Predictive analytics for enhancing travel time estimation in navigation apps of Apple, Google, and Microsoft

The explosive growth of the location-enabled devices coupled with the increasing use of Internet services has led to an increasing awareness of the importance and usage of geospatial information in many applications. The mobile navigation apps (often called “Maps”), use a variety of available data sources to calculate and predict the travel time for different modes. This paper evaluates the pedestrian mode of Maps apps in three major smartphone operating systems (Android, iOS and Windows Phone). We will demonstrate that the Maps apps on iOS, Android and Windows Phone in pedestrian mode, predict travel time without learning from the individual’s movement profile. Then, we will exemplify that those apps suffer from a specific data quality issue (the absence of information about location and type of pedestrian crossings). Finally, we will illustrate learning from movement profile of individuals using predictive analytics models to improve the accuracy of travel time estimation for each user (personalization)

Usability analysis of 3D Maps for Pedestrian Navigation among different demographic profiles

3-Dimensional (3D) maps may provide the users with a more real-world like view in comparison with the 2-Dimensional (2D) maps. 3D maps offer more degree of freedom in movement to the users, a first-person perspective view and other dynamic details such as time of the day, weather could also be incorporated. This paper demonstrates the evaluation of the usability of 3D maps for navigation purposes, in several general aspects including recognizing landmarks and using these visual cues for navigation among different representative user-groups. The 3D model was designed to replicate the High Street, Stratford, London, UK. The participants of the survey were required to explore the model, identify and memorize the landmarks and form a mental map. They were also asked to reproduce the route they took in a 2D paper map and answer a questionnaire on their perception of their own cognitive abilities and their response on the performance of the 3D model. The results confirmed that the usability can vary among users of different demographic profiles – age, gender and language and familiarity with 3D technologies. It also showed that with some improvements in level of details incorporated in the model and design, 3D maps could become a useful tool for navigation purposes