Future automotive vehicle trends are in developing more and more automated unmanned/hands-off/robotic vehicles to help drivers and road users, integrating sensors with vehicle control systems, with the road infrastructure, with other vehicles and with the web. Sensors can be seen as the front-ends of the vehicle which will provide awareness of the car’s systems in a complex environment (off road, liquid dirt) and severe weather conditions (rain, spray,snow) in order to achieve enhanced vehicle efficiency, safety and road system capacity. Along with ultrasonic, infrared, LIDAR and visible light sensor technologies the radar sensing is one of the most important.
Radio Frequency (RF)/Microwave sensors (radars) operating within the frequency bands suitable for both penetration through the complex scattering media and the discrimination of the road surface would offer the benefits of all-weather radar operation and provide pre-emptive automatic measures for potentially dangerous conditions of the driving surface at high frequencies(>20 GHz). In addition use of such sensors presents the opportunity to offer new applications including control of vehicle suspension systems using advance knowledge of the terrain and composition of the path ahead of the vehicle (wet grass, mud, rocks etc).
Two decades of radar research at Birmingham have had a profound impact on the automotive industry specifically adaptive cruise control (ACC) radar and blind spot monitoring development. Both are currently deployed across the Jaguar Land Rover (JLR) range.
University of Birmingham also contributed into development of pedestrian and collision avoidance systems, establishing the key operational parameters,investigating effects of rain and spray on the radar signatures of vehicles,pedestrians, animals and bicycles.
Our laboratory is currently developing new types of sensors of the future.These combine both acoustic and microwave sensing which will provide vehicles with the ability to sense the surface ahead of the vehicle to allow car systems to be prepared for the approaching terrain that is especially crucial for off road vehicles. We are also designing sensors which will allow drivers to“see” the depth and tilt angle of a vehicle in water and control its speed over ground. Optimum vehicle progress control offers environmental benefits by reducing energy wastage by inappropriate driving and also reduces damage to the terrain.
Speed over ground:
Currently all aid system of different vehicles depends on the availability of navigation signals. However it is extremely important to be prepared for such situation where all traditional navigation system will be absent or suffer an outage. In this case knowledge of vehicle speed is necessary for navigation.
Conventional vehicle speedometers derive the velocity information from the rotational speed of the wheels. Thus, they have the disadvantage that any slip between wheel and road surface is not detected. In situations such as wheel spin, locked breaks or vehicle side slip on low friction surfaces this information can be highly inaccurate. With the extreme cases being a stationary vehicle having fast wheel speed or indeed a sliding vehicle having no wheel speed whatsoever.
In many applications, e. g. navigation or velocity measurements in cars with Anti-lock Braking System (ABS), Anti Slip Regulation(ASR), etc., sensors are needed measuring true Speed Over Ground (SOG).Doppler radar and acoustic systems offer the possibility for slip-free,blocking rate-free, non-contact measurement of SOG. The goal of the MISL project is to get the true velocity of the vehicle, both translational speed& transverse speed.
Doppler sensing is based on the principle that a wave transmitted/received from a moving source/receiver experiences a shift in frequency related to the speed of the motion. The designed prototype system allows speed overground measurement with a high precision.
Automatic road profiling and image interpretation for vehicle control:
Road path determination and road profiling is crucial to future automated vehicle vision system, and current conventional solutions cannot accurately provide information about road conditions in front of the vehicle.Microwave/Millimetre-wave radars have all-weather capability and provide measurement of range, azimuth angle with high precision to the object and allow estimation of the object location and RCS. Major advantages of radar sensors include robustness against many severe weather conditions with obstructed vision of driver and high azimuth and range resolution. Therefore radar sensors can provide accurate estimation of the position of the obstacles at a stand-off distance, so that, being equipped with DSP, build a road map of incoming terrain, image interpretation to discriminate between different objects and road profile features extraction. Radars are capable of measuring relative velocities and have small physical dimensions; therefore the sensors can be mounted behind a plastic vehicle bumper.
MISL is conducting research on using the signal processing for the millimetre-wave radar backscatter data to extract the features of the road ahead, and from this, to interpret the road obstacle images in terms of size as well as positive or negative elevation. The developed techniques allow detecting and interpreting such objects like humps, kerbs, debris on the road tarmac, off road terrain profile and potholes on the road surface.
The current demand and still unsolved challenge is to provide real-time identification of road surface conditions in both complex environments (off road, liquid dirt) and weather conditions (rain, spray, snow). Potentially dangerous situations occur as a composition of the car manoeuvring (cornering, rapid steering for collision avoidance) on the surfaces fully, or partially covered by snow, ice, liquid dirt, grass, mud etc. The latter case of partial cover raises additional questions of discrimination of the partly different areas of the road for complex control of the vehicle wheels and suspension.
MISL is conducting a research where the information on the surface (material and conditions) is obtained through the analysis of the reflected signals. The advantage of radar sensors over optical would be that forward looking radars could detect low friction spots from a longer range at any weather conditions whereas optical sensors’ detection range is a few meters only and their performance depends on weather conditions. Ultrasonic sensors are usually used in automotive applications as short-range parking sensors and, in our development, they serve as an aid to compliment information gathered by other sensors. The advantage of ultrasonic sensors is their abundance and low cost.
The differentiation between surfaces is based on statistical classification/identification/recognition methods using clustering algorithms. Using the proposed techniques we have achieved reliable results in the recognition of surfaces in a number of important cases.
Our further research is focused on improving the algorithms and methods as well as to develop a working prototype of the automotive surface identification radar and sonar.
For a better idea on how this technology works on the technical level, a number of posters covering different aspects are provided here.
We also have a number of publications, all of which can be found in the “ Publications ” section of the MISL page.
For more information on this topic and for research position vacancies, please contact:
Professor Marina Gashinova (Project Leader)
School of Electronic, Electrical and Computer Engineering
University of Birmingham
Birmingham B15 2TT, United Kingdom
Tel: (+44) (0) 121 414 7599