Platooning is nowadays one of the most promising applications for vehicle-to-vehicle communications. Platooning makes multiple vehicles travel as closely as possible to get the maximum driving efficiency. The problem here is that the view of the rear vehicle driver may be blocked by the front vehicle. In order to improve rear driver's safety and psychological stability, video streaming among vehicles aims to provide the front view of the platoon leader to rear vehicle drivers. In this paper, we first focus on measurement of realtime video streaming performance using IEEE 802.11p broadcast in the platoon. As a result, packet delivery ratio dropped to 48% in the worst case that the collision and hidden terminal problem coexist. To mitigate the frame loss, we use pseudo-broadcast that can recover frames by retransmission instead of broadcast. In addition, we employ Request-To-Send/Clear-To-Send whose transmission power increased by 5 dB to solve the hidden terminal problem. Consequently, we can prevent the frame loss and increase the packet delivery ratio up to 96.8%. Our proposal enables vehicle-to-vehicle communications to exploit a new method integrating characteristics of unicast and broadcast to solve this problem. Besides, our proposal can easily apply to existing devices by updating a device driver without any hardware chip level modification.

Although Wireless Access in Vehicular Environment (WAVE) will be legally enforced from 2020 after the recent move by the U.S. Government [1], there is still an unresolved security issue. It is data plausibility, which is not addressed in any standard that comprises the WAVE framework. In particular, an attacker may forge false position values in safety beacons in order to cause unsafe response from startled receiving vehicles. The data plausibility is a longstanding issue for which various approaches based on sensor fusion, behavior analysis and communication constraints have been proposed. However, none of these completely solve the problem.

Smartphone magnetometer traces can be used to check if the owners moved in proximity. Using time-lagged cross-correlation of the traces, a fine-resolution judgement can be made within a few meters in any formation. The technique works indoors and outdoors, with no communication infrastructure, with less power and higher resolution than GPS, and with less privacy violation than beaconing. Research and practice on human interactions, such as epidemiology and sociology that need fine contact tracing between complete strangers, can harness the technique.

In the Internet of Things (IoT) era, smartphones are expected to frequently interact with IoT devices and even facilitate various IoT applications. Due to limited roles, energy constraints, etc., however, IoT devices may use mission-tailored or proprietary wireless protocols that smartphones do not speak natively. In this paper, we propose a novel approach to the wireless “language barrier” problem between the smartphones and IoT devices of the future. We first demonstrate that smartphones have become powerful enough to process software defined radio (SDR) for some known wireless protocols. Moreover, we show that the SDRs can be packaged as “apps” and be downloaded from app stores for OS-independent deployment. Second, we show different SDR protocols on the smartphone can concurrently run through a shared RF to serve multi-tasked applications on it as might happen in diversified IoT environments. For proof-of-concept, we implement a prototype architecture that has all the SDR logic and supporting middleware on an Android smartphone which uses a USRP as the simple RF-end. Finally, we demonstrate that IEEE 802.11p and IEEE 802.15.4 SDRs on a smartphone, respectively, communicate with a ZigBee sensor mote, a ZigBee smart lightbulb, and a commercial Wireless Access in Vehicular Environment (WAVE) device, concurrently.

In this paper, we explore the possibility of using smartphones as WAVE devices. When it is expected to take more than a decade from now to deploy the WAVE technology in full scale, smartphones running the WAVE protocol stack can bring the benefit of the technology earlier. In particular, we design and implement the lower layers of the WAVE stack in software defined radio (SDR) on smartphone platform and test its vehicle-to-vehicle (V2V) performance in the real driving scenarios. We also investigate the performance in the vehicle-to-pedestrian (V2P) communication context.

Designing and distributing effective vehicular safety applications can help significantly reduce the number of car accidents and assure the safety of many precious lives. However, despite the efforts from standardization bodies and industrial manufacturers, many studies suggest that it will take more than a decade for full deployment. We start this work with the hypothesis that smartphones may be suitable platforms for catalyzing the distribution of vehicular safety systems. Specifically, smartphones connected to their respective cellular networks can report sensing data to back-end application servers and exchange safety-related messages. This paper first evaluates the performance of the vehicular ad-hoc networking standards and the hardware platforms that implement them. Next, we perform empirical evaluations on the performance of cellular networks to confirm their applicability in vehicular networking. Based on our observations, we present the VoCell application development framework. VoCell, comprehends a set of components that eases the development of smartphone applications for vehicular networking applications. Using VoCell, developers can easily access internal and external sensing components and share this data to servers. We present a number of example applications developed using VoCell and evaluate their effectiveness in local and highway environments using a pilot deployment. We envision that VoCell can act as a building block for enabling new smartphone-based systems for vehicular networking applications.