Publication
A feasibility study on the use of smartphone sensors for development of Advanced Driver Assistance Systems
| Summary: | Technological evolution is impacting several industries, e.g., by allowing them to deliver higher levels of functionality. The automotive industry is an example of how technology is supporting the development of new solutions in vehicle safety and comfort. Advanced Driver Assistance Systems (ADAS) are cases of solutions that evolved significantly in recent years. This is possible not only due to the progress of electronic solutions but also because of higher quality in software. The smartphone is an example of this evolution with a broad range of applicability since these devices have been used to develop ADAS, making them an interesting cost-effective platform to develop such systems. Previous research has shown smartphones’ ability to output sensors data with the necessary quality for a broad number of applications with special focus in inertial sensors. However, such studies tend to be difficult to reproduce or lack the desired detail levels of their experimental methods. Concerns about how good are smartphone sensors and their use to develop ADAS emerge when reading existing literature, particularly, how the context of collecting data is controlled and which variables impact the collection process. In order to assess the feasibility of using smartphones as sensing devices, questions arise on how different parts of the collection setup affect the quality of data collected. Motivated by those questions, a study considering four different hypotheses is proposed to assess the impact of a controlled set of variables, namely: brands of inertial sensors, car mounts, sensor sampling rates, and vehicles. A set of controlled experiments is performed to assess the impact of each variable in the collection process of inertial sensors, more precisely the vertical acceleration. To perform the experiments, three special-purpose tools were developed. Smartphones used in the experiments feature an application to collect and export their sensors data. A researcher of an experiment operates another smartphone application to annotate road anomalies found while driving. A desktop application automates the computation and statistical validation of the vertical acceleration correlation from different setups. Dynamic Time Warping was used to compute the correlation coefficient of vertical acceleration as measured by different devices. Results show a baseline correlation coefficient of 0.892 with a standard configuration of software and hardware. When one of the independent variables is changed, the resulting coefficients range from 0.827 to 0.848. Randomization tests were executed to statistically validate experiments results, making use of a Random Shuffle algorithm on surrogate data. Such tests rejected all four proposed null hypotheses regarding dissimilarities on vertical acceleration sensed by different setups. From the controlled experiment a deeper understanding of the variables influencing data collection with smartphones was obtained. Results showed that varying the inertial sensors, car mounts, rates of sampling, or vehicles had a low impact on vertical acceleration sensed by smartphones. This is a good indicator that smartphones can be used to develop ADAS without the need to standardize every part of the collection setup. Thus, it possible to foresee the deployment of a system to a wider audience by taking advantage of existing equipment. |
|---|---|
| Main Authors: | Santos, Nuno Miguel Teixeira dos |
| Subject: | Advanced driver assistance systems Smartphones Inertial sensors Vertical acceleration Correlation coefficient Dynamic time warping Sistemas avançados de assistência ao condutor (Advanced driver assistance systems) Sensores inerciais Aceleração vertical Coeficiente de correlação |
| Year: | 2017 |
| Country: | Portugal |
| Document type: | master thesis |
| Access type: | open access |
| Associated institution: | Universidade do Minho |
| Language: | English |
| Origin: | RepositóriUM - Universidade do Minho |
| Summary: | Technological evolution is impacting several industries, e.g., by allowing them to deliver higher levels of functionality. The automotive industry is an example of how technology is supporting the development of new solutions in vehicle safety and comfort. Advanced Driver Assistance Systems (ADAS) are cases of solutions that evolved significantly in recent years. This is possible not only due to the progress of electronic solutions but also because of higher quality in software. The smartphone is an example of this evolution with a broad range of applicability since these devices have been used to develop ADAS, making them an interesting cost-effective platform to develop such systems. Previous research has shown smartphones’ ability to output sensors data with the necessary quality for a broad number of applications with special focus in inertial sensors. However, such studies tend to be difficult to reproduce or lack the desired detail levels of their experimental methods. Concerns about how good are smartphone sensors and their use to develop ADAS emerge when reading existing literature, particularly, how the context of collecting data is controlled and which variables impact the collection process. In order to assess the feasibility of using smartphones as sensing devices, questions arise on how different parts of the collection setup affect the quality of data collected. Motivated by those questions, a study considering four different hypotheses is proposed to assess the impact of a controlled set of variables, namely: brands of inertial sensors, car mounts, sensor sampling rates, and vehicles. A set of controlled experiments is performed to assess the impact of each variable in the collection process of inertial sensors, more precisely the vertical acceleration. To perform the experiments, three special-purpose tools were developed. Smartphones used in the experiments feature an application to collect and export their sensors data. A researcher of an experiment operates another smartphone application to annotate road anomalies found while driving. A desktop application automates the computation and statistical validation of the vertical acceleration correlation from different setups. Dynamic Time Warping was used to compute the correlation coefficient of vertical acceleration as measured by different devices. Results show a baseline correlation coefficient of 0.892 with a standard configuration of software and hardware. When one of the independent variables is changed, the resulting coefficients range from 0.827 to 0.848. Randomization tests were executed to statistically validate experiments results, making use of a Random Shuffle algorithm on surrogate data. Such tests rejected all four proposed null hypotheses regarding dissimilarities on vertical acceleration sensed by different setups. From the controlled experiment a deeper understanding of the variables influencing data collection with smartphones was obtained. Results showed that varying the inertial sensors, car mounts, rates of sampling, or vehicles had a low impact on vertical acceleration sensed by smartphones. This is a good indicator that smartphones can be used to develop ADAS without the need to standardize every part of the collection setup. Thus, it possible to foresee the deployment of a system to a wider audience by taking advantage of existing equipment. |
|---|