Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed: Models for an Urban Freight and Parcel Delivery Virtual Testbed in NYC

Chow, Joseph; Ozbay, Kaan; Davis III, Haggai; Yang, Hai; Namdarpour, Farnoosh; Landes, Hector; Gazard, Jack

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Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed: Models for an Urban Freight and Parcel Delivery Virtual Testbed in NYC

2023-05-01
By Chow, Joseph ; Ozbay, Kaan ; Davis III, Haggai ; ...

File Language:

English

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Creators:

Chow, Joseph ; Ozbay, Kaan ; Davis III, Haggai ; Yang, Hai ; Namdarpour, Farnoosh ; Landes, Hector ; Gazard, Jack
Corporate Creators:

Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART) ; New York University
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:

Congestion Pricing Freight Traffic Truck Routes Truck Traffic
Resource Type:

Tech Report
Geographical Coverage:

New York;United States
Edition:

Final Report 3/1/21-5/31/23
Corporate Publisher:

Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART)
Abstract:

This project explored routing app designs that can be of use to NYC DOT in informing truck drivers in NYC. This involved developing a prototype app and engaging in a hackathon in Fall 2022 to refine the visualization of the routing data. Second, we leveraged public data to construct a synthetic population of trucks that can be incorporated into a multiagent simulation that allows for dynamic passenger and commercial vehicle interactions. The synthetic truck population, which includes schedules of trip chains for each individual truck, will be incorporated into MATSim-NYC (He et al., 2021). Third, we proposed a new model for predicting zonal residential parcel delivery volumes and VMT that is applicable to large-scale scenarios and validate such a model using data from New York City (NYC).
Format:

PDF
Funding:

69A3551747119
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:f8da1fee47cc917f1194dc06b44fca6366d8d51ca8502bbe2fa4c641635b0a9623fab9ee756c7381adb8c0adef74143387e1b9b7b43bfda43c660c86b5dc3aaf
Download URL:

https://rosap.ntl.bts.gov/view/dot/68870/dot_68870_DS1.pdf
File Type:

[PDF - 7.19 MB ]

File Language:

English

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