Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobility of the nodes generate frequent topology changes and network fragmentations. For these reasons, and taking into account that there is no central manager entity, routing packets through the network is a challenging task. Therefore, offering an efficient routing strategy is crucial to the deployment of VANETs. This paper deals with the optimal parameter setting of the optimized link state routing (OLSR), which is a well-known mobile ad hoc network routing protocol, by defining an optimization problem. This way, a series of representative metaheuristic algorithms (particle swarm optimization, differential evolution, genetic algorithm, and simulated annealing) are studied in this paper to find automatically optimal configurations of this routing protocol. In addition, a set of realistic VANET scenarios (based in the city of Málaga) have been defined to accurately evaluate the performance of the network under our automatic OLSR. In the experiments, our tuned OLSR configurations result in better quality of service (QoS) than the standard request for comments (RFC 3626), as well as several human experts, making it amenable for utilization in VANET configurations.
Emerging Vehicle-to-Everything (V2X) applications such as Advanced Driver Assistance Systems (ADAS) and Connected and Autonomous Driving (CAD) requires an excessive amount of data by vehicular sensors, collected, processed, and exchanged in real-time. A heterogeneous wireless network is envisioned where multiple Radio Access Technologies (RATs) can coexist to cater for these and other future applications. The primary challenge in such systems is the Radio Resource Management (RRM) strategy and the RAT selection algorithm. In this paper, a Hybrid Vehicular Network (HVN) architecture and protocol stack is proposed, which combines Dedicated Short-Range Communication (DSRC) technology-enabled ad hoc network and infrastructure-based Cellular V2X (C-V2X) technologies. To this end, we address the design and performance evaluation of a distributed RRM entity that manages and coordinates Radio Resources (RR) in both RATs. Central to distributed RRM are adaptive RAT selection and Vertical Handover (VHO) algorithms supported by two procedures. (1) Measurement of Quality of Service (QoS) parameters and associated criteria to select the suitable RAT according to the network conditions. (2) Dynamic communication management (DCM) via implementing RR-QoS negotiation. The simulation results show the effectiveness of the proposed architecture and protocol suite under various parameter settings and performance metrics such as the number of VHOs, packet delivery ratio, and throughput, and latency.
Population concentration in cities brings new risks as an increase in pollution, which causes urban health problems. In order to address this problem, traffic reduction measures are being implemented as pedestrianization areas; they are the definition of Low Emissions Zones (LEZs). When the effectiveness of these types of measures is in doubt, smart city tools provide data that can be used to scientifically asses their impact. This article analyzes the situation of Madrid Central (Spain), a LEZ subject to controversy. We apply statistical and regression analyses to evaluate the effectiveness of this measure to reduce air pollution and outdoor noise. According to the results, this LEZ was able to significantly reduce NO , PM , and PM concentration locally, having the same positive impact in the rest of the city. In terms of noise, this measure was able to mitigate background noise levels generated by road traffic.
1 August 2010 in Engineering Applications of Artificial Intelligence