Accident Prevention through Visual Warnings: How to Design Warnings in Head-up Display for Older and Younger Drivers

Kazazi, Juela; Winkler, Susann; Vollrath, Mark

doi:10.1109/itsc.2015.171

Cited by 15 publications

(12 citation statements)

References 11 publications

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“…Participants adapted their driving behaviour by turning with a lower velocity after waiting longer at the intersection, and so avoided collisions. Visual warnings have also had a positive effect on drivers braking reaction time, for both older and younger participants [23]. The largest improvement was seen in critical situations, where collisions were successfully avoided due to the warning.…”

Section: In-vehicle Warning Systemsmentioning

confidence: 94%

“…With regard to the types of warning that can be provided, contextual warnings had limited importance to the behaviour of the driver, but users rated the system much higher due to them [33]. Additionally, it has been shown that in less critical situations a contextual caution warning sign is more suitable than a stop sign warning [23].…”

Section: In-vehicle Warning Systemsmentioning

confidence: 99%

“…In other words, where possible, information was captured about what objects were involved in the accident, why it happened and where it occurred. Out of this information a warning was generated, with the purpose to provide more information about a specific typical appearance of a hotspot instead of a general warning [23]. It has been shown that warnings making use of contextual objects and directions are preferred by users [33].…”

Section: Accident Hotspot Classificationmentioning

confidence: 99%

“…However, as the system at hand is tested in the field and does not warn of a specific upcoming object, but instead a historically hazardous location, many of these variables are unavailable to us. For example, measuring number of collisions or braking reaction time [24] is unsuitable, as the distance to other objects is unknown and there may be no need for a change in the driver's behaviour. As such, our dependent variable is the effect of the warnings on potentially dangerous braking events incurred by the driver, which is a key result of decision making driving behaviour.…”

Section: Field Study Descriptionmentioning

confidence: 99%

“…In addition, various research studies are geared towards how in-vehicle DSSs can encourage drivers to adapt their driving behaviour when necessary. Latest studies provide promising evidence that these systems can indeed have significant positive effects on driving behaviour and collision avoidance [23,57,63]. These systems can be delivered to vehicles through existing mobile or standalone satellite navigation systems [68].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Preventing traffic accidents with in-vehicle decision support systems - The impact of accident hotspot warnings on driver behaviour

Ryder

Gahr

Egolf

et al. 2017

Decision Support Systems

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A B S T R A C TDespite continuous investment in road and vehicle safety, as well as improvements in technology standards, the total amount of road traffic accidents has been increasing over the last decades. Consequently, identifying ways of effectively reducing the frequency and severity of traffic accidents is of utmost importance. In light of the depicted challenge, latest studies provide promising evidence that in-vehicle decision support systems (DSSs) can have significant positive effects on driving behaviour and collision avoidance. Going beyond existing research, we developed a comprehensive in-vehicle DSS, which provides accident hotspot warnings to drivers based on location analytics applied to a national historical accident dataset, composed of over 266,000 accidents. As such, we depict the design and field evaluation of an in-vehicle DSS, bridging the gap between real world location analytics and in-vehicle warnings. The system was tested in a country-wide field test of 57 professional drivers, with over 170,000km driven during a four-week period, where vehicle data were gathered via a connected car prototype system. Ultimately, we demonstrate that in-vehicle warnings of accident hotspots have a significant improvement on driver behaviour over time. In addition, we provide first evidence that an individual's personality plays a key role in the effectiveness of in-vehicle DSSs. However, in contrast to existing lab experiments with very promising results, we were unable to find an immediate effect on driver behaviour. Hence, we see a strong need for further field experiments with high resolution car data to confirm that in-vehicle DSSs can deliver in diverse field situations.

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Section: In-vehicle Warning Systemsmentioning

confidence: 94%

Section: In-vehicle Warning Systemsmentioning

confidence: 99%

Section: Accident Hotspot Classificationmentioning

confidence: 99%

Section: Field Study Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Preventing traffic accidents with in-vehicle decision support systems - The impact of accident hotspot warnings on driver behaviour

Ryder

Gahr

Egolf

et al. 2017

Decision Support Systems

View full text Add to dashboard Cite

show abstract

HMI Strategy – Warnings and Interventions

Winkler

Powelleit

Kazazi

et al. 2017

UR:BAN Human Factors in Traffic

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Spatial prediction of traffic accidents with critical driving events – Insights from a nationwide field study

Ryder

Dahlinger

Gahr

et al. 2019

Transportation Research Part A: Policy and Practice

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Despite the fact that semi-autonomous vehicles will become more and more prevalent in the coming decades, recent studies have highlighted that traffic accidents will persist as a core issue for road users, insurers, and policy makers alike. Researchers and industry players see potential in the technology embedded in semi-autonomous vehicles to combat this challenge by reliably predicting locations with a high likelihood of traffic accidents. This technology can be leveraged to detect accidents and 'near miss incidents', such as heavy braking and evasive manoeuvres, otherwise known as Critical Driving Events (CDEs). The locations of CDEs could identify areas of high accident exposure, offering automotive insurers a unique opportunity to reduce traffic accidents through the adoption of active loss prevention business models, such as providing saferouting services and in-vehicle warnings. To date, there is limited empirical evidence on whether the Crash Frequency and Crash Rate of locations can be accurately identified through CDEs. To address this research gap, an 18-week naturalistic driving field study of 72 vehicles was conducted in Switzerland, covering over 690,000 km. Data collected from the CAN Bus of these vehicles indicate that there is a proportional relationship between the CDEs of the fleet, and the Crash Frequency and Crash Rate of a location. Furthermore, a nationwide spatial regression analysis was applied to determine Crash Frequency across the majority of the Swiss road network. We identify the relationship between Crash Frequency, and the CDEs and Trip Frequency of the fleet, along with additional explanatory variables for urban and highway locations. These insights provide first evidence that insurance companies and other industry players with access to a nationwide semi-autonomous fleet can determine existing and emerging locations of high accident probability, enabling more proactive business models and safety focused services.

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Accident Prevention through Visual Warnings: How to Design Warnings in Head-up Display for Older and Younger Drivers

Cited by 15 publications

References 11 publications

Preventing traffic accidents with in-vehicle decision support systems - The impact of accident hotspot warnings on driver behaviour

Preventing traffic accidents with in-vehicle decision support systems - The impact of accident hotspot warnings on driver behaviour

HMI Strategy – Warnings and Interventions

Spatial prediction of traffic accidents with critical driving events – Insights from a nationwide field study

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