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Title: A Modeling Framework for Connectivity and Automation Co-simulation

Abstract

This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion. The framework, called RoadRunner, extends the capability of Autonomie, a vehicle energy consumption and performance modeling platform, to simulate the longitudinal movements of one or more user-defined vehicles along a user-defined route. In the first part of the paper, we provide an overview of how the framework is organized. The route attributes (position of traffic lights, grade, etc.) can be automatically extracted from a digital map after origin and destination are provided. The user defines which vehicle models to simulate and in which order. The Simulink model is then automaticallymore » generated from the scenario description. In the second part of the paper, we present an example case of a scenario with an eco-approach, using traffic signals that provide their signal phase and timing information to the vehicle. A two-stage control algorithm inspired by the literature is implemented to adjust the vehicle’s velocity while traveling through a signalized corridor with the goal of minimizing fuel consumption. Finally, we present simulation results for speed patterns and powertrain operations in typical roads with multiple intersection, comparing the energy savings with traditional driving of unconnected vehicles.« less

Authors:
; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technology
OSTI Identifier:
1482387
DOE Contract Number:  
AC02-06CH11357
Resource Type:
Conference
Resource Relation:
Journal Volume: 1; Conference: 2018 SAE World Congress Experience, 04/10/18 - 04/12/18, Detroit, MI, US
Country of Publication:
United States
Language:
English

Citation Formats

Kim, Namdoo, Karbowski, Dominik, and Rousseau, Aymeric. A Modeling Framework for Connectivity and Automation Co-simulation. United States: N. p., 2018. Web. doi:10.4271/2018-01-0607.
Kim, Namdoo, Karbowski, Dominik, & Rousseau, Aymeric. A Modeling Framework for Connectivity and Automation Co-simulation. United States. doi:10.4271/2018-01-0607.
Kim, Namdoo, Karbowski, Dominik, and Rousseau, Aymeric. Tue . "A Modeling Framework for Connectivity and Automation Co-simulation". United States. doi:10.4271/2018-01-0607.
@article{osti_1482387,
title = {A Modeling Framework for Connectivity and Automation Co-simulation},
author = {Kim, Namdoo and Karbowski, Dominik and Rousseau, Aymeric},
abstractNote = {This paper presents a unified modeling environment to simulate vehicle driving and powertrain operations within the context of the surrounding environment, including interactions between vehicles and between vehicles and the road. The goal of this framework is to facilitate the analysis of the energy impacts of vehicle connectivity and automation, as well as the development of eco-driving algorithms. Connectivity and automation indeed provide the potential to use information about the environment and future driving to minimize energy consumption. To achieve this goal, the designers of eco-driving control strategies need to simulate a wide range of driving situations, including the interactions with other vehicles and the infrastructure in a closed-loop fashion. The framework, called RoadRunner, extends the capability of Autonomie, a vehicle energy consumption and performance modeling platform, to simulate the longitudinal movements of one or more user-defined vehicles along a user-defined route. In the first part of the paper, we provide an overview of how the framework is organized. The route attributes (position of traffic lights, grade, etc.) can be automatically extracted from a digital map after origin and destination are provided. The user defines which vehicle models to simulate and in which order. The Simulink model is then automatically generated from the scenario description. In the second part of the paper, we present an example case of a scenario with an eco-approach, using traffic signals that provide their signal phase and timing information to the vehicle. A two-stage control algorithm inspired by the literature is implemented to adjust the vehicle’s velocity while traveling through a signalized corridor with the goal of minimizing fuel consumption. Finally, we present simulation results for speed patterns and powertrain operations in typical roads with multiple intersection, comparing the energy savings with traditional driving of unconnected vehicles.},
doi = {10.4271/2018-01-0607},
journal = {},
issn = {0148--7191},
number = ,
volume = 1,
place = {United States},
year = {2018},
month = {4}
}

Conference:
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