Warning Conditions Research Articles

A novel regional traffic control strategy for mixed traffic system with the construction of congestion warning communities

Large-scale congestion can lead to traffic paralysis, which severely hampers the flow of vehicles and disrupts the normal functioning of urban traffic. Traffic optimization strategies can effectively improve the performance of road networks, but often ignore the impact of regional traffic conditions and equity. This paper presents a novel traffic strategy to solve regional traffic congestion in large cities, particularly focusing on mixed traffic scenarios of connected and non-connected vehicles. The proposed method involves monitoring the traffic condition of the congestion warning community and adjusting the internal access flow within each region. The problem is formulated as a Stackelberg game, with traffic policymakers and road users as the key players. The upper layer aims to control traffic access by issuing a community warning index, with the objective of minimizing congestion warning conditions within the community. This information is then disseminated to connected vehicles which utilize it to generate personalized route guidance, while non-connected vehicles remain unaffected. The lower-level objective is to allocate vehicles in the transportation network in a user-optimal manner. To solve the bi-level programming model, the paper introduces a variable neighborhood search approach based on graph theory. The Frank-Wolfe algorithm is used to solve the lower-level model, with a penalty function introduced to transform the constrained traffic assignment problem (TAP) into an unconstrained TAP. The proposed method is applied using the data of Beijing urban road network and a sensitivity analysis is conducted to examine the impacts of critical parameters, such as regional partitioning and mixed traffic proportion. The results show that the method exhibits improved optimization performance across different parameter settings, effectively utilizing idle links and contributing to a reduction in the occurrence of traffic warning regions.

Effects of driving style on takeover performance during automated driving: Under the influence of warning system factors

Driving style has been proposed to be a critical factor in automated driving. However, the role of driving style in the process of taking over during automated driving needs further investigation. The main purpose of this study was to investigate the influence of driving style on takeover performance under the influence of warning system factors. In addition, this study also explored whether the impact of driving style on reaction time varies over time and the role of driving style on a comprehensive takeover quality indicator. Two driving simulation experiments with different takeover request (TOR) designs were conducted. In experiment 1, content warning information was provided in the TOR with different warning stage designs; in experiment 2, countdown warning information was provided in the TOR with different warning stage designs. Sixty-four participants (32 for experiment 1 and 32 for experiment 2) were classified into two groups based on their driving style (i.e., aggressive, or defensive) using the Chinese version of the Multidimensional Driving Style Inventory (the brief MDSI-C). The results suggested that drivers’ driving style had significant effects on takeover performance, but the effects were influenced by warning system designs. Specifically, defensive participants performed better takeover performance, i.e., shorter reaction time and cautious vehicle control behaviors, than aggressive participants in most warning conditions. The content and countdown warning information and warning stage design affected the roles of driving style on takeover performance: 1) compared to the one-stage warning design, the two-stage warning design significantly shortened the reaction time of the participants with different driving styles, 2) compared to the countdown warning information design, the design of content warning information can shorten the reaction time of aggressive participants and lengthen the reaction time of defensive participants in the two-stage warning conditions, and 3) compared to the content warning information design, countdown warning information can improve the safe takeover performance of defensive participants. This study provides a better understanding of the role of driving style on takeover performance, and driving style should be considered when designing warning systems for autonomous vehicles.

Development of Alarm Grit Ratio for Drought Forecasting and Its Application to the 2021–2023 Drought

The frequency and severity of droughts are increasing due to climate change and environmental disturbances brought on due to human development, making drought warning an essential tool in mitigating their effects. Drought warning can, however, be easily overlooked if people disregard its significance or repress water managers with the result of the drought warning. Therefore, in the current study, we developed an Alarm Grit Ratio (AGR) for drought warning to assess how active these have been thus far, and was estimated the ratio for the current drought in Korea from 2021 to 2023. The Korea Meteorological Administration issued three drought warnings, which were classified as agricultural, meteorological, and residential and industrial droughts. We proposed two indices to indicate how an institution issues a drought warning as a forecast for the actual drought warning that follows. These indices were AGR and Transitional Alarm Grit Ratio (TAGR). AGR measures how frequently an institute issues a drought warning forecast based on the number of actual warning conditions. Analysis of the current drought (2021–2023) indicates the issuance of warnings, while TAGR indicates the ratio of the drought warning issuance at each drought. The AGR and TAGR for the agricultural and meteorological droughts indicate underissuance of drought warnings, whereas warnings for residential and industrial droughts were appropriately issued due to the drought impact on residences and industries. Overall, we concludes that AGR and TAGR can be useful indicators of how actively an institution issues drought warnings. An institution in charge of drought warning can track these measurements and control the frequency of drought warnings by including AGR and TAGR data.

Evaluation of warning strategies to reduce faking during military recruitment

ABSTRACT The applicant faking literature suggests that faking warnings – brief messages that dissuade applicants from faking – can reduce faking on personality tests by up to 50%. However, the efficacy of warnings may be limited by their atheoretical construction. Further, these threatening messages can cause applicants to feel negatively about the personality test, potentially reducing their validity during the selection process. We tried to improve the efficacy of faking warnings, while minimizing negative applicant reactions, by leveraging theory from the accountability and morality literatures. We tested three new faking warnings that emphasized short-term accountability, long-term accountability, and morality. To do so, we tested 466 military trainees undergoing basic training at the Canadian Armed Forces and asked them to engage in a selection simulation. We assigned groups of trainees to the different faking warning conditions and guided them through the simulation. We found that a faking warning emphasizing short-term accountability, which threatened to detect fakers by contacting references and using “internal integrity checks,” reduced applicant faking. None of the other messages had any effect when compared to a no-warning control group.

Using a V2V- and V2I-based collision warning system to improve vehicle interaction at unsignalized intersections

Introduction: Unsignalized intersections are critical components of the road network where traffic collisions occur frequently. Method: This study aims to design a Vehicle-to-Vehicle (V2V)- and Vehicle-to-Infrastructure (V2I)-based unsignalized intersection collision warning system (UICWS) to improve driver performance and enhance driver safety at unsignalized intersections. A multi-user driving simulator experiment was conducted with 48 participants divided into 24 pairs. The dynamic interaction of each participant pair as they approached the intersection from straight-crossing directions was examined under different warning conditions (i.e., with vs without UICWS) and intersection field of view (IFOV) conditions (i.e., standard vs improved IFOV). Results and conclusions: The experimental results showed that the UICWS could effectively help drivers make appropriate operation decisions and reduce the number of right-angle collisions and near-collisions at unsignalized intersections. In the condition without UICWS, improved IFOV could prompt drivers to make crossing decisions in advance and adjust speed smoothly. Moreover, drivers’ crossing maneuvers changed with the relative distance between the subject and conflict vehicles and the intersection. The risks of collisions and near-collisions increased significantly when the two vehicles were at a similar distance to the intersection before they initiated any actions. Practical Applications: The findings show that the proposed UICWS can effectively reduce collisions or near-collisions at unsignalized intersections in a connected vehicle environment. On this basis, some active intervention strategies, such as specific speed guidance depending on the dynamics of the conflict vehicle, can be developed to ensure vehicles passing through unsignalised intersections safely.

Applicant faking warnings: Are they really effective?

Evidence suggests that a large percentage of job applicants fake their responses on personality tests. This faking has the potential to undermine the value and validity of personality tests in the selection context. Faking warnings are messages that try to dissuade applicants from faking by warning them about potential consequences and have been shown to be effective in reducing faking in some studies. We developed new faking warnings that leverage accountability and morality theory to reduce applicant faking. Accordingly, we examined the efficacy of our faking warnings in reducing applicant faking in one applied sample. We examined 534 mTurk participants who believed they were being considered for a real employment opportunity for a remote customer service position. Compared to participants not interested in the job, participants who were interested in the job had significantly more favorable personality scores. After informing participants that the position was fictitious and asking them to fill out the same personality measure as honestly as possible, the same previously interested participants received significantly less favorable personality scores. However, there were no differences in faking across the different faking warning conditions, suggesting the faking warnings were ineffective.

Testing front-of-package warnings to discourage red meat consumption: a randomized experiment with US meat consumers

BackgroundReducing red meat is a strategy to improve public health and mitigate climate change in the United States and other high-income countries. Policies requiring warnings on the front of red meat packages are a promising intervention to shift consumers towards healthier and more sustainable food choices. We aimed to explore participants’ reactions to health and environmental warning messages about red meat.MethodsBetween June and July 2020, we recruited a national convenience sample of US red meat consumers (n = 1,235; mean age 44 years) for an online survey. Participants were randomly assigned to one of four label conditions: no-label control, health warning, environment warning, and combined health and environment warning (both warnings shown side-by-side). Participants viewed three types of burritos (red meat [steak], chicken, and vegetarian) and selected their preferred item (primary outcome), the item they perceived to be most damaging to health, and the item they perceived to be most damaging to the environment (secondary outcomes). Participants then viewed their assigned warning on a series of other red meat products (no-label control participants were randomly re-assigned to one of the warning conditions) and rated the warnings on perceived message effectiveness, believability, negative emotions, perceived risk, attention, and learning something new. Finally, participants reported their intentions to reduce red meat consumption.ResultsThere were no significant differences in selection of the steak burrito between label conditions or in selection of the item most damaging to the environment. Those exposed to the health warning were more likely to select the steak burrito as most damaging to health compared to those exposed to other label conditions (health 73 %, combined 64 %, environment 60 %, no-label control 63 %, p < 0.05). The combined and health warnings elicited higher perceived message effectiveness ratings than the environment warning (combined mean 2.91, health 2.84, environment 2.61, p < 0.05).ConclusionsWarnings did not have a significant effect on item preference in the choice experiment. However, combined and health warnings performed better than the environment warning across a variety of warning label reaction measures. More research will be needed to understand whether warnings elicit behavioral change in real-world environments.Trial registrationAnalyses and hypotheses were preregistered on https://aspredicted.org/ph7mb.pdf on 23 June 2020.

The Impact of Varying Warning Color on E-Cigarette Advertisements: Results From an Online Experiment Among Young Adults.

Advertisement warnings are often overlooked, which reduces the opportunity for risk communication. We used Prolific to survey 1131 young adults (18-35) who currently used e-cigarettes or tobacco products. We randomized participants to one of four warning conditions: black text on white background (BW), white on black (WB), black on yellow (BY), and yellow on black (YB). We examined associations between condition and attention, recall, ad appeal, perceived message effectiveness (PME), and intentions to use e-cigarettes using chi-square and analysis of variance (ANOVA) where appropriate. We conducted logistic regressions by condition for attention and recall controlling for demographics and tobacco use. The warning was selected as the most attention-capturing area of the advertisement more often by those exposed to yellow warnings than white (59.9% vs. 46.8%), even after controlling for demographics and tobacco use (p < .05). Recall was greater among those exposed to yellow warnings than white (44.2% vs. 37.3%), which held in controlled models. There were no significant differences between yellow and white warnings for ad appeals, PME, or intentions to use. In subanalyses, WB warnings generated higher PME (10.1 vs. 9.5) and lower intentions to use e-cigarettes (3.0 vs. 3.3) than black on white (BW) (each p < .05). Yellow warning color increases attention and recall of the warning, but this increase in attention did not translate to differences in downstream effects. Among currently mandated warning variations, the white text on black background warning appears more effective than the BW. Future research should examine whether differences translate to behavior change. We tested color variations of the FDA-mandated nicotine text warning on e-cigarette advertisements. Yellow variations (yellow text on black background and BY) better-captured attention and increased warning recall compared to the mandated black and white warnings. Among the FDA-mandated BW and WB warnings, the WB variation appears more effective, generating higher perceived message effectiveness and lower intentions to use e-cigarettes. Given the difficulty in implementing pictorial warnings in the United States, color might represent an alternative to improve warning effectiveness. Findings may also be applicable to those designing tobacco-related health communications.

Efficacy of Canadian health warning statements on caffeinated energy drinks: an experimental study among young Canadians.

The current study examined the efficacy of health warnings on caffeinated energy drinks (CEDs). Participants aged 12-24 years (n = 2040) completed an online survey where they were asked to recall any existing warning statements on CED products and were randomized to one of 29 experimental warning conditions. Regression models were fitted to examine differences between conditions in product appeal, perceived safety and message recall. Overall, fewer than 30% of participants were able to accurately describe an existing CED product warning. Experimental findings indicated that exposure to CEDs with warning labels resulted in greater recall. Warnings on the back of CED cans featuring large font, a border, and a 'caution' heading resulted in significantly greater recall (P < 0.05 for all). Front-of-package 'High source of caffeine' labels resulted in greater recall than a quantitative description (P < 0.001); caffeine labels generally elicited lower product appeal (P < 0.001) and perceived safety (P = 0.002) ratings vs. no caffeine labels, and the qualitative caffeine statement elicited lower perceived safety ratings than the quantitative statement (P = 0.02). Existing warning statements in Canada have low levels of awareness. Warnings on CEDs could be enhanced to increase the salience of messages, with greater impact from clear, descriptive, front-of-package 'High source of caffeine' labels.

Distributed computing based on AI algorithms in battery early warning and SoH prediction of the intelligent connected vehicles

The foremost task of the battery management system is to estimate the end-of-life batteries, their capacity and internal resistance, which are commonly used to evaluate the State of Health (SoH) for the battery cells and packs. The SoH for batteries plays a vital role in intelligent connected vehicles. To evaluate the warning conditions of battery life units, this paper suggests the artificial intelligence-assisted particle swarm optimization for the SoH prediction of the intelligent connected vehicles. The key elements of this method include the battery ageing cycle, identifying the SoH and battery health forecasting based on the gradual changing processes of the battery. Besides, several accelerated test results are reported for intelligent connected vehicles, using battery mode packages. To validate the concept of the SoH prediction method, a simulation test-bed is developed and test results indicate that the idea is projected with a higher prediction rate.

Designing an Effective Front-of-Package Warning Label for Food and Drinks High in Added Sugar, Sodium, or Saturated Fat in Colombia: An Online Experiment

Policies to require warnings on the front of food and drinks high in nutrients of concern (e.g., added sugar, sodium, or saturated fat) are becoming increasingly common as an obesity prevention strategy. Colombia, a country with growing prevalence of obesity, is considering implementing a similar policy. The objective of this study was to assess perceptions and reactions to different warning designs. We conducted a randomized experiment in an online panel of adults age > 18y (n = 1997). Participants were randomized to view one of four labels: a control label (barcode), an octagon warning, a circle warning, and a triangle warning. Participants viewed their randomly assigned label on a series of products and answered questions (continuous outcomes ranged from 1–4). Compared to the control, all warnings led to higher perceived message effectiveness (increase in mean from 1.79 in the control to 2.59–2.65 in the warning conditions, p < 0.001), a higher percentage of participants who correctly identified products high in nutrients of concern (from 48% in the control condition to 84–89% in the warning conditions, p < 0.001), and reduced intentions to purchases these products (decrease in mean from 2.59 to 1.99–2.01 in the warning conditions, p < 0.001). Relative to the control, warnings performed similarly across education levels, suggesting this policy would be equitable in Colombia. Looking at differences by warning type, the pattern of results suggested that the octagon warnings performed best. After viewing all label types, 49% of participants selected the octagon warning as the one that most discouraged them from consuming products high in nutrients of concern, while 21% and 27% selected the circle and triangle warning. Colombian policymakers should consider the octagon warning as part of a front-of-package labeling policy to help consumers identify and reduce consumption of foods and drinks high in nutrients of concern.

BUBBLE PREDICTION AND COMPARATIVE ANALYSIS OF EMERGING AND MATURE MARKETS

By analyzing the financial bubbles, it can be observed that every bubble burst causes financial turmoil and severe economic recession. The paper utilize the technical analysis indicators for providing warning conditions for predicting the stock market bubbles. The significance of the technical analysis indicators are that they can provide early warning system for financial crisis and can help in avoiding such problems. We applied the early warning technical indicators to the stock market of US, South Korea, Brazil, China, Germany, and Japan for the period of 1995 to 2018. We also made comparison of the bubble warning conditions of emerging markets and the mature markets. The standard bubble warning conditions include K value 90, Bias 10%, and RSI value of 90. Empirical results shows that mature market shows less degree of volatility and lowering the warning baseline can improve the accuracy of bubble predictions. Furthermore, results shows that mature markets bursting time is about 6 months while in emerging market, the time is reduced to only 3 months. These results also indicate that mature market has good antirisk ability compare to the emerging markets.

Review of Lidar-Based Applications for Aviation Weather

Measurements collected by Leosphere Doppler lidars were reviewed to study meteorological processes such as wind shear, wind profiles, gust fronts, and wake vortices over airports. First, the basic concepts of lidar are discussed, then its use for wind environments with respect to high-impact weather events is presented. Issues related to previous definitions of wind-related algorithms and criteria are summarized to validate the use of Doppler lidar for clear-air environmental conditions. Based on International Civil Aviation Organization (ICAO) criteria that use a 500-m height threshold in the vertical for wind warning conditions, this work suggests that use of Doppler lidars can significantly improve the safety of flight environments along landing and takeoff corridors at airports by providing warnings to pilots and ground crew and optimizing air-traffic management. The wind measurements from the lidars are found to be accurate to 0.1 m s−1, and use of Doppler lidars can increase the probability of detection of wind-related severe weather conditions by up to 50% beyond the 500 m of the atmospheric boundary layer (ABL).

Effects of E-Cigarette Health Warnings and Modified Risk Ad Claims on Adolescent E-Cigarette Craving and Susceptibility.

A between-subjects experiment examines the effects of different warning types and modified risk e-cigarette ad claims on adolescent e-cigarette craving and future e-cigarette susceptibility for two different themes. One theme focuses on nicotine and addiction, and the other on the effects of potentially harmful constituents (eg, flavored chemicals and lung disease). The effects of warning type (control, text-only, graphic health warning [GHW] and text) and modified risk e-cigarette ad claims (control, exposure reduction, risk reduction) are tested experimentally with two different arms (themes) for a sample of 1011 adolescents who had tried either e-cigarettes or cigarettes. For addiction, the text-only warning led to significantly less e-cigarette susceptibility than the no warning control condition. As expected, there were no differences between the GHW + text condition and text-only or control conditions for e-cigarette craving. An interaction between warning type and modified risk claims revealed significantly fewer e-cigarette cravings and less susceptibility for the text-only warning and no claim (control) condition than for any other condition. For fatal lung disease, the GHW + text condition led to fewer e-cigarette cravings and less susceptibility than the text-only warning and no warning (control) conditions. Warning type effects can be very different under different themes (eg, addiction, fatal lung disease). In general, our results point to the effectiveness of the text-only warning for addiction and GHW + text for fatal lung disease. Relative exposure and risk modification claims (eg, less nicotine; less addicting) tend to undercut addiction warnings. More than one type of e-cigarette warning may be necessary as e-cigarette research evolves. Our results show different warning type effects (eg, text-only; GHW + text) on e-cigarette craving and future susceptibility for adolescent experimenters depending on the risk theme (eg, addiction; lung disease) and presence of ad claims (eg, exposure and risk reduction). As research emerges on risks associated with e-cigarette use, it is important to first know what at-risk populations (eg, adolescents) believe about such risks. Such research will aid our understanding of what types of warnings might be most effective, especially in the presence of ad claims.

Changes of drivers’ visual performances when approaching a signalized intersection under different collision avoidance warning conditions

Intersections have been recognized as hazard locations with lots of visual information that drivers need to process. Although the collision avoidance systems (CASs) have been proved to effectively reduce the crash rate and much research on the effectiveness of CASs has been conducted with regard to the driving behaviors, drivers’ visual performances under the effects of different collision avoidance warning conditions that were closely related to the effectiveness of CAS have been neglected. In this study, a driving simulator experiment was conducted to evaluate the relationships among drivers’ visual performances, drivers’ different warning conditions (warning timings × warning content) and driver’s gender when they crossed the intersections involved with red-light running (RLR) vehicles. The experimental results showed that warning timings had significant effects on the detection stage and reaction stage. Specifically, drivers could detect the conflicting RLR vehicle most quickly in the warning timings of 4.5 s ahead of a collision. When the warning was released earlier than 5.0 s ahead of a collision, driver tended to take brake action earlier than paying a fixation on a conflicting RLR vehicle. Warning content only had significant effects on drivers’ detection stage. Compared to the non-directional warning, the specific directional information could shorten the time spent in detecting the conflicting RLR vehicle. Besides, directional information could increase drivers’ average blink duration during the process of collision avoidance. Additionally, the results showed that female drivers were more likely to be involved with RLR collisions, and male drivers could detect the conflicting RLR vehicle more quickly than female drivers. Also, it had been found that later warning timings tended to increase female drivers’ blink rate, and non-directional warning tended to increase female drivers’ blink rate. These findings could direct warning condition design to improve the effectiveness of collision avoidance systems.

Use of remote sensing data in comprehending an extremely unusual flooding event over southwest Bangladesh

Flooding is one of the natural disasters that affect the livelihood of the people living in the floodplains, like Bangladesh. Here, we proposed to employ SAR satellite images in assessing the flood extent and crop damage with the hydrometeorological observations in the southwestern region of Bangladesh. We observed that the unusual flood of the year 2000 was the combined effect of the huge amount of rainfall in the local areas as well as oncoming water flows from West Bengal in India. During late monsoon of 2000, we experienced that the amount of rainfall was in several magnitudes (250–450%) than the expected over the region. Bangladesh, one of the largest deltas in the world, in general experienced recurrent flood events from the spill of the three mighty rivers in every year. However, we observed that during 2000 the river situation was slightly above the average year conditions and below the moderate level of flood warning conditions, indicating non-riverine flooding. Therefore, we used the SAR images in delineating the flood extent and its damages for the standing aman crops. We observed that the flood extent mapping was having more than 95% agreements with the ground data and crop damage information was about 75% in agreement with the government estimates. The flood extent and crop damage map was found to be useful during the unprecedented flood in the southwestern region of Bangladesh. The use of near real-time SAR imageries thus would be helpful in developing strategies for flood management and disaster mitigation activities and could be utilized on a regular basis.

Autonomous Driving

Autonomous vehicles will need de-escalation strategies to compensate when reaching system limitations. Car-driver handovers can be considered one possible method to deal with system boundaries. The authors suggest a bimodal (auditory and visual) handover assistant based on user preferences and design principles for automated systems. They conducted a driving simulator study with 30 participants to investigate the take-over performance of drivers. In particular, the authors examined the effect of different warning conditions (take-over request only with 4 and 6 seconds time budget vs. an additional pre-cue, which states why the take-over request will follow) in different hazardous situations. Their results indicated that all warning conditions were feasible in all situations, although the short time budget (4 seconds) was rather challenging and led to a less safe performance. An alert ahead of a take-over request had the positive effect that the participants took over and intervened earlier in relation to the appearance of the take-over request. Overall, the authors' evaluation showed that bimodal warnings composed of textual and iconographic visual displays accompanied by alerting jingles and spoken messages are a promising approach to alert drivers and to ask them to take over.

Perception of the risk of tsunami in a context of high-level risk assessment and management: the case of the fjord Lyngen in Norway

BackgroundNorth Norway, the banks of the fjord Lyngen are highly exposed to a rockslide tsunami hazard. However, the local municipality believes that the coastal community is well-informed about the risk and ready to evacuate, should a warning be issued. Accordingly, the social survey we conducted in this municipality was a matter of exploring three main questions: is the Lyngen population well-informed about the tsunami risk in general and about the potential evacuation time in particular? Is the local population as confident as the local municipality hope? Is there enough information on the tsunami risk for tourists, given their growing number?.ResultsThe survey shows that the local population has a clear perception of the tsunami hazard, but that warning and evacuation conditions are not sufficiently well-known, despite the local and national communication work. Moreover confidence in the municipal authorities seems to be imperfect, although confidence concerning hazard surveillance is higher than confidence in the information provided on risk and management. As often, tourists are less informed on natural hazards or evacuation conditions.ConclusionsThe municipal authorities have to improve the information locally delivered. Authorities must also disseminate information to the tourists, especially on a possible evacuation during their stay, so as not to raise anxiety or trigger a decline in the area's touristic appeal.

Drivers’ eye movements as a function of collision avoidance warning conditions in red light running scenarios

The intersection collision avoidance warning systems (ICAWSs) have substantial potentials in improving driving performance and reducing the number and severity of intersection collisions, through helping drivers timely detect hazardous conflicting vehicles in precrash scenarios. However, the influences of ICAWS on drivers’ visual performance have barely been discussed. This study focuses on exploring the patterns in drivers’ eye movements as a function of ICAWS’s warning conditions in red light running scenarios based on a driving simulation experiment. Two types of speech warning conditions including warning timings (varied form 2.5s to 5.5s) and directional information (with or without) are examined, and the no-warning condition is the baseline. The results revealed that more subjects would be likely to benefit from the ICWAS under the earlier warning timings. The warning condition of 4.5s ahead of a collision had the best effectiveness in terms of visual performances. Under such a warning timing, drivers had shorter fixation duration and higher frequency of searching for the red light running (RLR) vehicles. Compared to the warning condition without directional information, the directional warning information could capture drivers’ attention more efficiently, help driver direct fixations toward the RLR vehicles more quickly and lead to more scanning activities. Compared to female drivers, male drivers had more scanning activities when approaching intersections, detected the RLR vehicles more quickly and were more likely to avoid the RLR collisions. Besides, the experiment results indicated that the female drivers were more inclined to trust the warning information and got more benefits from the RLR-ICAWS in terms of the crash risk reduction rate than male drivers. Finally, the conclusions lead the way toward warning condition design recommendations for improving the effectiveness of the RLR-ICAWSs.

An experimental study of the effects of electronic cigarette warnings on young adult nonsmokers' perceptions and behavioral intentions.

BackgroundElectronic cigarette (“e-cigarette”) manufacturers use warning labels on their advertising that vary widely in content and the U.S. Food and Drug Administration has issued a warning label requirement for e-cigarettes. There is limited data on the effects of these warnings on e-cigarette perceptions and other potential predictors of future tobacco use behavior in populations of interest to inform future regulatory requirements. This study examined the effects of e-cigarette warnings on perceptions of e-cigarettes and cigarettes and other cognitive precursors to tobacco use among young adult non-smokers.MethodsNon-smoking young adults ages 18 to 30 years (n = 436) were recruited through an internet-based crowdsourcing platform for an online experiment. Participants completed pre-exposure measures of demographics, tobacco use, and other relevant constructs and were randomized to view 1 of 9 e-cigarette stimuli in a 3 (Ad/Warning condition: Ad Only, Ad with Warning, Warning Only) x 3 (E-cigarette brand: Blu, MarkTen, Vuse) design. After viewing e-cigarette stimuli, participants reported perceptions of e-cigarettes and behavioral intentions to use e-cigarettes. Participants in the Ad Only and Ad with Warning conditions also completed a heat-mapping task assessing aspects of the ads that captured their attention. Then, participants were randomized to view cigarette ads from 1 of 3 major cigarette brands and reported perceptions of cigarettes and intentions to smoke cigarettes.ResultsParticipants in the Warning Only condition reported significantly greater perceived harm and addictiveness of e-cigarettes and thoughts about not using e-cigarettes than the Ad Only and Ad with Warning conditions (p’s < .05). The Ad Only and Ad with Warning conditions did not differ on these outcomes. Participants in the Warning Only condition also reported the harms of e-cigarettes were closer to those of cigarettes than the Ad Only condition (p < .05), but neither differed from the Ad with Warning condition. Visual inspection of heat-mapping task data indicate warnings drew few participants’ attention. There were no significant differences across study conditions on perceptions of cigarettes or intentions to smoke.ConclusionsText-based warning messages influenced young non-smokers’ perceptions in a way that may dissuade e-cigarette use, but warnings appearing on advertisements had little impact.Electronic supplementary materialThe online version of this article (doi:10.1186/s12971-016-0083-x) contains supplementary material, which is available to authorized users.