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.

Recent developments and research needs in modeling lane changing

Graphs and matrices

The Mathematical Theory of Optimal Control. By L. S. Pontryagin, V. G. Boltyanskii, R. V. Gamkrelidze and E. F. Mishchenko. Pp. vii, 340. 93s. 1964. (Pergamon.)

In this article, a speed consensus strategy that combined distributed active disturbance rejection control (ADRC) framework with a consensus algorithm is proposed for the coordinated motion control of a wheel-leg robot. In addition, combined with the proposed strategy, a new steering system is designed. The proposed strategy can deal with the coordinated motion control problem of the robot with internal modeling uncertainty and external disturbances. To this end, a new ADRC consensus protocol for the robot motion control system is proposed under an undirected graph. By applying this consensus protocol to the robot motion control system, the problem of coordinated motion control can be solved. The proposed new steering system consists of four inverted Stewart platforms that can achieve an angle range of $ - \text{60}^{\circ} - + \text{60}^\circ $ and make the steering precisely and nimbly. To deal with the consensus issue with different leaders when the robot is steering, the proposed ADRC consensus protocol is combined with the new steering system. The application of the proposed method is illustrated in the electric parallel wheel-leg robot system. Experimental results are provided to verify the effectiveness of the proposed approach.

Coordinated Motion Control for a Wheel-Leg Robot With Speed Consensus Strategy

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

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 Microscopic Model for Lane-Less Traffic

In this paper, a collection of double integrator agents with bounded inputs is considered. Communication is possible between any two agents only if the inter-agent distance is less than a fixed threshold. A special node, referred to as the “ leader ,” generates an unknown reference trajectory to which all the other agents are required to converge in the shortest possible time. Assuming the initial communication graph to be connected, a directed spanning tree rooted at the leader is identified using a local algorithm. The dynamics of any two agents connected by an edge in the selected tree are modeled as a time-optimal pursuit–evasion game, while maintaining the inter-agent communication link. Using the corresponding feedback saddle-point strategies, local min–max time control laws for each pair of agents are formulated. For the selected tree, the proposed collection of local min–max time control strategies is shown to be the communication preserving global min–max time strategy.

Min–Max Time Consensus Tracking With Communication Guarantee

Computation of feedback control for time optimal state transfer using Groebner basis

In this paper, a distributed multi-agent consensus algorithm with theoretically provable convergence properties is implemented outdoors with three quadrotors. These quadrotors communicate with each other over an incomplete communication graph. Each quadrotor computes its position using only GPS data and transmits this information to the neighbouring quadrotors using Xbee wireless modules. The relative position information from all the neighbours is used by each quadrotor to compute the required pitch and roll angles, according to the consensus algorithm. It is shown that this distributed control law successfully navigates all the quadrotors to an autonomously decided consensus point. Details of the implementation and the consensus experiment are presented.

Implementation of distributed consensus on an outdoor testbed

The problem of computing the minimum time to consensus of multiple identical double-integrator agents is considered A distributed algorithm for computing the final consensus target state is proposed Local feedback time optimal control laws are synthesized to drive each agent to the computed final consensus target state Each agent is assumed to know the states of every other agent As a part of the algorithm, every possible triplet of agents compute their mutual minimum time to consensus The maximum value among these triplet minimum times is shown to be the required minimum time to consensus for the entire group Since the required computation can be performed for each triple separately, it can be distributed evenly among the agents

Ameer K. Mulla

Papers

A Microscopic Model for Lane-Less Traffic

Min–Max Time Consensus Tracking With Communication Guarantee

Computation of feedback control for time optimal state transfer using Groebner basis

Implementation of distributed consensus on an outdoor testbed

Distributed computation of minimum time consensus for multi-agent systems