Abstract

Drivers’ acceptance of advanced-driver-assistance-systems (ADAS), such as pedestrian alert systems (PAS), is vital if the full benefits are to be realised. However, the adoption and continued use of such technology is not only contingent on the system’s technical competence, but is also dependent upon drivers’ attitudes towards the system, and the impact that it has on their driving behaviour and performance. Understanding and integrating the factors that affect and define acceptance in a driving context is therefore important, but complex. We present an in-depth literature review, enriched by a driving simulator study (both conducted as part of the EU-Horizon2020 PROSPECT project), that together begin to collate these factors and explore their interrelationship. A preliminary, descriptive model of driver acceptance is subsequently presented. Further work will enhance and validate the model, with the aim of creating a predictive model that can be used to inform the design of future in-vehicle technologies.

Abstract

In-vehicle pedestrian-alert-systems (PASs) can be prone to ‘false positive’ declarations, with the likelihood of false interventions increasing as time-to-collision (TTC) extends. A high number of false alarms can annoy drivers and lead to poor acceptance and low trust in the technology. To explore this relationship, 24 experienced drivers negotiated a single-lane urban high-street – moderately populated with pedestrians – during 12 five-minute drives in a medium-fidelity driving simulator. PAS warnings were presented in response to pedestrians who approached the roadside, either as a static visual alert icon presented on a HUD and/or auditory icon. The number of accurately detected pedestrians (i.e. those who entered the roadway rather than waiting at the kerbside) decreased with increasing TTC, giving rise to ‘false positive alarms’. Subjectively, participants associated the highest level of trust, confidence and desirability, and lower levels of annoyance, when warnings were presented at intermediate TTCs (3.0 and 4.0-seconds, corresponding to false-alarm rates of 40% and 60%, respectively); trust and confidence reduced significantly with both increasing and decreasing TTC. Driving performance data show that earlier warnings encouraged drivers to begin braking sooner and apply braking force more gradually, ultimately stopping further from the pedestrian – on average 18.0m following 5.0-second warnings compared to 6.2m with 2.0-second warnings. Nevertheless, evidence suggests that some drivers may have disregarded the system at longer TTCs, choosing to rely on their own judgement. The results have implications for the design, evaluation and acceptance of PASs.

Abstract

Systems available on the market address also conflicts with vulnerable road users (VRUs) such as pedestrians"br" and cyclists. Within the European project PROSPECT (Horizon2020, funded by the EC) improved VRU ADAS"br" systems are developed and tested. However, before determining systems’ properties and starting testing, an"br" up-to-date analysis of VRU crashes was needed in order to derive the most important Use Cases (detailed"br" crash descriptions) the systems should address. Besides the identified Accident Scenarios (basic crash"br" descriptions), this paper describes in short the method of deriving the Use Cases for car-to-cyclist crashes."br" Method"br" Crashes involving one passenger car and one cyclist were investigated in several European crash databases"br" looking for all injury severity levels (slight, severe and fatal). These data sources included European statistics"br" from CARE, data on national level from Germany, Sweden and Hungary as well as detailed accident"br" information from these three countries using GIDAS, the Volvo Cars Cyclist Accident database and Hungarian"br" in-depth accident data, respectively. The most frequent accident scenarios were studied and Use Cases were"br" derived considering the key aspects of these crash situations (e.g., view orientation of the cyclist and the car"br" driver’s manoeuvre intention) and thus, form an appropriate basis for the development of Test Scenarios."br" Results"br" Latest information on car-to-cyclist crashes in Europe was compiled including details on the related crash"br" configurations, driving directions, outcome in terms of injury severity, accident location, other environmental"br" aspects and driver responsibilities. The majority of car-to-cyclist crashes occurred during daylight and in clear weather conditions. Car-to-cyclist crashes in which the vehicle was traveling straight and the cyclist is moving"br" in line with the traffic were found to result in the greatest number of fatalities. Considering also slightly and"br" seriously injured cyclists led to a different order of crash patterns according to the three considered"br" European countries. Finally the paper introduced the Use Cases derived from the crash data analysis. A total"br" of 29 Use Cases were derived considering the group of seriously or fatally injured cyclists and 35 Use Cases"br" were derived considering the group of slightly, seriously or fatally injured cyclists. The highest ranked Use"br" Case describes the collision between a car turning to the nearside and a cyclist riding on a bicycle lane"br" against the usual driving direction."br" Discussion"br" A unified European dataset on car-to-cyclist crash scenarios is not available as the data available in CARE is"br" limited, hence national datasets had to be used for the study and further work will be required to extrapolate"br" the results to a European level. Due to the large number of Use Cases, the paper shows only highest ranked"br" ones.