The car is rapidly transforming into a secure, connected, self-driving robot capable of sensing its surroundings, making intelligent decisions, and taking autonomous actions. One of the most significant changes in this evolution is the rise of small, self-driving public vehicles—such as taxis, carpool shuttles, or buses—that can transport passengers from transit hubs, downtown areas, or office zones to their final destinations, effectively solving the "last mile" challenge.
An example of this innovation is the NAVYA ARMA, a self-driving electric bus launched in October 2015. This compact vehicle can safely carry up to 15 passengers at speeds of up to 28 miles per hour and has been tested or deployed in various communities across Europe and the U.S. It even made an appearance on the streets of Las Vegas during CES 2017, showcasing the growing acceptance of autonomous mobility solutions.
To operate safely, autonomous vehicles rely on advanced sensor systems such as cameras, radar, and lidar to perceive their environment. These sensors work together with the Advanced Driver Assistance System (ADAS) to detect objects, monitor traffic, and make real-time decisions. A key component of this system is the use of multiple high-resolution video cameras—typically at least five, often up to eight. Front and rear-facing cameras must have high sensitivity and fast response times to help detect intersections, pedestrians, and potential collisions. These features are becoming standard in many modern cars and SUVs, offering enhanced safety and convenience.
For instance, Tesla’s latest hardware includes the NVIDIA Drive PX 2 platform, which processes data from eight cameras, ultrasonic sensors, and a radar system. This powerful setup enables real-time environmental awareness, precise mapping, and safe path planning. By combining deep learning, sensor fusion, and panoramic vision, these systems are revolutionizing the driving experience.
The performance of the camera system is crucial for both driver-assistance and fully autonomous vehicles. Cameras are placed around the vehicle and often far from the central processing unit. Their capabilities determine how far the ADAS can see, how small objects it can detect, and how quickly information is transmitted—depending on resolution, dynamic range, and frame rate. High bit error rates are not acceptable, especially given the high data rates involved. In a typical panoramic view system, each camera streams video at 1280 x 800 pixels with a 30 fps refresh rate.
In automotive systems, various communication buses like CAN, LIN, FlexRay, MOST, LVDS, and Ethernet are used. However, for video transmission, only LVDS and Ethernet are suitable due to their high data-rate capabilities.
A better alternative is the Gigabit Multimedia Serial Link (GMSL), an uncompressed solution that offers 10x faster data rates than Ethernet, reduces cable costs by 50%, and provides better electromagnetic compatibility (EMC). Maxim Integrated offers the MAX96707 and MAX96708 GMSL serializer/deserializer chips, which support high noise immunity and can transmit data over low-cost coaxial or twisted-pair cables up to 15 meters. These chips support megapixel cameras with serial bit rates up to 1.74 Gbps and include features like programmable pre-emphasis, error detection, and crosspoint switching for dual camera selection.
The MAX96707 serializer is available in a compact 24-pin TQFN package, operating within a 1.7–1.9V supply range and drawing a maximum current of 88mA. The MAX96708 deserializer enhances signal integrity with adaptive equalization and offers flexible output options. Both devices meet stringent automotive standards, including AEC-Q100, and feature robust ESD protection.
When designing an automated driving system, reliable camera communication is essential. I would thoroughly test the bit error rate under real-world conditions and worst-case noise scenarios. Given these requirements, GMSL technology stands out as a strong candidate, delivering high reliability while adhering to industry standards.
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