Future of Car Radar Technologies - Predictions and Insights

As self-driving cars continue to gain traction, more manufacturers are installing radar sensors. But how will this technology advance over time?

Matthias Feulner, Director ADAS Marketing of NXP Semiconductors, discusses recent advances in automotive radar, such as 28nm RFCMOS single-chip radar integration and high-resolution 4D imaging radar. These developments can help automakers meet ADAS and autonomous driving demands.

Table of Contents

1. LiDAR vs. Radar

LiDAR currently reigns supreme as an innovative remote sensing solution, turning aircraft and drones into high-resolution mapping maestros and providing high-resolution topographic maps that archeologists, disaster responders and urban planners cherish. Furthermore, this 3D data collection tool can also be found inside autonomous vehicles to improve spatial awareness; and is often chosen over other data collection methods due to its unparalleled accuracy and precision – especially useful when measuring traffic volume accurately for autonomous driving or precise traffic management applications.

However, lidar systems are vulnerable to environmental factors; rain, snow and dense clouds can all wreak havoc with performance; raindrops scatter or absorb pulsed laser beams which then scatter back at them, negatively impacting its performance and blinding cameras with glare or dirt. Radar technology, however, seems much less affected by weather conditions, providing superior visibility even during poor conditions as well as being significantly cheaper than lidar solutions – making radar a good option for robotaxis operating within limited spaces at slower speeds and also less costly alternatives such as lidar solutions; making radar an attractive solution when measuring distance between objects compared with cameras blinded by dust/glare/dirt or cameras being blinded by dust/glare/dirt.

2. 3D Imaging Radar

Long considered the cornerstone of advanced driver assistance systems (ADAS), radar has long been considered essential. Now with increasing levels of autonomy being demanded by OEMs, OEMs require sensors with better classifying abilities that enable 4D radars to provide this superior classification capability.

The radar market is expanding quickly and is expected to do so for some time to come, driven by various factors including advanced ADAS functionality and Level 5 autonomy requirements.

Robotaxis will fuel growth for automotive radar, as these vehicles require multiple radars to properly comprehend their environment and objects in it. IDTechEx expects forward facing ADAS systems will use 0.69 long-range radars per vehicle; however, robotaxis and privately owned Level 4 vehicles will require much more. Robotaxis in particular may use high performance imaging radars capable of distinguishing object height differences like pedestrians or low curbs in order to determine whether it is safe to cross an obstacle.

3. Radar vs. LiDAR

RADAR employs radio waves that bounce off objects and return as echos, measuring their time delay to pinpoint distance. Furthermore, using Doppler effect calculations it also calculates velocity.

Radar signals, unlike cameras, are unaffected by dust or glare and excel at detecting heights above road level. As such, radar can be an ideal solution for highway piloting or self-driving cruise control that require high-speed elevation separation capabilities.

Even with recent advances in radar technology, radar’s point-cloud density or quality is not yet on par with that of LiDAR; nonetheless it should become competitive over time as costs decrease and price gaps narrow. Many car companies currently utilize various sensor technologies for autonomous driving systems; Waymo, Toyota and Tesla all employ multiple types of sensor technologies within their vehicles for these systems – Waymo includes both cameras and radar within its vehicles while Tesla prefers radar over LiDAR; however this could change as costs decrease which would allow RADAR to achieve greater resolution or precision compared to its rival competitor LiDAR.

4. Radar vs. LiDAR Cost

Reliability in extreme weather conditions is a hallmark of robotaxi technology, yet its lack of human vision may limit it from becoming widely adopted for robotaxi services where drivers tend to rely solely on vehicle sensors. This may force companies to invest more heavily in both cameras and radar systems for these services to achieve optimal results.

Cost reduction has also enabled manufacturers to integrate numerous radar sensors into more affordable cars like the Volvo EX30. These additional sensors not only contribute to smarter driver assistance and autonomy systems but also bring practical features. Bosch is developing a rear-facing radar system which detects trailers being towed and automatically extends blind-spot warnings – an example being developed.

All these advancements have been achieved while keeping power consumption to an absolute minimum, which is an increasingly crucial consideration when dealing with electric vehicle demand. For instance, 60GHz radar systems being installed into cars by companies like Volvo only consume four watts–roughly half the amount consumed by an average household LED light bulb.