Eva Michelaraki1, Christos Katrakazas2, George Yannis1, Ashleigh Filtness3, Rachel Talbot3, Graham Hancox3, Fran Pilkington-Cheney3, Kris Brijs4, Veerle Ross4, Hélène Dirix4, An Neven4, Roeland Paul4, Tom Brijs4, Petros Fortsakis5, Eleni Konstantina Frantzola5, Rodrigo Taveira6. 1. National Technical University of Athens, Department of Transportation Planning and Engineering, 5 Heroon Polytechniou str., GR-15773 Athens, Greece. 2. National Technical University of Athens, Department of Transportation Planning and Engineering, 5 Heroon Polytechniou str., GR-15773 Athens, Greece. Electronic address: ckatrakazas@mail.ntua.gr. 3. Transport Safety Research Centre, Loughborough University, Loughborough LE11 3TU, United Kingdom. 4. UHasselt, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium. 5. OSeven Single Member Private Company, 27B Chaimanta Str., GR-15234 Athens, Greece. 6. Barraqueiro Transportes, Avenida Santos e Castro, 1750-265 Lisboa, Portugal.
Abstract
INTRODUCTION: Currently, risky driving behaviour is a major contributor to road crashes and as a result, wide array of tools have been developed in order to record and improve driving behaviour. Within that group of tools, interventions have been indicated to significantly enhance driving behaviour and road safety. This study critically reviews monitoring technologies that provide post-trip interventions, such as retrospective visual feedback, gamification, rewards or penalties, in order to inform an appropriate driver mentoring strategy delivered after each trip. METHOD: The work presented here is part of the European Commission H2020 i-DREAMS project. The reviewed platform characteristics were obtained through commercially available solutions as well as a comprehensive literature search in popular scientific databases, such as Scopus and Google Scholar. Focus was given on state-of-the-art-technologies for post-trip interventions utilized in four different transport modes (i.e. car, truck, bus and rail) associated with risk prevention and mitigation. RESULTS: The synthesized results revealed that smartphone applications and web-based platforms are the most accepted, frequently and easiest to use tools in cars, buses and trucks across all papers considered, while limited evidence of post-trip interventions in -rail was found. The majority of smartphone applications detected mobile phone use and harsh events and provided individual performance scores, while in-vehicle systems provided delayed visual reports through a web-based platform. CONCLUSIONS: Gamification and appropriate rewards appeared to be effective solutions, as it was found that they keep drivers motivated in improving their driving skills, but it was clear that these cannot be performed in isolation and a combination with other strategies (i.e. driver coaching and support) might be beneficial. Nevertheless, as there is no holistic and cross-modal post-trip intervention solution developed in real-world environments, challenges associated with post-trip feedback provision and suggestions on practical implementation are also provided.
INTRODUCTION: Currently, risky driving behaviour is a major contributor to road crashes and as a result, wide array of tools have been developed in order to record and improve driving behaviour. Within that group of tools, interventions have been indicated to significantly enhance driving behaviour and road safety. This study critically reviews monitoring technologies that provide post-trip interventions, such as retrospective visual feedback, gamification, rewards or penalties, in order to inform an appropriate driver mentoring strategy delivered after each trip. METHOD: The work presented here is part of the European Commission H2020 i-DREAMS project. The reviewed platform characteristics were obtained through commercially available solutions as well as a comprehensive literature search in popular scientific databases, such as Scopus and Google Scholar. Focus was given on state-of-the-art-technologies for post-trip interventions utilized in four different transport modes (i.e. car, truck, bus and rail) associated with risk prevention and mitigation. RESULTS: The synthesized results revealed that smartphone applications and web-based platforms are the most accepted, frequently and easiest to use tools in cars, buses and trucks across all papers considered, while limited evidence of post-trip interventions in -rail was found. The majority of smartphone applications detected mobile phone use and harsh events and provided individual performance scores, while in-vehicle systems provided delayed visual reports through a web-based platform. CONCLUSIONS: Gamification and appropriate rewards appeared to be effective solutions, as it was found that they keep drivers motivated in improving their driving skills, but it was clear that these cannot be performed in isolation and a combination with other strategies (i.e. driver coaching and support) might be beneficial. Nevertheless, as there is no holistic and cross-modal post-trip intervention solution developed in real-world environments, challenges associated with post-trip feedback provision and suggestions on practical implementation are also provided.