Development of Continuous Time, Temporally Constrained and Behaviorally Consistent Tour Pattern Generation System for Modeling the Impacts of Autonomous Vehicle Future

Details

• Creators:
  Zhang, Jingyue ; Mondal, Amit ; Enam, Annesha ; Konduri, Karthik C
• Corporate Creators:
  University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program
• Subject/TRT Terms:
  • Autonomous vehicles
  • Forecasting
  • Impacts
  • Travel demand
  • Predictive models
  • Travel behavior
  • Chronological time
  • Constraints
• Publication/ Report Number:
  2018 Project 11
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education
• Abstract:
  The primary objective of this research is to operationalize a new tour-based travel behavior modeling framework that addresses three limitations of existing frameworks. First, it represents time as a continuous entity. Second, it captures the interrelationship between stops and tours across the day. Third, it accommodates the temporal constraints within which an individual generates trips and activities. More specifically the report documents models that help implement the framework. A key contribution of the research is in the use of Multiple Discrete-Continuous Extreme Value (MDCEV) modelling approach formulated by Bhat 1. The report documents the models developed.
• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/61502/dot_61502_DS1.pdf
• File Type:
  [PDF - 1.24 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:07c20d3ec372dcb6fcca1f4dd8ee7bfccc578523246e530380c054acd480ff0a367c649f0edf505bc2c746ddce477a9980bd2e1c3e18cd0a2699c5a8fa028b0c