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You searched for +publisher:"ETH Zürich" +contributor:("Hermann, Andreas"). Showing records 1 – 2 of 2 total matches.

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ETH Zürich

1. Ryder, Benjamin. Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots.

Degree: 2018, ETH Zürich

Across the globe, injuries sustained from traffic accidents are the eighth leading cause of mortality, and with the number of annual deaths steadily rising to over 1.25 million, now account for 2.5 % of total worldwide fatalities. This growing issue is not limited to the low and middle-income regions of the world, as the frequency and severity of traffic accidents has also been increasing in developed countries over the last decades. For example, between 2014 and 2015 the amount of traffic fatalities in the United States rose sharply by 7.2 %. Through analysing the patterns and locations of traffic accidents, road authorities can identify dangerous sections of the road network and prioritise these locations for infrastructure improvement, helping to prevent these tragic events from occurring. However, traffic accident analysis is traditionally based on historic crash data and is restrictive in many ways, typically suffering from issues including small sample sizes, underreporting of traffic accidents, and data scarcity. Furthermore, in the limited number of countries where it is available, historical accident data is often only provided on a deferred basis and analyses can be severely out-of-date. Naturalistic driving data, available from the advanced sensors and technology em- bedded in connected, semi-, and fully-autonomous vehicles, potentially offers both road safety researchers and practitioners a new and dynamic source of variables for analysis. The technology in these vehicles can be leveraged to detect accidents and ‘near miss incidents’, or critical driving events, such as heavy braking and evasive manoeuvres, and reliably predict locations with a high likelihood of traffic accidents. Both researchers and industry players alike see the promise of this data to combat the existing challenges of accident analyses. For example, real-time assessment of the locations of these events could aid road authorities in monitoring existing accident hotspots, as well as identifying new and developing areas of high accident exposure, offering various possibilities to intervene before incidents occur there. Yet, despite the great potential in identifying the locations of traffic accident hotspots with insights from these vehicles, to date, there is limited empirical evidence on whether the perilousness of locations can be accurately predicted through naturalistic driving data. Furthermore, with these insights and the rise of increasingly connected and intelligent vehicles, as well as the emergence of smartphone turn-by-turn navigation applications, various safety-focused innovations become a possibility, such as providing safe-routing services and in-vehicle warnings of potential accident hotspots. Whereas safe-routing will attempt to avoid an accident hotspot entirely, encounter- ing these dangerous locations will always remain a possibility. Consequently, identifying ways of effectively reducing the frequency and severity of traffic accidents at these known locations remains of the utmost importance. Latest studies… Advisors/Committee Members: Fleisch, Elgar, Hermann, Andreas, Wortmann, Felix.

Subjects/Keywords: Road Traffic Accident Analysis; Driver Safety and In-Vehicle Warnings; Potential of Driving Data; The Impact of Accident Hotspot Warnings on Driver Behaviour; Spatial Prediction of Traffic Accidents with Heavy Braking Events

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ryder, B. (2018). Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/306251

Chicago Manual of Style (16th Edition):

Ryder, Benjamin. “Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots.” 2018. Doctoral Dissertation, ETH Zürich. Accessed December 06, 2019. http://hdl.handle.net/20.500.11850/306251.

MLA Handbook (7th Edition):

Ryder, Benjamin. “Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots.” 2018. Web. 06 Dec 2019.

Vancouver:

Ryder B. Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots. [Internet] [Doctoral dissertation]. ETH Zürich; 2018. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/20.500.11850/306251.

Council of Science Editors:

Ryder B. Improving Driver Safety through the Identification, Prediction, and Warning of Traffic Accident Hotspots. [Doctoral Dissertation]. ETH Zürich; 2018. Available from: http://hdl.handle.net/20.500.11850/306251


ETH Zürich

2. Loock, Claire-Michelle. Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption.

Degree: 2012, ETH Zürich

Subjects/Keywords: ENERGIESPAREN (ENERGIETECHNIK); BEHAVIOURISM + PSYCHOLOGY OF BEHAVIOUR; BEHAVIOURISMUS + VERHALTENSPSYCHOLOGIE; ENERGY CONSERVATION (ENERGY TECHNOLOGY); ELECTRICAL ENERGY MEASUREMENT + ENERGY CONSUMPTION MEASUREMENT (ELECTRICAL MEASUREMENT TECHNIQUE); ARBEITSMESSUNG + ENERGIEVERBRAUCHSMESSUNG (ELEKTRISCHE MESSTECHNIK); info:eu-repo/classification/ddc/333.7; info:eu-repo/classification/ddc/150; Natural resources, energy and environment; Psychology

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Loock, C. (2012). Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/58069

Chicago Manual of Style (16th Edition):

Loock, Claire-Michelle. “Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption.” 2012. Doctoral Dissertation, ETH Zürich. Accessed December 06, 2019. http://hdl.handle.net/20.500.11850/58069.

MLA Handbook (7th Edition):

Loock, Claire-Michelle. “Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption.” 2012. Web. 06 Dec 2019.

Vancouver:

Loock C. Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption. [Internet] [Doctoral dissertation]. ETH Zürich; 2012. [cited 2019 Dec 06]. Available from: http://hdl.handle.net/20.500.11850/58069.

Council of Science Editors:

Loock C. Smart metering for behavioral change: the effects of goal setting and feedback interventions on domestic energy consumption. [Doctoral Dissertation]. ETH Zürich; 2012. Available from: http://hdl.handle.net/20.500.11850/58069

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