Traffic Assignment
Traffic Assignment is traditionally the final step in the four step model of the traffic forecasting process, wherein the volumes of vehicles, pedestrians or non-motorised transport (NMT) are distributed onto the various routes connecting zones in a study area (Garber and Hoel (2014)). The volumes are distributed by assigning the numbers of trips (generated in the previous steps) between each Origin-Destination (O-D) pair to a certain route. Summing the assigned volumes of vehicles along all segments of these routes creates a prediction of the volume of traffic on the transport system for the chosen time in the study area. All traffic assignment models require a function that determines what routes will be chosen to travel along, generalised cost functions were therefore developed.
Generalised Cost
Travellers' perceptions of cost is multi-faceted, with monetary cost (fuel), congestion, required manoeuvres (e.g. parallel parking), scenery (Quercia et al. (2014)), distance and many other factors all having an influence. These factors make up route choice preferences and can be compiled in a generalised cost expression (de Dios Ort~Aozar and Willumsen (2011)).
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Basic generalised cost expressions consist of two factors: time and monetary cost, with the latter being seen as directly proportional to the distance travelled. These two factors are weighted and the sum is used to represent a user's perception of generalised cost. This research project thus used only travel time as generalised cost.
Wardrop's Equilibrium
Traffic assignment models that include the effect of congestion and link capacity attempt to replicate equilibrium conditions formulated by Wardrop in (1952). Wardrop's first principle defines an equilibrium in transport networks as follows:
'Under equilibrium conditions traffic arranges itself in congested networks such that all used routes between an O–D pair have equal and minimum costs while all unused routes have greater or equal costs.
Models that aim to replicate these conditions are referred to as "User Equilibrium" models which some authors refer to as a "selfish" equilibrium as Wardrop's (1952) definition assumes that all users act in their own best interest and try to minimise their own travel cost, with no regard to their effect on the network as a whole.
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This reserarch project aimed to take into account the effect of congestion and thus create a Wardop's equilibrium in a traffic network. The link below guides the reader to how this was implemented.
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