question: You are answering a 3D spatial-reasoning question from a SINGLE monocular driving image with numbered bounding boxes. Frontier models routinely get these right by luck while reasoning incorrectly: they lean on flat-image shortcuts ('lower in the frame = closer', 'bigger box = nearer', 'left in the image = to my left') that collapse on elevated roads, slopes, curves, and intersections. To answer reliably you must reconstruct the real 3D scene, not the pixel layout. Reason explicitly and quantitatively.
  
  Question: Consider object <8>, object <9>, object <11>, and object <22>. Please order them from closest to furthest from us.
  
  Reasoning protocol (metric 3D):
  1. For EACH referenced object, independently estimate its distance from ego in meters using apparent size, ground-contact point, and lane convergence — never raw image height.
  2. Estimate each object's signed lateral offset from the ego forward axis in meters (left positive, right negative).
  3. Compute the true 3D separation by combining longitudinal AND lateral differences. Do NOT assume two boxes near each other in the image are close in 3D, nor that a small image gap means a small metric gap.
  4. Map the computed separation (or comparison) to the answer.
  
  Finish with a single line in the exact format: 'Answer: <LETTER>'.
choices: A. <22>, <11>, <8>, <9> B. <11>, <8>, <9>, <22> C. <11>, <9>, <22>, <8> D. <8>, <9>, <11>, <22>