Collision avoidance and road safety applications require highly accurate vehicle localization techniques. Unfortunately, the existing localization techniques are not suitable for road safety applications as they rely on the error-prone Global Positioning System (GPS). Likewise, cooperative localization techniques that use intervehicle communications experience high errors due to hidden vehicles and the limited sensing/communication range. Recently, GPS-free localization based on vehicle communication with a low cost infrastructure installed on the roadsides has emerged as a more accurate alternative. However, existing techniques require the vehicle to communicate with two roadside units (RSUs) in order to achieve high localization accuracy. In contrast, this paper presents a GPS-free localization framework that uses two-way time of arrival to locate the vehicles based on communication with a single RSU. Furthermore, our framework uses the vehicle kinematics information obtained via the vehicles onboard inertial navigation system (INS) to further improve the accuracy of the vehicle location using Kalman filters. Our results show that the localization error of the proposed framework is as low as 1.8 meters. The resulting localization accuracy is up to 65% and 47.5% better than GPS-based techniques used without/with INS, respectively. This accuracy gain becomes around 73.3% when compared to existing RSU-based techniques.

Road safety applications in Vehicular Ad Hoc Networks (VANETs) necessitate highly accurate vehicle localization techniques. Unfortunately, Global Positioning System (GPS)-based localization techniques do not only suffer from the lack of ubiquitous GPS coverage but also are susceptible to high localization errors (10 m to 30 m). Consequently, such techniques are not suitable for road safety applications. Recently, GPS-free localization based on vehicle communication with installed roadside units (RSUs) has emerged as a more accurate alternative. However, existing GPS-free techniques require the vehicle to communicate with two RSUs in order to achieve high localization accuracy. Such techniques either increase the system cost due to the high number of needed RSUs or delay the localization decisions. In this paper, we propose a GPS-free localization framework that uses two-way time of arrival with partial use of dead reckoning to locate the vehicles based on communication with a single RSU. Our results show that the accuracy of the proposed framework is 13.1% to 20.1% better than the techniques that use 1 RSUs while completely depending on dead reckoning, and only 3% to 8.9% worse than those techniques that use 2 RSUs on both sides on the road.

One of the lifetime maximisation methods for wireless sensor network (WSN) depends on organising the dense sensors into groups which can work in a cooperative sequential manner. Each group contains a subset of sensors that cover all the monitored area and is called a complete cover or simply a cover. Increasing the number of organised covers and maximising the covers lifetime enable longer network lifetime. Here, the authors investigate the WSN lifetime problem as a two‐objective optimisation problem. The first objective is to find the maximum number of covers. The second objective considers the problem of wasted energy. Minimising the wasted energy in the critical sensors is achieved by defining a difference factor (DF). The DF is an indication of the difference between the critical sensor lifetime and the cover lifetime. This second objective is compared with other choices in the literature such as minimising the overlapping and minimising the variance. This optimisation problem is addressed using non‐dominated sorting genetic algorithm‐II (NSGA‐II). Simulation results are conducted for the network lifetime when using one‐objective and different two‐objective optimisation problem. The choice of DF as the second objective is proved to overcome drawbacks of other second objectives choices.