Connected Emission Control Technologies for Freight Vehicles [supporting datasets]

Boriboonsomsin, Kanok; Luo, Ji; Wang, Chao; Barth, Matthew; METRANS Transportation Center (Calif.); University of Southern California, Los Angeles

doi:10.6086/D1PT0J

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Connected Emission Control Technologies for Freight Vehicles [supporting datasets]

2020-02-11
See Associated Publication(s)
By Boriboonsomsin, Kanok ; Luo, Ji ; Wang, Chao ; ...

[PDF-207.15 KB]

English

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Details:

Creators:

Boriboonsomsin, Kanok ; Luo, Ji ; Wang, Chao ; Barth, Matthew

Boriboonsomsin, Kanok ; Luo, Ji ; Wang, Chao ; Barth, Matthew Less -
Corporate Creators:

METRANS Transportation Center (Calif.) ; University of Southern California, Los Angeles

METRANS Transportation Center (Calif.) ; University of Southern California, Los Angeles Less -
Corporate Contributors:

United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; University of California, Riverside. Center for Environmental Research and Technology

United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; University of California, Riverside. Center for Environmental Research and Technology Less -
Subject/TRT Terms:

[+]

Air Quality Management Algorithms Connected Vehicles Diesel Trucks Emission Control Systems Engine Tuning Environmental Impacts Environmental Justice Exhaust Gases Heavy Duty Trucks Pollutants Public Health Residential Areas Routing Traffic Models Trucks
Publication/ Report Number:

UCR-17-10
DOI:

https://doi.org/10.6086/D1PT0J
Resource Type:

Dataset
Geographical Coverage:

California ; United States

California ; United States Less -
Corporate Publisher:

Pacific Southwest Region University Transportation Center (UTC)
Abstract:

This project explores how connected vehicle technology can be used to reduce the impacts of air pollutant emissions from freight vehicles. Specifically, the objective of this project is to develop new vehicle routing algorithms for determining travel routes for heavy-duty diesel trucks that would reduce the exposure of local residents to air pollutant emissions from these trucks. The core of the methodology is to first estimate the total amount of human exposure to pollutant emissions generated by a truck when that truck travels on a particular road segment. Once this is performed for all road segments, the estimated exposure value can be used in a least cost path algorithm to find a travel route that would minimize the total exposure value for the trip. To evaluate the potential benefits of this air pollution mitigation strategy, simulation-based experiments were carried out using the Reseda-Northridge area of Southern California as a case study. Overall, it was found that as compared to the fastest route, the low exposure route could result in more than 30% reduction in total air pollutant exposure for about 40% of the 400 simulated trips while keeping the increase in trip travel time to no more than 10%.
Format:

PDF
Funding:

USDOT Grant 69A3551747109
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:80c6a267f2169ec5976c569dc1e21ee3276a2ef4bd5ccaa133ee86d485470120
Download URL:

https://rosap.ntl.bts.gov/view/dot/54632/dot_54632_DS1.pdf
File Type:

Connected_Emission_Control_Technologies_for_Freight_Vehicles_Dataset_Metadata.json

json

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