Mohan, Ranju

Dynamic Traffic Assignment (DTA) works on an iterative framework to reach dynamic user equilibrium which states that all routes used by the travellers leaving the same origin at the same time for the same destination will have equal and minimum travel time. The prime component of any DTA model is the underlying traffic flow model which computes travel time of vehicles. For a heterogeneous traffic flow network with lacking lane discipline conditions, traditional DTA models fail to predict travel time output even with an acceptable level of accuracy. Any traffic management measures based on this incorrect output could actually worsen the traffic congestion problem. This paper uses a recently proposed multi-class continuum model for traffic flow propagation in DTA, and the framework is tested on a hypothetical network under three traffic scenarios. The simulated network-level traffic variables, namely, inflow and travel time on paths and total system travel time, are compared with that from a microsimulation result. The paper shows that the proposed DTA framework, with its macroscopic traffic flow modelling approach, yields accurate and more intuitive prediction of network-level traffic variables in the context of heterogeneous traffic lacking lane discipline.

The paper discusses the major limitations of the existing speed–area occupancy curve for multi-class traffic. Any driver will react not to the actual area occupancy, but to a perceived area occupancy based on the spatial arrangement and percentage composition of vehicles. To address multi-class traffic peculiarities, this paper proposes a formulation for perceived area occupancy. Traffic flow is simulated on a road section using a calibrated microsimulation model for Electronics City, Bangalore, India. The speed–concentration curves are plotted for various functional forms using density, area occupancy, and perceived area occupancy. Analysis results showed that the speed–perceived area occupancy curve could capture the speed variation better than by the existing functional forms and could predict traffic flow significantly better than with that by speed–density curves when used with the fundamental equation of traffic flow.

This paper proposes a continuum model based on a three-dimensional flow-concentration surface for multi-class traffic. The model assumes that the flow of any vehicle class is a function of the class density as well as the fraction of road area occupied by other vehicle classes. By considering occupancy of road area instead of lane occupancy, the model effectively describes traffic flow that does not follow lane discipline. The propagation speed of small disturbance (PSSD), conventionally defined from the two-dimensional flow–density relationship, is reformulated for each class using a three-dimensional flow–concentration surface. Using the proposed PSSD and a speed–area occupancy (speed-AO) relationship, a second-order continuum model for multi-class traffic is formulated. The speed–AO relationship captures class-specific congestion and replicates the gap-filling behaviour commonly observed in lane-indisciplined traffic. Properties of the proposed model are validated theoretically where possible, and through numerical simulation when theoretical derivations are cumbersome. Numerical simulation of the proposed multi-class traffic model replicates field-observed phenomena such as shockwaves and rarefaction waves, local cluster effect, and gap-filling behaviour. Finally, the model is calibrated using field traffic data collected on a road section with bottleneck, and is found to replicate class-wise vehicle flows and speeds, and stop-and-go phenomena.