Who overtakes more? Explanatory analysis of the characteristics of drivers from low/middle and high-income countries on passing frequency

The passing manoeuvre requires a driver to make decisions and take actions which are dependent on his/her behavioural characteristics and driving ability. However, previous works on passing rate models have exclusively considered geometric and traffic-related variables. This study aims at bridging this gap by investigating the influence of driver profile (i.e., age, gender, nationality - Italian or Iranian - aggressive driving scores, driving exposure) on passing frequency. A driving simulation experiment involving 54 drivers (36 Italians, 18 Iranians) was conducted along a 6.67 km segment of a two-lane rural highway with passing manoeuvres permitted along 25% of its length. Controlled factors included traffic flow and speed in the oncoming direction, and speed in the driver direction, with a total of 27 scenarios assigned to drivers based on a 3³ confounded factorial design. A Poisson regression model was used to investigate the significance of independent variables. Age and gender and their interaction term were significant, thus the effects of age and gender on the number of passing manoeuvres are mutually interdependent. Furthermore, drivers who drive less often completed fewer overtaking manoeuvres. Sensitivity analyses were carried out to understand the magnitude of change in passing frequency attributable to a variation in the explanatory variables. The findings suggest that driver characteristics have a significant effect on passing frequency and should be considered when conducting a performance and safety evaluation of two-lane roads.     

What makes a good driver on public roads and race tracks? An interview study

Future vehicles may drive automatically in a human-like manner or contain systems that monitor human driving ability. Algorithms of these systems must have knowledge of criteria of good and safe driving behavior with regard to different driving styles. In the current study, interviews were conducted with 30 drivers, including driving instructors, engineers, and race drivers. The participants were asked to describe good driving on public roads and race tracks, and in some questions were supported with video material. The results were interpreted with the help of Endsley’s model of situation awareness. The interviews showed that there were clear differences between what was considered good driving on the race track and good driving on the public road, where for the former, the driver must touch the limit of the vehicle, whereas, for the latter, the limit should be avoided. However, in both cases, a good driver was characterized by self-confidence, lack of stress, and not being aggressive. Furthermore, it was mentioned that the driver’s posture and viewing behavior are essential components of good driving, which affect the driver’s prediction of events and execution of maneuvers. The implications of our findings for the development of automation technology are discussed. In particular, we see potential in driver posture estimation and argue that automated vehicles excel in perception but may have difficulty making predictions.     

Who’s more angry? Comparing driver anger and aggression within work and personal driving contexts

Anger and driver aggression increase crash risk. However, how these manifest according to the purpose of the journey (work vs personal) and the unique relationships between sources of anger and aggressive expressions of that anger is under-researched. The current study examined the relationships between different types of anger and aggression, recent crashes and infringements between drivers who drive mainly for work with those who drive mainly for personal reasons.Participants (N = 630) completed an online questionnaire reporting their driving anger tendencies across situations of travel delays, danger and hostility from others, frequency of aggressive driving (using the vehicle, verbal or physical) and crash and infringements in the previous year. Drivers were classified as work or personal drivers based on the percentage of the time they drove for each reason. Relationships between anger sources and aggression types were examined using Structural Equation Modelling, comparing models between the two groups. The relationships between aggression and safety outcomes were explored using Mann-Whitney U tests.The relationships between anger and aggression were similar across work and personal drivers. However, some group differences in the situations that contributed to anger and aggression were identified. Aggression was more frequent for drivers who drove mainly for work and had received a traffic violation, compared to those who had not received a traffic violation.These findings can inform the development of targeted interventions to manage the triggers of anger and aggression. Interventions are likely to impact work and personal drivers; thus, could target employers and road transport authorities.     

Eyes on the road,hands upon the wheel? Reciprocal dynamics between smartphone use while driving and job crafting

Smartphones are essential tools for communications and information management in organizational settings. However, smartphone use is a risky behavior when used while driving to and from work. As work experiences have been found to influence risky commuting behaviors, we hypothesized that job crafting, i.e., a set of proactive work behaviors through which employees change their job demands and resources, influences and is influenced by risky commuting behaviors. We argued that employees' smartphone use during driving commutes is related to how employees proactively choose to transform their demands and resources at work. A quantitative diary study was designed to investigate the process linking smartphone use during driving commutes to and from work and job crafting. A sample of 128 office employees completed two short daily questionnaires for five consecutive workdays (N = 627 observations). Results from multilevel analyses showed that daily talking on the phone while driving to work was positively associated with the proactive optimization of job demands, while daily proactive pursuing of challenging stimuli at work (i.e., seeking challenges) was positively related to looking at the phone when employees drove back from work. Furthermore, on days when employees reduced their hindering job demands, they reported less frequent talking on the phone while driving back from work. Results provide practical implications for the prevention of distracted driving and other risky driving behaviors.