Summary
Predicting future arrival for traffic is not as easy at it might seem. GPS data on key devices such as buses can help collect real time data on road conditions but it is not enough. Other items such as history and ancillary data is needed to do a good prediction job.
Analysis
Mapunity and Google among other players are attempting to provide key information on traffic impacted arrivals using spacial data analysis. The result is an attempt to predict when a bus might arrive or when a specific car might arrive at a particular destination. However, to do a good job requires more data than just the GPS data from a few buses or other target vehicles in the public sector. Additional data comes in the form of:
1. additional sources such as cell phones locations in traffic situations.
2. police and other reports identifying bottlenecks.
3. History data of previous incidents and average data based on time of day.
4. Inferred data about dispersed traffic into surrounding alternate routes when detours are expected.
5. Potential analysis of traffic patterns in the reverse direction.
6. Methods used to access the reliability of data received.
7. removing holes in the data stream.
This author consults with leading institutions through GLG
Analyses are solely the work of the authors and have not been edited or endorsed by GLG.
