Annoyance is the most prevalent community response to environmental noise. Observational and experimental lab studies have shown that exposure to environmental noise leads to annoyance, sleep disturbance, daytime sleepiness, increased heart rate and increased blood pressure. However, previous literature is preliminary based on controlled settings or experimental design, raising the question of the generalizability and applicability in daily life scenarios.
The objective of the project is how to measure (aircraft) noise annoyance in daily life. Recently, NLR developed a mobile-based app to open up the possibility of large scale studies (e.g. within communities around airports and approach routes) to assess the effect of different amounts of (nocturnal) aircraft noise exposure on (short-term) noise annoyance (and sleep disturbances). This internship will focus on the development of two functionalities within our app. Firstly, an algorithm that can handle radar tracks. The radar tracks should be linked to the corresponding time and location of the fly-over. This should relate to the GPS information we receive from the app. Secondly, the development of a data visualization that could map the degree of annoyance around airport in a visual way and over time. Ideally, the algorithm should be adaptive and, for example, annoyance-reducing measures can be included. This also involves the development of an annoyance score. In the score we can process the information from the app and the objective measurements. The annoyance score can then change adaptively in the map. Support in the literature study and elaboration of the questionnaire will be part of the internship.
Tasks to be foreseen:
- Supporting in a literature study about (aircraft) noise annoyance and how to measure noise annoyance
- Supporting in the elaboration of a questionnaire
- Development of an algorithm that can handle radar tracks
- Development of an annoyance map
- Report, including lessons learned and suggestions for next steps
- Present the outcome of the study to the department at NLR
This fulltime internship will be 5 to 6 months (shorter or longer is possible). We offer an inspiring high-tech aerospace-oriented working environment and an informal culture with room for personal initiative although you have to work remotely (because of COVID-19). You will receive a compensation for general expenditures.
- Higher professional education (HBO or WO) student
- Study in (Applied) Psychology, Data Science or Aviation or equivalent
- Good communication and writing skills
- Proven experience with Python
For more information, please contact Maykel van Miltenburg, MSc. (email@example.com; 088-5113389).
- A challenging internship in a high-tech working environment
- Informal culture with room for own initiative, in which result orientation and involvement are important pillars
- An internship allowance
NLR is a leading international research centre for aerospace. Its mission is to make air transport safer, more efficient, more effective and more sustainable. Bolstered by its multidisciplinary expertise and unrivalled research facilities, NLR provides innovative and comprehensive solutions to the complex challenges of the aerospace sector. NLR’s operator performance group has a wide range of both academic and practical knowledge on operator performance and human factors (HF) in complex environments. Operator-in-the-loop studies are performed to measure the manner in which personnel conduct themselves in an operational setting (either simulated or realistic). The assessment includes operator performance aspects such as (crew) workload, (team) situation awareness, usability, visual perception, vigilance, and (eye) fatigue. Data is gathered objectively (e.g. heart rate and eye-tracking) and subjectively (e.g. through interviews, workshops and questionnaires).
Send your application, together with your motivation letter and CV to firstname.lastname@example.org, attn. Maykel van Miltenburg. A first selection of candidates will be made ASAP. However more internships related to, and in continuation of, the current one are foreseen. Therefore late responses are also appreciated.
Datum : 10/09/2020
Locatie : Location is Amsterdam but as long as Corona measures are applied the work will be carried out remotely.
Uren : 40
Opleidingsniveau : HBO/WO
Achtergrond : (Applied) Psychology, Data Science or Aviation or equivalent