TY - JOUR AU - Keay Lisa AU - Ivers R. AU - Coxon K. AU - Clarke E. AU - Brown J. AU - Chevalier A. AU - Chevalier A. AU - Wall J. AB -

The data presented in this article are related to the research article entitled "A longitudinal investigation of the predictors of older drivers speeding behavior" (Chevalier et al., 2016) [1], wherein these speed events were used to investigate older drivers speeding behavior and the influence of cognition, vision, functional decline, and self-reported citations and crashes on speeding behavior over a year of driving. Naturalistic speeding behavior data were collected for up to 52 weeks from volunteer drivers aged 75-94 years (median 80 years, 52% male) living in the suburban outskirts of Sydney. Driving data were collected using an in-vehicle monitoring device. Global Positioning System (GPS) data were recorded at each second and determined driving speed through triangulation of satellite collected location data. Driving speed data were linked with mapped speed zone data based on a service-provider database. To measure speeding behavior, speed events were defined as driving 1 km/h or more, with a 3% tolerance, above a single speed limit, averaged over 30 s. The data contains a row per 124,374 speed events. This article contains information about data processing and quality control.

AD - The George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia.
Safer Roads Consulting, 53 Lachlan St, Thirroul, NSW 2515, Australia.
Kolling Institute of Medical Research, Sydney Medical School, The University of Sydney, Level 10, Kolling Building 6, Royal North Shore Hospital, St Leonards, NSW 2065, Australia.
The Centre for Road Safety, Transport for NSW, Level 3, 84 Crown St, Wollongong, NSW 2500, Australia.
The George Institute for Global Health, Sydney Medical School, The University of Sydney, GPO Box 5389, Sydney, NSW 2001, Australia; School of Science and Health, Western Sydney University, Narellan Road Campbelltown, NSW 2560, Australia.
Neuroscience Research Australia (NeuRA), Margarete Ainsworth Building, Barker St, Randwick, NSW 2031, Australia. AN - 27294182 BT - Data Brief C2 - PMC4889889 CN - [IF]: 0.065 DP - NLM ET - 2016/06/14 LA - eng LB - AUS
INJ
FY16 N1 - Chevalier, Anna
Chevalier, Aran John
Clarke, Elizabeth
Wall, John
Coxon, Kristy
Brown, Julie
Ivers, Rebecca
Keay, Lisa
Netherlands
Data Brief. 2016 May 16;8:136-41. doi: 10.1016/j.dib.2016.05.016. eCollection 2016 Sep. N2 -

The data presented in this article are related to the research article entitled "A longitudinal investigation of the predictors of older drivers speeding behavior" (Chevalier et al., 2016) [1], wherein these speed events were used to investigate older drivers speeding behavior and the influence of cognition, vision, functional decline, and self-reported citations and crashes on speeding behavior over a year of driving. Naturalistic speeding behavior data were collected for up to 52 weeks from volunteer drivers aged 75-94 years (median 80 years, 52% male) living in the suburban outskirts of Sydney. Driving data were collected using an in-vehicle monitoring device. Global Positioning System (GPS) data were recorded at each second and determined driving speed through triangulation of satellite collected location data. Driving speed data were linked with mapped speed zone data based on a service-provider database. To measure speeding behavior, speed events were defined as driving 1 km/h or more, with a 3% tolerance, above a single speed limit, averaged over 30 s. The data contains a row per 124,374 speed events. This article contains information about data processing and quality control.

PY - 2016 SN - 2352-3409 (Electronic)
2352-3409 (Linking) SP - 136 EP - 41 T2 - Data Brief TI - Naturalistic speeding data: Drivers aged 75 years and older VL - 8 Y2 - FY17 ER -