Publication Date: 2018
Summary:

This research paper estimates carbon dioxide (CO2) emissions and vehicle-miles traveled (VMT) levels of two delivery models, one by trucks and the other by unmanned aerial vehicles (UAVs), or “drones.”

Using several ArcGIS tools and emission standards within a framework of logistical and operational assumptions, it has been found that emission results vary greatly and are highly dependent on the energy requirements of the drone, as well as the distance it must travel and the number of recipients it serves.

Still, general conditions are identified under which drones are likely to provide a CO2 benefit – when service zones are close to the depot, have small numbers of stops, or both. Additionally, measures of VMT for both modes were found to be relatively consistent with existing literature that compares traditional passenger travel with truck delivery.

Authors: Dr. Anne Goodchild, Jordan Toy
Recommended Citation:
Goodchild, Anne, and Jordan Toy. "Delivery by Drone: An Evaluation of Unmanned Aerial Vehicle Technology in Reducing CO2 Emissions in the Delivery Service Industry" Transportation Research Part D: Transport and Environment 61 (2018): 58-67.
Paper

Evaluating CO2 Emissions, Cost, and Service Quality Trade-Offs in an Urban Delivery System Case Study

 
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URL: https://doi.org/10.1016/j.iatssr.2011.05.001
Publication: International Association of Traffic and Safety Sciences (IATSS)
Volume: 35 (1)
Pages: 15-Jul
Publication Date: 2011
Summary:

Growing pressure to limit greenhouse gas emissions is changing the way businesses operate. This paper presents the trade-offs between cost, service quality (represented by time window guarantees), and emissions of an urban pickup and delivery system under these changing pressures. A model, developed by the authors in ArcGIS, is used to evaluate these trade-offs for a specific case study involving a real fleet with specific operational characteristics. The problem is modeled as an emissions minimization vehicle routing problem with time windows. Analyses of different external policies and internal operational changes provide insight into the impact of these changes on cost, service quality, and emissions. Specific consideration of the influence of time windows, customer density, and vehicle choice are included.

The results show a stable relationship between monetary cost and kilograms of CO2, with each kilogram of CO2 associated with a $3.50 increase in cost, illustrating the influence of fuel use on both cost and emissions. In addition, customer density and time window length are strongly correlated with monetary cost and kilograms of CO2 per order. The addition of 80 customers or extending the time window 100 minutes would save approximately $3.50 and 1 kilogram of CO2 per order. Lastly, the evaluation of four different fleets illustrates significant environmental and monetary gains can be achieved through the use of hybrid vehicles.

The results demonstrate there is not a trade-off between CO2 emissions and cost, but that these two metrics trend together. This suggests the most effective way to encourage fleet operators to limit emissions is to increase the cost of fuel or CO2 production, as this is consistent with current incentives that exist to reduce cost, and therefore emissions.

Authors: Dr. Anne Goodchild, Erica Wygonik
Recommended Citation:
Wygonik, Erica, and Anne Goodchild. "Evaluating CO2 Emissions, Cost, and Service Quality Trade-Offs in an Urban Delivery System Case Study." IATSS Research 35, No. 1 (2011): 7-15.
Paper

Using Truck Probe GPS Data to Identify and Rank Roadway Bottlenecks

 
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URL: https://doi.org/10.1061/(ASCE)TE.1943-5436.0000444
Publication: American Society of Civil Engineers (ASCE) Journal of Transportation Engineering
Volume: 139(1)
Pages: 7-Jan
Publication Date: 2013
Summary:

This paper describes the development of a systematic methodology for identifying and ranking bottlenecks using probe data collected by commercial global positioning system fleet management devices mounted on trucks. These data are processed in a geographic information system and assigned to a roadway network to provide performance measures for individual segments. The authors hypothesized that truck speed distributions on these segments can be represented by either a unimodal or bimodal probability density function and proposed a new reliability measure for evaluating roadway performance. Travel performance was classified into three categories: unreliable, reliably fast, and reliably slow. A mixture of two Gaussian distributions was identified as the best fit for the overall distribution of truck speed data. Roadway bottlenecks were ranked on the basis of both the reliability and congestion measurements. The method was used to evaluate the performance of Washington state roadway segments, and proved efficient at identifying and ranking truck bottlenecks.

Authors: Dr. Ed McCormack, Wenjuan Zhao, Daniel J. Dailey, Eric Scharnhorst
Recommended Citation:
Zhao, Wenjuan, Edward McCormack, Daniel J. Dailey, and Eric Scharnhorst. "Using truck probe GPS data to identify and rank roadway bottlenecks." Journal of Transportation Engineering 139, no. 1 (2012): 1-7.
Paper

Free and Secure Trade Commercial Vehicle Crossing Times at the Pacific Highway Port of Entry

 
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URL: http://dx.doi.org/10.1061/(ASCE)TE.1943-5436.0000159
Publication: Journal of Transportation Engineering
Volume: 136(10)
Pages: 932-935
Publication Date: 2010
Summary:

At the Pacific Highway port of entry between the United States and Canada, typical delays are known to regional carriers and internalized into schedules. Due to their relative infrequency, the largest crossing times are not internalized into schedules and cause significant disruptions to regional supply chains. This technical note describes the recent patterns of very long crossing times (defined as more than 2 h or the largest 1% of crossing times) and explores the relationship between arrival volume and crossing time. To do so, this study uses commercial vehicle crossing time data from GPS technology and volume data from the British Columbia Ministry of Transportation. Results show a weak correlation between border crossing time and arrival volume when considering individual observations, but a stronger correlation when data are aggregated. Results show a high percentage of crossing time can be attributed to sources other than primary booth delay, particularly for the most disruptive, very long crossing times.

Authors: Dr. Anne Goodchild, Li Leung, Susan Albrecht
Recommended Citation:
Goodchild, Anne, Li Leung, and Susan Albrecht. "Free and secure trade commercial vehicle crossing times at the Pacific Highway port of entry." Journal of Transportation Engineering 136, no. 10 (2010): 932-935. 
Paper

Toward Predicting Stay Time for Private Car Users: A RNN-NALU Approach

 
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URL: https://doi.org/10.1109/TVT.2022.3164978
Publication: IEEE Transactions on Vehicular Technology
Volume: 71 (6)
Pages: 6007 - 6018
Publication Date: 2022
Summary:

Predicting the stay time of private cars has various applications in location-based services and traffic management. Due to the associated randomness and uncertainty, achieving the promising performance of stay time prediction is a challenge. We propose an RNN-based encoder model to solve this problem, which consists of three components, i.e., an encoder module, an exception module, and an MLP dropout. First, we encode the stay behaviour into hidden vectors at a specific time to avoid the effect of time sparsity. The encoder module utilizes a multilayer perceptron (MLP) to learn spatiotemporal features from the historical trajectory data, such as the inherent relationship between the stop points and corresponding stay time. We proved a linear relationship problem that cannot be ignored in the stay time prediction problem. In particular, we have added basic arithmetic logic units to the network framework to find linear relationships. By reconstructing the basic arithmetic and logical relations of the network, we have improved the ability of the neural network to handle linear relations and the extrapolation ability of the neural network. Our method can remember the number patterns seen in the training set very well and infer this representation reasonably. Moreover, we utilize the dropout technique to prevent the prediction model from overfitting. We perform extensive experiments based on a large-scale real-world private car trajectory dataset. The experimental results demonstrate that our method achieves an RMSE of 0.1429 and a MAPE of 55.8533%. Furthermore, the results verify the effectiveness and advantages of the proposed model when compared with the benchmarks.

Authors: Amelia Regan, Qibo Zhang; Fanzi Zeng; Zhu Xiao; Hongbo Jiang; Kehua Yang; Yongdong Zhu
Recommended Citation:
Q. Zhang et al., "Toward Predicting Stay Time for Private Car Users: A RNN-NALU Approach," in IEEE Transactions on Vehicular Technology, vol. 71, no. 6, pp. 6007-6018, June 2022, doi: 10.1109/TVT.2022.3164978.
Paper

Systematic Approach for the Design of Flight Simulator Studies

 
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URL: https://doi.org/10.1177/1071181319631524
Publication: Proceedings of the Human Factors and Ergonomics Society 2019 Annual Meeting
Volume: 63:01:00
Pages: 833-837
Publication Date: 2019
Summary:

The examination of commercial pilot workload often requires the use of controlled simulated studies to identify causal effects. The specific scenarios to consider within a simulator study require an extensive understanding of the safety situations that can occur in flight while also considering the specific training that pilots are provided within a simulated environment. The purpose of this paper is to provide a more systematic approach to scenario identification based on historical data, feasibility of capturing behavioral changes, simulator constraints, and training curricula.

Authors: Fiete Krutein, Linda Ng Boyle
Recommended Citation:
Krutein, K. F., & Boyle, L. N. (2019). Systematic approach for the design of flight simulator studies. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63(1), 833–837. https://doi.org/10.1177/1071181319631524
Paper

Impact of Transit Network Layout on Resident Mode Choice

 
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Publication: Mathematical Problems in Engineering
Volume: 4
Publication Date: 2013
Summary:
This study reviews the impact of public transit network layout (TNL) on resident mode choice. The review of TNL as a factor uses variables divided into three groups: a variable set without considering the TNL, one considering TNL from the zone level, and one considering TNL from the individual level. Using Baoding’s travel survey data, a Multinomial Logit (MNL) model is used, and the parameter estimation result shows that TNL has significant effect on resident mode choice. Based on parameter estimation, the factors affecting mode choice are further screened. The screened variable set is regarded as the input data to the BP neural network’s training and forecasting. Both forecasting results indicate that introducing TNL can improve the performance of mode choice forecasting.

 

 

Authors: Dr. Ed McCormack, Jian Gao, Peng Zhao, Chengxiang Zhuge, Hui Zhang
Recommended Citation:
Gao, J., Zhao, P., Zhuge, C., Zhang, H., & McCormack, E. D. (2013). Impact of Transit Network Layout on Resident Mode Choice. Mathematical Problems in Engineering, 2013.
Paper

From the Last Mile to the Last 800 Feet: Key Factors in Urban Pick-Up and Delivery of Goods

 
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URL: http://dx.doi.org/10.3141/2609-10
Publication: Transportation Research Record: Journal of the Transportation Research Board
Volume: Freight Systems, Volume 1
Pages: 85-92
Publication Date: 2017
Summary:

Pickup and delivery operations are an essential part of urban goods movements. However, rapid urban growth, increasing demand, and higher customer expectations have amplified the challenges of urban freight movement. In recent years, the industry has emphasized improving last-mile operations with the intent of focusing on what has been described as the last leg of the supply chain. In this paper, it is suggested that solving urban freight challenges requires an even more granular scale than the last mile, that is, the last 800 ft. The necessary operations in the last 800 ft require integration of diverse stakeholders, public and private infrastructure, and a diverse set of infrastructure users with multiple, varied objectives. That complexity has led to a gap in the needs of delivery operations and the characteristics of receiving facilities (i.e., unloading and loading facilities and pickup–drop-off locations). This paper focuses on accessibility for pickup and drop-off operations, taking a closer look at urban goods movement in the last 800 ft from the final customer. The paper presents and analyzes previously documented approaches and measures used to study the challenges at the proposed scale. Finally, it proposes a more holistic approach to address accessibility for urban pickup–delivery operations at the microscale to help develop more comprehensive urban freight transportation planning.

Authors: Polina ButrinaDr. Anne GoodchildGabriela Girón-ValderramaJosé Luis Machado León, Pramod Ayyalasomayajula
Recommended Citation:
Butrina, Polina. Gabriela Del Carmen Girón-Valderrama, José Luis Machado-León, Anne Goodchild, and Pramod C. Ayyalasomayajula. From the Last Mile to the Last 800 ft: Key Factors in Urban Pickup and Delivery of Goods. Transportation Research Record 2609, no. 1 (2017): 85-92. 
Paper

NCFRP Report: Smart Growth and Urban Goods Movement

 
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URL: https://dx.doi.org/10.17226/22522
Publication: TR News
Volume: 295
Publication Date: 2014
Summary:

Smart growth design, a strategy for improving the quality of life in urban areas, has typically focused on the areas of passenger travel, land use and nonmotorized transport adoption. The role of goods movement is often ignored in discussions of smart growth. This article reports on National Cooperative Freight Research Program (NCFRP) Report 24, which addresses the importance of the relationship between smart growth and goods movement. A number of principles of smart growth are identified, as are areas where there are research gaps. Urban transportation forecasting models have shown that smart-growth land use offers benefits both for passenger travel and goods movement. Additionally, smart-growth improvements to transit and nonmotorized transportation have been found to offer greater benefits to trucks than do roadway investments.

Authors: Dr. Anne GoodchildDr. Ed McCormack, Alon Bassok
Recommended Citation:
McCormack, Ed, Anne Goodchild, and Alon Bassok. National Academies of Sciences, Engineering, and Medicine. 2013. Smart Growth and Urban Goods Movement. Washington, DC: The National Academies Press. https://doi.org/10.17226/22522.