Impact of Efficient Driving in Professional Bus Fleets

Diesel engines of the vehicles in the transport sector are responsible for most of the CO2 emissions into the environment. An alternative to reduce fuel consumption is to promote efficient driving techniques. The aim of this paper is to assess the impact of efficient driving on fuel consumption in professional fleets. Data captured from the engine control unit (ECU) of the vehicles are complemented with external information from weather stations and context data from the transport companies. The paper proposes linear and quadratic models in order to quantify the impact of all the terms influencing energy consumption. The analysis was made from the traces captured from a passenger transport company in Spain with more than 50 bus routes. 20 vehicles of five different models were monitored and 58 drivers participated in the study. The results indicate that efficient driving has significant influence on fuel consumption, which confirms efficient driving as a valid and economical option for reducing consumption and therefore emissions of harmful particles into the atmosphere. According to the proposed model, in average external conditions, a driver that increases efficiency from 25% to 75% can reach savings in fuel consumption of up to 16 L/100 km in the analysed bus fleet, which is a significant improvement considering the long distances covered by professionals of the transport sector

Adaptive Streaming: A subjective catalog to assess the performance of objective QoE metrics

Scalable streaming has emerged as a feasible solution to resolve users' heterogeneity problems. SVC is the technology that has served as the definitive impulse for the growth of streaming adaptive systems. Systems seek to improve layer switching efficiency from the network point of view but, with increasing importance, without jeopardizing user perceived video quality, i.e., QoE. We have performed extensive subjective experiments to corroborate the preference towards adaptive systems when compared to traditional non-adaptive systems. The resulting subjective scores are correlated with most relevant Full Reference (FR) objective metrics. We obtain an exponential relationship between human decisions and the same decisions expressed as a difference of objective metrics. A strong correlation with subjective scores validates objective metrics to be used as aid in the adaptive decision taking algorithms to improve overall systems performance. Results show that, among the evaluated objective metrics, PSNR is the metric that provide worse results in terms of reproducing the human decision

Understanding opportunistic networking for emergency services: Analysis of one year of GPS traces

Opportunistic networking can help emergency services in both their daily operation and disaster relief. This idea has been extensively explored in previous research, but most studies are based on little knowledge of real mobility. In order to support future research, this paper analyses one year of GPS traces from a fire department. The results reveal the characteristics of hypothetic opportunistic networks formed by devices following this mobility considering different communication ranges. We found that the networks analysed are heterogeneous in many dimensions. They are also sparse and partitioned, but delay-tolerant routes connecting these partitions exist. To ease the discovery of these routes, we reveal in the connections between nodes. These findings can be applied in the design and deployment of solutions from the physical to the application layer