Naturalistic driving study for older drivers based on the DriveSafe app

2019 IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, 27-30 Oct. 2019Elderly population is increasing year after year in the developed countries. However, the knowledge of actual mobility needs of senior drivers is scarce. In this paper, we present a naturalistic driving study (NDS) focused on older drivers through smartphone technology and using our DriveSafe app. Our system automatically generates a driving analysis report based on objective indicators. The proposal supposes an improvement over the traditional surveys and observers, and represents an advance over the current NDSs by using smartphones instead of complex instrumented vehicles. Our method avoids the problems of manual annotation by using an automatic method for data reduction information. Furthermore, a comparison between traditional questionnaires and information provided by our system is carried out and conclusions are presented.Ministerio de Economía y CompetitividadDGTComunidad de Madri

Driver and Passenger Identification from Smartphone Data

The objective of this paper is twofold. First, it presents a brief overview of existing driver and passenger identification or recognition approaches which rely on smartphone data. This includes listing the typically available sensory measurements and highlighting a few key practical considerations for automotive settings. Second, a simple identification method that utilises the smartphone inertial measurements and, possibly, doors signal is proposed. It is based on analysing the user behaviour during entry, namely the direction of turning, and extracting relevant salient features, which are distinctive depending on the side of entry to the vehicle. This is followed by applying a suitable classifier and decision criterion. Experimental data is shown to demonstrate the usefulness and effectiveness of the introduced probabilistic, low-complexity, identification technique.Jaguar Land Rover under the Centre for Advanced Photonics and Electronics (CAPE) agreement

Fuzzy System to Assess Dangerous Driving: A Multidisciplinary Approach

Dangerous driving can cause accidents, injuries and loss of life. An efficient assessment helps to identify the absence or degree of dangerous driving to take the appropriate decisions while driving. Previous studies assess dangerous driving through two approaches: (i) using electronic devices or sensors that provide objective variables (acceleration, turns and speed), and (ii) analyzing responses to questionnaires from behavioral science that provide subjective variables (driving thoughts, opinions and perceptions from the driver). However, we believe that a holistic and more realistic assessment requires a combination of both types of variables. Therefore, we propose a three-phase fuzzy system with a multidisciplinary (computer science and behavioral sciences) approach that draws on the strengths of sensors embedded in smartphones and questionnaires to evaluate driver behavior and social desirability. Our proposal combines objective and subjective variables while mitigating the weaknesses of the disciplines used (sensor reading errors and lack of honesty from respondents, respectively). The methods used are of proven reliability in each discipline, and their outputs feed a combined fuzzy system used to handle the vagueness of the input variables, obtaining a personalized result for each driver. The results obtained using the proposed system in a real scenario were efficient at 84.21%, and were validated with mobility experts’ opinions. The presented fuzzy system can support intelligent transportation systems, driving safety, or personnel selection