Abstract
Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region.
Highlights
Wireless sensor networks are usually used for monitoring activities in the city
We put forward a Traffic Lights Localization (TLS) algorithm based on traffic light information to solve the location problem with sparse deployment of sensors on urban roads
If the Dn successfully matches with Km, we can consider the intersection node group (Dn is constructed by this intersection node group) to be near this traffic light (Km is constructed by this traffic light information)
Summary
Wireless sensor networks are usually used for monitoring activities in the city. The localization of sensors is crucial for monitoring activities because monitoring messages often make no sense without the location information. Rang-free methods localize with simple sensing, such as anchor proximity [5] and wireless connectivity [9], which have a low system cost It sacrifices localization accuracy for urban road sensor networks. To address this issue, we put forward a Traffic Lights Localization (TLS) algorithm based on traffic light information to solve the location problem with sparse deployment of sensors on urban roads. We put forward a Traffic Lights Localization (TLS) algorithm based on traffic light information to solve the location problem with sparse deployment of sensors on urban roads This algorithm is built on an observation: controlled by the traffic lights, the time segment of vehicles and no vehicles is a regular cycle on each road.
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