arXiv subjects

Saugat Shahi

Publications and source records attributed to Saugat Shahi.

3 recordsLinked to original sources

arXiv2026

A heuristic for optimal coordination of autonomous vehicles: static problems

We consider the coordination of autonomous vehicles at unsignalized intersections, where trajectory planning and crossing-order decisions are intrinsically coupled, thereby making their simultaneous optimization intractable in practice. To this end, we propose a heuristic based on a hierarchical structure consisting of a series of nonlinear programs (NLP) in the lower level, which optimizes trajectories of each vehicle for a given crossing order, and a high-level heuristic to design new crossing schedules that exploits sensitivity information from the lower-level NLPs. Extensive numerical simulations across a broad range of traffic scenarios demonstrate that our strategy achieves substantially improved scheduling with respect to first-in-first-out ordering while preserving computational tractability.

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arXiv2026

A heuristic for optimal coordination of autonomous vehicles: dynamic problems

The coordination of autonomous vehicles at unsignalized intersections requires deciding both the trajectories of the vehicles and their crossing order, with the additional difficulty that the set of vehicles to be coordinated changes as traffic flows through the intersection. Since the resulting mixed-integer optimal control problem is hard to solve online, we propose an arrival-triggered receding-horizon scheme built around a schedule-refinement heuristic: for a fixed crossing order, a single nonlinear program (NLP) optimizes all trajectories and crossing times, and the first-order sensitivities of the cost with respect to the vehicle schedule are used to select adjacent swaps that are likely to reduce the overall cost. Replanning is triggered only when a new vehicle arrives, the new vehicle is appended at the tail of the current crossing order, and a memory of evaluated swaps that persists across replanning steps avoids redundant computations. Simulations of traffic scenarios involving streams of a few hundred heterogeneous vehicles show that the proposed scheme recovers most of the optimality gap incurred by first-in-first-out scheduling.

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arXiv2026

A heuristic for optimal coordination of autonomous vehicles: real-time algorithms

When coordinating connected and automated vehicles at an unsignalized intersection, the crossing order and the vehicle trajectories must be decided jointly. For a fixed crossing order, the problem can be formulated conveniently in a bi-level form where each vehicle solves its own optimal control problem, whose optimal value is a function of its entry and exit times, and a coordinator optimizes these times subject to precedence constraints. We compute the first and second order sensitivities of lower-level problems, which are required to solve the upper-level problem, by means of algorithmic differentiation using the real-time software package \texttt{acados}. This implementation exploits tailored algorithms to obtain a computationally efficient implementation of the optimal coordination algorithm. We validate our implementation in numerical simulations that demonstrate both real-time feasibility and effectiveness of our algorithm.

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