Data sources for Vehicle Dynamics Model validation?

[AbsoluteUnit]

Hello all,

I have written a VDM for my Masters thesis, unfortunately, since I am from a discipline other than mechanical engineering I don't have access to reliable validation material or a way to produce it (moreover, we don't have an actual vehicle testing lab/area at the U that I know of). Furthermore, I am not familiar with the resources that ME students might already know. I have discussed this with my advisor to no avail, since the topic I am working on unexpectedly branched way outside both our domain of expertise.

Essentially, I am looking for a data set (open source, or proprietary-- at this point, I can spend some money if needed) that I can perform validation on. The key maneuvers are:

1. Straight braking to a stop
2. Braking in a turn

The key features of the data should include:

• Vehicle trajectory and orientation
• Vehicle velocity
• Tire parameters, e.g. slip stiffness and carcass stiffness

I have been thralling the internet for such material and found some papers here and there e.g.

• Validation of Computer Simulations of Vehicle Dynamics, Bernard & Clover
• Test Methods and Computer Modeling for the Analysis of Ground Vehicle Handling (1986), Allen et. al
• Yaw Testing of an Instrumented Vehicle with and without Braking (2004), Cliff et al.
• Development and Validation of a Vehicle Model for the National Advanced Driving Simulator (1996) Salaani, M. (and some other of Salaani's works)

But I don't think I can get a reliable data set by grabbing it off those papers by tracing/eyeballing and the datasets are typically incomplete/obscured.

I am in the final stretch of my thesis and this has been the issue that is plaguing me for a while now, so I hope someone here can give me some recommendations. Thank you kindly.

 

[jedishrfu]

Have you tried contacting the authors of the papers that may be able to provide something for you to use?

Also could you simulate a couple of datasets, one with perfect numbers and one where you randomly vary the perfect numbers by some tolerance amount. While not perfect, it could be sufficient to test your code for your advisor to say okay you did it.

 

[jedishrfu]

I found this dataset for self driving cars that may have what you're looking embedded inside its metadata:

https://www.a2d2.audi/a2d2/en.html

and this blog on available datasets for self driving cars:

 

[AbsoluteUnit]

I found this dataset for self driving cars that may have what you're looking embedded inside its metadata:

https://www.a2d2.audi/a2d2/en.html

and this blog on available datasets for self driving cars:

jedishrfu,

Thank you for the suggestions.
I read through the description of the data sets, but I'm not sure if it contains what I need, or if I currently have the luxury of time or expertise to tinker around a lot (maybe in the future, this is actually pretty cool stuff ngl!).

Have you tried contacting the authors of the papers that may be able to provide something for you to use?

Also could you simulate a couple of datasets, one with perfect numbers and one where you randomly vary the perfect numbers by some tolerance amount. While not perfect, it could be sufficient to test your code for your advisor to say okay you did it.

I have currently resorted to validating my model against the model results presented in "An Analysis of Tire Traction Properties and Their Influence on Vehicle Dynamic Performance" (Dugoff, Fancher, Segel) which presents maneuvers such as: steady-state turning, lane change, and braking while in a turn; and provides sufficient information regarding the tire parameters assumed, and inputs (torque, steer angles) to their model. For example:

I plan to digitize their plots and compare it to my model outputs. I believe that should be sufficient to indicate that "hey, my model isn't that silly"?

However, the pure straight-line braking was not presented in the paper, and I am figuring out a way to externally validate simple braking in the simulation (although I am also not sure if it is necessary). I am thinking that I can probably do some hand computations or write a simple linear model and compare the result to my model... Sounds silly in my head but I suspect that's reasonable? Sorry, just throwing stuff at the wall and hope something sticks.

Thank you for the feedback, I don't really have anyone to do a back-and-forth on this in my department.
AU

 

[jedishrfu]

I had a math prof who used that very expression as he tried to get me a physics major to attend some math seminars because of my interest saying if you throw enough mud at the wall some of it will stick.

I guess I was the wall and the mud was math now that I think about it.