CycleGuard

Every year 41,000 cyclists die in road traffic-related incidents worldwide [47]. One of the most startling and infuriating conflicts that cyclists experience is the so-called "right hook". It refers to a vehicle striking a cyclist heading in the same direction by turning right into the cyclist. To prevent such a crash, this work presents CycleGuard, an acoustic-based collision detection system using smartphones. It is composed of a cheap commercial off-the-shelf (COTS) portable speaker that emits imperceptible high-frequency acoustic signals and a smartphone for reflected signal reception and analysis. Since received acoustic signals bear rich information of their reflecting objects, CycleGuard applies advanced acoustic ranging techniques to extract those information for traffic analysis. Cyclists are alerted if any pending right hook crashes are detected. Real-time alerts ensure that cyclists have sufficient time to react, apply brakes, and eventually avoid the hazard. To validate the efficacy of CycleGuard, we implement a proof-of-concept prototype and carry out extensive in-field experiments under a broad spectrum of settings. Results show that CycleGuard achieves up to 95% accuracy in preventing right hook crashes and is robust to various scenarios. It is also energy-friendly to run on battery-powered smartphones.

Optimal Transponder Array and Survey Line Configurations for GNSS-A Observation Evaluated by Numerical Simulation

The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) has enabled us to measure seafloor crustal deformation in the precision of centimeters, leading to numerous discoveries of subseafloor tectonic phenomena. The moving observation conducted by our research group allows us to measure both the horizontal and vertical absolute positions of a reference point on the seafloor. However, the observation frequency of our GNSS-A observation system is still insufficient to observe short-term phenomena. This paper focused on the possibility to reduce the observation time per a seafloor site by shrinking the seafloor transponder array size and the survey line radius, which were empirically defined to be equal to the seafloor site depth in the early research. We evaluated the effects of changing these sizes on the GNSS-A positioning accuracy by conducting a series of numerical experiments. The results of the numerical experiments indicated that for a seafloor site with a depth of 3,000 m, the positioning accuracy is rapidly degraded as the transponder array size and the survey line radius are reduced to less than 3,000 m. Additional experiments done for transponder array sizes and survey line radii around 2,000–4,000 m revealed that shrinking the survey line radius has a dominant effect on the decrease in positioning accuracy. Thus, shrinking the transponder array size and the survey line radius is not a suitable option for reducing observation time, and the empirically defined observation configurations are concluded to be quite optimal when regarding both the positioning accuracy and the observation time.

Application of Phase-Only Correlation to Travel-Time Determination in GNSS-Acoustic Positioning

The GNSS-acoustic technique is a geodetic method for oceanic areas that combines GNSS positioning of a sea-surface platform and acoustic ranging of seafloor stations. Its positioning accuracy is typically a few and several centimeters for the horizontal and vertical positions, respectively. For further accuracy enhancement, we examined the errors in travel time, the most fundamental data in acoustic ranging. The reference signal used in our observations is a series of sinusoidal waves modulated by binary phase-shift keying with a maximal length sequence whose auto-correlation has a clear main peak at zero lag. However, cross-correlation between the actual returned signal and reference signal is often accompanied by many large sidelobes and looks very different from the synthetic auto-correlation. As a practical measure, we have chosen empirically one peak among several comparable peaks in the cross-correlation, though that is likely to lead to systematic errors in travel time. In this study, we revealed that a variety of cross-correlation waveform primarily depends on the incident angle of acoustic paths and that sidelobes were significantly reduced by substituting phase-only correlation (POC) for conventional cross-correlation. We therefore developed a template-matching technique using POC for the peak detection. POC templates were prepared by stacking actual POCs with certain ranges of the incident angle for each campaign. In the application of this method to actual data, we achieved successful results of our numerous campaign data to date. We consider that POC is advantageous in identifying the main peak uniquely and performing template matching more robustly, because POC enhances short-period components and thus highlights the timing of phase changes further than conventional cross-correlation.

GARPOS: Analysis Software for the GNSS‐A Seafloor Positioning With Simultaneous Estimation of Sound Speed Structure

Global Navigation Satellite System–Acoustic ranging combined seafloor geodetic technique (GNSS-A) has extended the geodetic observation network into the ocean. The key issue for analyzing the GNSS-A data is how to correct the effect of sound speed variation in the seawater. We constructed a generalized observation equation and developed a method to directly extract the gradient sound speed structure by introducing appropriate statistical properties in the observation equation, especially the data correlation term. In the proposed scheme, we calculate the posterior probability based on the empirical Bayes approach using the Akaike’s Bayesian Information Criterion for model selection. This approach enabled us to suppress the overfitting of sound speed variables and thus to extract simpler sound speed field and stable seafloor positions from the GNSS-A dataset. The proposed procedure is implemented in the Python-based software “GARPOS” (GNSS-Acoustic Ranging combined POsitioning Solver).