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Introduction

Introduction

DRACULA INTERFACE

DRACULA INTERFACE

The dynamic network microsimulation framework DRACULA (Dynamic Route Assignment Combining User Learning and microsimulation) has been developed at the University of Leeds since 1993 (Liu et al 1995). It adapted a new approach to modelling road traffic networks whereby the emphasis is on the “microsimulation” of individual trip makers’ choices and individual vehicles’ movements. The model attempts to represent directly the behaviour of individual drivers and vehicles in real-time as these evolve from day to day. This is coupled with a detailed within-day traffic simulation model of the second-by-second movements of individual vehicles according to car-following, lane-changing rules and traffic controls. In combination they model the evolution of the traffic system over a representative number of days so that both within-day and between-day variabilities are included and interaction between the demand and supply modelled.

The current release version, code named DRACULA-MARS (Microscopic Analysis of Road Systems), includes only the traffic simulation model and a simplified departure-time choice model of DRACULA. This version is designed primarily for existing SATURN users who can combine the SATURN route assignment with DRACULA traffic micro-simulation for detailed network design and/or short-term forecasting.

Functions

Within DRACULA-MARS, there are functions for choice of departure-time to be modelled, and a wide range of network variability and traffic dynamics. These include modelling of:

  • Variability in network demand and supply conditions
  • More realistically dynamic phenomena
  • Complex traffic controls
  • Public transport operation and bus priority measures
  • Dynamic traffic demand management measures

Models

Basic traffic simulation model

  • Driver-vehicle characteristics
  • Car-following models
  • Lane-changing models
  • Gap-acceptance models

Models of day-to-day demand variability

  • Generated from a known variance

Models of supply variability

  • Day-to-day global variability, due to, e.g. weather lighting
  • Modelled via variable link free-flow speeds
  • Day-to-day and within-day local variability: e.g. incidents, road works
  • Modelled as road/lane blockages
  • Pre-specified location and duration of blockages

Models of emission and fuel consumption

  • Modelling COx and NOx

Models of ITS and traffic management policy

  • Intelligent speed adaptation
  • Autonomous vehicles
  • Variable speed limits
  • Dynamic road pricing
  • Dynamic and responsive signal controls

Models of public transport and priority measurement

  • Guided bus operations
  • Bus lanes
  • Bus responsive signal controls
  • Bus operation
  • Individual passenger demand

Models of complex junction interaction and special features

  • Interaction between vehicles and pedestrians (DRACULA-PEDSIM model)
  • Vehicular interactions at complex intersections (e.g. partially signalised roundabouts)
  • Motorway merge, Rare overtaking (e.g. using the opposite lane), Driving on the left/right