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Title: Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint

Abstract

The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs andmore » HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.« less

Authors:
 [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1412834
Report Number(s):
NREL/CP-5400-70473
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: To be presented at the Transportation Research Board (TRB) 97th Annual Meeting, 7-11 January 2018, Washington, D.C.
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; navigation API; fuel-saving assessment; GPS travel data; hybrid electric vehicles; fuel savings

Citation Formats

Zhu, Lei, Holden, Jacob, and Gonder, Jeffrey D. Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint. United States: N. p., 2017. Web.
Zhu, Lei, Holden, Jacob, & Gonder, Jeffrey D. Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint. United States.
Zhu, Lei, Holden, Jacob, and Gonder, Jeffrey D. Wed . "Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint". United States. doi:. https://www.osti.gov/servlets/purl/1412834.
@article{osti_1412834,
title = {Navigation API Route Fuel Saving Opportunity Assessment on Large-Scale Real-World Travel Data for Conventional Vehicles and Hybrid Electric Vehicles: Preprint},
author = {Zhu, Lei and Holden, Jacob and Gonder, Jeffrey D},
abstractNote = {The green routing strategy instructing a vehicle to select a fuel-efficient route benefits the current transportation system with fuel-saving opportunities. This paper introduces a navigation API route fuel-saving evaluation framework for estimating fuel advantages of alternative API routes based on large-scale, real-world travel data for conventional vehicles (CVs) and hybrid electric vehicles (HEVs). The navigation APIs, such Google Directions API, integrate traffic conditions and provide feasible alternative routes for origin-destination pairs. This paper develops two link-based fuel-consumption models stratified by link-level speed, road grade, and functional class (local/non-local), one for CVs and the other for HEVs. The link-based fuel-consumption models are built by assigning travel from a large number of GPS driving traces to the links in TomTom MultiNet as the underlying road network layer and road grade data from a U.S. Geological Survey elevation data set. Fuel consumption on a link is calculated by the proposed fuel consumption model. This paper envisions two kinds of applications: 1) identifying alternate routes that save fuel, and 2) quantifying the potential fuel savings for large amounts of travel. An experiment based on a large-scale California Household Travel Survey GPS trajectory data set is conducted. The fuel consumption and savings of CVs and HEVs are investigated. At the same time, the trade-off between fuel saving and time saving for choosing different routes is also examined for both powertrains.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Dec 06 00:00:00 EST 2017},
month = {Wed Dec 06 00:00:00 EST 2017}
}

Conference:
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