# A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research
## 7 Conclusions  
Advances in the field of vehicles with a high degree of automation are growing very rapidly, as can be seen from the study carried out in this review on perception systems. Every so often, new sensors appear (e.g., solid state LiDAR or MMW RADAR,) applied to autonomous driving or technologies that were unthinkable a few years ago beyond the use of research centres or large companies (e.g., rotational 3D LiDAR). The different electromagnetic spectrum bands used by the sensors studied in this work give each type of sensor advantages and disadvantages that limit its application. For example, MMR is \begin{table}
\begin{tabular}{l l l} \hline \hline
**Country** & **No Access** & **Partial Access** & **High Access** \\ \hline Australia & X & \\ China & X & \\ France & X & \\ Germany & & X \\ Japan & X & \\ New Zealand & & X \\ South Korea & & X \\ Sweden & & X \\ The Netherlands & & X \\ Singapore & & X \\ UK & X & \\ USA (Alaska) & & X \\ USA (Arizona) & & X \\ USA (California) & & X \\ USA (Florida) & & X \\ USA (Nevada) & & X \\ USA (rest of States) & X & \\ Remaining countries & X & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Permitted access to public roads for AVs. used for tracking objects, calculation of relative speeds or in ADAS systems for detection of objects in blind spots; they also have an excellent response in all types of weather conditions. 3D LiDARs have a high spatial resolution and high precision that make them the perfect element for navigation and mapping the environment. Visible cameras have a chromatic reproduction that makes them vital when it comes to discerning between the objects present on the road (pedestrians, vehicles, signs, etc.). The new generation of thermal cameras allow operation in total darkness or in very bright environments with total precision. The analysis of the spider charts shown in Figure 7 shows that there is no perfect sensor, so it is necessary to carry out sensorial fusion by means of specific algorithms that make it possible to alleviate the defects of each sensor and combine their advantages. We must highlight the good results that are being obtained in the area of data fusion with CNN. In the area of positioning systems, RTK systems that offer centimetre accuracy at the expense of using base stations that correct the GNSS signal should be highlighted. In this area, there are efforts in the deployment of this type of infrastructure to give precise coverage to the new fleet of autonomous vehicles that in a short space of time will flood cities. Autonomous driving is a challenge that involves different risks for road users. The deployment of technology that enables the automation of driving requires very exhaustive tests in real driving and road conditions, tests that in most countries cannot be carried out either in the quantity or in the actual driving conditions that would be required due to the absence of appropriate legislation, as explained in Section 6. This gap is largely covered by simulation. As observed in Section 5, the simulation possibilities of an autonomous vehicle are very broad. Over 200 works have been found related to the simulation of autonomous vehicles. The options are reduced when the simulation is focused on the Perception System, in this case around 50 of the works consulted. Not all the works have been studied, only those with an impact factor (publications in congresses or research journals, which have passed a peer review) have been taken into account. On the other hand, we consulted the proposals offered by companies dedicated to modelling and simulation, robotics, and automation. Undoubtedly, the most widespread simulators used in the field of research are robotics simulators. This is logical, considering that autonomous vehicles are a branch of robotics. However, not all robotic simulators are prepared to provide the necessary realism required in these cases. That is why the tendency is to use customized solutions using existing modelling and simulation platforms.