Get Google's help to influence road quality improvement around the world
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We can all agree that road conditions all around the world (most cities in most countries) could do with a lot of improvement. The problem gets exacerbated in overcrowded cities with poor road quality (e.g. India and other developing nations).
We all use Google Maps most of the time, not just to navigate, but also to check how long it will take us to reach the destination. Even if a handful of users use Google Maps at any point in time, that crowd-sourced information is sufficient for Google to assign a realistic color code (blue, yellow, red) as well as a highly accurate ETA for the destination (which is nothing but Distance divided by Average Traffic Speed over the distance).
So the solution is pretty simple, but to summarize, it's this -
- Publish a scorecard showcasing the ability (or inability) of city administrations to manage road traffic by socializing a simple metric that is easily understood
How do you do that?
- Assign a numerical value of speed to every part of every road within a city for every minute of every day.
- Calculate the weighted average road traffic speed of the entire city for that day, viz. (road lengths x associated speeds x time) / (road lengths x time).
- Publish a daily/weekly/monthly/annual ranking of all major cities around the world in terms of road traffic speed
- If possible, also publish a daily/weekly/monthly/annual ranking in terms of average distance covered, and average commute time (based on users' phones)
- Create global awareness by socializing this as part of Google's annual trend reports (which words were the most popular, etc)
Reasons why Google should do this -
- Because Google can.
- Because only Google can.
- Because Google has the data.
- Because Google cannot be influenced by local city governments.
- Because this creates a simple metric that people can understand.
- Because this can help citizens hold their elected governments to better accountability in a tangible way.
Solution approach -
For simplicity's sake, let's assume a subset of the city, say a road of 6 km -
- 1 km is tagged as 20 kmph for 4 hours, 30 kmph for 6 hrs and 40 kmph for 14 hours
- 2 km are tagged as 30 kmph for 3 hrs, 50 kmph for 8 hrs and 60 kmph for 13 hrs
- 3 km are tagged as 15 kmph for 6 hrs, 25 kmph for 8 hrs and 40 kmph for 10 hrs
- The average road traffic speed for the entire stretch of 6 km would be --- (1*(20*4 + 30*6 + 40*14) + 2*(30*3 + 50*8 + 60*13) + 3*(15*6 + 25*8 + 40*10)) / (6*24), i.e. (1*820 + 2*1270 + 3*690) / 144, i.e. 37.7 kmph
- When you do this for the entire length and breadth of the city, the best portions and the worst portions will average each other out, and give us a single numerical value that represented the city's performance on road traffic management for that day.
- Increase the measuring window to a week, or a month, or a year, and you get a simple single metric that encapsulates performance for any given time period.
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