Wave propagation of the traffic flow dynamic model based on wavefront expansion

This paper discusses propagation of perturbations along traffic flow modeled by a modified second-order macroscopic model through the wavefront expansion technique. The coefficients in this expansion satisfy a sequence of transport equations that can be solved analytically. One of these analytic solutions yields information about wavefront shock. Numerical simulations based on a Padé approximation of this expansion were done at the end of this paper and results showed that propagation of perturbations at traffic flow speed conforms to the theoretical analysis results.

Continuum modeling of freeway traffic flows:State-of-the-art,challenges and future directions in the era of connected and automated vehicles

Connected and automated vehicles(CAVs)are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling.While numerous studies have proposed optimal modeling and control strategies for CAVs with various objectives(e.g.,traffic efficiency and safety),there are uncertainties about the flow dynamics of CAVs in real-world traffic.The uncertainties are especially amplified for mixed traffic flows,consisting of CAVs and human-driven vehicles,where the implications can be significant from the continuum-modeling perspective,which aims to capture macroscopic traffic flow dynamics based on hyperbolic systems of partial differential equations.This paper aims to highlight and discuss some essential problems in continuum modeling of real-world freeway traffic flows in the era of CAVs.We first provide a select review of some existing continuum models for conventional human-driven traffic as well as the recent attempts for incorporating CAVs into the continuum-modeling framework.Wherever applicable,we provide new insights about the properties of existing models and revisit their implications for traffic flows of CAVs using recent empirical observations with CAVs and the previous discussions and debates in the literature.The paper then discusses some major problems inherent to continuum modeling of real-world(mixed)CAV traffic flows modeling by distinguishing between two major research directions:(a)modeling for explaining purposes,where making reproducible inferences about the physical aspects of macroscopic properties is of the primary interest,and(b)modeling for practical purposes,in which the focus is on the reliable predictions for operation and control.The paper proposes some potential solutions in each research direction and recommends some future research topics.

Iterative learning control approach for ramp metering

An iterative learning control scheme is developed to the traffic densitycontrol in a macroscopic level freeway environment. With rigorous analysis, the proposed intelligentcontrol scheme guarantees the asymptotic convergence of the traffic density to the desired one. Thecontrol scheme is applied to a freeway model, and simulation results confirm the efficacy of theproposed approach.

A Piecewise Switched Linear Approach for Traffic Flow Modeling

Traffic modeling is a key step in several intelligent transportation systems（ITS） applications. This paper regards the traffic modeling through the enhancement of the cell transmission model. It considers the traffic flow as a hybrid dynamic system and proposes a piecewise switched linear traffic model. The latter allows an accurate modeling of the traffic flow in a given section by considering its geometry. On the other hand, the piecewise switched linear traffic model handles more than one congestion wave and has the advantage to be modular. The measurements at upstream and downstream boundaries are also used in this model in order to decouple the traffic flow dynamics of successive road portions. Finally, real magnetic sensor data, provided by the performance measurement system on a portion of the Californian SR60-E highway are used to validate the proposed model.

Incident indicators for freeway traffic flow models

Developed in this paper is a traffic flow model parametrised to describe abnormal traffic behaviour.In large traffic networks,the immediate detection and categorisation of traffic incidents/accidents is of capital importance to avoid breakdowns,further accidents.First,this claims for traffic flow models capable to capture abnormal traffic condition like accidents.Second,by means of proper real-time estimation technique,observing accident related parameters,one may even categorize the severity of accidents.Hence,in this paper,we suggest to modify the nominal Aw-Rascle(AR)traffic model by a proper incident related parametrisation.The proposed Incident Traffic Flow(ITF)model is defined by introducing the incident parameters modifying the anticipation and the dynamic speed relaxation terms in the speed equation of the AR model.These modifications are proven to have physical meaning.Furthermore,the characteristic properties of the ITF model is discussed in the paper.A multi stage numerical scheme is suggested to discretise in space and time the resulting non-homogeneous system of PDEs.The resulting systems of ODE is then combined with receding horizon estimation methods to reconstruct the incident parameters.Finally,the viability of the suggested incident parametrisation is validated in a simulation environment.

An integrated approach for dynamic traffic routing and ramp metering using sliding mode control

The problem of designing integrated traffic control strategies for highway networks with the use of route guidance, ramp metering is considered. The highway network is simulated using a first order macroscopic model called LWR model which is a mathematical traffic flow model that formulates the relationships among traffic flow characteristics in terms of density, flow, and mean speed of the traffic stream. An integrated control algorithm is designed to solve the proposed problem, based on the inverse control technique and variable structure control（super twisting sliding mode）. Three case studies have been tested in the presence of an on-ramp at each alternate route and where there is a capacity constraint in the network. In the first case study, there is no capacity constraint at either upstream or downstream of the alternate routes and the function of the proposed algorithm is only to balance the traffic flow on the alternate routes. In the second case study, there is capacity constraint at downstream of alternate routes. The proposed algorithm aims to avoid congestion on the main road and balance the traffic flow on the alternate routes. In the last case study, there is capacity constraint at upstream of alternate routes. The objective of proposed algorithm is to avoid congestion on the main road and to balance the traffic flow on the alternate routes. The obtained results show that the proposed algorithms can establish user equilibrium between two alternate routes even when the on-ramps, located at alternate routes, have different traffic demands.