Microscopic Traffic Simulator

 

A MIcroscopic Traffic SIMulator (MITSIM) has been developed for modeling traffic flows in networks involving advanced traffic control and route guidance systems [Yang and Koutsopoulos(1996)]. MITSIM represents networks at the lane level and simulates movements of individual vehicles using car-following, lane changing, and traffic signal response logic. Probabilistic route choice models are used to capture drivers' route choice decisions in the presence of real time traffic information provided by route guidance systems. MITSIM is designed as a testbed for evaluating traffic management systems with the following characteristics:

• it provides real-time sensor data that mimics the surveillance capacities of the traffic management systems in an ITS environment;
• it accepts traffic controls and routing information as input from traffic management systems and maintains the state of traffic signals and signs in the simulated network; and
• it calculates a set of measures of effectiveness (MOE) that represent the performance of the systems to be evaluated.

In this chapter we first present the overall design of MITSIM. Then we describe the details of its major elements: network, traffic controls and surveillance sensors, incidents, travel demand, vehicle routing, and vehicle movements. We conclude by discussing the main simulation output.

• Overall Design
• Network Representation
  • Nodes:
  • Links:
  • Segments:
  • Lanes:
• Toll Plazas
• Traffic Surveillance and Control Devices
  • Surveillance Sensors
  • Traffic Control Devices
• Incidents
• Travel Demand
• Vehicle Characteristics
  • Maximum acceleration rate:
  • Maximum deceleration rate:
  • Normal deceleration rate:
  • Desired speed:
  • Speed distribution across lanes:
  • Target speed:
• Vehicle Routing
  • Route Choice Model
  • Route Switching Model
  • Properties and Extensions
• Vehicle Movements
  • Reaction Time
  • Vehicle Loading
  • Acceleration Rate
    • Car following
      • Free flowing regime:
      • Emergency regime:
      • Car-following regime:
    • Merging
    • Event Responding
      • Traffic signals and signs:
      • Incidents:
      • Connection to downstream link:
      • Courtesy yielding:
  • Lane Changing
    • Lane Change Decisions
    • Gap acceptance
    • Nosing and Yielding
      • Probability of nosing:
      • Feasibility of nosing:
• Simulation Output
  • Sensor Readings
  • Measures of Effectiveness (MOE)
  • Graphical User Interface
    • Traffic network:
    • Traffic sensors:
    • Traffic controls and incidents:
    • Animation of vehicle movements:
• Validation