# A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research
## 5 Simulation
### Vehicle Test Simulation
Most of the HIL tests of the ADAS functions are reduced to sending a series of simulated objects to the unit under test. Depending on the sensor systems involved, information on the kinematics of the object can be included, as well as whether the object is a vehicle, a pedestrian, or something else. In addition to the current sensor data, supplementary vehicle data from other ECUs may be required. Depending on the configuration, several real ECUs can be part of the test bed and connect through automotive network systems such as CAN, FlexRay or Automotive Ethernet. A consortium called ADAS iiT [57] demonstrated a recent example of a HIL test system that uses the platform-based approach for sensor fusion testing. This group demonstrated an ADAS test configuration that can synchronously simulate RADAR, LiDAR, communications and camera signals for an ADAS system. In one case, the configuration was able to simulate a virtual test unit using the CarMaker software (by IPG Automative) and VeriStand (by National Instruments). To select an XIL simulator, several factors must be taken into account:* Availability and compatibility of models: The main companies provide you with convenient and powerful solutions to run complex physical models designed with Simulink [58], Stateflow [59], Simscape [60], or any other MathWorks [61] software tool on highest performance multi-core CPUs, GPU and FPGAs. The majority of companies offer Open Models; on other occasions, it will be necessary to develop a custom model or buy one. * Subsystems which can be tested: simulators were built according to a specific purpose. For example, a Micro HIL system offers a simpler and more economical solution; the strategy is restricted to the analysis of ECU outputs, when excited by specific controlled inputs. * Real-time simulation communications protocols available, including CAN, FlexRay, ARINC 429, MIL-STD-1553, EtherCAT, real-time UDP and XCP. * Compliant with ISO 26262: The development of high-integrity systems within the automotive industry is characterized by demonstrating compliance with ISO 26262, an international standard for road vehicle functional safety. To perform this type of simulation, many of the works found in the literature mainly make use of MathWorks tools [62]. MathWorks is the leading developer of mathematical computing software. MATLAB, the language of technical computing, is a programming environment for algorithm development, data analysis, visualization, and numeric computation. Simulink is a graphical environment for simulation and Model-Based Design for multi-domain dynamic and embedded systems. In particular, Simulink models are used in the development of most pre-ADAS vehicle controllers, and can even be deployed directly to ECUs (following a code generation process). Recently Matlab extended its capabilities for ADAS development with the Autonomous Driving Toolbox, available from the 2017b release. This toolbox provides algorithms and tools for designing and testing ADAS and autonomous driving systems. It allows engineers to automate ground-truth labelling, generate synthetic sensor data for driving scenarios, perform multi-sensor fusion, and design and simulate vision systems. Table 3 shows some of the simulators or simulation platforms used for the validation and testing of autonomous vehicles, following a model-based approach.