Hello everyone,
I am working on a typical problem of real-time data analysis/datamining of an urban transport system where i have following information
- Data about how many vehicles are part of the transport system with their last known location always updated as GPS coordinates.
- Data about different routes the buses may travel with a list of stops, their zone and their GPS coordinates. Worth mentioning that a stop can be part of more than one routes where buses going to different destinations may share some stops with other buses.
- Data about the journeys that have been travelled and more specifically the journeys that are being travelled right now in real-time. This contains information about the routes, stops and then actual arrival and departures times being reported. It also contains information about planned start/end time of the journey (based on planning) and actual start and end time for the whole journey. It also contains planned arrival and departures time for each stop that is/will be travelled by the bus.
Having all that data available, I need little creative thinking to suggest what different scenarios or problems that can be addressed using analysis/mining of this data. Like congestion detection, different types of congestion, scenarios for delays and emergency situations, resource planning, rerouting - anything you can think of will be helpful. Please share your ideas.
Regards
It's one of our main subject of operational research. Next week with my team we try to come back to you with answers. Are you looking for research parteners on this subject (I mean to build a collaborative R&D project)?
Good to see that data is available. In urban transport system, travel time savings are important. Scenarios may include accidents on a major route and finding out alternatives, road closures and alternative routes, converting some roads into one way street, banning right turns, major public events such as football match, speed reduction, removing on-street parking etc.
We used these data for:
1 Estimates of the impact on the speed of the allocation of separate lanes for buses.
2 site search routes and the time of day with the highest drop rate
3 Creation of mobile applications for passengers.
i think should be used this information in the analysis of the motion the vehicles of the transport, i think you information its very interesting of model this motion, I think you could be also used to investigate the functioning of the system and propose fresh ideas to improve this system. You can also use it to phone application, in order it could be used in many ways, I am interested in helping.
I think the crowd management in case of emergency or non-emergency conditions, flash demand arising out of some peak hour activity or some technical snag, etc, re-routing or alternate routing for peak hour peak direction demands, may be explored. besides this some rapid buses- mean buses stopping lesser and only important stops having very high demands may be explored especially for longer routes so as to reduce travel time and resulting into lower automobile dependency.
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