The study of multiple vehicle routing strategies
For navigation purposes, drivers rely on applications such as Google maps or navigating devices mounted on their vehicles. These applications use algorithms to compute the optimum path for a vehicle to reach its destination from its origin. Dijkstra’s algorithm is usually used to calculate the sh...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/66626 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | For navigation purposes, drivers rely on applications such as Google maps or
navigating devices mounted on their vehicles. These applications use algorithms to
compute the optimum path for a vehicle to reach its destination from its origin.
Dijkstra’s algorithm is usually used to calculate the shortest path but without
stochastic variables these paths will be unreliable. By including some stochastic
variables we are able to improve the reliability of the shortest path. The purpose of
this report is to study various routing strategies and which of this strategies will result
in the minimum amount of travel time by simulating them using SUMO. The first
strategy is the shortest path which uses the minimum length. The second strategy is
K-Shortest path which computes multiple shortest paths and pick one randomly on a
red light. The third strategy is the minimum travel time which uses the current travel
time of an edge to compute the route. The fourth strategy is the dynamic route
assignment which uses the current travel time of an edge to solve a minimized
equation. In addition, the report will also talk about how certain stochastic variables
can improve the findings of the data. |
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