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This paper presents a sampling-based motion planning algorithm for real-time and propellant-optimized autonomous spacecraft trajectory generation in near-circular orbits. Specifically, this paper leverages recent algorithmic advances in the field of robot motion planning to the problem of impulsively-actuated, propellant-optimized rendezvous and proximity operations under the Clohessy-Wiltshire-Hill (CWH) dynamics model. The approach calls upon a modified version of the Fast Marching Tree (FMT*) algorithm to grow a set of feasible trajectories over a deterministic, low-dispersion set of sample points covering the free state space. To enforce safety, the tree is only grown over the subset of actively-safe samples, from which there exists a feasible one-burn collision avoidance maneuver that can safely circularize the spacecraft orbit along its coasting arc under a given set of potential thruster failures. Key features of the proposed algorithm include: (i) theoretical guarantees in terms of trajectory safety and performance, (ii) amenability to real-time implementation, and (iii) generality, in the sense that a large class of constraints can be handled directly. As a result, the proposed algorithm offers the potential for widespread application, ranging from on-orbit satellite servicing to orbital debris removal and autonomous inspection missions., Comment: Submitted to the AIAA Journal of Guidance, Control, and Dynamics (JGCD) special issue entitled "Computational Guidance and Control". This submission is the journal version corresponding to the conference manuscript "Real-Time, Propellant-Efficient Spacecraft Planning under Clohessy-Wiltshire-Hill Dynamics" accepted to the 2016 IEEE Aerospace Conference in Big Sky, MT, USA