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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. © 2021 Elsevier B.V.

Department of Civil & Infrastructure Engineering

World University root node

Physica A: Statistical Mechanics and its Applications

Multi-class traffic flow model based on three dimensional flow–concentration surface

This paper discusses on the choice of a recently proposed multi-class, speed-area occupancy based, one-dimensional continuum model towards the measurement of network level traffic flow variables, namely, travel time and outflow. The parameters of the model are calibrated for a hypothetical mid-block with four vehicle classes, using the micro simulation data from VISSIM software. Analysis result indicates that the model produces travel time and outflow result closer to that by the VISSIM micro simulation. To explore this macroscopic model towards accurate modelling of lacking lane disciplined traffic, i.e. the traffic with frequent lateral movements, a two-dimensional formulation of the model is proposed. It is shown that the new formulation retains the properties of its original version as well as the desirable properties of any traffic flow model. © 2019 Informa UK Limited, trading as Taylor & Francis Group.

International Journal of Modelling and Simulation

Multi-class AR model: comparison with microsimulation model for traffic flow variables at network level of interest and the two-dimensional formulation

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. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Transportation Letters

On the modelling of speed–concentration curves for multi-class traffic lacking lane discipline using area occupancy

Multi-class traffic flow modelling has various approaches several of which have focused on analytical proofs. A key limitation in this field of research is the limited field data applications. This study proposes a speed-gradient-based multi-class second-order model and shows its application to three different road sections, a mid-block section, a section with a bottleneck, and a section with a signal at the end, in Chennai, India. The model captures the congestion formation and dissipation phenomena well and could predict outflow and speed fluctuations generally observed in the field scenarios accurately. The prediction of traffic flow dynamics by the proposed model is also observed to be better when compared with two existing higher-order multi-class models. © The Institution of Engineering and Technology 2020

IET Intelligent Transport Systems

Field data application of a non-lane-based multi-class traffic flow model

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the ‘gap filling’ behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models. © 2016 Elsevier B.V.

Physics Letters, Section A: General, Atomic and Solid State Physics

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Blade failure is a common problem of a steam turbine and it's failure in-service results in safety risks, repair cost and non operational revenue losses. Thus, the reliability of these blades is very important for the successful operation of a steam turbine. Dynamic analysis of a steam turbine blade in computational environment is carried out in the present work. In order to gain physical insight into the flexural dynamics of such turbine blades with the inclusion of the rotor dynamic effect, the turbine blade was approximated as a twisted cantilever beam with an asymmetric aerofoil cross-section fixed on a rigid rotor disk. Methods to validate the computational procedures for cantilever beam were established. Similar computational procedures were leveraged for the turbine blade. Critical speeds were obtained for different excitations.

INTERNOISE 2014 - 43rd International Congress on Noise Control Engineering: Improving the World Through Noise Control

Vibration analysis of a steam turbine blade

An accurate Dynamic Traffic Assignment (DTA) model should capture real world traffic flow dynamics and predict ‘dynamic’ travel times. Traditional DTA models used simple traffic flow functions such as exit flow functions, delay functions, point queues, and deterministic physical queue models. Recently, simulation based models apply well accepted traffic flow theoretic models to simulate traffic flow. However, a significant number of papers over the last decade have adopted an approximation of LWR traffic flow model, the cell transmission model, for simulating traffic flow in a DTA model. This paper compares three models, namely, LWR, Payne and Aw-Rascle, models, for their suitability to be embedded in a DTA model. Model calibration and flow simulation is performed separately using two different speed–density relationships. Results showed the importance of choice of speed-density relationship in traffic flow simulation. Models were used to simulate traffic state at different discretization levels and it was observed that as discretization becomes finer, the models' accuracy increases. Finally, the models were applied to a two node, two link network to analyze their performance in a DTA framework. The higher-order models captured congestion dissipation better than LWR model which consistently underestimates congestion and travel time. © 2014, Springer Science+Business Media New York.