Article Preview
TopIntroduction
Owing to the current advancement in technology, the autonomous industry’s predilection for Autonomous Vehicles (AVs) is plausible. It has been observed that automobile companies have proliferated ever since leading market giants like Tesla, Volvo and Bosch have contributed towards this field of research and towards the field of Industry 4.0. The concept of self-driving cars was first introduced by Norman Bel Geddes in 1939 GM’s exhibit which instigated the automotive industry to persevere in this domain. Thus, all the efforts are put forth to achieve a singleton goal of making these autonomous robots, a commercial product with complete social acceptance. Among the various technologies used in these self-driving cars, the most prominent one is, Internet of Things (IoT) which encompasses the ability to transfer data over a network without human interaction. Subsequently, the efficient operation of an AV requires extensive efficient information management for service delivery.
Information management enables the stakeholders to manage their data assets judiciously using information and communication technologies (ICTs) to make effective decisions and meet operational and strategic objectives. It is a cyclic process of collecting and identifying needs, storing and organising information, dissemination of products and services and ultimately destruction of information (Detlor, 2010). With the disembarkation of the shared communication, demand responsive transit and telematics-based system in AV, new information management methods are required to support this developing field of technology. Szilárd Szigeti et al. (Szigeti, Csiszár, & Földes, 2017) study presented a coherent model of the architecture and functions of the complex information system, taking into account its operators and users, which further aimed to aid in the future development of related projects.
According to Hussain and Zeadally (Hussain & Zeadally, 2019), an autonomous car can be defined as a computer-controlled entity which can automatically detect and identify the essential features in its surroundings and accordingly make decisions to operate smoothly without threat to ethical and safety standards. As suggested by the National Highway Traffic Safety Administration (NHTSA), they can be classified into levels of autonomy which is delineated in Figure 1. (The Evolution of Automated Safety Technologies, n.d.). Level 0 encompasses the vehicles with complete human control where functions are performed manually by the driver. Level 1 depicts ‘driver assistance’ which includes common functionalities present in majority of the cars nowadays, such as cruise control. ‘Partial automation’ is depicted by level 2, which activates in peculiar scenarios and aids in the automatic acceleration, steering and applying brakes in the car. However, the vehicle’s independent decision is still considered to be the responsibility of the driver and therefore human alertness is a necessity. Level 3 refers to the ‘conditional automation’. This activates when the favourable situations exist and the autonomous system can perform various driver tasks on its own along with the precaution that the driver must be prepared to overtake the controls whenever necessary. Level 4 corresponds to high automation which means on the suitable conditions of the surroundings, the AV can perform complete operations independently without any input from the human. Furthermore, in level 5, ‘full automation’ is expected and this is where self-driving is justified to its full potential. The vehicle underlying in this category can handle any road and any condition that a human driver can face thus the only input required from the driver is to enter destination. Indeed, within the purview of the discussed architecture, the automotive industry is currently as level 2+ (Ionita, 2017). Meanwhile, level 3 vehicles are commercially available, their competency is yet to be proved. However, in the current scenario, there is no strict definition for the levels of autonomy due to which, any level of autonomy is referred to as autonomous (Faisal, Yigitcanlar, Kamruzzaman, & Currie, 2019).
Figure 1.
Commonly referenced levels of Autonomy