Crucial to the advancements in ADAS are rapidly improving sensor technologies. Image sensors, in particular, are driving the improved effectiveness of ADAS. Backup cameras are already warning drivers of obstacles behind them when they are parking. Other cameras mounted around the vehicle body provide drivers with a 360° view of their surroundings, eliminating the dangerous blind spots that lead to accidents during lane changes. Increasingly, sensor technologies are being used in automated systems that prevent the car from moving into danger. Sophisticated features such as LED flicker mitigation and high dynamic range overcome the problems caused by bad lighting conditions that would otherwise disrupt the ADAS algorithms.
At the same time, vehicle manufacturers are taking advantage of sensor fusion to blend data from modalities that include visual images, infrared, radar, LiDar and ultrasound. In this way, sensors can compensate for the situations that would otherwise compromise performance, such as driving in heavy fog, rain or when the sun is close to the horizon. Coupled with advanced control algorithms, the network of sensors makes the prospect of fully autonomous driving on public highways feasible in the near future.
With the increased use of electronic sensing and computation comes risk. Although fusion can handle the highly varied driving environments ADAS-enabled vehicles will face, the systems can be forced to misbehave if the data streams they handle are corrupted. Sensor fusion can help overcome the corruption from a malfunctioning device but a bigger problem is that of deliberate tampering, especially if the corruption is designed to overcome normal error-correction routines.
The spectre of hacking has shifted from being a theoretical concern to become a genuine threat as exemplified by a number of proof-of-concept hacks demonstrated by several security researchers. So far, the proof-of-concept attacks have focused on individual subsystems, such as the engine control or attempts to fool different types of sensor. A growing problem for safety assessments is the increasingly complex nature