Agent-based Intelligent KPIs Optimization of Public Transit Control System

Public transit has a wide variety of resources. There is an infrastructure including stations and routes with multiple trips provided by different modes of transportation (metro, subway, bus). These resources must be well exploited to ensure good quality of service to passengers and especially against perturbations that may occur during the day. The contribution of this work is to model and implement a transit control system that detects perturbations and finds, through optimization, the best regulation action while respecting the constraints of the traffic situation. This system combines various measures of Key Performance Indicators (KPIs) into a single performance value, covering several dimensions depending on the type of service quality to be guaranteed. To take into account the complex and dynamic nature of transportation systems, a multiagent approach is adopted in the modelling of our system. The validation is based on real traffic data. The results show better performance of our system compared to the current resolution.

[2]  Tomer Toledo,et al.  Mesoscopic Modeling of Bus Public Transportation , 2010 .

[3]  Federico Malucelli,et al.  Delay Management in Public Transportation: Service Regularity Issues and Crew Re-scheduling , 2015 .

[4]  Wei Feng,et al.  Definition and Properties of Alternative Bus Service Reliability Measures at the Stop Level , 2012 .

[5]  Vaniyapurackal Jilu Joseph.  Punctuality Index for the City Bus Service , 2015 .

[6]  Rosaldo J. F. Rossetti,et al.  Using BDI agents to improve driver modelling in a commuter scenario , 2002 .

[7]  Noorfakhriah Yaakub,et al.  Public Transport: Punctuality Index for Bus Operation , 2011 .

[8]  R. Crookes,et al.  Reduction potentials of energy demand and GHG emissions in China's road transport sector , 2009 .

[9]  Daniel J. Graham,et al.  Development of Key Performance Indicator to Compare Regularity of Service between Urban Bus Operators , 2011 .

[10]  Steve Callas,et al.  DETERMINANTS OF BUS DWELL TIME , 2004 .

[11]  Viktor Mikhaĭlovich Glushkov,et al.  An Introduction to Cybernetics , 1957, The Mathematical Gazette.

[12]  Yunlong Zhang,et al.  Analyzing Urban Bus Service Reliability at the Stop, Route and Network Levels , 2009 .

[13]  Peter W. Eklund,et al.  Toward real-time decision making for bus service reliability , 2012, 2012 International Symposium on Communications and Information Technologies (ISCIT).

[14]  Avishai Ceder,et al.  Public Transit Planning and Operation: Theory, Modeling and Practice , 2007 .

[15]  Suwardo,et al.  Punctuality Index and Expected Average Waiting Time of Stage Buses in Mixed Traffic , 2011 .

[16]  Zhenliang Ma,et al.  A framework for the development of bus service reliability measures , 2013 .