Leveraging Personal Navigation Assistant Systems Using Automated Social Media Traffic Reporting

Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amount of vehicular traffic congestion and incidents. Existing incident detection techniques are limited to the use of sensors in the transportation network and hang on human-inputs. Despite of its data abundance, social media is not well-exploited in such context. In this paper, we develop an automated traffic alert system based on Natural Language Processing (NLP) that filters this flood of information and extract important traffic-related bullets. To this end, we employ the fine-tuning Bidirectional Encoder Representations from Transformers (BERT) language embedding model to filter the related traffic information from social media. Then, we apply a question-answering model to extract necessary information characterizing the report event such as its exact location, occurrence time, and nature of the events. We demonstrate the adopted NLP approaches outperform other existing approach and, after effectively training them, we focus on real-world situation and show how the developed approach can, in real-time, extract traffic-related information and automatically convert them into alerts for navigation assistance applications such as navigation apps.Comment: This paper is accepted for publication in IEEE Technology Engineering Management Society International Conference (TEMSCON'20), Metro Detroit, Michigan (USA

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

On the Experimental Evaluation of Vehicular Networks: Issues, Requirements and Methodology Applied to a Real Use Case

One of the most challenging fields in vehicular communications has been the experimental assessment of protocols and novel technologies. Researchers usually tend to simulate vehicular scenarios and/or partially validate new contributions in the area by using constrained testbeds and carrying out minor tests. In this line, the present work reviews the issues that pioneers in the area of vehicular communications and, in general, in telematics, have to deal with if they want to perform a good evaluation campaign by real testing. The key needs for a good experimental evaluation is the use of proper software tools for gathering testing data, post-processing and generating relevant figures of merit and, finally, properly showing the most important results. For this reason, a key contribution of this paper is the presentation of an evaluation environment called AnaVANET, which covers the previous needs. By using this tool and presenting a reference case of study, a generic testing methodology is described and applied. This way, the usage of the IPv6 protocol over a vehicle-to-vehicle routing protocol, and supporting IETF-based network mobility, is tested at the same time the main features of the AnaVANET system are presented. This work contributes in laying the foundations for a proper experimental evaluation of vehicular networks and will be useful for many researchers in the area.Comment: in EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 201