Modeling the effects of real time traffic information on travel behavior: A case study of Istanbul Technical University

Use of mobile technologies for driving, road accidents, health and psychological variables in Colombian drivers

“…This is partially due to the fact that the current study only investigates the use/non-use of each device. Investigating the frequency and function of use of these applications (Gokasar & Bakioglu, 2018) could lead to models with greater explanatory capacity on the use of such mdad. Even within the evolution of road mobility towards more autonomous vehicles, knowledge of drivers' psychological, emotional, and cognitive variables will be necessary to accommodate the maneuverability design of these vehicles and of mobile applications to the psychological competencies required for driving, taking into account the variables that may condition its use: impulsiveness (Wickens et al, 2008;Lazarus, Richard, Poulter, Powell, & Ypsilanti, 2019), tendency to road relapse (Lijarcio, Bosó, & Martí Belda, 2018), or, in our case, the educational level required to use and take advantage of the functions of these mobile applications.…”

“…In front of these situations, many public and academic efforts have been directed towards the development of traffic status estimating systems, necessary for the institutions responsible for managing traffic (Leduc, 2008;Kurzhanskiy & Varaiya, 2015) as well as for road users (Gokasar & Bakioglu, 2018) when it comes to making decisions about when to start a journey, which route to follow from the available options, foresee the arrival time, duration of the journey, among other uses (Astarita, Festa, & Giofré, 2018). So, driving efficacy is not simply a self-perception matter (Bannach & Bianchi, 2021); mobile technologies also have something to say.…”

“…It is based on the users' collaboration by direct participation or by indirect or passive drivers' participation, and it provides information on the vehicle's position only by activating the application (Barata et al, 2014). As for Google Maps®, it is a pre-installed application on most android system phones, which perhaps explains why this is one of the most used applications in some countries (Gokasar & Bakioglu, 2018) and interacts with other applications (Barata et al, 2014;Shi et al, 2018). In addition, it does not require direct registration and provides visualization and audio guidance of the route.…”

“…Now, in relation to human behavior, there have been developments of applications and devices to study the drivers themselves. Along the same line, through the data provided by the gps or mobile applications, the study of decision-making while driving has approached, to change lanes, to accelerate or to follow or not the route indicated by the mobile application (Gokasar & Bakioglu, 2018) driving styles (Stoichkov, 2013;Astarita et al, 2018), distractions (Astrain, Bernaus, Claverol, Escobar, & Godoy, 2003), or the level of aggressiveness when driving (Valana, Luele, Astartita, & Caruso, 2014).…”

A CPT modified interval type-2 hesitant fuzzy PROMETHEE II model to prioritize risks in self-driving vehicles

“…There is no doubt that driver behaviors or driving skills are playing an essential role in road traffic safety (Petridou et al, 2000). Typically, unsafe driver behavior includes traveling at higher speeds as legally allowed, using a mobile phone while driving, and so on (Gokasar et al, 2018). Vehicle fault (e.g., brake failure), or surrounding facilities conditions also causes road unsafety.…”