Brief overview of driving activity and risk management respect to neuroscience

One of the most commonly used models to describe driving activity is the Michon model \cite{michon1985critical}. This approach divides driving behavior into two main classes: taxonomies and functional models. Taxonomies have the advantage of disturbing and classifying the different components of driving activity, but do not express the dynamics between these components. In turn, functional models, give an idea of the relationship between the elements, but are sometimes too restrictive and do not always go beyond their own field of study. Thus, the cognitive model of automotive activity by Michon is presented in a simple and flexible structure, which can group different hierarchical and theoretical levels \cite{michon1985critical}. The model is further divided into three main parts corresponding to levels of competence in driving activity. The level of rational operation, which contains all the necessary actions to control the car. The tactical level, which refers to placement and positioning maneuvers in traffic and infrastructure. Finally, the strategic level allows planning of driving objectives, route and choice of transportation mode. These different levels influence each other in such a way that driving conditions or the driver’s willingness to drive can change in any time. For instance, when a driver interacts with traffic and unexpectedly changes the route. Another example would be taking an exit off a highway, for which our strategic driving can change due to the availability of different options. The driver can make the tactical choice of overtaking, which involves significant speed reduction and lateral positioning of the vehicle at the rational operating level. On the contrary, the driver can also tactically choose not to make a road overtaking, which will facilitate the rational positioning of the vehicle to the next point on the route. The decision between these two options will depend in part on the driver’s risk management and perception. According to the risk homeostasis model \cite{wilde1998risk}, decisions corresponding to the strategic level of the Michon model \cite{michon1985critical} depend on an optimization of the driver’s risk decision making. In fact, the driver would choose the most appropriate manoeuvre based on four dimensions related to the risk homeostasis model: (i) expected benefits and (ii) expected costs of the risk behavior, and (iii) expected benefits and (iv) costs of the safe behavior. According to the risk model, driving always involves some risk. Likewise, there is always a goal to achieve. A driver will have a specific level of risk, deriving maximum benefit associated to the accomplishment of such a goal. The risk threshold would determine is the risk is worth taking in order to achieve a particular goal. Thus, risk taking may be voluntary if the individual decides to perform a maneuver by accepting the risks. In contrast, it can also be involuntary, because the individual could make a decision without knowledge of all the critical elements of the situation \cite{wilde1998risk}. Behaviors related to driving are directly linked with this real world experience. Unfortunately, given the internal/ecological validity trade-off, the majority of experimental laboratory approaches related to the driving activity and its risk management tend to lack ecological validity. These studies, focus on exploring the impact of optimization of sensory processing on decision-making as well as on executive functions [need citation]. In this sense, considering more reliable variables that are closer to real world driving behavior, should be a main goal in the design of experimental protocols. Thus developing a more ecological approach to studying the psychobiological correlates of the driving activity. We argue that experimental designs should aim at reproducing the complex and dynamic tasks that people face in their daily lives. It is for this reason that driving should be considered in relation to cognition, behavior, and technological devices in the actual environment where it occurs \cite{Menary_2013,Gallagher_2008}. Furthermore, the relationship between drivers and cars must be established as a joint cognitive system that functions in real-world settings. Consequently, any interventions aiming at improving and supporting the driving activity should focus on the neural bases of sensory, perceptual and cognitive functions and actions in relation to driving technologies and urban road settings. Providing thus opportunities for translational research between neuroscience, human behaviors variability, engineering, computer science, and public policy and socio-political sciences.
Recent knowledge about neural bases of sensory and cognitive functions underlying driving sheds light on the understanding of human behavior and to improve the performance in a wide range of driving settings [need citation]. A key area where neuroscientific interventions can be applied is in the creation of tailored strategies for optimizing perceptual sensory processing as a safety measure in automobile driving designed from and for the human brain. Reaching this goal would require examining sensory and perceptual processes in driving, which tend to be overly demanding on normal driving settings \cite{lee2008defining,walter2001neural,Deery_1999,Ranney_1994}. According to studies about accident records, the proportion of fatal crashes for drivers on highways is expected to increase due to demographic shifts in the modern cities \cite{mcgwin1998identifying,mcgwin1999characteristics}. Recent findings suggest a 155% increase by 2030, for instance, for drivers aged 65 and above \cite{lyman2002older}. These projections of increased crash risk for different type drivers can arise from age related factors and psychophysical performance associated with sensory, perceptual processing and attentional impairments, among others. These variables can in turn be caused by external factors such as distractions, as well as internal ones, such as a deteriorations in some perceptual modality (e.g. visual or hearing impairments) \cite{preusser1998fatal,owsley1991visual,ball1993useful}. For this reason, the study of the driving activity demands a multidisciplinary translational approach which must merge elements of cognitive psychology and human factors to study brain structure and function in everyday environments, which are often studied in isolation and so present a challenge in generalizing neurophysiological findings to predict driving safety behavioral actions. In this direction, cognitive neurophysiology can be used to explain and understand the mechanisms for instance of attentional breakdown that might be associated with driving behavior problems. Thus, a more complete picture of the the basic sensory processes that drivers need in the real-world might come from examining their performance in controlled laboratory studies to determine the the basic neurophysiological requirements for perceptual sensory processing to operate effectively and successfully in all driving scenarios. Future research on the driver’s performance might further explore the ability of sensory entrainment to modulate the sensory processing systems in order to determine how well the driver can compensate and improve their sensory, perceptual and behavioral ability. Results from these type of efforts might play a role in the reduction of accidents. A physiological perspective and neuroscientific approach to drivers’ perceptive skills can be useful to investigate a variety of cognitive states that affect various driving settings.