least as percentages of trucks and commuter buses increase, partly in response to reducing the carbon footprint of individual
transport options. However, these larger units, while capable of carrying increased loads and commuter numbers,
involve trade-off of benefits against potentially negative impacts, such as additional delays, safety [2] and so on. Other challenges
for these traffic systems are rooted in the details of urban road features and related vehicle movement [3,4]. Although
macroscopic models can capture traffic flow dynamics for large networks, micro-simulation models are required for a detailed
description and analysis of the influence of traffic mix. The popularity of cellular automata (CA) models, e.g., owes
much to their ability to incorporate flexible updating rules able to describe complexities, such as stop and go traffic, transition
from free flow to congestion and impact of vehicle and driver type, which are not readily accessible through top-down
differential equation models. Thus, the aim of urban network modelling is, typically, to explore congestion; in particular,
intersections and other configurations, which are ‘‘bottlenecks’’ of the network, and hence an important focus for microsimulation
investigations. With large traffic volumes, breakdown of traffic flow is likely to occur, particularly on single-lane
roads where both turning and straight ahead vehicles wait in a single queue. Nonetheless, most European cities still rely, to
some extent, on single-lane connections to major arterial routes.