{"id":180,"date":"2024-03-23T02:20:06","date_gmt":"2024-03-23T02:20:06","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamd8\/?p=180"},"modified":"2024-03-23T03:14:26","modified_gmt":"2024-03-23T03:14:26","slug":"kaitlyns-status-report-for-3-23-24","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teamd8\/2024\/03\/23\/kaitlyns-status-report-for-3-23-24\/","title":{"rendered":"Kaitlyn’s Status Report for 3\/23\/24"},"content":{"rendered":"

Work Done<\/strong><\/p>\n

This week I finalized the lane detection in SUMO+TraCI.<\/p>\n

I spent a whole day trying to debug why the function to collect the waiting time for a car did not work and realized it was ultimately due to a type error. There was no documentation on the error and the error did not indicate what was wrong, so I looked on forums and StackOverflow for guidance. Since SUMO is not a very widely used software, I did not find anything helpful to my error and had to just randomly try debugging and looking at the source code.<\/p>\n

This is the error I was receiving for reference:<\/p>\n

traci.exceptions.FatalTraCIError: Received answer 189,18,0 for command 173,18,0.<\/pre>\n
Also the software kept bugging out when I was placing the lane areas, so it required a lot of manual adjusting. It didn’t tell me what was wrong, but I guessed that it was due to a weird overlap error, so I had to move the lanes a bunch even though sometimes it worked and sometimes it didn’t.<\/p>\n
This is a picture of the simulation running with lane area detectors that simulate what the cameras we have would detect. Since Ankita predicts about 50m detection on each side of the intersection, I set the lane area to be about 50 meters. The output shown on the left in the terminal is the average wait time of all the lane areas.<\/p>\n
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I am also finishing up the code to spawn in the cars based on the Traffic API data. The code is written, however I need to calibrate and map real life coordinates to the simulation coordinates and define the regions that represent the areas we plan on gathering API data from. I also plan on discussing with Ankita more about how I should implement the code to spawn in cars based on the camera data this week.<\/p>\n
Schedule<\/strong><\/p>\n
I should be on track to finish the simulation spawning and an unoptimized machine learning model by the time we demo for the Interim Demo. I am posting this on Friday due to being busy all of Saturday, but I plan to finish the simulation spawning on Sunday\/Monday to remain on track to have the basic ML model implemented next week.<\/p>\n
I updated the schedule with the shifted tasks.<\/p>\n
Tasks This Week<\/strong><\/p>\n