In the dense urban core, high volumes of human activity and variable transits yield the need for an efficient personal rapid transportation (PRT) network. Efficient network performance involves a trade-off between cost, transport efficiency, and fault tolerance. Biological networks have developed a high degree of efficiency through evolutionary cycles and may suggest an acceptable solution to this combinatorial optimization problem. We draw inspiration from Physarum polycephalum (P.p.) slime mold, which naturally produces networks with low average node separation, low average degree of separation and high resiliency. Necessary nodes in our urban transportation network are identified where high volumes of human transits occur within our predefined boundaries.
Such areas may consider academic and civic institutions, existing public transit hubs and commercial districts. This high activity downtown area of 2,8 km2, consisting of 12 exchange nodes, is scaled for use in laboratory testing with the Physarum polychepalum. Repeated experiments with the slime mold yield a solution to the network with the aforementioned characteristics. The solution’s average degree of separation, node separation and fault tolerance are analyzed and compared to those of other common combinatorial optimization solutions known as the Steiner minimal tree and the minimal spanning tree. Additionally, the solution is compared to a mathematical model of the P. polychepalum simulated in the CompuCell3D cellular potts environment.
The results demonstrate that over 50% of the total possible exchanges are maintained when 85% of the nodes of the biologically inspired experimental network are disconnected, while less than 20% of the total exchanges are preserved for the other common combinatorial optimization solutions. This biologically inspired network solution is used as a reference guide for the design and layout of paths and connections for the personal rapid transportation network to ensure a high degree of efficiency and robustness.
| Date | 16 Oct 2013 |
|---|
| Original language | French |
|---|
| Awarding Institution | - École de technologie supérieure
|
|---|
| Supervisor | Mathias Glaus (Supervisor) |
|---|
Maiorano, M. (Author),
Glaus (Supervisor),
16 Oct 2013Student thesis: Master's thesis › Master in Engineering: Engineering