The Burgeoning Use of Sensors for Advanced Driver Assistance Systems

By Carolyn Mathas

Contributed By Electronic Products

When one thinks of automotive sensor systems, global positioning navigation systems predictably come to mind. Helping drivers that are lost, however, is not the impetus for the fastest-growing sector in automotive electronics and sensor systems. Today’s automotive safety technology is designed to prevent accidents due to driver error, distraction, and drowsiness.

According to ABI Research, advanced driver assistance systems (ADAS) have been around on luxury vehicles for a decade. For model year 2012, however, such features as adaptive cruise control, lane departure warning, and low-speed collision mitigation will be resident on high-volume models include the Ford Focus and Mercedes Benz C-Class. As a result, estimates are that the global ADAS market value should near $10 billion in 2011 and mushroom to $130 billion in 2015.

ABI attributes the burgeoning revenue forecast to technical advances in sensor design and manufacturing that delivers lower cost and better performance, and the development of additional features that make the systems more attractive to new-car buyers.

What parts will account for that $130 billion? Let’s look.

Lane departure warning (LDW) systems

Lane departure warning systems alert the driver when an unintentional lane departure is going to occur. The driver is then responsible to act. LDW systems alone are expected to reach a worldwide market value of more than $14.3 billion by 2016. There are two types of LDW systems on the market: camera-based and infrared systems.

Camera systems

In camera-based LDW systems, a forward-looking CCD or CMOS camera tracks visible lane markings. The lane markings on the road are used to calculate the lateral divergence and divergence angle from the center of the lane. Algorithms are used to estimate the vehicle’s future position. Image recognition software computes inputs for vehicle information including speed, yaw rate, and steering angle. If the system discovers that the vehicle is veering off its intended path, it warns the driver and the driver must take corrective action.

A camera at the rear of the vehicle monitors the lane position as well, and is also used to monitor parking.

Camera systems can now compensate for adverse road conditions should weather limit road marking visibility. They can also compensate for the changes that occur suddenly when vehicles enter tunnels.

Infrared systems

These systems use infrared light sensors that are mounted on the front bumper to identify lane markings. The sensors contain an infrared light-emitting diode and a detection cell to monitor the variations in the reflections from the infrared beams emitted by the diode onto the road. Should a vehicle move over a lane marking and the turn signal is not in use, the system alerts the driver.

Infrared systems detect white lines and temporary road markings in color. It is, unlike some camera systems, unaffected by poor visibility. It also tends to be lower in cost. However, infrared systems tend to detect actual land departures; rather than being predictive, it is reactive.

Lane-change assistance systems

Lane-change assistance (LCA) systems include blind spot monitoring that observes the blind spots to the side and rear of vehicles, and lane change warning systems that monitor the areas around and behind vehicles. It is important that the systems be able to discern the difference between moving vehicles and roadside barriers.

Sensors used in blind-spot monitoring include radar, camera, infrared, and ultrasonic varieties.

Radar sensors are the most common automotive sensors in use. They are mounted in the rear bumper and are used to detect vehicles that are on the side of the vehicle or are approaching the vehicle from a position slightly behind it. The driver is alerted as the vehicle approaches until it is out of collision range.

Camera sensors are mirror mounted so that cameras take images of the lanes on both sides of the vehicle, analyze them, and warn the driver if necessary. The same camera apparatus is used for night driving to detect headlights. As with radar sensors, drivers are alerted until the danger has passed.

Infrared sensors are easily integrated into a variety of vehicle features such as mirrors, bumpers, and vehicle side designs. They monitor the lane temperature adjacent to the vehicle. Should a change in temperature take place that is sufficient to detect the presence of another vehicle, the driver is alerted.

Ultrasonic sensors are used in blind spot monitoring, typically in trucks that are particularly long, employing a series of sensors affixed to the side and rear of the vehicle. The sensors produce ultra-sonic waves that are able to detect vehicles in adjacent lanes, sending a warning to the driver if they are discovered.

Warnings to drivers take place either through flashing warning symbols in mirrors or next to the mirror. Drivers are also warned if the system is not performing correctly.

Lane-change warning systems

In addition to lane change assistance for blind spots, lane-change warning systems (LCW) monitor both the blind spot as well as the area behind the vehicle on both sides to detect approaching vehicles, so that lane changes take place only when safe. Camera sensors are used that incorporates a pattern recognition capability. Radar sensors are also used in LCW systems. Two radar sensors are placed on the rear bumper that monitor blind spot or hazardous approach dangers and let the driver know that lane change maneuvers should not be attempted at that time.

Beyond sensors

More than sensors are needed to make these safety systems do their job. For example, the Texas Instruments TMS570LS3137 (Figure 1) is a high-performance automotive-grade microcontroller family for safety systems including active driver assistance systems. The safety architecture includes Dual CPUs in lockstep, CPU, and memory built-in self-test (BIST) logic, ECC on both the Flash and the data SRAM, parity on peripheral memories, and loop back capability on peripheral IOs. The TMS570LS3137 integrates the ARM Cortex-R4F Floating Point CPU which offers an efficient 1.6 DMIPS/MHz, and has configurations that can run up to 180 MHz, providing up to 288 DMIPS.

Texas Instruments TMS570L3137

Figure 1: The TI TMS570L3137 has dual CPUs and memory BIST.

For automotive video collision avoidance systems, Maxim’s MAX9526 (Figure 2) is a low-power video decoder that converts NTSC or PAL composite video signals to 8-bit or 10-bit YCbCr component video. The device powers up in fully operational mode and automatically configures itself to decode the detected input standard. The MAX9526 typically consumes 200 mW of power in normal operation and typically less than 100 µW in shutdown mode.

Maxim MAX9526

Figure 2: Maxim MAX9526 functional diagram.

An internal 10-bit 54-MHz analog-to-digital converter (ADC) samples the input with four times oversampling. The MAX9526 features a dc restoration circuit with offset correction and automatic gain control to accurately optimize the full-scale range of the ADC. The MAX9526 includes a 2:1 input multiplexer with automatic signal selection based on activity at the inputs.

Intersil TW8816

Figure 3: Functional block diagram for the Intersil TW8816.

Displaying the data collected is also critical. The Intersil TW8816 LCD controller with on-chip MCU and CCFL controller is a multi-purpose display solution with a high-quality NTSC/PAL/SECAM 2D video decoder and a 2D De-interlacer/Scaler supporting digital and analog panels. The TW8816 can directly display video and graphic content from a variety of devices including backup cameras used in safety systems.


Automotive collision avoidance/driver assistance systems can use a variety of different sensors placed within a vehicle to warn its driver of any dangers that may lie ahead on the road. Some of the dangers that these sensors can pick up on include how close the car is to other cars surrounding it and how close the car is to wandering into another lane or going off the road.

Data from these sensors is then sent to microcontrollers or video decoders to determine whether the current situation is outside safety parameters and to determine next steps. We’ve discussed a sampling of these parts; more information can be obtained through the links provided to product pages on the Digi-Key website.

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