Heading and Yaw Rate Measurements

Question

I am working in the field of automated vehicles mainly in the domain of passenger and commercial vehicles. I have been studying whatever I can get regarding the measurement the state (relative position, relative velocity, relative heading and roation, a.k.a. yaw rate) of surrounding objects especially other vehicles using sensors.

While everything else is possible to measure precisely using on-board sensors, I have found out that not much literature is available for measuring the vehicle heading and yaw rate of other vehicles which is baffling to me given the extreme precision of laser based sensing (albeit using time stamps).

I am looking for:

1. Reference to literature with experiments for estimation of yaw rate and vehicle heading.

2. As I can see from the literature available (or the lack thereof), no direct way of measuring yaw rate is available but by using LIDAR or Camera with consecutive time stamps or scans of data. However, this inherently requires the data to be correct. Hence, I would think that due to the inaccuracies involved, this method is not used! Is this correct?

3. Are there any commercially available sensors that give accurate heading and yaw rate information of other vehicles?

Sources and research papers would be most welcome!

Edit: By this inherently requires the data to be correct I mean, given the high sensitivity to error in heading or yaw rate at high vehicle speeds, the values computed using sensor information is not accurate enough to be put to use in practice!

Answer 1

You're looking for a heading sensor - do you mean a compass? Or is there something else you're looking for? A compass gives you an absolute measurement, and a gyroscope provides yaw rate information.

:EDIT:

OP clarified that the yaw angle and yaw rate of interest is that of other vehicles, specifically the vehicle in front of the controlled vehicle.

I'm not sure I understand why you even care about their heading, unless you're trying to fake autonomy by just copying what the car in front is doing. That's a dangerous assumption, though, as the car in front may change lanes when it is safe for them and not for you, may make turns and exit roads you don't want to, etc.

You also state (about yaw estimation from LIDAR and cameras) that "this requires the data to be correct," which is the problem with all sensors. This is why we use filters. Noise, measurement error, biases - these all degrade feedback and create erroneous feedback signals, which are then treated as "truth" and acted on by the system.

All sensors have flaws; it's up to you to know your sensor and compensate for those flaws accordingly. A gyroscope not only has noise and bias offsets, but also a random walk that means the bias offset actually shifts over time, so even if you start out with a perfect measurement of the offset, that value changes and thus you still don't get a perfect feedback.

These problems exist even in weapons-grade (tactical) IMU sensors. The problem will likely be worse for LIDAR and camera-based systems, but again, it's always something you need to look out for and correct yourself.

As with a lot of questions that get asked here, it seems that you've already talked yourself into a solution (calculate the yaw angle and rate of the car in front of you) and have come here trying to determine how to implement that solution.

My advice would be to give more context to the problem you're trying to solve, introduce your solution concept, then state the trouble you're having. In that way you can simultaneously get feedback on your method and also get suggestions for other ways to solve the problem.