With before-and-after analysis, Big Data can show which solutions work and which don’t.
Analyzing cut-through traffic restrictions is difficult because volume data is expensive and time-consuming to collect. Surveys suffer from small sample sizes and stated preference discrepancies.
![Cut-Through-Traffic-Prevention-Case-Study square](https://learn.streetlightdata.com/hs-fs/hubfs/Case%20Studies/Did%20Cut%20Through%20Measures%20Help%20or%20Hurt/Cut-Through-Traffic-Prevention-Case-Study%20square.jpg?width=285&name=Cut-Through-Traffic-Prevention-Case-Study%20square.jpg)
In this case study you’ll learn:
- How Big Data collected actual point-to-point trip information
- Where cut-through was causing congestion
- What analysis proved impact of restrictions
- Why constituents supported the results