PROJECT TITLE :

Visually Exploring Transportation Schedules

ABSTRACT:

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service sometimes deviates from the set up. Thus, transportation analysts need to identify, compare and explain both eventual and systemic performance problems that has got to be addressed therefore that better timetables will be created. The purely statistical tools commonly utilized by analysts cause several difficulties thanks to the big variety of attributes at trip- and station-level for planned and real service. Additionally challenging is the requirement for models at multiple scales to go looking for patterns at completely different times and stations, since analysts don't recognize specifically where or when relevant patterns may emerge and would like to compute statistical summaries for multiple attributes at different granularities. To help in this analysis, we tend to worked in close collaboration with a transportation professional to style TR-EX, a visible exploration tool developed to identify, examine and compare spatio-temporal patterns for planned and real transportation service. TR-EX combines two new visual encodings impressed by Marey's Train Schedule: Trips Explorer for trip-level analysis of frequency, deviation and speed; and Stops Explorer for station-level study of delay, wait time, reliability and performance deficiencies such as bunching. To tackle overplotting and to provide a strong illustration for a massive numbers of journeys and stops at multiple scales, the system supports variable kernel bandwidths to realize the level of detail needed by users for different tasks. We justify our style choices based on specific analysis wants of transportation analysts. We tend to provide anecdotal proof of the efficacy of TR-EX through a series of case studies that explore NYC subway service, which illustrate how TR-EX can be used to confirm hypotheses and derive new insights through visual exploration.