**3. Perceived controllability**

*Models and Technologies for Smart, Sustainable and Safe Transportation Systems*

accidents [1].

the world by 2030.

could explain their behavior.

or even generalized: alcohol interlocks (that prevents drink driving), Intelligent Speed Assistance (that prevents speeding), and even autonomous cars (that prevent driving). Despite the considerable efforts of car engineers, and the crucial role of traffic laws to increase road safety with licensing and enforcement conditions, there will always be someone in the car that will have to make some decisions and inappropriate behaviors are often considered as contributing for a large part to

Traffic accidents currently represent one of the biggest health problems in the world. According to the World Health Organization [2], the number of road traffic deaths continues to rise steadily, reaching 1.35 million in 2016. There has also been more progress in reducing the number of road traffic deaths among middle- and high-income countries than low-income countries. There has been no reduction in the number of road traffic deaths in any low-income country since 2013. According to the World Health Organization [3], based on motorization in the developed world, traffic accidents are expected to become the fifth leading cause of death in

There are numerous causes that can explain traffic accidents and their severity. These can range from external factors such as infrastructure (i.e. road maintenance or design), the weather or those related to the vehicle (i.e. age) to human factors. Our interest is focused on human factors, not so much in the physiological characteristics of the driver (i.e. age, gender, …), but as in the psychological processes that

An empirically verified fact is that the majority of traffic accidents occur as a result of risky behaviors that drivers assume, more or less, voluntarily. Drivers are not aware of the perception of risk, cognitive overload and the subjective perception of control that we believe we have. We wrongly estimate the probabilities of obtaining a desired result. On many occasions, we are unable to learn from failures since we attribute failures to external factors. Awareness of how this cognitive process works and involvement in driving could favor the modification of risk behaviors. We start from the study of the driver's personality traits, specifically optimism

and pessimism [4]. Scheier and Carver [5] have characterized optimism as a

how these thoughts play a prominent role in decision-making.

**2. Optimism and pessimism in road safety**

powerful predictor of behavior. Optimistic people can pursue risky goals, where the chances of success are minimal and have many factors against them; as long as they believe that in their case they can achieve what they want (i.e., perceived controllability) [6]. These drivers predict future events, and therefore anticipate what results they may obtain. They explain in a reasoned way about their intentional behavior and plan their behaviors to achieve the desired results [7–9]. Our interest starts from the study of a type of thoughts (i.e., prefactuals and counterfactuals) that reflect the intention of the person, based on the causal inferences that are established; and

In the study of the human factor and road safety, a key component are the driver's own personality traits. Like Hampson [10], we consider personality processes to analyze how personality manifests itself in the thoughts, feelings, and behaviors of people to give rise to consequent results. Different investigations have focused on personality traits, such as optimism and pessimism [4]. From the theory of the self-regulation of behavior proposed by Scheier and Carver [11], it is contemplated that optimistic people are the ones who believe they can achieve a desirable outcome, and strive to do so. Pessimists, on the other hand, consider that the outcomes are unattainable, and either give up or do not commit to the actions that would lead

**78**

In road safety, it is the driver's own behavior, more or less voluntary, that causes traffic accidents in most cases [21]. The role of perceived controllability is decisive, since drivers, on the one hand, frequently underestimate the probability that they may experience negative events; and on the other hand, they tend to overestimate that they experience positive events, especially when they believe they have sufficient personal resources to face situations or challenges [22]. A theoretical model focused on the field of driving, such as the Task–Capability Interface (TCI) model [23], analyzes the relationships established between the driving task and the capability of the driver. The model indicates that both elements interact to determine task difficulty and the outcome for the driver in terms of whether control is maintained or lost. Azjen [24] specifically insisted in the driver's control beliefs. So, he contemplates that, "Perceived control is determined by control belief concerning the presence or absence of facilitators and barriers to behavioral performance, weighted by their perceived power (impact of each control factor to facilitate or inhibit the behavior)".

This control belief is what can have a direct relationship with the intention of the driver. In this regard, Montaño and Kasprzyk, [25] give a determining role to perceived control in the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), which assumes that the best predictor of action is intention. When a person has the intention of taking an action, and believes that they control the process to carry it out, the chances of that intention turning into action are very high. Furthermore, Like Harris [26], we think that perceived controllability is a powerful and robust psychological variable that can help predict behavior, as it reflects the intentions of the driver.

On the other hand the results of some studies show reveal that the possession of smart car technologies influences on drivers' perception of control and attachment. While the previous studies have dealt with perceived control as a predictor of the traffic safety behavior, new studies [27] examines it as one of the 'effects' of smart car technology. This is because the extent to which a driver feels easy or difficult to perform the function of driving will vary depending on the degree of possession and use of smart car technology. Recent studies show contradictory results on this issue. For example, Alliani et al. [28] have found that parking becomes easier under a smart parking system based on vehicle-to-vehicle communication. Birrell and Fowkes [29] have verified that the use of smartphone applications during vehicle operation is very informative rather than visually distractive. It has also been shown that context-based or simulation technologies such as head- 6 up displays and in-vehicle information systems contribute to driving space recognition and information acceptance [30, 31]. These studies support that smart car technology helps drivers feel easier to control the vehicle than before. As many advertisements claim, smart car technologies enhance driving pleasure and control by reducing the driver's cognitive effort in manipulating the vehicle.

The motivational cognitive theoretical models within the Traffic Psychology model have focused especially on the study of risk perception and decision-making. Ajzen [24] incorporated the construct of perceived control over the performance of the behavior, to the Theory of Planned Action, to explain the risks assumed by the driver. In some cases, perceived control may be linked to situations of assumed risk, in which the driver behaves prudently, safely, etc., as predicted by the Zero Risk Model. This model incorporates motivational factors in driver's decisions making [32]. In other cases, when they face risky situations, they drive showing mastery, skill, technique, etc. These skills are determined by the driver's subjective perception of the risk of suffering a road accident (i.e., perceived risk) and by the level of risk willing to accept or tolerate (i.e., perceived risk level), as detailed in the Theory of Homeostasis of the Risk [33].

We previously noted that, cognitive biases in optimism and risk perception. Now, we have contemplated how perceived control can be understood as a generalized belief (i.e., illusion of control) related to one's own person. From the theory of self-regulation of behavior proposed by Scheier and Carver [11], commented previously. The conception of perceived controllability is also integrated. Either the intention or/and behavior would show a direct relation with the feedback control. Where the perceived control would be a generalized belief more related to oneself than to a specific situation. In contrast to the expectations of self-efficacy [34], which would be related to specific beliefs about one's ability to successfully perform a task in a given situation.

In the context of driving, perceived high control can overstate your own ability. This leads us to consider that both optimism and the perceived controllability of the event are closely related [35, 36]. In fact, people manifest their optimistic biases in their perception of personal risk [37, 38], and when they have an accident, they tend to attribute it to external factors (eg, rain, a blowout, etc.), and not to internal factors related to driving [39, 40]. This is because drivers show a tendency to think that they are more skilled than other drivers [41–43]. In addition, they think that they are more likely to obtain the desired results, regardless of the tasks they have to perform [44]. McKenna [22] pointed out how drivers believe they are less likely, in relation to others, to suffer a traffic accident, if they are the ones who drive (i.e, personal control). But if they were passengers, the chances of suffering an accident would be equal to those of the rest of the people. It is the illusion of control that leads them to attribute the successes of driving to their own ability and not to the influence of external factors [19, 45].

**81**

*Cognitive Profile of Optimistic Offender Drivers Affected by Psychological Interventions…*

technology [53] can also weaken the sense of control over automobiles.

We have commented that most traffic accidents are due to risky behaviors that drivers assume, more or less, voluntarily. Drivers are generally unaware of the perception of risk and the subjective perception of control during driving. They erroneously estimate the probabilities of obtaining a desired result and, at these times, are unable to learn from failures as they attribute failures to external factors, beyond their control. Next, we will focus on a type of factual thoughts that capture

The ultimate goal of any study focused on the human factor within Road Safety, is to be able to explain or predict what a driver could do in the future. As in previous sections, we continue to focus on intention as a predictor of action. At this moment, we incorporate thinking as an explanatory variable. We believe, like Malle and Tate [54], that the best way to explain a future event is based on reasoned explanations of intentional behavior. In our daily life, we continuously anticipate and predict what possible results we could obtain, and with this we plan what we must do to achieve our objectives [8, 9]. Similarly, thoughts about what could have been or what could have been done are frequent, especially after disappointing results [55]. The thoughts that we simulate before the event are called "prefactual", and those alternative thoughts that appear after the event has occurred or that the results have

On the one hand, prefactual thoughts focus on predicting behavior and have to do with intentions to take future action. These types of thoughts appear before taking an action and, the subject can generate various alternatives to achieve the objective (eg, "If it were at the established speed, then it would avoid a fine"). It is important to note that, at the time the thought is generated, neither the alternatives nor the results have been carried out, and may or may not be carried out in the future [61]. On the other hand, counterfactual thoughts are important because they imagine changing aspects of the mental representation of reality. In this cognitive process, different alternatives are generated and compared with the results obtained [55]. Therefore, counterfactual thinking focuses on those thoughts about what

In these types of thoughts, the subject's intentionality is reflected in the subjec-

tive perception of control it shows, in the choice of alternatives and the probability of achieving the proposed objectives. Under the structure of a conditional

On the other hand, there are also studies that show that smart car technology does not affect or even reduce control. Rajaonah et al. [46] conducted an experimental study, but did not reveal the relationship between driving assistance and the driver's confidence. Larsson [47] shows the more the driver uses ADAS, the more (s) he perceives the limits of the device itself. Stanton and Young [48] also explain that vehicle automation can help in situational awareness, but does not affect control over the vehicle. In a situation where the smart car technology is not yet complete and the driver is not assimilated enough, the smart car technology may cause a burden of cognitive overload or hyper-connection. The fatigue of the operation of the media device may interfere with the control of the vehicle. Featherstone [49] emphasizes the emergence of new risks as the degree of dependence on software is increased, mentioning the driver needs to constantly manage various technical devices and information, like an airplane pilot. Different autors [50–52] also suggest that manipulating a smartphone or a digital device attached to the vehicle during operation increases the accident rate. Concerns about malfunctioning of smart car

*DOI: http://dx.doi.org/10.5772/intechopen.96249*

the intentionality of the drivers.

**4. Prefactual and counterfactual thoughts**

already been obtained, are known as "counterfactual" [56–60].

might have been, if other actions had been different [62–64].

#### *Cognitive Profile of Optimistic Offender Drivers Affected by Psychological Interventions… DOI: http://dx.doi.org/10.5772/intechopen.96249*

On the other hand, there are also studies that show that smart car technology does not affect or even reduce control. Rajaonah et al. [46] conducted an experimental study, but did not reveal the relationship between driving assistance and the driver's confidence. Larsson [47] shows the more the driver uses ADAS, the more (s) he perceives the limits of the device itself. Stanton and Young [48] also explain that vehicle automation can help in situational awareness, but does not affect control over the vehicle. In a situation where the smart car technology is not yet complete and the driver is not assimilated enough, the smart car technology may cause a burden of cognitive overload or hyper-connection. The fatigue of the operation of the media device may interfere with the control of the vehicle. Featherstone [49] emphasizes the emergence of new risks as the degree of dependence on software is increased, mentioning the driver needs to constantly manage various technical devices and information, like an airplane pilot. Different autors [50–52] also suggest that manipulating a smartphone or a digital device attached to the vehicle during operation increases the accident rate. Concerns about malfunctioning of smart car technology [53] can also weaken the sense of control over automobiles.

We have commented that most traffic accidents are due to risky behaviors that drivers assume, more or less, voluntarily. Drivers are generally unaware of the perception of risk and the subjective perception of control during driving. They erroneously estimate the probabilities of obtaining a desired result and, at these times, are unable to learn from failures as they attribute failures to external factors, beyond their control. Next, we will focus on a type of factual thoughts that capture the intentionality of the drivers.
