How to warn drivers in various safety-critical situations - Different strategies, different reactions

Effects of driver's braking behavior by the real-time pedestrian scale warning system

A driver warning system can improve pedestrian safety by providing drivers with alerts about potential hazards. Most driver warning systems have primarily focused on detecting the presence of pedestrians, without considering other factors, such as the pedestrian's gender and speed, and whether pedestrians are carrying luggage, that can affect driver braking behavior. Therefore, this study aims to investigate how driver braking behavior changes based on the information about the number of pedestrians in a crowd and examine if a developed warning system based on this information can induce safe braking behavior. For this purpose, an experiment scenario was conducted using a virtual reality-based driving simulator and an eye tracker. The collected driver data were analyzed using mixed ANOVA to derive meaningful conclusions. The research findings indicate that providing information about the number of pedestrians in a crowd has a positive impact on driver braking behavior, including deceleration, yielding intention, and attention. Particularly, It was found that in scenarios with a larger number of pedestrians, the Time to Collision (TTC) and distance to the crosswalk were increased by 12%, and the pupil diameter was increased by 9%. This research also verified the applicability of the proposed warning system in complex road environments, especially under conditions with poor visibility such as nighttime. The system was able to induce safe braking behavior even at night and exhibited consistent performance regardless of gender. In conclusion, considering various factors that influence driver behavior, this research provides a comprehensive understanding of the potential and effectiveness of a driver warning system based on information about the number of pedestrians in a crowd in complex road environments.

A freeway vehicle early warning method based on risk map: Enhancing traffic safety through global perspective characterization of driving risk

In the era of rapid advancements in intelligent transportation, utilizing vehicle operating data to evaluate the risk of freeway vehicles and study on vehicle early warning methods not only lays a theoretical foundation for improving the active safety of vehicles, but also provides the technical support for reducing accident rate. This paper proposes a freeway vehicle early warning method based on risk map to enhance vehicle safety. Firstly, Modified Time-to-Collision (MTTC), a two-dimensional indicator that describes the risk of inter-vehicle travel, is used as an indicator of road traffic risk. This paper designs a transformation function to probabilistically transform MTTC into Risk Indicators (RI). The single-vehicle risk map is generated based on the mapping relationship between the risk values and the corresponding roadway segments. These single-vehicle risk maps of all vehicles on the road are superimposed to construct the risk map, which is used to describe the risk distribution in the freeway. Then, a vehicle early warning framework is built based on the risk map. The risk values in the risk map are compared with predefined early warning thresholds to alert the vehicle when it enters a high-risk state. Finally, VISSIM is used to carry out simulation experiments. The experiment simulates a freeway accident stopping situation. This scenario includes sub-scenarios such as unplanned stopping and lane-changing, continuous lane-changing, and adjacent lane overtaking. We analyze the risk map and vehicle warning results in different sub-scenarios, evaluate the risk changes of the vehicles before and after receiving the warning, and compare the warning results of the method in this paper with other alternative methods. The method is applied to 17 vehicles in the simulation to adjust their motion states. The results show that the total warning time is reduced by 29.6% and 73.3% of vehicles change lanes away from the accident vehicle. The overall results validate the effectiveness of the vehicle early warning method based on risk map proposed in this paper.

High visual salience of alert signals can lead to a counterintuitive increase of reaction times

It is often assumed that rendering an alert signal more salient yields faster responses to this alert. Yet, there might be a trade-off between attracting attention and distracting from task execution. Here we tested this in four behavioral experiments with eye-tracking using an abstract alert-signal paradigm. Participants performed a visual discrimination task (primary task) while occasional alert signals occurred in the visual periphery accompanied by a congruently lateralized tone. Participants had to respond to the alert before proceeding with the primary task. When visual salience (contrast) or auditory salience (tone intensity) of the alert were increased, participants directed their gaze to the alert more quickly. This confirms that more salient alerts attract attention more efficiently. Increasing auditory salience yielded quicker responses for the alert and primary tasks, apparently confirming faster responses altogether. However, increasing visual salience did not yield similar benefits: instead, it increased the time between fixating the alert and responding, as high-salience alerts interfered with alert-task execution. Such task interference by high-salience alert-signals counteracts their more efficient attentional guidance. The design of alert signals must be adapted to a "sweet spot" that optimizes this stimulus-dependent trade-off between maximally rapid attentional orienting and minimal task interference.

Effects of collision warning characteristics on driving behaviors and safety in connected vehicle environments

With the emerging connected vehicle (CV) technologies, a novel in-vehicle omni-direction collision warning system (OCWS) is developed. For example, vehicles approaching from different directions can be detected, and advanced collision warnings caused by vehicles approaching from different directions can be provided. Effectiveness of OCWS in reducing crash and injury related to forward, rear-end and lateral collision is recognized. However, it is rare that the effects of collision warning characteristics including collision types and warning types on micro-level driver behaviors and safety performance is assessed. In this study, variations in drivers' responses among different collision types and between visual only and visual plus auditory warnings are examined. In addition, moderating effects by driver characteristics including drivers' demographics, years of driving experience, and annual driving distance are also considered. An in-vehicle human-machine interface (HMI) that can provide both visual and auditory warnings for forward, rear-end, and lateral collisions is installed on an instrumented vehicle. 51 drivers participate in the field tests. Performance indicators including relative speed change, time taken to accelerate/decelerate, and maximum lateral displacement are adopted to reflect drivers' responses to collision warnings. Then, generalized estimation equation (GEE) approach is applied to examine the effects of drivers' characteristics, collision type, warning type and their interaction on the driving performance. Results indicate that age, year of driving experience, collision type, and warning type can affect the driving performance. Findings should be indicative to the optimal design of in-vehicle HMI and thresholds for the activation of collision warnings that can increase the drivers' awareness to collision warnings from different directions. Also, implementation of HMI can be customized with respect to individual driver characteristics.

Developing a two-stage auditory warning system for safe driving and eco-driving at signalized intersections: A driving simulation study

In-vehicle intersection warning systems represent a promising approach for informing drivers of potential danger to reduce crashes and improve intersection safety. However, there is limited research on drivers' eco-driving performances, such as fuel consumption and emission, when drivers adapt their behaviors to the systems. In this study, an innovative two-stage in-vehicle intersection warning system was proposed to reduce red-light running (RLR) violations. Forty-five drivers participated in a simulated driving experiment and their driving performances at the intersections were evaluated to examine the effectiveness of the warning system. The measures included stop/go decision, RLR rate, average speed and deceleration, brake transition time, brake level, fuel consumption, and emission of CO and NOx. The results indicated that the warning system had a positive effect on drivers' safe driving and eco-driving performances, such as reducing the RLR rate, advancing and smoothing the deceleration and reducing fuel consumption and emission. Moreover, the impact of warning on drivers' performances varied with the time to the onset of yellow light. The research has practical implications for the automobile industry to use vehicle-to-infrastructure technology in the design of in-vehicle warning systems to improve driver behaviors at intersections.

Potentially Critical Driving Situations During "Blue-light" Driving: A Video Analysis

INTRODUCTION

Driving with warning lights and sirens is highly demanding for ambulance drivers, and the crash risk is much higher than that during normal driving. In this study our goals were to establish a coding protocol to observe how often and how long potentially critical driving situations (PCDS) occur during "blue-light" driving (driving with emergency response lights) and to describe traffic and environmental conditions preceding and accompanying the PCDS.

METHODS

We collected randomly drawn video data of real ambulance driving between 2014-2017 in two German federal states. A coding protocol was developed to categorize PCDS into four types ("right of way," "crosswalks," "overtaking" [passing], and "other") and to describe them within the context of road characteristics, incident type, traffic, weather conditions, and driving style.

RESULTS

A total of 172 videos of 71 different drivers were chosen randomly covering 1125 minutes of driving with warning lights and sirens. The drivers had a mean age of 33.7 years, and 25.4% were female. A total of 2048 PCDS occurred with a mean duration of five seconds (range of 1-66), amounting to one PCDS every 33 seconds. Twenty percent of the driving time involved PCDS. The rapid driving style (10.5%) showed more PCDS (one every 28.5 seconds), and the defensive driving style showed fewer PCDS (one every 49.6 seconds). Of all detected PCDS, "right of way" situations (57.5%) were most frequent, followed by "overtaking" [passing] maneuvers (30.2%).

CONCLUSION

This study used a detailed coding protocol to describe driving with warning lights and sirens. The PCDS occurred less frequently than anticipated, although they were still common events when driving an ambulance, representing significant potential for crashes or near-crashes. These results can be used for insight training programs to raise ambulance drivers' awareness of typical PCDS and associated potential crash risk.

The effects of age and physical exercise on multimodal signal responses: Implications for semi-autonomous vehicle takeover requests

The present study examined whether the non-chronological age factor, engagement in physical exercise, affected responses to multimodal (combinations of visual, auditory, and/or tactile) signals differently between younger and older adults in complex environments. Forty-eight younger and older adults were divided into exercise and non-exercise groups, and rode in a simulated Level 3 autonomous vehicle under four different task conditions (baseline, video watching, headway estimation, and video-headway combination), while being asked to respond to various multimodal warning signals. Overall, bi- and trimodal warnings had faster response times for both age groups across driving conditions, but was more pronounced for older adults. Engagement in physical exercise was associated with smaller maximum braking force for younger participants only, and also corresponded to longer average fixation durations, compared to the non-exercise group. Findings from this research can help to guide decisions about the design of warning and information systems for semi-autonomous vehicles.

How do pedestrians respond to adaptive headlamp systems in vehicles? A road-crossing study in an immersive virtual environment

Three-fourths of pedestrian fatalities in the U.S. occur in the dark (National Center for Statistics and Analysis, 2020). Adaptive Headlight Systems (AHS) offer the potential to address this problem by improving the visibility of pedestrians for drivers and alerting pedestrians to approaching vehicles. The goal of this study was to investigate how pedestrians respond to different types of AHS. We conducted a mixed factor experiment with 106 college-age adults using a large-screen pedestrian simulator. The task for participants was to cross a stream of continuous traffic without colliding with a vehicle. There were four AHS treatment conditions that differed in the color (white or red) and timing of an icon projected on the roadway in front the participant as an AHS vehicle approached. Participants in the treatment conditions encountered a mix of AHS and non-AHS vehicles. There was also a control condition in which participants encountered only non-AHS vehicles. We found that the color and the timing of the icon projected on the roadway influenced the size of the gaps crossed. Participants in the red icon with early onset condition chose the largest gaps for crossing. An unexpected outcome was that participants in the AHS treatment conditions chose larger gaps even when crossing in front of non-AHS vehicles, suggesting that experiences with AHS vehicles generalized to non-AHS vehicles. We conclude that AHS can have a significant, positive impact on pedestrian road-crossing safety.

A Systematic Review of Virtual Reality Applications for Automated Driving: 2009–2020

While virtual reality (VR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of VR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to VR technology, at present, the pool of findings is heterogeneous and non-transparent. We investigated N = 176 scientific papers of relevant journals and conferences with the goal to analyze the status quo of existing VR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of VR technology which is applicable at specific level of vehicle automation and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on designing automotive experiences in VR, safety aspects, and vulnerable road users. Trust, simulator and motion sickness, and external human-machine interfaces (eHMIs) also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Finally, we discuss a set of open challenges, and give recommendation for future research in automated driving at the VR side of the reality-virtuality continuum.

Factors affecting behavior of mobile phone use while driving and effect of mobile phone use on driving performance

This study analyzed factors affecting behavior of mobile phone use while driving and its effects on driving performance, in terms of speed, lateral position, steer deviation, steer speed, following distance, perception-reaction time, and occurrence of a near miss situation. To investigate the factors affecting behavior of mobile phone use while driving, 1106 respondents from four different regions in Thailand participated in the questionnaire survey study. Theory of Planned Behavior (TPB) was used to explain these factors including two additional extended factors which are risk perception and law enforcement knowledge. The outcome of this part shows that attitude, norm, and law enforcement knowledge significantly affect the intention and behavior of the drivers. Even though approximately 90 percent of drivers realized that using a mobile phone while driving was dangerous and against the law, they have reported that they still use mobile phone while driving. To determine the effect of mobile phone use on driving performance, a 2-lane, straight rural highway, with a leading vehicle and an unexpected "STOP" sign, were simulated in order to examine the driving performance of drivers "without a phone", "talking on a phone call", and "texting a message" conditions. The results found that using mobile phone while driving can reduce speed and following distance, but increase lateral deviation, steer deviation, steer speed, perception-reaction time, and number of near misses leading to higher risks for road crashes.

Car drivers coping with hazardous events in real versus simulated situations: Declarative, behavioral and physiological data used to assess drivers' feeling of presence

More than 1.3 million people lose their lives every year in traffic accidents. Improving road safety requires designing better vehicles and investigating drivers’ abilities more closely. Driving simulators are constantly being used for this purpose, but the question which often arises as to their validity tends to be a barrier to developments in this field. Here we studied the validity of a simulator, defined as how closely users’ behavior under simulated conditions resembles their behavior on the road, based on the concept of drivers’ feeling of presence. For this purpose, the driving behavior, physiological state and declarative data of 41 drivers were tested in the Sherpa2 simulator and in a real vehicle on a track while driving at a constant speed. During each trial, drivers had to cope with an unexpected hazardous event (a one-meter diameter gym ball crossing the road right in front of the vehicle), which occurred twice. During the speed-maintenance task, the simulator showed absolute validity, in terms of the driving and physiological parameters recorded. During the first hazardous event, the physiological parameters showed that the level of arousal (Low Heart Rate/High Heart Rate ratio x10) increased up to the end of the drive. On the other hand, the drivers’ behavioral (braking) responses were 20% more frequent in the simulator than in the real vehicle, and the physiological state parameters showed that stress reactions occurred only in the real vehicle (+5 beats per minute, +2 breaths per minute and the phasic skin conductance increased by 2). In the subjects’ declarative data, several feeling of presence sub-scales were lower under simulated conditions. These results suggest that the validity of motion based simulators for testing drivers coping with hazards needs to be questioned.

Scientometric Analysis of Safety Sign Research: 1990-2019

The purpose of this paper is to summarize the research themes and hotspots of safety signs research between 1990 and 2019 through the scientometric analysis method. In total, 3102 articles of literature from the Web of Science core database were analyzed by the CiteSpace visualization tool and the results were displayed in mapping knowledge domains. The overall characteristics analysis showed that safety sign is an emerging research field in a rapid development stage—81.4% of the literature works were published in the past ten years, and the United States was in the leading position, followed by China and Canada. The keyword co-occurrence analysis indicated that traffic signs and driving safety were the most popular research topics and have been combined with simulation technology in recent years, whereby individual mental health has been added as an influential factor. The journals and category co-citation analysis showed that the safety signs research involved many subjects, mainly engineering, transportation and public safety. The results indicated that the safety signs research is multi-disciplinary, and it will continue to develop in various scientific domains in the future. The conclusions can provide help and reference for potential readers, as well as help with the sustainable development of safety signs research.

The most difficult at-fault fatal crashes to avoid with current active safety technology

OBJECTIVE

We studied which current fatal at-fault crashes would occur despite the most advanced current active safety devices (up to SAE level 2 of driving automation) and how frequent these crashes would be.

METHODS

We carried out a cross-sectional study of passenger cars that were first registered during the period 1st January 2010 to 31st December 2017 in Finland. To gain the true exposure for these cars, we accessed the national Vehicular and Driver Data Register to obtain the mileage information and the registration count for the study period of 2010-17. Similarly, we accessed the registry of Finnish road accident investigation teams and included all fatal at-fault crashes among the cars in our study for the same period. We used a real world reference technology for each active safety system in our analysis and chose one car brand as an example. This gave us exact system specifications and enabled testing the operation of the systems on the road. We performed field tests to gain further information on the precise operation of the safety systems in different operating conditions. Finally, we gathered all information on the studied active safety systems and analyzed the investigated at-fault fatal crashes case-by-case using our four level method.

RESULTS

Cars in our study were the primary party in 113 investigated fatal accidents during the years 2010-17. In 87 of the accidents, the leading cause of death was the injuries due to the crash, and these cases were classified as "unavoidable" (n = 58, 67 %), "avoidable" (n = 26, 30 %) or unsolved (n = 3, 3 %). Of the 58 "unavoidable" crashes 21 (36 %) were suicides, 21 (36%) involved active driver input which would have prevented the safety system operation, 15 (17 %) featured circumstances beyond the safety system performance and in one loss-of-control crash the driver had disabled the relevant safety system (electronic stability control). The registration years of the cars in our study (2010-17) totaled 3,772,864 and during this period, the cars travelled 75.9 billion kilometers. The crash incidence of the "unavoidable" at-fault fatal crashes was 0.76-0.80 fatal crashes per billion kilometers and 15-16 fatal crashes per million registration years.

CONCLUSIONS

We calculated a crash incidence for the "unavoidable" crashes which was 20-27% smaller than the observed crash rate of ESC-fitted passenger cars in our previous study. We concluded that suicides, active driver input until the crash, and challenging weather and road conditions are the most difficult factors for current active safety systems. Our analysis did not account for issues such as system usability or driver acceptance and therefore our results should be regarded as something that is currently theoretically achievable. However, the observed incidence is a good reference for automated driving development and the crash rate of automated cars.

Effects of Different Intervention Methods on Novice Drivers’ Speeding

The objective of this work is to examine the human response to different interventions to determine its direct intervention effect and education effect on the speeding of novice drivers. Several experiments, in which participants received different interventions when they were speeding, were conducted on the simulating driving system. The direct intervention effect of different intervention methods was measured by speed reduction and the education effect of voice intervention was measured by questionnaires. A total of 60 novice drivers and 20 experienced drivers were involved in this study, and the personality, gender and driving experience were considered in the analysis. We found that the steer wheel vibration has a significant influence on the intervention effect, but the lighting does not. The driving experience has more impact on the intervention effect of voice intervention with the Rational Style. While gender mainly influences the intervention effect of Emotional Style. The education effect of voice intervention designed with Emotional Style performs better than Rational Style. The personality from Eysenck Personality Questionnaire (EPQ) does not have a significant influence on the intervention effect. At last, a new driving style variable which can be calculated automatically from driving data was designed and the novel intervention strategy was proposed according to the research results. Our research provides a novel intervention strategy for drivers’ speeding behavior and gives an underlying insight into urban traffic safety, which is beneficial to ensure the safety, efficiency, and sustainability of the transportation system. It also serves as a reference for traffic safety research management agencies, the government, and the produced smart vehicles companies, providing guidance not limited to speeding intervention and aimed at improving other unsafe driving behavior.

Practice makes better - Learning effects of driving with a multi-stage collision warning

Advanced driver assistance systems like (forward) collision warnings can increase traffic safety. As safety-critical situations (especially in urban traffic) can be diverse, integrated adaptive systems (such as multi-stage warnings) need to be developed and examined in a variety of use cases over time instead of the more common approach of testing only one-time effectiveness in the most relevant use case. Thus, this driving simulator experiment investigated a multi-stage collision warning in partially repetitive trials (T) of various safety-critical situations (scenarios confronting drivers with hazards in form of pedestrians, obstacles or preceding vehicles). Its output adapted according to the drivers' behavior in two warning stages (W1 - warning for moderate deceleration in less critical situations; W2 - urgent warning for strong, fast braking in more critical situations). To analyze how much drivers benefit from the assistance when allowed practice with it, the driving behavior and subjective ratings of 24 participants were measured over four trials. They comprised a baseline without assistance (T1) and three further trials with assistance - a learning phase repeating the scenarios from T1 twice (T2 + T3) and a concluding transfer drive with new scenarios (T4). As expected, the situation criticality in the urgent warning (W2) scenarios was rated higher than in the warning (W1) scenarios. While the brake reaction time differed more between the W1 scenarios, the applied brake force differed more between the W2 scenarios. However, the scenario factor often interacted with the trial factor. Since in later warning stages reaction time reductions become finite, the reaction strength gains importance. Overall the drivers benefited from the assistance. Both warning stages led to faster brake reactions (of similar strength) in all three assisted trials compared to the baseline, which additionally improved successively over time (T1-T3, T1 vs. T4, T2 vs. T4). Moreover, the drivers applied the gained knowledge from the learning phase to various new situations (transfer: faster brake reactions in T4 compared to T1 or T2). The well accepted and positively rated (helpful and understandable) two-stage collision warning can thus be recommended as it facilitates accident mitigation by earlier decelerations. Practice with advanced driver assistance systems (even in driving simulators) should be endorsed to maximize their benefits for traffic safety and accident prevention.