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❱❱ DIL simulation gets drivers into test vehicles early in the development phase


simultaneous sources, using logic to set confidence thresholds, logging and/or alerting when things do not look quite right and, perhaps most importantly including failsafe redundancies, so that when faults do occur, there are appropriate safety layers in place.” The design of the testing regime is


complex and as implementation and inter-system complexities increase, there comes a point where physical testing cannot cover all possible combinations. So typically, the approach is to employ statistical methodologies such as Design of Experiments (DOE) to predict cause- and-effect relationships for relevant factors and variables. “Off-line simulation is used to create maps and response surfaces that describe complex behaviours. Then a set of carefully selected “checkpoints” on these maps can be confirmed by physical testing. This level of testing is somewhere south of infinity so it can actually be covered in the available time,” continued Morse.


Jonathan Newell finds out how simulation is providing an answer to the challenge of testing the complex sensor arrangements associated with ADAS


the system will operate in all possible circumstances, something which with a potentially infinite set of possibilities becomes an impossible task. Statistical analysis in the early design phases, software simulation and ultimately, real-world hardware testing all play a role in validating such complex designs and Hardware-in-the-Loop (HIL) simulation has now become prominent in achieving this with reduced lead times. To understand more about simulation


❱❱ Phil Morse of Ansible Motion


in ADAS and autonomous vehicle testing, I spoke to Ansible Motion’s Technical Liaison, Phil Morse. According to an article Morse wrote recently, Driver-in-the-Loop (DIL) simulators provide a means for developers to take account of certain safety aspects of the design and the Human Machine Interface (HMI) requirements. Vehicles at all levels of autonomy still have a human at the wheel and the HMI is all important in passing control to and from the on-board computers and for regaining control in critical circumstances such as sensor failures.


Rather than waiting until final hardware testing when a human can be placed at the controls to experience the safety envelope of the car on test circuits, DIL simulation enables both human and vehicle responses to be studied in extreme situations. This offers a safer environment for the tester as well as providing the ability to test a wider scope of failure modes. I asked Morse how sensor reliability is built into the


overall approach to advanced driver assistance testing. He explained that “virtual cars” can be constructed, which take the form of Driver-in-the-Loop (DIL) simulators in which large amounts of data are pushed around. “A whole chain of events requires reliability from measurement collection to the fusion of these sensor outputs with other measurements, to data gathering and monitoring. A number of things can corrupt this process such as electrical noise or physical faults and things will inevitably go wrong at times,” Morse said. “Robust systems are developed by gathering and fusing data from multiple,


DIL SIMULATION IN CONTEXT DIL simulation is one part of a whole series of tests and simulation exercises the manufacturers need to go through to assure their products and is part of a progressive series of steps that take an increasing approach to realism. As Morse explained, there are usually three simultaneously occurring layers of testing. The first is to connect actual hardware components and production-deployable computer code with simulations where possible. This is HIL and Software-in-the-Loop (SIL) simulation. The next is to connect real test drivers with off-line, HIL, and/or SIL simulation. This is DIL simulation. The third step is to connect real test drivers with real pre-production full prototype vehicles – everything-in-the-loop. “The aim of DIL simulation is to get real people connected with imagined systems early and often in the vehicle development process,” he said. Looking to the future, in the real world of vehicle production, DIL simulation will bring a vital competitive edge to its industry users. “DIL simulator experiments can become extremely valuable – not because the virtual test driving eliminates the need to perform the physical testing completely – but because testing in the DIL lab enables its users to eliminate all the usual what-ifs and time-eaters that would otherwise consume tight testing windows,” concluded Morse. EE


DAQ, Sensors & Instrumentation 2017 /// 3


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