Vehicle-based Sensing for Energy and Emission Reduction

Li, Xiaopeng; Liang, Zhaohui; Shi, Xiaowei; Yao, Handong

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Vehicle-based Sensing for Energy and Emission Reduction

2021-12-14
By Li, Xiaopeng ; Liang, Zhaohui ; Shi, Xiaowei

File Language:

English

Details

Creators:

Li, Xiaopeng ; Liang, Zhaohui ; Shi, Xiaowei ; Yao, Handong
Corporate Creators:

University of South Florida. Department of Civil and Environmental Engineering ; Cornell University. Center for Transportation, Environment, and Community Health
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:
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

07/01/2020-09/30/2021
Corporate Publisher:

Cornell University. Center for Transportation, Environment, and Community Health. (CTECH)
Abstract:

Emerging automated vehicles (AV) may be able to provide advanced information about the surrounding information with video cameras, radar sensors, lidar sensors, etc. Such information will enable estimating and predicting transportation system states on mobility, energy, and emissions. In this study, a physical informed neural network is developed to perform an accurate tire-road friction estimation by utilizing those advanced vehicle sensors. A runway friction tester is employed as the ground truth. More than 15,000 global positioning system (GPS) date points and other vehicle dynamic data points are collected during the field experiment, as a result, short convergence time and desired prediction accuracy are achieved by introducing the magic tire model and the slip-slop factor into the loss function.
Format:

PDF
Funding:

69A3551747119
Download URL:

https://rosap.ntl.bts.gov/view/dot/60816/dot_60816_DS1.pdf
File Type:

[PDF - 801.87 KB]
Collection(s):

Artificial Intelligence Deployment Center of Excellence (AI COE) ; Autonomous Vehicles ; University Transportation Centers
Main Document Checksum:

urn:sha-512:135c9e9a109560eb47d064c8a3e06c39d3610e458774c2f325a130d531e2a296b5331717ba29f5d5b0b5a388c88b8119c8c814b6c3d60275648d31f11b1734a8

File Language:

English

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