Transportist: September 2021

Catbagger n. Someone who tries to put the cat back in the bag. I.e. someone attempting a futile act too late, which may have been prevented but cannot be reversed.

In Australia are currently experiencing an exponential increase in COVID-19 cases as part of the Delta Wave. This is sad, and results in a few deaths daily (a rate, mind you, that is low enough other countries use it as a level at which lockdowns are lifted, rather than imposed). The rise is due to any number of mistakes that went previously. I won’t re-litigate the past. Instead, I posit that had those mistakes not been made at that time, lessons from those mistakes wouldn’t have been learned, and a similar mistake would have then been made shortly thereafter. This is not an apology for incompetence, and I am sure none of the Transportist readers would have made those mistakes had they been in charge, but is an acknowledgement that like COVID-19, incompetence is endemic and no one competent person can be everywhere simultaneously, and everyone relies on systems that are only as good as their weakest link.

If not for some outbreak, people would not (over)-react, leaving the same conditions in place for a later outbreak. While on average one prefers to avoid mistakes, it is only by mistakes that lessons are learned, pre-planning is imperfect, and we can plan and prepare for any number of eventualities that would never occur at great cost, leaving us worse off than those who react to the eventualities that do actually occur without having wasted resources preparing for those that don’t.

So while it may be psychologically or politically important to blame individuals who should have done this instead of that, or have learned from the mistakes of others, (and obviously the best people do better than the worst, by definition), and hopefully select slightly less incompetent administrators, that merely would have delayed the mostly inevitable outcome in terms of cases and deaths. And until there were COVID outbreaks, or very obvious prospects of COVID outbreaks, no vaccine would have been developed, no vaccine would have been manufactured, and no one would have gotten vaccinated, leaving everyone vulnerable to a COVID outbreak.



  1. For authors, considering peer review: Are you biased so as to be more likely to accept papers that cite you? Are others (generally) similarly biased?

  • I am/Others are 46.3%

  • I am not/Others are 24.4%

  • I am/Others are not 0%

  • I am not/Others are not. 29.3%

At least no one admitted to being more unethical than the population as a whole (choice 3). About half the people admitted bias (choice 1 and 3), indicating that the people who thought “Others are not” (choices 3 and 4) are hopelessly naive. I tend towards choice 2 for myself, at least I hope I am not.

  1. How much time would you be willing to sacrifice at the end of your life (your life would be X units of time shorter) to forego 1 month of lockdown for yourself?

  • 0-1 hour 44.4%

  • 1-24 hours 17.8%

  • 1-6 days 11.1%

  • 7 or more days 26.7%

Now these are Twitter polls, so sampling bias is rife, and questions cannot be particularly sophisticated (lockdown means different things to different people in different places, what about lockdown for other people, etc.), but it does suggest that many people think that lockdown makes their life worse off in a way that suggests their benefits (reducing COVID cases) need to be countered with their costs (diminished quality of life). It also suggests that some other people really like lockdown, and if there had been negative numbers, some people who elected for choice 1 might have given up time at the end of their life to preserve lockdown longer. This I think gets pack to the Plants vs. Animals dichotomy I developed last year.




  • Viewpoint: Turning streets into housing
    Adam Millard-Ball, University of California Los Angeles 

  • The inevitability of automobility: how private car use is perpetuated in a Greenfield estate
    Jennifer Kent, University of Sydney 


  • Traffic-Land Use Compatibility and Street Design Impacts of Automated Driving in Vienna, Austria
    Emilia Brucke and Aggelos Soteropolis, Technical University of Vienna 

  • Traffic Noise Feedback in Agent-Based Integrated Land-Use/Transport Models
    Nico Kuehnel (Technical University of Munich), Dominik Ziemke (Technical University of Dresden, and Rolf Moeckel (Technical University of Munich) 



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