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A Proactive Real-Time Control Strategy Based on Data-Driven Transit Demand Prediction
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A Proactive Real-Time Control Strategy Based on Data-Driven Transit Demand Prediction (2020)A Proactive Real-Time Control Strategy Ba…Modelling bus bunching and holding control with vehicle overtaking and distributed passenger boarding behaviour (2017)Modelling bus bunching and ho…Forecasting exchange rate using deep belief networks and conjugate gradient method (2015)Forecasting exchange rate usi…Design of limited-stop bus service with capacity constraint and stochastic travel time (2015)Design of limited-stop bus se…How much can holding and/or limiting boarding improve transit performance? (2012)How much can holding and/or l…A self-coördinating bus route to resist bus bunching (2012)A self-coördinating bus route…Bus arrival time prediction at bus stop with multiple routes (2011)Bus arrival time prediction a…Hybrid predictive control for real-time optimization of public transport systems’ operations based on evolutionary multi-objective optimization (2009)Hybrid predictive control for…Analyzing urban bus service reliability at the stop, route, and network levels (2009)Analyzing urban bus service r…Optimal Slack Time for Schedule-Based Transit Operations (2006)Optimal Slack Time for Schedu…The Real–Time Stop–Skipping Problem (2005)The Real–Time Stop–Skipping P…Real-Time Optimization Model for Dynamic Scheduling of Transit Operations (2003)Real-Time Optimization Model …Design and Implementation of Bus–Holding Control Strategies with Real-Time Information (2002)Design and Implementation of …The Holding Problem with Real–Time Information Available (2001)The Holding Problem with Real…An Analytic Stochastic Model for the Transit Vehicle Holding Problem (2001)An Analytic Stochastic Model …The real-time deadheading problem in transit operations control (1998)The real-time deadheading pro…Maintaining a bus schedule (1964)Maintaining a bus scheduleA headway-based approach to eliminate bus bunching: Systematic analysis and comparisons (2009)Real-time holding control for high-frequency transit with dynamics (2015)Joint optimization of scheduling and capacity for mixed traffic with autonomous and human-driven buses: A dynamic programming approach (2020)Control Strategies for an Idealized Public Transportation System (1972)Dynamic Bus Arrival Time Prediction with Artificial Neural Networks (2002)Estimation of trip travel time distribution using a generalized Markov chain approach (2016)A machine learning based personalized system for driving state recognition (2019)Simulation-based robust optimization of limited-stop bus service with vehicle overtaking and dynamics: A response surface methodology (2019)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Dynamic bus holding strategies for schedule reliability: Optimal linear control and performance analysis (2011)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Forecasting exchange rates using feedforward and recurrent neural networks (1995)Neural network forecasting of the British Pound/US Dollar exchange rate (1998)Portfolio formation with preselection using deep learning from long-term financial data (2019)A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions (2021)Financial applications of machine learning: A literature review (2023)Impacts of Holding Control Strategies on Transit Performance (2011)Measuring service quality in urban bus transport: a modified SERVQUAL approach (2012)Transit network design based on travel time reliability (2014)Chapter 2 Public Transit (2006)Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits (2009)A real-time bus dispatching policy to minimize passenger wait on a high frequency route (2015)Public transport for smart cities: Recent innovations and future challenges (2022)A survey on demand-responsive public bus systems (2022)On Controlling Randomness in Transit Operations (1974)
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References

  • 2011Bus arrival time prediction at bus stop with multiple routes316 cited
  • 2001The Holding Problem with Real–Time Information Available293 cited
  • 2012How much can holding and/or limiting boarding improve transit performance?264 cited
  • 2012A self-coördinating bus route to resist bus bunching239 cited
  • 2001An Analytic Stochastic Model for the Transit Vehicle Holding Problem237 cited
  • 2015Forecasting exchange rate using deep belief networks and conjugate gradient method234 cited
  • 2009Analyzing urban bus service reliability at the stop, route, and network levels209 cited
  • 2003Real-Time Optimization Model for Dynamic Scheduling of Transit Operations199 cited
  • 2005The Real–Time Stop–Skipping Problem198 cited
  • 1964Maintaining a bus schedule180 cited
  • 2017Modelling bus bunching and holding control with vehicle overtaking and distributed passenger boarding behaviour177 cited
  • 2015Design of limited-stop bus service with capacity constraint and stochastic travel time158 cited
  • 2009Hybrid predictive control for real-time optimization of public transport systems’ operations based on evolutionary multi-objective optimization144 cited
  • 2006Optimal Slack Time for Schedule-Based Transit Operations141 cited
  • 1998

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The real-time deadheading problem in transit operations control
139 cited
  • 2002Design and Implementation of Bus–Holding Control Strategies with Real-Time Information136 cited
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