Name
Abstract | ||
|---|---|---|
Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1155/2017/7691370 | COMPLEXITY |
Field | DocType | Volume |
Elementary cellular automaton,Virtual machine,Software deployment,Traffic signal,Simulation,Robustness (computer science),Real-time computing,Artificial intelligence,Limiting,Mathematics,Machine learning | Journal | 2017 |
ISSN | Citations | PageRank |
1076-2787 | 3 | 0.48 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jorge Zapotecatl | 1 | 17 | 1.70 |
| David A. Rosenblueth | 2 | 122 | 21.97 |
| Carlos Gershenson | 3 | 392 | 42.34 |