Professor Richard Romano

Profile

I have over twenty five years of experience developing and testing AVs and ADAS concepts and systems using operator in the loop, hardware in the loop, and software in the loop simulation methods which began with the Automated Highway Systems (AHS) project while I directed the Iowa Driving Simulator in the early 1990's.

Employment History

• 2022-Present, Staff Researcher – Vehicle Systems, General Motors, Warren, MI
• 2021-2022, CTO, Granite Automation, Inc., Potsdam, NY
• 2015-2021, Leadership Chair in Driving Simulation, Institute for Transport Studies, University of Leeds
• 1997-2015, Founder and President, Realtime Technologies, Inc., Royal Oak, MI
• 1995-1997, Supervisor - Brake System Simulation, ITT Automotive, Auburn Hills, MI
• 1992-1995, Manager - Simulator Research and Development, University of Iowa
• 1990-1992, Research Engineer, University of Iowa

Professional Engagements

• Member, Simulation Subcommittee, Transportation Research Board, 1995-1998, 2003-2012
• Chair, Ground Vehicle Simulation Special Interest Group, IMAGE Society, 1996-2002
• Society of Automotive Engineers
• Safety Research using Simulation (SAFER-SIM) UTC Advisory Board

www.researchgate.net/profile/Richard_Romano3

Research interests

Key Research Interests

I am interested in the development, validation and application of transport simulation to support the human-centred design of vehicles and infrastructure.  This includes:

• Real-time multi-body and ground vehicle dynamics
• Motion drive algorithms
• Control loading for driving simulators
• Rapid development of geo-specific databases
• Ambient traffic models for driving simulators
• Autonomous vehicles
• Real-time software design
• Simulator sickness

Research Projects and Experience

Programme for Simulation Innovation (PSi) Theme 3 'Driving Simulation', CoI
Sponsor: EPSRC

Multi-Resolution of Ground Platform Dynamic Performance and Mobility, PI
Sponsor: US Small Business Administration

Designed a methodology and software to convert offline vehicle dynamics models into real-time models for use in driving simulators. Conversions of Cartesian based models into recursive formulations with cut joints and advanced numerical solvers were designed and implemented.

Integration of Vehicle Models and Analytical Simulations, PI
Sponsor: US Small Business Administration

Designed a methodology and developed software to rapidly convert and integrate vehicle models from multiple simulation environments and render the results in real-time in CAVE and PowerWall environments.

Simulator Monitor and Control (SMAC) System, PI
Sponsor: US Small Business Administration

Designed and developed a system that allows simulation centers to safely and effectively run laboratory-based operator in the loop simulations in a cost-effective fashion. This includes the development of a JavaScript based scenario scripting system now marketed as SimVista and a video and data collection system and after action review system (SimObserver).

Integrating a Motion Base into a CAVE Automatic Virtual Environment, PI
Sponsor: US Small Business Administration

Implemented a portable ground vehicle simulator with motion base that installs in a CAVE. Performed human center research to evaluate the best motion cues when driving off-road. Developed a new approach for steering control loading using a DSP and high rate vehicle dynamics.

Qualifications

• PhD, Motion Drive Algorithms for Large Excursion Motion Bases, Industrial Engineering, University of
• MASc, Aerospace Engineering, University of Toronto
• BASc, Engineering Science, University of Toronto

Student education

PhD Research Topics

I am happy to consider supervising research projects in a range of areas related to Key Research Interests or adjacent to them.  My current ideas include:

Robust, Long Haul, Distributed, Research Driving Simulation

Driving simulators have been used for human factors research and vehicle design for several decades.  In addition, distributed driving simulators have been used in training for a similar time period.  With the emergence of new vehicle and infrastructure technologies and methods to improve safety and reduce congestion such as Connected Vehicles (CV), Advanced Driver Assistance Systems (ADAS) and the potential deployment of Autonomous Vehicles (AV), research driving simulators need to be integrated into a distributed framework.  This framework will allow research with multiple drivers which is important when comparing the impact of new technologies with the existing driving environment.

Pedestrian Simulation

With the introduction of new Head Mounted Displays such as Oculus Rift and Samsung Gear VR, there is renewed interest in pedestrian interactive simulators. Oculus Rift based simulators have been recently created:

http://news.softpedia.com/news/uk-transportation-issues-are-being-currently-solved-using-virtual-reality-487981.shtml

However there are a multitude of challenges when using HMDs. It is not clear that a CAVE based pedestrian environment is not better for this type of research:

http://safersim.nads-sc.uiowa.edu/uploads/article_30/Virtual%20and%20Augmented%20Reality%20in%20Transportion%20-%20Examples%20from%20Academia.pdf

In addition to the user interface for the simulator, the underlying software is also a compelling area of research.  Making realistic city environments with excellent AI and rich compelling scenes is an additional challenge.  There is both a Human Factors component as well as a Computer Science component.  Research in either or both is encouraged.

Real-time Multi-Body Vehicle Dynamics

Gaming technology often focuses on impulse based dynamics while automobile manufacturers use multi-body physics and recursive multi-body dynamics.  To handle high frequency elements like bushings an implicit-explicit solver is often used.  There is an opportunity to integrate impulse based collisions, recursive multi-body dynamics, and implicit-explicit solvers to create new real-time solutions that can handle a variety of problems in automotive as well as other disciplines.

Research groups and institutes

• Human Factors and Safety

Current postgraduate researchers

• Davide Maggi
• Edward Lambert
• Mr Isam Bitar
• Kai Tian
• Yiming HOU