Musing and Walking About Oxford Street

I was back at my hotel that early that Tuesday evening, January 21st, my client having been so kind as to have me join them on the taxi ride back from their Pall Mall offices.  I had planned to try again to walk a route back to the Radisson Blu Portman, just as I had tried the day before, but I readily accepted this invitation.  Speaking with my client was my priority the entire trip, of course.

Instead of spending an hour on the elliptical in the gym, though, I went out for my exercise walk later that evening. I needed to eat dinner at an affordable eatery, McDonald's as it turned out, and perhaps also buy souvenirs for my family. I knew how to get to Oxford Street easily (above), so I headed there.

It was cool and drizzly, but not bad at all. London was otherwise sunny and in the 40°s for the four days I was there this week. Such a welcome relief from Chiberian (Chicago + Siberia) weather. Post-holiday Oxford Street wasn't so populated or trafficked, and that was perfectly fine with me.

I did my T'ai Chi workout right before heading out, so I was warmed up and well stretched. But I was baffled and aggravated that my left shin got so painful. I had to stop several times to massage it, and I was thankful to have found that McDonald's after 20 minutes of walking. It was a bit better on the walk afterwards. It must've been my shoes. I don't normally wear gym shoes when I walk.

I reminded myself that I did a very good job locating the Radisson on foot, late one night in December, when my client transport never showed up. Years ago, when Karen and Eva were with me, we managed to find the Conrad at night time as well and then the Fulham station the following day, both on foot. I have had a handful of other walking abouts, and found places quite well, really.

So getting turned around the evening before, and flat out getting lost, was exception for me.

I found myself in a stretch of getting lost, when I lived in Dubai, that I decided to formulate an Algorithm for Spatial Orientation. It was a dramatic improvement right away: from finding my way just one out of five times, to four out of five times.

An algorithm is smart, and it learns, and it adapts itself to particular situations. So I will try that walk again, when I'm back in London, and let's see how well I do.