Situations involving navigation among maneuvering agents are critical for the study of visual guidance of autonomous vehicles. This paper addresses the case of translational motion with polynomial regimes and defines a general class of temporal parameters (TP) relevant for navigation, enable a qualitative description of the observed agents' depth trajectories. These parameters are shown to be visually recoverable. Instances of such temporal parameters include Time-to-Collision (TTC) and Time-to-Synchronization (TTS), useful for docking or platooning maneuvers. The results are specialized to lower order motions. The recovery of TTC and TTS for arbitrary regimes is a special corollary of our analysis. Computations from direct and feature-based methods are described. A scheme for addressing model order determination, collision detection and temporal parameter estimation is proposed and tested. Experimental results on synthetic and real images are given.