Adaptive Cruise Control

The past decade has seen a rapid development of advanced driver assistance systems (ADAS). Through the development of intelligent systems based on detection onboard detection and perception, engineers aim to significantly improve road safety. When these systems are fully developed, advanced driver assistance systems (ADAS) can detect potential unsafe conditions early and avoid the possibility of a crash. One of the big advanced driver assistance systems (ADAS) applications currently in use is the Adaptive Cruise Control system (ACC) (Padhi, 2019).

The Adaptive Cruise Control system is usually detected through the Radar and Lidar sensor suite that is installed in front of the vehicle. The radar sensors help the Adaptive Cruise Control maintain the speed that the driver sets as long as the road in front are free of any vehicle or obstacles and then gently slows down by engaging the brake system when the vehicle detects slowing vehicles at a predetermined range (Bosch, 2018).

One challenge facing the Adaptive cruise control is that it works well when a car directly follows another car but often fails to detect stationary objects. Adaptive cruise control is programmed to focus on maintaining a safe distance from other moving vehicles and to ignore stationary objects as the human operator should be able to steer clear of stationary objects. The result is not always the case. This situation is most likely going to result in a crash. The software to complement and utilize the full potential of autonomous-vehicle hardware still has a way to go. Development timelines have stalled given the complexity and research-oriented nature of the problems (Padhi, 2019).

The ability to detect both moving and stationary vehicles and objects will be the major update to the Adaptive Cruise Control. The field of advanced driver assistance systems still has a long way to go due to the complexity of developing the necessary software technology.

References

Bosch. (2018). Adaptive cruise control. Retrieved from https://www.bosch-mobility-solutions.com/en/products-and-services/passenger-cars-and-light-commercial-vehicles/driver-assistance-systems/adaptive-cruise-control/

Padhi, A. (2019). Autonomous-driving disruption: Technology, use cases, and opportunities | McKinsey. Retrieved from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/autonomous-driving-disruption-technology-use-cases-and-opportunities

FIRRE UGV Joint Battlespace Command and Control System

The Joint Battlespace Command and Control System (JBC2S) is the command-and-control element for the Family of Integrated Rapid Response Equipment (FIRRE) such as the FIRRE UGV. JBC2S is a network-centric, geospatial command and control system that allows the field commander and above to plan and execute missions utilizing multiple and disparate manned and unmanned assets. It utilizes standard map formats (GeoTIFF, DNC, CADRG) for displaying map data and for tracking asset placement and movement.

JBC2S is a fusion of the framework of the Multiple-robot Operator Control Unit (MOCU), the functionality of the Multiple Resource Host Architecture (MRHA). The look of JBC2S is much more improved over the MRHA through the display of raster graphics data in addition to vector graphics data. The use of raster images reveals much more detail about the environment and presents a modern, state-of-the-art user interface (Kramer et al., 2006). JBC2S control station operates either in Monitor mode, in which the operator observes and monitors the status of the unmanned vehicles and sensors or the operator is in direct control of a single resource.

The FIRRE UGV provides telemetry data such as engine speed, engine temperature, hydraulic pressure, hydraulic temperature, track speed, fuel level, battery voltage, and obstacle detection data to the JBC2S through the MRHA IDD protocol. It also provides the pan/tilt positions of a SeaFLIR imager and the AN/PPS-5D radar located on the FIRRE UGV. JBC2S uses pan/tilt information to display coverage areas for these sensors on the map. The Platform Get Status response includes several flags such as GPS failure, emergency halt, low-battery warning, tamper alarm, and diagnostic failure. (Kramer et al., 2006).

The look and feel of the JBC2S is much better with the incorporation of the ArcGIS Engine architecture which is a library of embeddable GIS components such as the toolbar, ArcMap (2-D), ArcGlobe (3-D), and ArcScene (3-D) components.

Reference

Kramer, T. A., Laird, R. T., Dinh, M., Barngrover, C. M., Cruickshanks, J. R., & Gilbreath, G. A. (2006).  FIRRE joint battlespace command and control system for manned and unmanned assets (JBC2S). Paper presented at the , 6230 623020. doi:10.1117/12.666191 Retrieved from https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6230/623020/FIRRE-joint-battlespace-command-and-control-system-for-manned-and/10.1117/12.666191.short