Simulation in the context of traffic flow and control

According a special report by the Transportation Research Board [14], traffic simulations were run on computers in the United States of America as early as 1954. According to the report it became accepted that traffic simulation was possible and feasible by about 1960, at which time efforts were increasingly directed to the development, validation and use of large-scale simulation programs.

When investigating the role of simulation in the context of traffic flow and control, the work of Barcel´o [6] and Papacostas and Prevedouros [33, 35] is central. Simulation is considered to be an important tool for the analysis of highways and urban street networks, as it is through simulation that transport experts are able to study the formation and dissipation of congestion on roadways, assess the impact and effectiveness of various traffic control strategies and compare different geometric roadway designs [33]. A variety of commercial traffic simulation models are available which vary according to the specifications of the systems for which they were designed.

Gibson [16] classifies traffic simulation models as those concerned with modelling intersections, arterials, urban networks, freeways, and freeway corridors.

In this section, three different types of traffic simulation modelling approaches are described.

These approaches are prevalent in the literature, and are microscopic traffic simulation, macro-scopic traffic simulation and mesomacro-scopic traffic simulation.

3.4.1 Microscopic traffic simulation

Microscopic modelling of traffic flows is concerned with the motion characteristics, i.e. accel-eration, deceleration and lane changes, of each individual vehicle comprising the traffic stream [6]. To model driver reactions to the surrounding traffic, a vehicle following model is typically employed. A number of vehicle following models are proposed in the literature, each of vary-ing degree of complexity. The classical vehicle followvary-ing approach is relatively straightforward in that each vehicle attempts to travel at its desired speed while maintaining a safe following distance from the vehicle in front of it [35]. Barcel´o [6] describes the pioneering work carried out on vehicle following models in the 1950s, some of which were based on the California Motor Vehicle Code, as follows: “A good rule for following another vehicle at a safe distance is to allow yourself at least the length of a car between your vehicle and the vehicle ahead for every ten miles per hour of speed at which you are travelling.” Most microscopic traffic simulation models are stochastic in nature, employing Monte Carlo processes to generate random numbers used in generating vehicle arrival times as well as driver and vehicle behaviour in the system.

A microscopic simulation approach was followed in the development of the traffic simulation model presented later in this thesis. The entities of the model include the vehicles, the traffic lights themselves and the road sections on which the vehicles travel. The attributes of each individual vehicle include the velocity at which the vehicle travels, its position along a road section, its position in the queue along the road section, and its colour. The attributes associated with the traffic lights are the timings of each phase in the cycle, and the attributes of the road sections are the positions of their entry, turning, stopping and destination points. The exogenous events of the model include the arrival of a new vehicle to the system, while the endogenous events include the commencement of a vehicle’s deceleration, acceleration or changing of lanes, as well as a phase change in the cycle of the traffic lights. The service that vehicles compete for is the green signal provided by the traffic lights, and all vehicles experience a delay as they wait for service.

Microscopic traffic simulation software

Traffic simulation has become an indispensable instrument for transport planners and traffic engineers. Barcel´o [12] presents information on one such microscopic traffic flow simulator, VIS-SIM. VISSIM is a microscopic, behaviour-based multi-purpose traffic simulation model which may be used to analyse and optimise traffic flows. It is a commercial software tool, and is

used worldwide within consultancies and industry, public agencies and academic institutions.

The software is primarily suited to traffic engineers. However, as the need for greater detail in intelligent transport systems increases, so too does the number of transport planners who use VISSIM. Some common areas of application of VISSIM include, but are not limited to the development and analysis of management strategies on motorways (including impacts during phases of construction), corridor studies on arterials with signalised and non-signalised intersec-tions, analysis of alternative actuated and adaptive signal control strategies in traffic networks, and investigations with respect to so-called traffic calming schemes.

Papacostas and Prevedouros [35] describe a second microscopic simulation model called NET-SIM. NETSIM, or the NETwork SIMulation model, was originally called UTCS-1, because its development was supported by the Office Of Research of the U.S. Federal Highway Administra-tion as part of its Urban Traffic Control System program. NETSIM is a microscopic, interval scanning simulation model capable of representing complex urban networks, traffic control sys-tems and vehicular performance characteristics. The motion of each vehicle in the system is governed by a vehicle following model, including several vehicle characteristics such as vehicle turning.

3.4.2 Macroscopic traffic simulation

Macroscopic traffic flows are typically modelled from an aggregated point of view, based on a hydrodynamic analogy, by regarding traffic flows as a particular fluid process whose state is characterised by aggregate macroscopic variables, such as density, volume and speed [6]. A continuum model is usually employed when modelling traffic macroscopically. This continuum model consists of a continuity equation which represents the relationship between the speed, density and volume of the traffic flow. However, the simple continuum model does not consider acceleration and inertia effects and cannot describe non-equilibrium traffic flow dynamics with precision. A higher order continuum model accounts for this lack of accuracy, by incorporating acceleration and inertia effects by means of a momentum equation which describes the dynamic speed-density relationships observed in real traffic flow, together with a continuity equation [35].

Macroscopic traffic simulation software

A macroscopic traffic simulation package called TRANSYT is described by Papacostas and Prevedouros [35]. The TRAffic Network StudY Tool, or TRANSYT, was originally developed by Dennis Robertson at the Transport Road Researach Laboratories (UK) in 1967. Individual vehicles and their properties are not represented in TRANSYT; instead all calculations are based on average vehicle flow rates, turning movements and queue lengths. TRANSYT-7F may be used as both a simulation tool and an optimisation tool. Implementing it as a simulation tool, the performance of the existing model without any alterations is generated as output.

When run as an optimisation tool, it manipulates the cycle lengths, green splits and offsets of intersections in an attempt to minimise delays and improve progression.

3.4.3 Mesoscopic traffic simulation

Mesoscopic traffic simulation, in essence, combines aspects of both microscopic traffic simulation and macroscopic traffic simulation, in that it has the ability to account for individual vehicles in the system, but is still primarily concerned with the traffic dynamics of the vehicles as a whole

and does not explicitly consider the details of the vehicle lane changing and vehicle following behaviour [6, 35]. Because of this modification, mesoscopic models are usually less demanding of data and computationally more efficient when compared to microscopic traffic simulation models. There are two variations of mesoscopic models, those in which individual vehicles are not considered and vehicles are instead grouped into packages or platoons which move along road links, and those in which flow dynamics are determined from simplified dynamics of the individual vehicles [6].

Mesoscopic traffic simulation software

The COntinuous TRaffic Assignment Model, or CONTRAM, is an example of a traffic assign-ment and simulation model that treats groups or packets of vehicles as single entities [35]. It was developed primarily for traffic assignment purposes and can be used for simulating vehicle routing in complex traffic systems.

3.5 Summary

In this chapter, various types of simulation approaches and models were described. The various components which make up a simulation model were also described, and the steps that are typically followed in a sound simulation study elaborated upon in §3.1. The advantages and disadvantages associated with simulation studies were stated in§3.2 and §3.3, respectively. The chapter closed with a brief description of the applicability of simulation with respect to modelling and investigating traffic flows along road networks as well as commercially available software packages for the various types of traffic simulation modelling.

CHAPTER 4