A Microscopic Simulation Modelling of Vehicle Monitoring Using Kinematic Data Based on GPS and ITS Technologies

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Journal of Software

• Publication date

  2014-01-06

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.4304/JSW.9.6.1382-1388
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• AN OVERVIEW OF SECURITY ISSUES INVOLVING MARINE CONTAINERS AND PORTS

  2003cited by this paper
• Antiterrorism Security and Surface Transportation Systems: Review of Case Studies and Current Tactics

  2003cited by this paper
• DEVELOPMENT AND ADAPTATION OF CONSTRUCTIVE PROBABILISTIC NEURAL NETWORK IN FREEWAY INCIDENT DETECTION

  2002cited by this paper
• FREEWAY INCIDENT DETECTION USING KINEMATIC DATA FROM PROBE VEHICLES

  2002cited by this paper
• Mobile Sensor and Sample-Based Algorithm for Freeway Incident Detection

  2002cited by this paper
• Protecting public surface transportation against terrorism and serious crime : an executive overview

  2001cited by this paper
• FUZZY-WAVELET RBFNN MODEL FOR FREEWAY INCIDENT DETECTION

  2000cited by this paper
• EMERGENCY PREPAREDNESS FOR TRANSIT TERRORISM

  2000cited by this paper
• A neuro-genetic-based universally transferable freeway incident detection framework

  1996cited by this paper
• Application of Fuzzy Logic and Neural Networks to Automatically Detect Freeway Traffic Incidents

  1994cited by this paper
• Simulation Of Freeway Incident Detection Using Artificial Neural Networks

  1993cited by this paper
• FREEWAY INCIDENT DETECTION THROUGH FILTERING

  1993cited by this paper
• Catastrophe theory and patterns in 30 second freeway traffic data, implications for incident detection

  1989cited by this paper
• DEVELOPMENT OF FREEWAY INCIDENT-DETECTION ALGORITHMS BY USING PATTERN-RECOGNITION TECHNIQUES

  1979cited by this paper

• Detecting Traffic Anomalies in Urban Areas Using Taxi GPS Data

  2015cites this paper