This is my last of a three part blog series on the topic of transportation. Motivated by the Global Engineering Innovation Challenge, my friend and I brainstormed on what can be done to improve the road share in a limited right of way.
The goal is to pack a collection of objects, cars, buses, and bikes, into the minimum
number of fixed-size bins, the road lanes. The resemblance between this and the classic bin packing problem is eminent. In a bin
packing problem one may pack based on first fit, or first best fit, based on
ascending or descending ordered list of object based on its size. Here we will be packing based on time of use.
The existing infrastructure of surface transport is sliced
in at least three bins
The side
walks at least one on each side
The roads
at least one for each direction, North-South or East-West
Surface -> {Sidewalk, Road1,
Road2}
The objects are bikes, cars, buses, and trucks
Items -> {Bikes, Cars, Buses,
Trucks}
In solving this problem it is important to consider the time
of the week day as the constraint to optimize.
Time -> { 06 < T < 10 // demand is high because it is morning rush hour
10 <
T < 14 // demand is low
14 <
T < 20 // demand
is high because it evening rush hour
20 <
T < 24 // demand
is low
}
The solution is:
Time -> {
06 < T < 10 Surface
-> {Sidewalk No
constraint
, Road1 Car-pool, Buses only
, Road2 Car-pool,
Buses only
}
10 < T < 14 Surface -> {Sidewalk No constraint
, Road1 Bikes, Cars, Buses, Trucks
, Road2 Cars, Buses,
Trucks
}
14 < T < 20 Surface ->
{Sidewalk No constraint
, Road1 Car-pool, Buses only
, Road2 Car-pool,
Buses only
}
20 <
T < 24 Surface
-> {Sidewalk No
constraint
, Road1 Bikes, Cars, Buses, Trucks
, Road2 Cars, Buses,
Trucks
}
}
This proposal promotes better, safer sharing of the road by distributing the load of its usage through out the day.
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