Multi Mode Commute - Who wins?

The Matrix Team travelled from Toowong into the CBD (Brisbane) on Thursday 23rd August during the AM commuter peak.  As a team we undertook this data collection of a variety of transport modes as ways to commute to work for a range of purposes.  To test our theories, to bond as a team and a valid excuse to have a team breaky in the city.

  Figure 1 – Matrix Team at the finish line

Figure 1 – Matrix Team at the finish line

On this occasion we were able to utilise 13 different modes of transport, it has been pointed out to us that we neglected to include motorbike in the data but alas no one on the Matrix Team has a motorbike or a motor bike license.  We will see what we can do in future.

The team gathered at the designated area at 7:45am, “the old Woolworths carpark opposite Toowong Village”. All commuters were instructed that the end point was the Lion Statues at front of King George Square, in the CBD.

This stretch of commute into the city had been chosen for this test as it offered a wide range of transport modes.  Train, Bus, City Cycle, main road and exceptional bike and walking paths along Coronation Drive.

At the agreed time of 8am, all Commuters left the carpark for their journey into the city. 

The aim of this experiment was to record;

·       Time;

·       Cost;

·       Kilojoules burnt (trying to include an active travel component).

The map below shows the route used. Commuters used Garmin / Apple devices to record their trip.

  Figure 2 – Travel Time Route (Toowong to the City)

Figure 2 – Travel Time Route (Toowong to the City)

The graph below shows the headline time results for the commute to the city.

  Figure 3 – Commute Times

Figure 3 – Commute Times

Firstly, time isn’t everything. In a recent Matrix survey 54% of respondents ranked time as their top priority.

  Figure 4 – Journey to work priorities

Figure 4 – Journey to work priorities

As per the time graph, our two cyclists arrived at the end point in position 1 and 2.

The end of trip difference between these 2 cyclists is significant for some.

The E Bike rider arrived in work clothes and was able to walk straight into the office.  The road bike rider arrived in Lycra and required “end of trip facilities” to shower and change before heading off to work.  (These comments are noted by the bike rider’s comments in the spreadsheet).  The 3rd bike in our experiment was a Yellow City Cycle, this rider arrived at the end point 6th.  The time difference here was due to the time it took before and after the trip to dock the bike in and out of a docking station. 

Other observations include;

·       The commuter who travelled by Uber arrived at the end point before the self-drive car commuter as they did not have to take time to park and walk to the meeting spot.

·       E Scooter and E Skateboard shared very similar arrival times.  We are currently seeking advice on the use of E Skateboards on public routes.

·       The Ferry journey took a little longer than the other 2 public transport modes. This could be because the Ferry Terminal is a longer walking distance than the Train and Bus stop from the starting point or because there are less frequent services running or because the changeover of foot traffic at Ferry Terminals takes longer due to health and safety than the other modes of public transport.

An attempt to add a nominal cost to each mode of transport has been estimated.  We have kept the methodologies very simple.  It would be very easy to poke holes in costing calculations.

  Figure 5 – Trip Costs

Figure 5 – Trip Costs

The Uber trip cost the most and had a 2X premium on the normal fare.  The Uber did arrive at the pickup point in 2 minutes, which was quicker than we thought.  The car cost includes the travel cost (per KM) as well as the parking cost.  Parking was the majority of this cost.  We didn’t apply any cost to the Bicycles or Scooter, assuming that these users would already own the equipment.  Charging costs for the E bike, E Scooter and E Skateboard are nominal (10c to 30c max).

We also attempted to record the kilojoules burnt by the commuters during their trip to the city.  The science is not exact, however the graph below shows 4 distinct groups.  The number 1 and 2 positions are running and walking.  Both modes are around the 1500 kilojoule mark.  The next group includes the non-assisted bike and roller blades.  The Electric “E” modes then take up the middle ground.  Then, Ferry, Car, Bus, Uber and Train bring up the rear.  Most of the last groups kilojoules being burnt by their walk to and from their transport modes.

  Figure 6 – Kilojoules Burnt

Figure 6 – Kilojoules Burnt

Conclusion

This was a fabulous exercise, as a team love a challenge and we always have fun testing theories. This was not designed as a technical paper.  It is an experiment to highlight different transport modes.  The one obvious conclusion is that if you build a quality piece of infrastructure such as the bicentennial bike path (Coro Drive BikePath), then people will use it.  The quality infrastructure makes active travel options the superstars.