How I can collect the results of veins example? - performance

I am using veins example and I replaced the scenario by real map of open street map. It work well but I do not know how I collect the result to prove the work.
I expected to have a result for example the delay and how the accident message delivered on the time for the neighbouring vehicle and we avoid another accident and road congestion if I am not right please advise me what results we can got if such example

Related

Sumo/Veins not spawning all vehicles

I am using Omnet, SUmo and Veins to simulate Vanets. The issue I face is that with certain maps, not all cars in the route file are spawned, at least not when they are supposed to. From what I understand it is because there is "not enough space in the network". I find it weird because the map I currently have covers 5*4 Manhattan blocks and should be big enough to accommodate thirty vehicles.
When I use departLane and departPos with "free", cars spawn, but the simulation fails randomly. I used a much bigger map with thirty vehicles and that one worked fine.
Any ideas, thanks in advance.
At depart time SUMO does not check for general space in the network but on the given departLane (which defaults to the rightmost usable lane) of the first edge in the route that's why vehicles are delayed. You already found out what to do against it, use departLane="free".
As for the second problem please give at least the error message preferrably with a more detailled description and the SUMO version.

Building my own veins scenario

I need to build a scenario from scratch.
Two vehicles moving on a straight road. There is a single rsu.
The rsu brodcasts the speed value every 10s. Vehicles should slow down to reach that value.
My question is
can i consider the msg as a beacon? If yes, how can i set the beacon msg in the rsu application? And if no, how to implement such scenario
You can have a look at the following answered questions, since they are somewhat similar to your question or at least give you some insight in how messages between vehicles are handled in Veins.
Please note that you should get a basic understanding of how OMNeT++ works first. You can use the TicToc tutorial to do that.
how to getting start to build a veins application
what policy is based vehicle rerouting in case of accident?
What exactly does handleParkingUpdate() do?
The necessity of handleSelfMsg in BaseWaveApplLayer

Disable/remove the NIC module of some vehicle in Veins

Dear OMNeT++/SUMO/Veins community,
There is a correct way to disable/remove the NIC module for some vehicle in the Veins?
I have lot of vehicles in my scenario and I want set only one part them with communication module, for example 50 %. For this I created one method that set half the vehicles to start the sendBeacon and other method to drop the beacon/data for half (same half that no start sendBeacon) the vehicles. I already see this question.
I think there is a correct way to do this, because in my code all the vehicle have the communication module and just not use or ignore the package that arrived.
I'd appreciate any help.
If you want only a certain fraction of vehicles to participate in the network simulation, you can set the penetration rate parameter in https://github.com/sommer/veins/blob/veins-4.4/src/veins/modules/mobility/traci/TraCIScenarioManagerLaunchd.ned#L58 to a value smaller than one.
For example, if you set the penetration rate to 0.5 only half of the cars will take part in the network simulation (but still in the road traffic simulation), thus modeling a network where half of the cars are not equipped with VANET technology.

How to analyse path-loss in omnet++ for veins example?

How can i analyse the path-loss in veins, during the communication between two nodes. I looked through the analogue modules files and found that simple path-loss module is used but i don't know how this module could be used to accumulate the path-loss results. Do i have to add separate statistics to extract the path-loss results?
The path-loss is a communication phenomena. If you want to analyze it your have to look at metrics which quantify its effect.
As an analogy, if someone calls your name from distance you might not hear because the signal power (amplitude of the voice) has been attenuated due to the distance.
For example, you can look at recvPower in decider80211p, or higher level statistics which are recorded in mac1609_4
For more information about the path loss in Veins, you can consider this Q&A: Maximum transmission range vs maximum interference distance

Odd correlated posterior traceplots in multilevel model

I'm trying out PyMC3 with a simple multilevel model. When using both fake and real data the traces of the random effect distributions move with each other (see plot below) and appear to be offsets of the same trace. Is this an expected artifact of NUTS or an indication of a problem with my model?
Here is a traceplot on real data:
Here is an IPtyhon notebook of the model and the functions used to create the fake data. Here is the corresponding gist.
I would expect this to happen in accordance with the group mean distribution on alpha. If you think about it, if the group mean shifts around it will influence all alphas to the same degree. You could confirm this by doing a scatter plot of the group mean trace against some of the alphas. Hierarchical models are in general difficult for most samplers because of these complex interdependencies between group mean and variance and the individual RVs. See http://arxiv.org/abs/1312.0906 for more information on this.
In your specific case, the trace doesn't look too worrisome to me, especially after iteration 1000. So you could probably just discard those as burn-in and keep in mind that you have some sampling noise but probably got the right posterior overall. In addition, you might want to perform a posterior predictive check to see if the model can reproduce the patterns in your data you are interested in.
Alternatively, you could try to estimate a better hessian using pm.find_hessian(), e.g. https://github.com/pymc-devs/pymc/blob/3eb2237a8005286fee32776c304409ed9943cfb3/pymc/examples/hierarchical.py#L51
I also found this paper which looks interesting (haven't read it yet but might be cool to implement in PyMC3): arxiv-web3.library.cornell.edu/pdf/1406.3843v1.pdf

Resources