Abstract:In this paper we first present an extension of the macroscopic traffic flow model METANET to multi-class flows. The resulting multi-class model takes into account the differences between, e.g., fast vehicles (cars) and slow vehicles (trucks) including their possibly different free-flow speeds and critical densities. Next, we show how this model can be used in a model-based predictive control approach for coordinated and integrated traffic flow control. In particular, we use Model Predictive Control (MPC) to coordinate various traffic control measures such as variable speed limits, ramp metering, etc. Using a simple benchmark example from the literature we illustrate that by taking the heterogeneous nature of multi-class traffic flows into account a better performance can be obtained.

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Modern urban traffic management depends heavily on the efficiency of road features, such as controlled intersections and multi-lane roundabouts. Vehicle throughput at any such configuration is modified by traffic mix, by rules governing manoeuvrability and by driver observance, as well as by traffic density. Here, we study heterogeneous traffic flow on two-lane roads through a cellular automata model for a binary mix of long and short vehicles. Throughput is investigated for a range of arrival rates and for fixed turning rate at an intersection: manoeuvres, while described in terms of left-lane driving, are completely generalisable. For a given heterogeneous distribution of vehicle type, there is a significant impact on queue length, delay times experienced and throughput at a fixed-cycle traffic light controlled two-way intersection and two-lane roundabout, when compared to the homogeneous case. As the proportion of long vehicles increases, average throughput for both configurations declines for increasing arrival rate, with average queue length and waiting time correspondingly increased. The effect is less-marked for the two-lane roundabout, due to absence of cross-traffic delays. Nevertheless, average waiting times and queue lengths remain uniformly high for arrival rates >0.25 vehicle per second (900 vph) on entry roads and for long vehicle proportion above 0.30–0.35.

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The characteristics of heterogeneous traffic (with variation in vehicle length) are significantly different from those for homogeneous traffic. The present study describes an overview of the development and validation of a stochastic heterogeneous traffic-flow simulation model for an urban single-lane two-way road, with controlled intersection. In this paper, the interaction between vehicle types during manoeuvres at the intersection are analysed in detail. Two different motorised vehicle types are considered namely cars and buses (or similar length vehicles). A twocomponent cellular automata (CA) based model is used. Traffic flow data, captured manually by Dublin City Council at a local intersection, are analysed to give a baseline on how the distribution of short and long vehicles affect throughput. It is anticipated that such detailed studies will aid traffic management and optimisation strategies for traffic flow.