ADAS steering the future

Jon Lawson

Bringing steering testing into the laboratory can save time and money. By adding in a virtual component, a more diverse range of parameters can be analysed, as Juliet Elliot explains

Due to restrictions and lockdowns over the past year, the global automotive industry has been under great pressure to maintain its logistics chains, production flows and working environments. On top of this, more stringent emissions legislation is coming into force as well as changes in consumer views. This together forces the industry to find new ways of optimising its operations and reducing time to market.

As of 2022, new safety technologies will become mandatory in European vehicles to protect passengers, pedestrians and cyclists. These technologies include advanced safety features commonly known as Advanced Driver Assistance Systems or ADAS. The objective is to assist the driver in different traffic scenarios such as helping to keep the car in its lane, a function also known as Lane Keeping Assist. Most new vehicles today are already equipped with this technology.

This commonly uses the input of the vehicle’s front-mounted camera to identify the road markings and then operate the vehicle’s power steering to adjust the steering wheel angle in order for the car to stay in its lane. Development of these systems are traditionally conducted in SIL (Software-in-the-Loop), MIL (Models-in-the-Loop) and HIL (Hardware-in-the-Loop) environments where software, models and hardware components are used in a simulated environment to calibrate functionalities.

From the HIL, the development is then transferred to road testing. However, testing on the road is both time-consuming and resource-intensive so an alternative approach is to calibrate the performance of the ADAS function while still in the repeatable environment of the laboratory.

A different approach to ADAS testing

Rototest is a Swedish company specialising in vehicle test systems that allow road testing to be moved indoors. This enables a higher efficiency in the development process by providing a highly reproduceable, controlled laboratory testing environment. Rototest’s powertrain dynamometers offer many modes of operations, of which Road Load Simulation is the most used.

The design features a unique floating installation - it is not fixed to the floor. This enables the system to accept steering manoeuvres that are being conducted while running in the dynamometer system. The steering angle is then connected to the dynamometer controller that controls wheel speeds to correlate with the steering radius.

As the dynamometer units follow steering very easily on the floor, this fulfils many applications where the use of steering is enough. For more complex applications, the steering torque may be required, such as when replicating driving on the road. This could even be extended to fully autonomous driving. So, the steering torque can be used as a feedback signal for the vehicle’s internal model and supervision system.

The company recently acquired a new patent involving a solution that can replicate the self-aligning torque, meaning the torque that tends to steer the wheel while rotating around its vertical axis. This solution does not need any modification to the test vehicle and it even works on vehicles with 4-wheel steering. It’s called Natural Steering, and it installs in minutes and adds a servo-assistance functionality to the dynamometer, thereby providing the vehicle with a representative steering torque.

The dynamometer system, in combination with the servo-assisted steering, can be operated and is fully supported through the system’s integrated 14-DoF vehicle model. For customers wishing to utilise their own simulation experience with the dynamometer system, the systems support an open API to externally control the unit independently, meaning that it can connect to any simulation environment regardless of interface such as CAN, UDP or EtherCAT.

ADAS going virtual

To simplify the step from HIL to Vehicle-in-the-Loop, Rototest has partnered with the German company IPG Automotive. Its simulation environment for light-duty vehicles is called CarMaker and the partners have implemented the EtherCAT API of the CarMaker TestBed to make it a ready-to-run interface.

The benefit of integrating this way is that the whole environment for the vehicle can be simulated, like the image for the vehicle’s front-mounted camera, to recognise the road markings as in the ADAS example above.

Automatic emergency braking is another ADAS function that commonly relies on a front-mounted radar sensor. In CarMaker’s virtual environment, complex traffic scenarios can be created with objects such as other cars, trucks, bicycles and pedestrians. These objects can then be represented through sensor models and transmitted over-the-air with a radar target simulator to make the test vehicle believe that it is running in a real traffic scenario.

Imagine a pedestrian in the virtual environment suddenly stepping out into the road in front of the simulated test vehicle. The pedestrian will pass through the sensor model in IPG CarMaker and generate information (targets) that are sent to the radar target simulator. This then generates a radar signal that creates an image for the vehicle which then reacts to the pedestrian it perceives and activates its automatic emergency braking. The braking torque is registered with the dynamometer system and fed back into the virtual environment which then simulates the vehicle stopping.

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