Found, Linear regression data from Los Angeles 1980

(Having trouble getting the graph right)

   I found my linear regression travel time analysis of automobile and public bus travel in Los Angeles. The trips were made in 1978 
and 1979. 

    In the table below, the Los Angeles 1980  trips are slower than the El Granada - Pacifica -San Mateo trips made in 2009-2010.

    The analysis was done in 1980 from the trip records using topographic maps and a drafting scale for computing airline distance between points. The regression calculations were done using a HP-41 programmable calculator. I published the program through the HP contributed software  service. 

   I  need to check if the distance value I measured using maps in 1980 has an error compared to the great circle value I have used for 2009 calculations. In 1980 I used topographic maps that are marked with a 1000 meter Mercator grid. I used this grid without any documentation. Fortunately I have a paper record for each trip.

Linear  regression coefficients for travel time.
For Los Angeles in 1979-1980 and El Granada-Pacifica-San  Mateo in 2009-2010
Not yet tested for differences in measurement and calculation method.

Travel time in minutes. minutes per mile +minutes
Bycar2010EG 1.41 12.09
Bycar1980LA 1.68 8.04
Bybus2010EG 4.20 24.51
Bybus1980LA 8.54 16.88
Same equation expressed in popular units:
Vehicle behavior miles per hour +minutes
Bycar2010EG 43 12
Bycar1980LA 36 8
Bybus2010EG 14 25
Bybus1980LA 7 17

The real bus trip alters my previous linear regression

The recent bus trip I took from home to work modifies my previous linear regression calculations of a "travel time equation". The "real" bus trip had modest walking and very little waiting

For travel distances expressed in great circle miles:
Auto:              1.41 minutes/mile + 12.09 minutes  = 

Samtrans bus: 4.20 minutes/mile + 24.51 minutes =

The 3-16-2010 journey has these calculated  and real travel times

Auto, calculated  = 35.3 min.   Real = 45 min
Bus,   calculated = 93.52  min.  Real = 80 min.

Taking the bus to work

Finally I got organized and made a trip to work using the public bus. I look forward to testing my linear regression formula and reviewing my total cost of a trip analyses I made earlier in  this blog.
For this first trip, I took notes on the number of passengers. The table below shows the "load factor" of the buses I rode as I made a trip to work during a workday morning. 
For the advocacy of this blog here are some of the observations I was interested in during this journey:
  • Is the rear door and rear area of the public transit buses adaptable freight carts?
  • Do the SamTrans buses board wheelchairs?
  • How busy is the bus driver?
  • What is  the level of time and destination automation being used on the buses?
  • Are there active advertising signs inside the bus?
  • Are there any clues to the potential  for making the bus an autonomous vehicle?
  The following table shows the load factor generally increasing as the buses I rode moved from a suburban setting to a highly urbanized setting.

Definitions: Time = clock time. On = count of people who board Off = count of people who get off Riders = count of riders including the observer Seats = count of seats Load factor = riders (up to this stop) / seats. Minutes = interval between rows.

3/16/2010 bus trip home to work
Time On Off Riders Seats Load factor Minutes Comment
5:51 Leave house
6:00 0:09 Arrive at bus stop
6:03 1 8 39 0:03 Bus 294 arrive
6:11 1 1 8 39 0.21 0:08 Stop on 92 near Peets
6:18 3 11 39 0.21 0:07 Main x Kelly HMB loop
6:36 1 10 39 0.28 0:18 92 x Alameda de las Pulgas
6:38 1 9 39 0.26 0:02 Near high school
6:41 1 8 39 0.23 0:03 Near library
6:44 8 0 39 0.21 0:03 End El Camino Real x 31st
6:45 12 39 0:01 Board 390 Southbound
6:46 7 19 39 0.31 0:01
6:48 1 20 39 0.49 0:02
6:49 1 21 39 0.51 0:01
6:50 1 22 39 0.54 0:01
6:52 4 26 39 0.56 0:02
6:54 1 25 39 0.67 0:02
6:57 2 23 39 0.64 0:03
6:58 1 22 39 0.59 0:01
7:00 1 4 19 39 0.56 0:02
7:02 1 18 39 0.49 0:02
7:03 1 17 39 0.46 0:01 End bus ride ECR x Brewster
7:08 0.44 0:05 Arrive gate
7:11 0:03 Arrive at work
1:20 total trip time

Brown for Governor, Poisner for Governor and Meg Whitman - can they say the unpopular truth?

This tractor is used to place rocks and sand to prevent cliff erosion.

I write this on March 4th 2010. 

Around the state (California) there are demonstrations asking "Restore the funds cut from education." I  feel the demonstrations neglect to speak to much larger public and political problem: 
The public dialogue will not contemplate enacting higher taxes.
How will the three candidates for governor engage with the following unpopular truths?
  • Revenue to the California state government needs to be substantially increased.
Revenue must be increased to fund a modern society that does provide public education, health support, social security and other services and benefits.  

The problem with raising the basic tax rate for all is how to do it fairly and evenly. I  favor raising the sales tax rate to 11%, and then doing adjustments and credits at the level of the state income tax.

  • Real estate in California over a 40 to 50 year period has become over valued by 40-50%. 

The entire state (indeed the entire nation) is caught in this unpleasant state of affairs.  Nobody enjoys the vanished "wealth effect" that ended when property price appreciation stalled out in 2007-2009. 

The over valuation of real estate (I refer mainly to homes) is the root of a cascade of problems. 

One of  these problems is the large amount of mortgage debt. The  nation hasn't  yet started to have a  dialogue about  how to get off of the hook of enormous mortgages that often require two working parent incomes.

From another point of view,  critics describe the mortagage  industry as about twice as big as it should be. 

Another aspect of the over valuation is: Young adults starting a family can't afford a home. See "The coming collapse of the middle class" below.


Henry_George advocate of land value taxation

YouTube - The Coming Collapse of the Middle Class