Search arXivSearch

arXiv · 2001.01283

One-Shot Coordination of First and Last Mode Transportation

Abstract

In this paper, we consider coordinated control of feeder vehicles for first and last mode transportation. The model is macroscopic with volumes of demands and supplies along with flows of vehicles. We propose a one-shot problem for transportation of demand to or from a hub within a fixed time window, assuming the knowledge of the demand and supply configurations. We present a unified optimization framework that is applicable for both operator profit maximization and social welfare maximization. The latter goal is useful for applications such as disaster response. The decision variables in the optimization problem are routing and allocations of the vehicles for different services. With K.K.T. analysis we propose an offline method for reducing the problem size. Further, we also analyze the problem of maximizing profits by optimally locating the supply for a given total supply and present a closed form expression of the maximum profits that can be earned over all supply configurations for a given demand configuration. We also show an equivalence between optimal supply location in the first mode problem and the last mode problem. We present a model for pricing based on the cost and travel time of the best alternate transportation and present necessary conditions for the feeder service to be viable. We illustrate the results through simulations and also compare the proposed model with a traditional vehicle routing problem. Through simulations, we also compare with the microscopic version of the problem with the decision variables being integers. We demonstrate that the route reduction algorithm proposed for the macroscopic formulation is still useful for computing nearly optimal solutions to the microscopic problem with much improved computational efficiency.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Subhajit Goswami, Pavankumar Tallapragada. 2021-05-08. One-Shot Coordination of First and Last Mode Transportation. https://arxiv.org/abs/2001.01283

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Ensuring Stability of Non-Minimal Modes in Input-Output Data-Driven Representation

Many recent data-driven control approaches for linear time-invariant systems are based on output trajectory prediction using input-output data matrices. The system dynamics described by this predictor, which we refer to as the input-output data-driven representation, yields non-unique autoregressive with exogenous inputs (ARX) models having possibly unstable non-minimal modes. In this note, we show that the stability of these non-minimal modes is ensured by a certain choice of ARX model, which coincides with the minimum-norm least-squares predictor using the Moore-Penrose inverse of the data matrix. This stability guarantee holds regardless of the underlying system's stability. Moreover, the stability persists under sufficiently small noise in data when a suitably truncated Moore-Penrose inverse is used. Consequently, the ARX model need not be reduced to the true system order in order to avoid unstable additional modes.

eess.SY

Optimization-Based Formation Flight on Libration Point Orbits

A model predictive control (MPC) framework is developed for station-keeping in spacecraft formation flight along libration point orbits. At each control period, the MPC policy solves a multi-vehicle optimal control problem (MVOCP) that tracks a reference trajectory, while enforcing path constraints on the relative motion of the formation. The control policy makes use of a limited set of control nodes consistent with operational constraints that allow only a small number of maneuver opportunities per revolution. To promote recursive feasibility, path constraints are progressively tightened across the prediction horizon. An isoperimetric reformulation of the constraints is used to prevent inter-sample violations. The resulting MVOCP is a nonconvex program, which is solved via sequential convex programming. The proposed approach is evaluated in a high-fidelity ephemeris model under uncertainties for a formation along the near-rectilinear halo orbit (NRHO), and subject to path constraints on inter-spacecraft separation and relative Sun phase angle. The results demonstrate maintenance of a spacecraft formation that satisfies the path constraints with realistic cumulative propellant consumption.

eess.SY

Certificates Synthesis for A Class of Observational Properties in Stochastic Systems: A Unified Approach

In this paper, we investigate the probabilistic formal verification of stochastic dynamical systems over continuous state spaces. Motivated by problems in state estimation and information-flow security, we introduce the notion of observational properties, which characterize the inferences an external observer can draw from system outputs. These properties are formulated as probabilistic hyperproperties based on HyperLTL over finite traces, yielding a unified framework that subsumes several existing notions studied separately in the literature. We reduce the verification problem to reachability analysis over an augmented structure that integrates the system dynamics with an automaton representation of the specification. Building on this construction, we develop stochastic barrier certificates that provide probabilistic guarantees for property satisfaction while avoiding explicit state-space discretization. The effectiveness of the proposed framework is demonstrated through a case study.

eess.SY