Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks

Table 4

Outline of all microscopic simulation frameworks.

Simulation frameworks	Applications	Important characteristics				Limitations
		Mixed traffic	Lane changing	Continuous manoeuvre	Vehicle heterogeneity
AIMSUN	Dynamic traffic assignment, signal planning, highways, VMS					Lateral displacement within a lane cannot be modelled, and slow-moving vehicles form a bottleneck in mixed traffic modelling
CARSIM	Urban traffic flow, congestion conditions, motorways	—		—		Follows the car-following model while modelling emergency braking neglecting driver’s behaviour parameters
CORSIM	Merging sections, incidents, signal designs, VMS	—		—		Gap acceptance behaviour is fixed, no 3D animation, not well validated, no ramp metering
MITSIM	Intersection control, traffic management, ITS, ramp control, VMS			—		Insufficient parameters, difficulty in calibration, the smoother reaction of leading vehicle causing emergency deceleration
NETSIM	Pedestrian modelling, signal designing, congested flow conditions, urban roads	—		—		Cannot simulate many vehicles, more simulation time than real-time, only for academic purposes
PARAMICS	Intersections, roundabouts, automated signs, congestion conditions, transit controls			—		Unstable traffic assignment, improper control options, inaccuracy in modelling vehicle guidance
SimTraffic	Signal design, intersections, roundabouts, pedestrians	—		—		Fixed headway, no ramp metering, unstable saturation flow rates
SUMO	Heterogeneous traffic, freeways, intersections,	—		—		Longer computational rates, discrete lane changing, lateral displacement within a lane cannot be modelled, bottleneck formation due to low-speed vehicles
VISSIM	Heterogeneous traffic, pedestrians, intersections, signal control, transit operations, ramp metering			—		Lateral displacement within a lane cannot be modelled, bottleneck formation due to low-speed vehicles in mixed traffic flow, no traffic assignment algorithm