Name
Abstract | ||
|---|---|---|
The travel time to proceed from one location to another in a network is an important consideration in many urban transportation settings ranging from the planning of delivery routes in freight transportation to the determination of shortest itineraries in advanced traveler information systems. Accordingly, accurate travel time predictions are of foremost importance. In an urban environment, vehicle speeds, and consequently travel times, can be highly variable due to congestion caused, for instance, by accidents or bad weather conditions. At another level, one also observes daily patterns (e.g., rush hours), weekly patterns (e.g., weekdays versus weekend), and seasonal patterns. Capturing these time-varying patterns when modeling travel speeds can provide an immediate benefit to commercial transportation companies that distribute goods, since it allows them to better optimize their routes and reduce their environmental footprint. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ejtl.2020.100006 | EURO Journal on Transportation and Logistics |
DocType | Volume | Issue |
Journal | 9 | 4 |
ISSN | Citations | PageRank |
2192-4376 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maha Gmira | 1 | 0 | 0.34 |
| M. Gendreau | 2 | 377 | 28.81 |
| Andrea Lodi | 3 | 2198 | 152.51 |
| Jean-Yves Potvin | 4 | 2037 | 164.03 |