Automated, Data-Driven Performance Regime for Operations Management, Planning, and Control

Abstract

As public transit agencies install new technology systems, these agencies are gaining increasing amounts of data. These data have the potential to change how transit agencies operate by generating better information for decision making. Deriving value from these data and applying it to improve service requires changing the institutional processes that developed when agencies had little reliable information about their systems and customers. This research used the Massachusetts Bay Transportation Authority as a case study. The research assessed how the agency measured performance and then redesigned and advanced the agency's daily performance reports for rapid transit through a collaborative and iterative process with the operations control center staff. These reports were used to identify poor performance, to implement pilot projects to address the causes of poor performance, and to evaluate the effects of these pilots. Through the case study, this research found that service controllers’ trust and interpretation of performance information determined the impact the information had on operations. The results showed that new data would be most effective in producing service improvements if measurements accurately reflected human experience and were developed in conjunction with their intended users. Developing small pilot projects during this collaborative process would also enable new performance information and results in sustainable service improvements.

Monitoring Multimodal Travel Environment Using Automated Fare Collection Data: Data Processing and Reliability Analysis

“…The information obtained from an AFC system is primed to help us better assess transit network reliability and improve operating performance (Tribone et al 2014). Transit network reliability is a concept that captures the extent of unexpected increase or decrease in travel environment measures.…”

Identifying Public Transit Commuters Based on Both the Smartcard Data and Survey Data: A Case Study in Xiamen, China

“…Fortunately, Automatic Fare Collection (AFC) systems have been widely implemented in China as a more efficient way of 2 Journal of Advanced Transportation managing fare over the manual collection method [12]. At the same time, smartcard data can provide more abundant and higher quality travel data with less cost, through which travel patterns could be analyzed based on precise observations of individuals' smartcard usage in a time period [10,[13][14][15][16][17][18].…”

A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions

“…Tannock et al (2007) developed a supply chain model builder and presented its concept and working in the article. The authors suggested that data-driven simulation is helpful in improvement in SCs Tribone et al (2014). presented the projects and reports showing the effect of temporal and simple spatial data for vehicles and customers on targeted improvements in institutional service and process by utilizing the focused and collaborative design.…”