Rakesh Chavan

Bio: Rakesh Chavan is an academic researcher from MathWorks. The author has contributed to research in topics: Traffic wave & Overtaking. The author has an hindex of 2, co-authored 3 publications receiving 18 citations.

A Microscopic Model for Lane-Less Traffic

Abstract: In this paper, a new model is introduced for traffic on broad roads, where the drivers do not follow lane-discipline. For both longitudinal and lateral motions, the driver reactions are assumed to be influenced by possibly a number of vehicles, obstacles, and unmodeled entities in visibility cones to the front and to the sides of each vehicle. The network of influences and the resultant interaction is modeled by “influence graphs.” In congested traffic situations, it is assumed that the influence structure is time invariant and all drivers are forced to behave homogeneously. Then, the collection converges to a layered formation with fixed intervehicle distances. In sparse and heterogeneous traffic, the velocity and intervehicle separations in the set of modeled vehicles, though can oscillate continuously, are uniformly bounded. These model-based predictions are verified experimentally. Videos of typical traffic on a sample road in Mumbai city, India, are recorded. Detailed motion information of groups of cars is extracted through image processing techniques. The proposed model is initialized with the extracted data and the computed trajectories are compared with the actual ones calculated from the images. It is verified that the proposed model, in addition to macroscopic patterns, can also accurately predict complex maneuvers, such as overtaking, sideways movements and avoiding collisions with slower moving vehicles.

A model for lane-less traffic with local control laws

Abstract: In this paper, a new model for traffic on roads with multiple lanes is developed, where the vehicles do not adhere to lane discipline. Assuming identical vehicles, the dynamics is split along two independent directions — the Y-axis representing the direction of the traffic and the X-axis representing the lateral or the direction perpendicular to the traffic direction. Different influence graphs are used to model the interaction between the vehicles in these two directions. The instantaneous accelerations of each vehicle, in both X and Y directions, are functions of the measurements from the neighbouring vehicles according to these influence graphs. Under time invariant influence structure, expected for example, in dense traffic, the collection converges to a layered formation with fixed inter-vehicle distances. In general, the formation is BIBO stable with the velocity and inter vehicle separations oscillating between a finite number of equilibrium points.

A dynamic model for lane-less traffic

Abstract: The problem of modeling road traffic, when the drivers do not obey lane discipline, in considered. Identical vehicles are assumed to influence each other based on proximity and visual feedback. This percolation of influence across suitably defined layers of vehicles, in modeled using weighted directed graphs. Drivers accelerate, decelerate or maneuver sideways with the objective of maintaining safe inter-vehicle distances between the cars. This target inter-vehicle distance varies with the absolute velocity of the cars. When the influence structure is time invariant, e.g. in dense traffic, the collection converges to a layered formation with inter-vehicle distances based on vehicle velocities. In general, for a changing influence topology the inter-car distance can oscillate, while remaining uniformly bounded.

Recent developments and research needs in modeling lane changing

Abstract: This paper comprehensively reviews recent developments in modeling lane-changing behavior. The major lane changing models in the literature are categorized into two groups: models that aim to capture the lane changing decision-making process, and models that aim to quantify the impact of lane changing behavior on surrounding vehicles. The methodologies and important features (including their limitations) of representative models in each category are outlined and discussed. Future research needs are determined.

Lane-free Artificial-Fluid Concept for Vehicular Traffic

Abstract: A novel paradigm for vehicular traffic in the era of connected and automated vehicles (CAVs) is proposed, which includes two combined principles: lane-free traffic and vehicle nudging, whereby vehicles are "pushing" (from a distance, using communication or sensors) other vehicles in front of them. This traffic paradigm features several advantages, including: smoother and safer driving; increase of roadway capacity; and no need for the anisotropy restriction. The proposed concept provides, for the first time since the automobile invention, the possibility to actively design (rather than describe) the traffic flow characteristics in an optimal way, i.e. to engineer the future CAV traffic flow as an efficient artificial fluid. Options, features, application domains and required research topics are discussed. Preliminary simulation results illustrate some basic features of the concept.

Lane-Free Artificial-Fluid Concept for Vehicular Traffic

Abstract: Vehicular traffic has evolved as a crucial means for the transport of persons and goods, and its importance for the economic and social life of modern society cannot be overemphasized. On the other hand, recurrent vehicular traffic congestion, which appears on a daily basis, particularly in metropolitan areas, around the globe, has been a (increasingly) serious, in fact threatening, problem that calls for drastic solutions. Traffic congestion causes excessive travel delays, substantial fuel consumption and environmental pollution, and reduced traffic safety. Conventional traffic management measures are valuable [1] – [3] but not sufficient to address the heavily congested traffic conditions, which must be addressed in a more comprehensive way that exploits gradually emerging and future ground-breaking capabilities of vehicles and the infrastructure.

Optimal internal boundary control of lane-free automated vehicle traffic

Abstract: A recently proposed paradigm for vehicular traffic in the era of CAV (connected and automated vehicles), called TrafficFluid, involves lane-free vehicle movement. Lane-free traffic implies that incremental road widening (narrowing) leads to corresponding incremental increase (decrease) of capacity; and this opens the way for consideration of real-time internal boundary control on highways and arterials, in order to flexibly share the total (both directions) road width and capacity among the two directions in dependence of the bi-directional demand and traffic conditions, so as to maximize the total (two directions) flow efficiency. The problem is formulated as a convex QP (Quadratic Programming) problem that may be solved efficiently, and representative case studies shed light on and demonstrate the features, capabilities and potential of the novel control action.