Vehicle-in-the-Loop in Global Coordinates for Advanced Driver Assistance System

Abstract

Most vehicle controllers are developed and verified with V-model. There are several traditional methods in the automotive industry called “X-in-the-Loop (XIL)”. However, the validation of advanced driver assistance system (ADAS) controllers is more complicated and needs more environmental resources because the controller interacts with the external environment of the vehicle. Vehicle-in-the-Loop (VIL) is a recently being developed approach for simulating ADAS vehicles that ensures the safety of critical test scenarios in real-world testing using virtual environments. This new test method needs both properties of traditional computer simulations and real-world vehicle tests. This paper presents a Vehicle-in-the-Loop topology for execution in global Coordinates system. Also, it has a modular structure with four parts: synchronization module, virtual environment, sensor emulator and visualizer, so each part can be developed and modified separately in combination with other parts. This structure of VIL is expected to save maintenance time and cost. This paper shows its acceptability by testing ADAS on both a real and the VIL system.

Designing an Artificial Intelligence Control Program Model to be Tested and Implemented in Virtual Reality for Automated Chevrolet Camaro

“…Production of those elements and connections between components allowed complete programing of a robotic vehicle to operate in alternate dynamic and kinematic regimes, including the usage of the data, not only the display of some information [6]. Using virtual reality in the manufacturing/development process of the specific operating environment for the robotic vehicle is a complex task, which places the present study in a symbiotic relation with the rest of the research [8][9][10][11][12]. With the VR program, three important scenarios for applying AI in a robotic car should be considered as the following: 1. environmental inspection automated vehicle, 2. as a taxi, and 3. as an ambulance.…”

“…Mechatronic systems should be precisely programmed like automated robots to perform safely in complex traffic scenarios [10]. Artificial intelligence may be implemented in electric cars to improve performance and responses [11][12][13][14]. Standards and measures are provided by different entities regarding self-driving cars to solve safety problems and to optimize road traffic flows [9,[15][16][17][18]].…”

Motorway Measurement Campaign to Support R&D Activities in the Field of Automated Driving Technologies

“…During the measurement campaign, the following sensors have been used. The front zone of the vehicles are covered by a pair of forward looking cameras (6 and 6 ), a pair of forward looking long range radars (3 and 3 ), and a forward looking wide angle short range radar (12). The side zones of the tractors and the combination are covered at each side by wide angle short range radars (4 and 4 ) and front corner placed down looking fisheye cameras (8 and 8 ), where both of the fisheye cameras cover the vehicle front and the corresponding vehicle sides.…”

“…When using the terminology of a recent V2X testing survey [11], our paper covers V2X performance testing (especially latency testing) that involves vehicle gateway testing. Nevertheless, the major achievement here is presenting how live field-testing has been planned and executed in order to evoke further, digital-twin-based validations through Vehicle-in-the-Loop (ViL) [5,12] or Scenario-in-the-Loop (SciL) [13] methodologies. The concepts and perspectives of ViL and SciL have been summarized well by [14].…”

5G-Enabled Autonomous Driving Demonstration with a V2X Scenario-in-the-Loop Approach

“…The various virtual environment approaches for testing are becoming commonly acceptable and used in practice. These include Hardware-in-the-Loop (HiL), Software-in-the-Loop (SiL), Vehicle-in-the-Loop (ViL), or Scenario-in-the-Loop (SciL) [ 35 ]. Regarding the Scenario-in-the-Loop (SciL) testing environment [ 36 ], not only the vehicle’s physical attributes are evaluated, but its sensors are also tested by virtual twin realization.…”