## 5 Results on a Real Road Section  
The optimization algorithm was applied to a long distance trip of approximately 100 km on the route between Madrid and Barcelona (Spain) along the A2 highway. The road geometry was measured using an instrumented vehicle with an Astech G12 GPS receiver (Thales Navigation, Inc. Santa Clara, CA, USA) and an inertial measurement system comprising a Correvit L-CE- non-contact speed sensor (Corrsys-Datron Sensorsysteme GmbH. Wetzlar, Germany) and an RMS FES 33 gyroscopic platform (RMS Dipl.-Ing Schafer GmbH & Co, KG. Hamburg, Germany) [70; 71; 72; 73]. The slopes profile is shown in Figure 4. Additionally, fixed and variable speed limits have been identified (Table 3). The vehicle is a Ford Focus with a ZETEC 2 litre petrol engine (Ford Motor Company. Dearborn, MI, USA). It is considered that the trip begins at 12 h and the arrival time is expected at 13:15. The system defines the optimal speed profile (Figure 5) considering the speed limits and informs the driver. Comparing this speed profile with a constant speed one that provides the same travel time, except stretches with some kind of limit, fuel savings of 4.0% have been obtained, assuming that the acceleration and deceleration processes are similar in both cases. This fuel savings value is similar to that presented in [35], but a little bit lower because large trip distances with flat vertical profiles diminish the optimization effect. The system takes advantage of the knowledge of the variable speed limits in order to find the best strategy in which the effect of those kinds of limits is reduced, adapting the speed before and after them and fuel savings remains in significant values. In this sense, the system could recommend speeding up (as can be seen in Figure 6) or slowing down to reduce the amount of time the vehicle is involved in the traffic limit section when the limit is active. Figure 4: Road slopes profile. Figure 5: Optimal speed profile (only fixed and variable speed limits expected before the trip begins). Furthermore, the system can adapt in real time the information provided to the driver according to the new information that the vehicle receives along the trip by wireless communications between vehicles or with the infrastructure. The network access devices used are MTM-CM3100 (Maxfor Technology Inc. Seongnam, Korea), based on the TeloSB platform (Memsic Inc. San Jose, CA, USA). This allows connectivity with any computer platform and acts as a gateway to access the vehicular GeoNetwork. This device works under Linux (TinyOS) operating system (an open source software). In order to access the wireless network to 2.4 GHz in mesh, it uses the IEEE 802.15.4 standard at physical and link level and a mesh routing protocol, which guarantees the desired functionality of the VANET at transmission rates up to 250 Kbps and in a range of 100 meters. That way, Figures 6 and 7 show how the system adapts the speed profile when the vehicle receives the information about a traffic perturbation between kilometric points 53 and 55.5 that makes vehicles move at an average speed of 20 km/h between 12:36 and 12:54. Figure 6 presents the constant speed profiles between road sections with special speed limitations defined by step 1 of the method described in section 4.7. in the following three situations:  
1. The system does not obtain any information about this traffic perturbation until the vehicle reaches the road section of kilometric point 50 (quite near to the perturbation section), so it maintains the same speed profile until the perturbation forces the vehicle to miss it. 2. The system receives the information when the vehicle is located at kilometric point 25, so the speed profile is adapted from that point in order to meet the established schedule. 3. The system receives the information at the beginning of the trip, so the speed profile is adapted from that point in order to meet the established schedule.