A Modeling Framework for Connectivity and Automation Co-simulation

Conference · Tue Apr 10 04:00:00 EDT 2018

DOI:https://doi.org/10.4271/2018-01-0607· OSTI ID:1482387

Kim, Namdoo; Karbowski, Dominik; Rousseau, Aymeric

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.

• Research Organization: Argonne National Laboratory (ANL)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technology
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1482387
• Country of Publication: United States
• Language: English