Driver assistance systems for transport system efficiency: Influencing factors on user acceptance

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Volumn 17, Issue 3, 2013, Pages 245-254

  Holtl, Arne ^a   Trommer, Stefan ^a  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

Author keywords

Driver assistance; Driving efficiency; Emissions; User acceptance model

Indexed keywords

CO-OPERATIVE SYSTEMS; DRIVER ASSISTANCE; DRIVER ASSISTANCE SYSTEM; INTELLIGENT TRANSPORTATION SYSTEMS; MAJOR SUCCESS FACTORS; SUSTAINABLE IMPACTS; TECHNICAL SOLUTIONS; USER ACCEPTANCE;

AUTOMOBILE DRIVERS; ENERGY EFFICIENCY; HIGHWAY ACCIDENTS; HIGHWAY TRAFFIC CONTROL; INTELLIGENT SYSTEMS; PARTICULATE EMISSIONS;

BEHAVIORAL RESEARCH;

ENERGY EFFICIENCY; FUEL CONSUMPTION; INTELLIGENT TRANSPORTATION SYSTEM; NUMERICAL MODEL; RESEARCH WORK; TRAFFIC EMISSION; TRAFFIC MANAGEMENT; TRANSPORTATION DEVELOPMENT; TRANSPORTATION SYSTEM;

EID: 84887959285     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450.2012.716646     Document Type: Article

References (27)

1. AutoCar. (2009). ESP: Mandatory by 2011. Retrieved from http://www.autocar.co.uk/www.autocar.co.uk/News/NewsArticle/AllCars/239528
2. Auto-Motor-Sport. (2009). Navigationsgerate-Test: Spart ein Navi wirklich Kraftstoff? Retrieved from http://www.auto-motor-und-sport.de/testbericht/ sparen-navigationsgeraete-wirklich-kraftstoff-1477779.html
3. Barkenbuis, J. (2009). Eco-driving: An overlooked climate change initiative. Energy Policy, 38, 762-769.
4. Beusen, B., Broekx, S., Denys, T., Beckx, C., Degraeuwe, B., Gijsbers, M.,... Panis, L. (2009). Using on-board logging devices to study the longer-term impact of an eco-driving course. Transportation Research Part D: Transport and Environment, 14(7), 514-520.
5. Brookhuis, K. A., & de Waards, D. 2005. ADAS' acceptance and effects on the behaviour: The consequences of automatisation? In G. Underwood (Ed.), Traffic and transport psychology, Theory and application (pp. 273-278).
6. Chen, C., Fan, Y.-W., & Farn, C.-K. (2007). Predicting electronic toll collection service adoption: An integration of the technology acceptance model and the theory of planned behavior. Transportation Research Part C, 15, 300-311.
7. CIECA. (2007). Internal project on eco-driving in category B driver training & the driving test. Retrieved from http://www.ecodrive.org/ fileadmin/dam/ecodrive/Downloads/CIECA-Eco-driving-project-final-report-EN.pdf
8. Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318.
9. Dorrer, C. (2003). Effizienzbestimmung vonFahrweisen und Fahreras-sistenz zur Reduzierung des Kraftstoffverbrauchs unter Nutzung von telematischen Informationen. Renningen, Germany: Expert Verlag.
10. eCoMove. (2010). Cooperative mobility systems and services for energy efficiency. Retrieved from http://www.ecomove-project.eu/.
11. European Commission. (2010). Commission strategy to reduce CO2 emissions from cars and vans. Retrieved from http://ec.europa.eu/clima/policies/transport/ vehicles/index-en.htm
12. European Commission. (2011). Reduzierung des Kraftstoffverbrauchs durch umweltbewusstes Fahrverhalten ("Eco-Driving"). Climate action article. Retrieved from http://ec.europa.eu/clima/sites/campaign/news/news10-de.htm
13. Fiat. (2010). Eco-driving uncovered. Retrieved from http://www.fiat.co. uk/ecodrive/en/#ecodrive-en/thefacts
14. Fiat. (2011). Daten und Fakten zu Eco: drive. Retrieved from http://services.fiat.de/ecodrive/images/ECO-DRIVING-Zusamme nfassung-2010-DE.pdf
15. infas & DLR. (2010). MiD 2008-Mobilitat in Deutschland: Survey on behalf of the German Federal Ministry of Transport, Building and urban Affairs (BMVBS). Data provision by DLR Clearinghouse Transport (www.clearingstelle- verkehr.de).
16. Lee, C., Ran, B., Yang, F., & Loh, W. (2010). A hybrid tree approach to modeling alternate route choice behavior with online information. Journal of Intelligent Transportation Systems, 14(4), 209-219.
17. Man, W., Bie, J., & van Arem, B. (2010). User needs in green ITS: The result of a questionnaire survey on Dutch and Japanese drivers. ITS World Congress in Busan, Korea, October.
18. Masrom, M. (2009). Technology acceptance model and e-learning. 12th International Conference on Education, Sultan HassanalBolkiah Institute of Education University Brunei Darussalam, May.
19. Meschtscherjakov, A., Wilfinger, D., Scherndl, T., & Tscheligi, M. (2009). Acceptance of future persuasive in-car interfaces towards a more economic driving behaviour. Proceedings of the First International Conference on Automotive User Interfaces and Interactive Vehicular Applications, Automotive UI in Essen, Germany, September, (pp 81-88).
20. RITA. (2012). ITS evaluation guidelines-ITS evaluation resource guide. Retrieved from http://www.its.dot.gov/evaluation/eguide-resource.htm
21. Schrank, D., Lomax, T., & Eisele, B. (2011). TTI's 2011 urban mobility report. Texas Transportation Institute, The Texas A&M University System, September. Retrieved from http://tti.tamu.edu/documents/mobility-report- 2011-wappx.pdf
22. Travolution. (2012). Hohe volkswirtschaftliche Einsparungen. Retrieved from http://www.travolution-ingolstadt.de/index.php?id=68
23. Unger, M. (2002). Stress im Strafienverkehr. Norderstedt, Germany: GRIN-Verlag.
24. Van Aarem, B. (2004). Applications of integrated driver assistance. IEEE ITS Council Newsletter, 6(2), 5.
25. Van der Laan, J. D., Heino, A., & De Waard, D. (1997). A simple procedure for the assessment of acceptance of advanced transport telematics. Transportation Research Part C, 5(1), 1-10.
26. Van Driel, C., & van Aarem, B. (2010). The impact of a congestion assistant on traffic flow efficiency and safety in congested traffic caused by a lane drop. Journal of Intelligent Transportation Systems, 14(4), 197-208.
27. Wu, C., Zhao, G., & Ou, B. (2011). A fuel economy optimization system with applications in vehicles with human drivers and autonomous vehicles. Transport Research Part D, 16, 515-524.