Name
Title | ||
|---|---|---|
Performance Study of Economical and Environmentally Friendly Geocast Routing in Vehicular Networks |
Abstract | ||
|---|---|---|
Economical and Environmentally Friendly Geocast (EEFG) uses traffic signals to communicate with approaching vehicles. The communication can be signal-to-vehicle (TLS2V) and vehicle-to-vehicle (V2V). Based on the information sent, the vehicle receiving the message adapts its speed to a recommended speed (SR), which helps the vehicle reduce fuel consumption and emissions. Our previous paper titled “Optimization of Fuel Cost and Emissions Using V2V Communications” [1] develops a model to determine the optimum SR. It also proposes heuristic expressions to compute the optimum or near-optimum SR. This paper validates by simulation the applicability of EEFG in real life scenarios based on actual measurements of traffic data. It shows the impact of using EEFG in a modeled realworld network in the city of Waterloo, Canada, considering four case studies: (1) a suburban environment at the peak hour; (2) a suburban environment at the least busy hour; (3) an urban environment at the peak hour; (4) an urban environment at the least busy hour. The results show that EEFG saves fuel and CO2 emission in all four cases, where Case 3 has the most saving (up to 8%). In TLS2V, the optimization and heuristic expressions give the same SR results. However, the results might slightly differ ( 1%) if V2V is involved. In addition, the paper studies the effect of communication parameters on fuel and emission. Having high transmission range, low packet delay, and low packet loss, can save more fuel and emission. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TVT.2014.2358943 | Vehicular Technology, IEEE Transactions |
Keywords | Field | DocType |
computational modeling,protocols,economic impacts,optimization,routing | Automotive engineering,Heuristic,Computer science,Environmentally friendly,Computer network,Fuel efficiency,Fuel cost,Geocast,Vehicular ad hoc network | Journal |
Volume | Issue | ISSN |
PP | 99 | 0018-9545 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maazen Alsabaan | 1 | 58 | 5.27 |
| Kshirasagar Naik | 2 | 846 | 73.83 |
| Tarek Khalifa | 3 | 32 | 5.45 |
| Saad Alaboodi | 4 | 0 | 0.34 |