===== Group Members: Vikram Tholakapalli, BJ Kim, Rithwik Mylavarapu Story: Poor road conditions cause billions of dollars in vehicle damage and cause over one-third of all traffic accidents. Additionally, they can substantially slow traffic down causing numerous other externalities such as decreased productivity for workers, higher pollution, increased travel times, etc. the list goes on and on. In fact, according to the American Society of Civil Engineers, bad roads will cost American Businesses estimated $240 billion from 2019 to 2022. However, despite large support for infrastructure rebuilding across the aisle, governments still lack adequate funding. Therefore in order to maximize benefits of the funds available to CDOT our project seeks to answer where CDOT should focus its effort.
Specifically, the goal of our project is to create a visual map that will show the areas that CDOT should prioritize. Our plan is the following:
What we need to do:
- Get Data and Store in Hash Table
- The Json files are stored in the same folder as data collection and use nlohmann's Json for Modern C++ for parsing
- It adds data from the json into two different hash tables. One for traffic and the other for road quality
- Then using values in the traffic, it calculates average traffic per length for a certain hwy and adds this to every data node in the Hash Table for quality.
- Then the priority queue makes use of this data in order to determine which highways need to be fixed the soonest.
- Priority Queue
- It needs a priority queue that takes into account the road quality and traffic volume through the section. It prioritizes the sections of road which have the worst quality and the greatest traffic volume
- Formula for determining Priority
- If traffic volume is above a certain point it can also recommend other infrastructure upgrades such as HOV/Toll lane