Chloropleth map of constituencies: how to evade visual deception

Hi everybody! I am doing a map of proposed multi-member-constituencies for the German federal parliament. Nr. 1 to 43 denote the constituencies and the greyscales the mean district size (magnitude). Constituency Nr. 1 and Nr. 11 have the some colour, but Nr. 1 looks way more darker, since the neighboring constituencies of Nr. 1 have a lighter grayscale than the neighboring constituency of Nr. 11. So in fact, a classicial example of visual deception. But what can I do about it? Or do I have

Limitations to Choropleth Maps: A Warning on Misleading Data - Population Education

1939: 2016 Election Map - explain xkcd

Empirical Studies on the Visual Perception of Spatial Patterns in Choropleth Maps

Map - Junk Charts

How to Avoid Being Fooled by Bad Maps - Bloomberg

Color-Balancing Vote Margins and Vote Totals in the US Election Map [OC] : r/dataisbeautiful

View of Review of Unclassed Choropleth Mapping

March 2019 – OUseful.Info, the blog…

choropleth maps Musings on Maps