# Cloud Incubator Car: A Reliable Platform for Autonomous Driving
## 1 Introduction  
It appears clear that the road transport will be going through enormous changes in the near future (intelligent transport systems), although, presumably, gradual, in which new technologies will have a prevailing role [1]. Thus, in the Horizon 2020 EU work program, smart, green, and integrated transport are placed as the main pillars for transport in the future. Among the program lines the following can be distinguished: \"Safe and connected automation in road transport, where specific requirements are imposed on simple automation, limiting its foreseeable scope in the short term.\" Without a doubt the most disruptive technological challenge is focused on the so called autonomous vehicle and, the next step, autonomous cooperative vehicles [2]. However, some issues need to be addressed: (1) the operation must be completely reliable and safe [3]: this specification is a highly demanding requirement, which usually complies with limiting the application of these vehicles to controlled scenarios, simple applications, or at reduced speeds of operation. Thus, it is understood that autonomous driving is viable in dedicated lanes or areas in situations of congestion or in parking manoeuvres, which is already a reality in many cases. Collision avoidance safety systems are more complex, especially those that take control of the vehicle in emergency manoeuvres; (2) the cost of sensors and control hardware must comply with what the market can assume, so that the mass production of vehicles can be economically affordable [4]; (3) much work is still necessary concerninglegal and social issues, i.e., the question of liability where an automated vehicle is involved in an accident causing property damage or personal injury [5]. Regarding the above, it can be said that fully automated driving is not a technological utopia, but its practical implementation on the roads should be carefully analysed [6]. Researchers and manufacturers advocate for automation in successive stages, firstly approaching longitudinal control, then simple side controls, to reach complete automation in scenarios of increasing complexity. In a few words, the change from conventional to assisted driving is now a reality, and the leap is being made towards automated driving in its different stages: partial, high, or fully automated. Intelligent vehicles (IV) are one of the key elements within intelligent transport systems. When an IV has intelligence--understood as the fact that the control relies on the onboard vehicle processing systems, it can move autonomously. The onboard vehicle intelligence becomes aware of the situation of the vehicle in its environment and performs all the necessary control actions to proceed towards its destination. Driving automation--considered a low-risk activity for humans--is a matter that needs the continuous evaluation of two main factors: (a) the current vehicle state (position, velocity, acceleration, direction) and (b) the environmental conditions (nearby vehicles, obstacles, pedestrians, etc.). To the extent that these two factors are accurately assessed, appropriate decisions can be taken towards reliable autonomous driving, and we will be closer to a vehicle-centric [6] approach to autonomous driving, where the main goal is the safe movement of the vehicle. It is not an easy task to define what an IV with autonomous abilities is, although it is possible to describe its capacities, as detailed in Table 1[7]. But, what exactly does autonomous driving mean? Following the policy defined by the NHTSA (National Highway Traffic Safety Administration, USA) [8], the International Society of Automotive Engineers (SAE) has set three categories of advanced driving automation, which imply the automation of both the driving actions (steering, throttle, and break) and the monitoring of the driving environment (see Table 2) [9].