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According to the NHTSA study of connected vehicle technology, Vehicle-to-Vehicle (V2V) communication has the potential to reduce crashes by up to 80 percent (NHTSA, 2014). Especially, Locative Mobile Social Network Systems (LMSNS) are becoming popular, enabling to connect and locate other road users (De Souza, 2010). However, most research is technology-driven, enabling cars to talk to each other, and does not take a fundamental view inside the nature of collaborative driving.
Interactions with other road users are an essential element of the driving activity, mostly negotiating on how to share a common section of a road (Rokotonirainy, Schroeter & Soro, 2014). These negotiations are often limited through the bandwidth of the communication channel and the connectivity between drivers. Although there exist pre-set traffic rules that apply to all road users, additional communication and interactions are necessary to make their intentions clear and to avoid accidents. In addition to the driving behavior itself, drivers often use lights or horns in order to exchange information, both being very limited in bandwidth. Therefore, this can lead to misunderstandings or conflicts, which potentially cause stress and extreme emotional responses such as aggressive driving behavior (Renner & Johannson, 2006; DCPC, 2005). For instance, an impatient driver activates the flash light on the highway to force vehicle in front to move to the first lane, which is normally perceived as aggressive by him/her.
Lamas et al. (2014) stated that the usage of innovate communication technologies may address exactly the problem of limited communication channels between different vehicles. Considering the information exchange and the technology readiness level of current V2V technologies, the front-seat passenger could be an intermediate facilitator in order to communicate with the other vehicle until those systems may take over in an automated driving environment.
Compared to the driver/co-driver communication and collaboration inside the vehicle, which is predominantly verbal and face-to-face, the interaction between driver/co-driver pairs across vehicles has specific communication attributes and challenges (Lamas et al., 2014). First, after closing a door of the car, “people are encapsulated in a domestic, cocooned, moving capsule, an iron bubble” (Urry, 2007, p. 120). Therefore, communication partners of different vehicles experience a spatial separation and physical barrier (Wang, 2017). Second, successful communication and collaboration is also constrained by the speed of the two vehicles and their relative position. Often drivers do not have much time to transmit their messages because the vehicles are travelling at high speed (Lamas et al., 2014). Third, drivers have to cope with the lack of visual information. Facial expressions and gestures are hard to recognize at night (Lamas et al., 2014). Fourth, being constrained in front of the steering wheel and interacting with non-human like machines on the road, drivers are detached from their environment and social society. As a result, their feelings of belongingness (Satici, Uysal & Deniz, 2016) are decreased. These and other aspects can make it difficult to verify the precise intent of another driver/co-driver pair as well to communicate with each other.