| 1. |
- Kovaceva, Jordanka, 1980, et al.
(author)
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Identification of aggressive driving from naturalistic data in car-following situations
- 2020
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In: Journal of Safety Research. - : Elsevier BV. - 0022-4375. ; 73, s. 225-234
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Journal article (peer-reviewed)abstract
- Introduction: Aggressive driving has been associated as one of the causes for crashes, sometimes with very serious consequences. The objective of this study is to investigate the possibility of identifying aggressive driving in car-following situations on motorways by simple jerk metrics derived from naturalistic data. Method: We investigate two jerk metrics, one for large positive jerk and the other for large negative jerk, when drivers are operating the gas and brake pedal, respectively. Results: The results obtained from naturalistic data from five countries in Europe show that the drivers from different countries have a significantly different number of large positive and large negative jerks. Male drivers operate the vehicle with significantly larger number of negative jerks compared to female drivers. The validation of the jerk metrics in identifying aggressive driving is performed by tailgating (following a leading vehicle in a close proximity) and by a violator/non-violator categorization derived from self-reported questionnaires. Our study shows that the identification of aggressive driving could be reinforced by the number of large negative jerks, given that the drivers are tailgating, or by the number of large positive jerks, given that the drivers are categorized as violators. Practical applications: The possibility of understanding, classifying, and quantifying aggressive driving behavior and driving styles with higher risk for accidents can be used for the development of driver support and coaching programs that promote driver safety and are enabled by the vast collection of driving data from modern in-vehicle monitoring and smartphone technology.
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| 2. |
- León Cano, Jorge Alejandro, et al.
(author)
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Automatic incident detection and classification at intersections
- 2009
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In: 21st International Conference on Enhanced Safety of Vehicles, ESV. ; , s. Paper 09-0234
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Conference paper (other academic/artistic)abstract
- Collisions at intersections are common and their consequences are often severe. This paper addresses the need for information on accident causation; a knowledge that can be used to obtain more effective countermeasures. A novel method that can be applied to data recorded in a groundbased observation system or similar is proposedfor classifying vehicle interactions into a set ofpredefined traffic scenarios. The classification isbased on possible combinations of trajectories of two interacting vehicles that have passed through an intersection. Additionally, the authors present an incident detection algorithm that uses the classified vehicle interactions. This algorithm constitutes the core of a video-based automatic incident detection at intersections (AIDI) system. The performance of the AIDI system was successfullyverified both in a driving simulator and in real traffic conditions.
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| 3. |
- Amin, Khabat, et al.
(author)
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Injury Reducing Effect of GSHP-Heated Pedestrian Paths
- 2024
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In: International Ground Source Heat Pump Association-Research Conference. ; , s. 227-235
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Conference paper (peer-reviewed)abstract
- In Sweden, falls amongst pedestrians during wintertime, due to slipping on ice and snow, is a costly and growing problem. Using data on pedestrian falls from four Swedish cities, the injury-reducing effect of heated surfaces was studied. The results indicate that heated surfaces have a significant injury-reducing effect especially in cities with more ice and snow. Currently, district heating is used as a heat source and at an increasing cost. By using GSHP systems as a heat source, the cost could be considerably lowered, and in this way secure the further use and expansion of heated pedestrian paths.
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| 4. |
- Bärgman, Jonas, 1972, et al.
(author)
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On data security and analysis platforms for analysis of naturalistic driving data
- 2011
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In: Proceedings of the 8th European Congress and Exhibition on Intelligent Transport Systems and Services, June 2011, Lyon.
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Conference paper (peer-reviewed)abstract
- Studies involving naturalistic driving data, of which Naturalistic Field Operational Tests (N-FOTs) are a subset, are becoming increasingly important for understanding the factors influencing accident causation as well as for the development and evaluation of active safety systems. The methodology project FESTA developed a handbook on how to plan and implement FOTs. This handbook has been extensively used as a guideline in the euroFOT project. However, “the devil is in the details” when implementing e.g. the platforms for data security and analysis in projects which deal with analysis of large amounts of sensitive naturalistic driving data, such as euroFOT. That is, although a guideline such as FESTA is used, how the details are implemented is what makes the implementation a success or not. This paper is a case description of the implementation of the data security and analysis platform used for euroFOT (and other naturalistic data projects) at the SAFER Vehicle and Traffic Safety Centre. The paper covers aspects ranging from physical access to analysis rooms and corresponding digital access, via the platforms for pre-processing of data, to the platforms for information extraction for hypothesis analysis and statistics. The considerations in the design and choice of these platforms include subjects (drivers) privacy concerns, industry commercial concerns, as well as the needs and requirements from the analysis.
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| 5. |
- Bärgman, Jonas, 1972, et al.
(author)
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The UDrive dataset and key analysis results
- 2017
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Reports (other academic/artistic)abstract
- UDrive is a large European naturalistic driving study, sponsored by the European Commission (FP7).Nineteen partners across Europe have come together and, along with stakeholders, defined researchquestions, developed data acquisition, collected and managed data, and finally, performed a first analysis onthe UDrive dataset with respect to driver/rider behaviour related to traffic safety and the environment (ecodriving).This document presents key results of the UDrive analysis performed in UDrive Sub-project 4: Data analysis.It also describes the UDrive dataset and, in brief, how we got here.
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| 6. |
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| 7. |
- Carlsson, Anna K, 1966, et al.
(author)
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Skadereducerande Effekt av Uppvärmda Trottoarer, Gång- och Cykelstråk
- 2018
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Reports (other academic/artistic)abstract
- Nearly two out of three fall crashes with seriously injured pedestrians occur in the winter (December-March), i.e. twice as many pedestrians are seriously injured during these four months compared to the rest of the year. During the winter period (December-March) almost nine out of ten fall crashes are caused in the traffic environment due to slipping on ice/snow.
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| 8. |
- Carlsson, Anna K, 1966, et al.
(author)
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Skadereducerande Effekt av Uppvärmda Trottoarer, Gång- och Cykelstråk - En Inledande Studie
- 2019
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Conference paper (other academic/artistic)abstract
- Nästan två av tre fallolyckor med allvarligt skadade fotgängare sker under vintern; dubbelt så många fotgängare skadas allvarligt under dessa fyra månader jämfört med årets övriga. Under vinterperioden orsakas nästan nio av tio fallolyckor i trafikmiljö av halka pga is/snö. De skador som drabbar fotgängare (och cyklister) på halt underlag behöver i allmänhet betydligt längre vårdtid jämfört med om det inte varit halt. Det finns alltså en stor skadereducerande potential i förbättrad halkbekämpning. Syftet med studien är att: - Kartlägga uppvärmda ytor i stadsmiljön för de största städerna i Sverige - Analysera den skadereducerande effekten av uppvärmda ytor för fotgängare, och (om möjligt) cyklister.
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| 9. |
- Carsten, Oliver, et al.
(author)
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Driver Distraction and Inattention
- 2017
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Reports (other academic/artistic)abstract
- In UDRIVE, the major focus of the work on driver inattention and distraction has been focused on obtaining a better understanding of whether and how drivers manage their secondary task activities — when they choose to engage, what tasks they select, whether they adjust their activity to different situations and whether they are willing to surrender secondary task activities as the primary task of driving becomes more demanding. In other words, the focus is on self-regulation, on how drivers manage their secondary task activity in the context of the dynamics of the traffic and road situation. That management includes the determination not to engage in such tasks in the first place or only to engage in some particular activities. NDS are particularly suited to such an investigation, since experimental studies in driving simulators and even on test tracks tend to suffer from an instruction effect, in that participants are typically instructed to carry out an activity at a given moment. Thus such experimental studies provide insight into how driver attention, driver information processing and driving performance are affected by secondary tasks, but are less useful when research is focused on driver management of task activity
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| 10. |
- Cieślik, Ilona, et al.
(author)
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Improving the effectiveness of active safety systems to significantly reduce accidents with vulnerable road users - the project PROSPECT (Proactive Safety for Pedestrians and Cyclists)
- 2019
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In: 26th ESV Conference Proceedings.
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Conference paper (peer-reviewed)abstract
- Accidents involving Vulnerable Road Users (VRU) are still a very significant issue for road safety. ́PROactive Safety for PEdestrians and CyclisTs ́ is a collaborative research project funded by the European Commission. The objective of PROSPECT was to improve significantly the effectiveness of active VRU safety systems compared to those currently on the market by: (i) expanding the scope of urban scenarios addressed (ii) improving the overall Autonomous Emergency Braking (AEB) and Autonomous Emergency Steering (AES) system performance (iii) proposing extensive validation methodologies for consumer testing, simulation and acceptance studies with tools for testing. Concepts for sensors and control systems were shown in three vehicle demonstrators and a mobile driving simulator and tested with novel VRU dummy specimen. Those systems address the well-known barriers of current AEB systems such as limited sensors field-of-view, fuzzy path prediction, unreliable intent recognition and slow reaction times for the actuation. User acceptance tests with the participation of drivers were also crucial in PROSPECT for the success of all active safety systems. Driving simulator studies were then used in a controlled and repeatable environment for the collection of data regarding the interaction between the driver and the safety function. Finally, project consortium implemented a novel benefit estimation methodology that includes an assessment of the combined effect of active and passive safety measures of PROSPECT-like systems.
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