LARGE-SCALE PARALLEL GRAPH-BASED SIMULATIONS - MATSim

Chapter 2
The Queue Model for Traffic Dynamics
2.1 Introduction
A traffic flow simulation consistent with the multi-agent approach discussed in Chapter 1 and
e.g., by [67, 65] should fulfill the following conditions:
The model should have individual travelers/vehicles 1 in order to be consistent with all
agent-oriented learning approaches.
The model should be simple in order to be comparable with static assignment and in
order to allow concentration on computational issues rather than modeling issues.
This includes the ability of task parallelization into software.
The model should be computationally fast so that scenarios of a meaningful size can be
run within acceptable periods of time.
For the work presented here, a fourth condition is also stated:
The model should be somewhat realistic so that meaningful comparisons to real-world
results can be made.
These conditions make the use of existing software packages, such as DynaMIT [17],
DYNASMART [18], or TRANSIMS [59], difficult since these software packages are already
fairly complex and complicated. An alternative is to select a simple model for large scale microscopic
network simulations, and to re-implement it. If one wants queue spill-back, there are
essentially two starting points: queueing theory, and the theory of kinematic waves.
In queueing theory, one can build networks of queues and servers [76, 14, 73]. Packets
enter the network at an arbitrary queue. Once in a queue, they wait typically in a first-in firstout
(FIFO) queue until they are served; servers serve queues with a given rate. Once the packet
is served, it will enters the next queue.
This can be directly applied to car/vehicle traffic, where packets correspond to vehicles,
queues correspond to links, and serving rates correspond to link capacities. The decision of a
vehicle about which link to enter after it is served at an intersection is given by the vehicle’s
route, which is a list of nodes (intersections) that a vehicle must pass through during its trip.
1 Terminology: In multi-agent simulations, agents are units. The traffic flow simulation described here simulates
the vehicle traffic. The agents in the traffic model are vehicles. Agents and vehicles are used on reciprocal
terms. Although a vehicle is an agent of transmission and is generally not restricted to a “car”, it represents a car
and accordingly a driver who is of person-type throughout this thesis.
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