Name
Abstract | ||
|---|---|---|
This paper presents tests conducted on routes determined from a Dijkstra-based shortest path problem and a Variance-Constrained Shortest Path problem under varying conditions of traffic and weather in a simulated 'smart environment'. Utilizing envisioned future advanced transportation systems' real-time information on traffic parameters allows data fusion techniques to provide situation awareness to its users. Taking advantage of this real-time data, the routing methodologies and data capture techniques studied in this paper provides Emergency Medical Services with better routes when responding to a vehicular crash. Comparing the performance of both routing methodologies in terms of both their ability to provide better routes as well as computation times demonstrates two alternatives for aiding in future emergency response. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1057/jors.2014.21 | JORS |
Keywords | Field | DocType |
routing,emergency response,data fusion | Crash,Smart environment,Shortest path problem,Computer science,Situation awareness,Operations research,Sensor fusion,Automatic identification and data capture,Intelligent transportation system,Dijkstra's algorithm | Journal |
Volume | Issue | ISSN |
66 | 4 | 0160-5682 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew J. Henchey | 1 | 1 | 0.37 |
| Rajan Batta | 2 | 849 | 89.39 |
| Alan Blatt | 3 | 43 | 3.63 |
| Marie Flanigan | 4 | 22 | 2.02 |
| Kevin Majka | 5 | 1 | 0.37 |