Advanced driver assistance systems (ADAS) is basically a kit of functions utilized to improve safety by reducing a probabilities of the vehicle accidents.
ADAS can be used not only for enhancing road safety and avoiding traffic accidents but also as means of developing a better driver control by analyzing types and frequency of violations made by a particular driver.
In this article we will briefly describe ADAS functionality and its benefits for fleet management.
ADAS collects and analyzes various data from the car surrounding environment to provide a driver insightful help in critical road situations. In practice, ADAS functionality is enabled by a combination of software, hardware, various sensors, and embedded equipment. Contingently, ADAS system could be divided onto the following interconnected components:
- proprioceptive sensors: detect and respond to danger situation by analyzing the driver and vehicle behaviour;
- exteroceptive sensors (radar, lidar, ultrasonic, infrared and various vision sensors): respond on an earlier stage and predict possible dangers;
- sensor networks: application of multisensory platforms and traffic sensor networks.
- software and communication protocols.
Upon detection dangerous situations, ADAS may warn a driver by sound signal, indication or vibration. This is so-called passive control. If the system has a complex structure and more in-depth integration with a vehicle, control can be active: system could stop a car, automatically prenevent an unintended lane departure, etc.
Some key ADAS features include:
- Lane Assist (LA)
- Crash Warning System (CWS)
- Blind Spot Detection (BSD)
- Adaptive Cruise Control (ACC)
- Smart Park Assist (SPA)
- Cross Traffic Alert (CTA)
- Automatic Emergency Braking (AEB)
- Traffic Jam Assist (TJA)
- Other custom / advanced options
As sensors and detection/classification algorithms become more effective, ADAS systems would become more feature-reach, accurate and advanced.
ADAS: technology driven efficiency enchancement
Progress in ADAS functionallity requires to utilize more advanced and efficient sensors, hardware, and algorithms. Efficient ADAS applications must be able to sense, analyze the data, and act upon that data accordingly.
Figure below shows the different types of sensors needed. Sensor data is then fused together in a central sensor fusion platform that also combines V2X (vehicle-to-everything) communication, GPS, and digital maps for localization.
After the sensor data is compiled, the system must decide how to react to the obtained data: by braking, steering, or accelerating. All of this processing should happen in real time,almost instantaneously. In addition to advanced sensors, a new class of high-performance systems-on-chip (SoC) is required to rapidly process and bind together obtained sensor data. An example of such ADAS SoC architecture by cadence is shown on a figure below.
ADAS SoCs allow vehicles to effectively scan the surrounding space, but entailes related questions such as chip area, power consumption, and performance. Even though, progress in this field is really intense. For example, Ambarella recently announced CV22FS and CV2FS automotive camera SoCs for ADAS.
Both chips target forward-facing monocular and stereovision ADAS cameras, computer vision and higher levels of autonomy. As well, both featuring extremely low power consumption and potentially could be used in electronic mirrors with blind spot detection (BSD), interior driver/cabin monitoring cameras, and around view monitors (AVM) with parking assist.
ADAS: towards Autonomous Future
ADAS already providing a range of benefits to driver and vehicle safety. Modern sensors and systems enable the promise of so-called L5 Autonomous vehicle – self driving where even the steering wheel is not necessary. The L5 technology currently a subject of intense debates and development.
Once implemented, level 5 vehicles do not require human attention. Most probably, Level 5 cars would be “steering wheels-less” withought even acceleration/braking pedals. They will be free from geofencing, able to go anywhere and do anything that an experienced human driver can do. Currently, fully autonomous cars are undergoing testing in several parts of the world as a prototypes, but none of them yet available to the general public.
ADAS for Fleet Management
ADAS functionality helps not only drivers but fleet owners and insurance companies as well. To achieve this, ADAS systems are integrated with telematics platforms. Such symbiotic system could become a crucial fleet owners ally, helping to Avoid crashes, control and train employees, improve safety and reduce fleet costs.
Thus, ADAS can be used not only for enhancing road safety and avoiding traffic accidents but also as a means of developing better driver control by analyzing types and frequency of violations made by a particular driver. By receiving extensive information on each driver’s violations, companies will be able to сonsistently work towards improving their employee’s driving behavior and will get a more accurate assessment tool.
- Review of advanced driver assistance systems (ADAS), Adam Ziębiński et al., 2017