Traffic accidents are a complex phenomenon resulting from a combination of environmental, vehicular and human factors, which have become one of the leading causes of death worldwide. Inattention is one of the main factors contributing to traffic accidents. The aim was to analyze the relationships between attention and the error proneness while driving. Posner's model states three attentional networks quantified by reaction time measures: orienting, alerting, and executive control (Posner, 1994; Fan et al., 2002). Orienting is responsible for the information selection. Alerting facilitates achieving and sustaining an alert state. Executive attention controls interference and solves conflicts between possible responses. Driver inattention was conceptualized from a perspective of individual differences as a "tendency or personal propensity of drivers to experience attentional lapses" (Ledesma et al., 2010, 2015). This tendency can be expressed at different levels of driving behavior: operational level, maneuvering, and strategic level (Michon, 1985). The sample consisted of 70 drivers from Buenos Aires (Argentina), both genders (57% female; Mage= 29.29; sd= 9.258; M experience years = 9.83; sd= 8.861), inclusion criteria: driver's license, regular driving during the last two months (at least once a week), normal vision, and at least one year of driving experience. Factorial design 2 (low- high for each of the attentional networks) x 2 (gender). Measures: ARDES-ERIC (Ledesma et al., 2010): a 19-items self-report instrument to evaluate individual differences in the propensity to commit attentional failures while driving and can be classified according to the driving task level at which they occur (navigation, maneuvering, or control) (Alpha: .88; navigation Alpha: .744, maneuvering Alpha: .727, and control Alpha: .770), Attention Network Test (Fan et al., 2002) to measure three attentional networks: alerting (Alpha: .52), orienting (Alpha: .61), and executive attention (Alpha: .77) and RT attention (Alpha: .87) and a sociodemographic questionnaire that includes question about driver behavior (e.g. frequency and experience). Results show that no relationship was detected between ARDES and age but there are significant correlation between ARDES and driving task level with Global Reaction Time (Global RT). ANOVA results show a significant interaction between Global Reaction Times and expertise on driving errors [F(1,64)= 7.746; p < .01; η²= .108]. Experts drivers with low RT (lower processing speed) have a higher propensity to commit attentional failures while driving (Mlow rt= 35.58; sd= 13.08; Mhigh rt= 26.95; sd= 5.21). There are no interactions between Global RT, sociodemographics variables (age, gender), and driving frequency on propensity to commit errors. Global rt correlates significantly with total score driving errors (r= .373, p < .01). Executive Attention has a significant effect on total driving errors [F(1,66)= 3.760; p= .05; η²=.054], and only on the Control Dimension [F(1,66)= 7.889; p < .01; η²=.124]. There are no effects of Alerting and Orienting on total driving errors neither on each dimension of driving. A linear regression model involving the Orientation network and Global rt explained the 20% of the total variance of the error proneness while driving (R2 adjusted= .203). A higher level of Orienting attention is related to a lower propensity to commit errors (ß= -.332; p < .01), and a lower processing speed (higher Global RT) explained higher driving errors (ß = .242; p < .05). Results are consistent with previous studies (López-Ramón et al., 2011) and provide new evidence about the role of executive control on specific dimensions of driving. In addition, the findings provide new evidence on the role of reaction times and attentional networks, in interaction with sociodemographic variables and expertise on the propensity to commit errors while driving. Limitations and theoretical-practical implications will be discussed. [ABSTRACT FROM AUTHOR]