Friday, March 29, 2024

Self-Driving Cars Platform and Their Trends (Part 2 of 2)

V.P. Sampath is a senior member of IEEE and a member of Institution of Engineers India. He is currently working as technical architect at AdeptChips, Bengaluru. He is a regular contributor to national newspapers, IEEE-MAS section, and has published international papers on VLSI and networks

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These sensor systems are continuing to get smaller and will be ideal for a number of embedded applications. Instruments and techniques such as the compass, sextant, LORAN radiolocation and dead reckoning. These are among those that have been used with varying degrees of accuracy, consistency and availability.

For autonomous vehicles, the navigation and guidance sub-system must always be active and keep checking how the vehicles are doing versus the goal. For example, if the originally optimum route has unexpected diversions, the path must be re-computed in real time to avoid going in the wrong direction. Since the vehicles are obviously constrained to roadways, this takes much more computational effort than simply drawing a straight line between A and B.

The primary sub-system used for navigation and guidance is based on a GPS receiver, which computes the present position based on complex analysis of signals received from at least four constellations of over 60 low-orbit satellites. A GPS system can provide location accuracy of the order of one metre (actual number depends on many subtle issues), which is a good start for the vehicle. Note that, for a driver, who hopes to hop in the car and get going, a GPS receiver takes between 30 and 60 seconds to establish initial position, so the autonomous vehicle must delay its departure until this first fix is computed.

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GPS sub-systems are now available as sophisticated system-on-chip (SoC) ICs or multi-chip chipsets that require only power and antenna, and include an embedded, application-specific compute engine to perform intensive calculations. Although many of these ICs have an internal RF preamp for the 1.5GHz GPS signal, many vehicles opt to put the antenna on the roof with a co-located low-noise amplifier (LNA) or RF preamplifier, and locate the GPS circuitry in a more convenient location within the vehicle. The antenna must have right-hand circular polarisation characteristics to match the polarisation of GPS signals, and it can be a ceramic-chip unit, a small wound stub design or have a different configuration.

A complete GPS module
Fig. 4: A complete GPS module

An example of a GPS module is RXM-GPS-F4-T from Linx Technologies, shown in Fig. 4. This 18mm×13mm×2.2mm surface-mount unit requires a single 1.8V supply at 33mA, and can acquire and track up to 48 satellites simultaneously—more channels allow the GPS to see and capture more data and, thus, yield better results and fewer dropouts. Its sensitive front-end requires signal strength of -159.5dBm for operation. After it computes locations based on GPS received signals, it provides output data to the system processor via the serial interface using industry-standard National Marine Electronics Association message format.

 

While GPS is an essential function for autonomous vehicles, it is not sufficient by itself. The GPS signal is blocked by canyons, tunnels, radio interferences and other factors, and these outages can last for many minutes. To supplement the GPS, the autonomous vehicle uses inertial guidance that requires no external signal of any type. The inertial measurement unit (IMU) consists of a platform fixed to the vehicle, and this platform has three gyroscopes and three accelerometers, one pair oriented each for orthogonal x, y and z axes. These sensors provide data on the rotational and linear motion of the platform, which is then used to calculate the motion and position of the vehicle, regardless of speed or any sort of signal obstruction. Note that, an IMU cannot tell you where you are, only the motion, so the initial location of the vehicle must be determined by the GPS or entered manually.

The in-vehicle IMU would not be practical without the development of MEMS based gyroscopes and accelerometers. The historical and fully-refined IMU is based on a spinning-wheel gyroscope and a gimbaled platform, which has served many applications quite well (missile guidance/Space missions), but it is simply too large, costly and power-hungry for an autonomous vehicle.

A representative MEMS device is A3G4250D IC from ST Microelectronics, a low-power three-axis angular rate sensor that provides a high degree of stability at zero rate level and with high sensitivity over temperature and time, shown in Fig. 5. It provides 16-bit digitised sensor information to the user’s microprocessor via a standard SPI or I2C digital interface, depending on the chosen version. With its tiny size of just 4mm×4mm, operation from a 1.8V supply, and stability and accuracy specifications, it is well-suited for inertial automotive navigation when combined with a three-axis accelerometer, for a complete six-axis IMU.

 MEMS devices have changed the implementation of IMU functions, such as gyroscopes and accelerometers
Fig. 5: MEMS devices have changed the implementation of IMU functions, such as gyroscopes and accelerometers

The autonomous car must be able to see and interpret what is in front when going forwards (and behind when in reverse, of course). It is also necessary to see what is on either side. In other words, it needs a 360-degree view. An array of video cameras is the obvious choice, plus a camera to determine where the lane is and sense objects or markers on the road.

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