Publication

The Sweden Michigan Naturalistic Field Operational Test (SeMiFOT) project – a SAFER project running from January 2008 to December 2009 – gathered 13 organizations from the automotive industry (AB Volvo, Autoliv, Lindholmen Science Park, Länsförsäkringar, SAAB, Scania, Volvia, Volvo Cars), road authority (Swedish Road Administration), and academia (Chalmers, VTI, SP, UMTRI) around the topic of development of the Naturalistic FOT method. This method combines elements from both Naturalistic Driving Studies and Field Operational Tests, as also can be seen in the recent Distraction in CVO study (Olson et al., 2009) and the SHRP2 project (Boyle et al., 2009). In addition to these organizations, the SeMiFOT was partly financed by Swedish Governmental Agency for Innovation Systems (VINNOVA) and Michigan Department of Transportation (MDOT). 39 primary and secondary drivers (27 male, 11 female, mean age 41.3) drove 14 vehicles (10 cars, 4 trucks) a total of 171440 km for 2944 hrs in 7934 trips during a data collection period of over 6 months. The following safety sytems were included across a mix of vehicles: Adaptive Cruise Control, Forward Collision Warning with Emergency Brake, Lane Departure Warning, Blind Spot Information System, Electronic Stability Control, and Impairment Warning. The main advances by SeMiFOT address challenges related to (a) technology and implementation, and (b) analytical approaches. Some advances regarding technology and implementation: Review and analysis of a wide range of commercially available data acquisition systems from USA, EU and Japan, and their potential use in together with insurance companies; In-house development of state-of-the-art data acquisition systems, database/storage, and analysis tools together with UMTRI; Implementation of data handling and sharing procedures for a joint database sharing both open and proprietary data from 4 OEMs; Importantly, SeMiFOT also provided the opportunity for learning and development on a large variety of topics which were very practical or mundane. The time spent on data acquisition and data preparation for analyses far exceeded expectations and future gains in these areas are particularly useful. Highlights regarding advances in analytical approaches include: Development of the Crash-Relevant Events analysis method, involving a new trigger approach, coding scheme, integration with accident statistics geographically, and a new CRE-based safety impact assessment methodology; Development of a novel Events-Prevented analysis method performing “what-if” analyses emerging out of parameters from specific situations; Development and implementation of visual behavior analyses of data from 13 eyetrackers, which revealed large quality difficulties in sensing and classification of eye/head movements in naturalistic data; Implementation of map-matching and use of map-data in analysis of automatic speed camera; Integration of the naturalistic FOT method into company development processes.