
Professor Andry Rakotonirainy
Faculty of Health,School - Psychology and Counselling,
Research - CARRSQ
Personal details
- Name
- Professor Andry Rakotonirainy
- Position(s)
- Centre Director, CARRS-Q and Professor
Faculty of Health,
School - Psychology and Counselling,
Research - CARRSQ - Principal Research Fellow
Faculty of Health,
School - Psychology and Counselling,
Research - CARRSQ - IHBI Membership
Institute of Health Biomedical Innovation (IHBI),
IHBI Health Projects,
IHBI Psych and Counc - IPTM - Discipline *
- Distributed Computing, Other Psychology and Cognitive Sciences
- Phone
- +61 7 3138 4683
- Fax
- +61 7 3138 7532
- r.andry@qut.edu.au
- Location
- View location details (QUT staff and student access only)
- Identifiers and profiles
-
- Qualifications
-
PhD in Computer Science (Universite de Paris VI)
- Professional memberships
and associations - PhD in 1995 from Universite Pierre Marie Curie (Paris 6) and French National Institute in Computer Science (INRIA).
- Director CARRS-Q.
- Research Professor in Intelligent Transport Systems and Human factors.
- Member of Institute of Health and Biomedical Innovation (IHBI) – Injury Prevention and Rehabilitation Domain at QUT; Faculty of Health
- Keywords
-
Intelligent Transport Systems, Pervasive computing, road safety
Biography
Professor Andry Rakotonirainy is the Director of CARRS-Q and founder of its Intelligent Transport Systems human factors research program, establishing its Advanced Driving Simulator laboratory. With 25 years research and management experience in computer science, he brings advanced expertise in road safety and ITS design and implementation. He is a member of the Australian Research Council (ARC) College of Experts and is a regular member of EU funded projects’ advisory boards. He has authored over 250 internationally refereed papers in prestigious journals and conferences. The impact of his research is significant, with one paper cited 994 times (4710 citations in total), and he has an h-index of 32. He has been awarded 11 Australian Research Council (ARC) grants, serves on international conference and journal committees, and reviews internationally competitive grants.
Professor Rakotonirainy’s ITS research has been recognised both nationally and internationally. He has proactively investigated the use of existing and emerging ITS from multiple disciplines such as computer science, mathematics, human factors, engineering, psychology and sociology. His research has made extensive use of driving simulators, traffic simulators and instrumented vehicles for developing system prototypes, assessing cost-benefits, understanding human errors and evaluating system deployment. He has been successful in securing numerous competitive grants and has established partnerships with many road safety stakeholders. Presently, he is involved in a€6,4 million EU funded (Horizon 2020) project called Levitate led by Loughborough University on ‘Societal Level Impacts of Connected and Automated Vehicles’. He isalso the lead researcher on two projects as part of CAVI initiative on Automated and Cooperative Vehicles.
- A large-scale pilot project validating the effectiveness of emerging cooperative vehicle technologies with Queensland’s Department of Transport and Main Roads (TMR), iMOVE CRC and QUT. The pilot will involve around 500 private and fleet vehicles retrofitted with Cooperative-ITS devices. The large-scale, 3.5 year project will commence with the design and equipment-testing phase, culminating in a 9 month on-road trial in Ipswich, Queensland in late 2019.
- Use of a small passenger automated vehicle (SAE level 4) to study human factor related issues with Queensland’s Department of Transport and Main Roads (TMR), iMOVE CRC and QUT.
Teaching
Research intensive Professor
Experience
- International experience in Intelligent Transport System (ITS) and human factors research (10 ARC grants, over 250 publications.
- Average research income of 4 Million dollars per year for the last five years
- Developed an extensive research network with industries, government bodies and international researchers.
Publications
- Ghasemi Dehkordi S, Larue G, Cholette M, Rakotonirainy A, Rakha H, (2019) Ecological and safe driving: A model predictive control approach considering spatial and temporal constraints, Transportation Research Part D: Transport and Environment p208-222
- Li X, Oviedo Trespalacios O, Rakotonirainy A, Yan X, (2019) Collision risk management of cognitively distracted drivers in a car-following situation, Transportation Research Part F: Traffic Psychology and Behaviour p288-298
- Vaezipour A, Rakotonirainy A, Haworth N, Delhomme P, (2019) A simulator study of the effect of incentive on adoption and effectiveness of an in-vehicle human machine interface, Transportation Research Part F: Traffic Psychology and Behaviour p383-398
- Li X, Vaezipour A, Rakotonirainy A, Demmel S, (2019) Effects of an in-vehicle eco-safe driving system on drivers' glance behaviour, Accident Analysis and Prevention p143-152
- Rastgoo M, Nakisa B, Rakotonirainy A, Chandran V, Tjondronegoro D, (2018) A critical review of proactive detection of driver stress levels based on multimodal measurements, ACM Computing Surveys p1-35
- Vaezipour A, Rakotonirainy A, Haworth N, Delhomme P, (2018) A simulator evaluation of in-vehicle human machine interfaces for eco-safe driving, Transportation Research, Part A: Policy and Practice p696-713
- Li X, Rakotonirainy A, Yan X, Zhang Y, (2018) Driver's visual performance in rear-end collision avoidance process under the influence of cell phone use, Transportation Research Record p55-63
- Nakisa B, Rastgoo M, Rakotonirainy A, Maire F, Chandran V, (2018) Long short term memory hyperparameter optimization for a neural network based emotion recognition framework, IEEE Access p49325-49338
- Larue G, Wullems C, Sheldrake M, Rakotonirainy A, (2018) Validation of a driving simulator study on driver behaviour at passive rail level crossings, Human Factors p743-754
- Ghasemi Dehkordi S, Larue G, Cholette M, Rakotonirainy A, (2018) Benefit assessment of new ecological and safe driving algorithm using naturalistic driving data, Proceedings of the 29th IEEE Intelligent Vehicles Symposium p1931-1936
For more publications by this staff member, visit QUT ePrints, the University's research repository.
Research projects
Grants and projects (Category 1: Australian Competitive Grants only)
- Title
- Intention-Aware Cooperative Driving Behaviour Model for Automated Vehicles
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP180103491
- Start year
- 2018
- Keywords
- Title
- Understanding impact of autonomous vehicles on behaviour and interactions
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP160101021
- Start year
- 2017
- Keywords
- Title
- Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP150100979
- Start year
- 2016
- Keywords
- Title
- CoopEcoSafe: a new cooperative, green and safe driving system
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DP140102895
- Start year
- 2014
- Keywords
- eco-driving; road safety; driver behavior
- Title
- The Australian naturalistic driving study: innovation in road safety research and policy
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP130100270
- Start year
- 2014
- Keywords
- Road Safety; Naturalistic Driving Study; Driver Behaviour
- Title
- Integrating Technological and Organisational Approaches to Enhance the Safety of Roadworkers
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP100200038
- Start year
- 2011
- Keywords
- Roadworker Safety; Road Construction Site Safety; Safety Culture; Workplace Health and Safety; Road Safety Policy; Speeding
- Title
- A unique driver assessment tool to improve four wheel drive and sedan driving competencies
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP0669606
- Start year
- 2006
- Keywords
- Road Safety; Intelligent Transport Systems; Driver Training;
- Title
- Ubiquitous Data Mining and Situation Awareness for Improving Road Safety
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- LP0560865
- Start year
- 2005
- Keywords
- Road Safety; Ubiquitous Data Mining
Supervision
Current supervisions
- Design and develop a predictive-interaction-aware crash risk assessment system
PhD, Principal Supervisor
Other supervisors: Dr Andy Bond - Augmented Reality to Improve Fallback-Readiness in Conditional Automated Vehicles
PhD, Associate Supervisor
Other supervisors: Associate Professor Ronald Schroeter, Professor Daniel Johnson - How Intended Pathway Information shared via an Augmented Reality HUD can assist in Semi-Automated Driving
PhD, Principal Supervisor
Other supervisors: Dr Sherrie-Anne Kaye
Completed supervisions (Doctorate)
- Building an Augmented Map for Road Risk Assessment (2013)
- An assessment system for evaluation of driving competencies (2011)
- An examination of monotony and hypovigilance, independent of fatigue: Relevance to road safety (2011)
- Mining Patterns and Factors Contributing to Crash Severity on Road Curves (2010)
- Predicting effects of monotony on driver's vigilance (2010)
- Reducing Uncertainty in New Product Development (2009)