The robustness for the number of covered demand points is 88.93%, and the frequency associated with every candidate is between 11.71% and 69.49%. In this case study, the robustness of the objective function is above 99.99%. This paper presents a maximal covering location formulation and proposes a robustness analysis considering spatial location perturbations. In this paper, the authors present a case study of optimal rain gauge location based on an actual database of rainfall events with impacts on urban mobility in the city of Sao Paulo (Brazil). However, those services should consider the uncertainties about the registers of rainfall impacts. A well-distributed set of rain gauges is crucial for monitoring services in smart cities. Ī sustainable transportation system should represent a win-win situation: minimizing transport's impact on the environment and reducing natural disasters' effects on transportation. By adopting the compatibility, the simulation results could show alternative paths with the lowest RCV (road capacity value).
Second, to accommodate the route recommendation, we simulate and utilize a new measure, called road capacity value, along with the Dijkstra algorithm. The performances of the traffic prediction are around 60.78–73.69%, 63.64–77.39%, and 60.78–73.69%, for accuracy, precision, and recall respectively. First, it predicts the traffic conditions by using Knowledge-Growing Bayes Classifier on which the dataset is obtained from crawling the public CCTV feeds and TomTom digital map application for each observed road. In this research, we propose a framework for a contextual route recommendation system that is compatible with traffic conditions and vehicle type, along with other relevant attributes (traffic prediction, weather, temperature, humidity, heterogeneity, current speed, and road length).
#ROAD TRIP PLANNER WITH WEATHER FORECAST DRIVER#
Meanwhile, route recommendation such as navigation and Advanced Driver Assistance Systems (ADAS) is limited to particular vehicles only. Motorcycles dominate the road with 77.5% compared to other types. The traffic composition in developing countries comprises of variety of vehicles which include cars, buses, trucks, and motorcycles.