The impact of green bond issuance on carbon emission intensity and path analysis.

Reducing carbon emission intensity is crucial for achieving sustainable development. Carbon emission intensity is expressively affected by the issuance of green bonds. Thus, it is imperative to assess the influence of green bond issuance on carbon emissions and examine their correlation. Such research holds great potential to expedite the overhaul and modernization of businesses and to construct a circular economy system. This paper uses the spatial Durbin model to draw empirical conclusions by using data from 26 provinces in China between 2016 and 2021. Firstly, under different spatial matrices, it has been analyzed that an increase of 1% in the issuance of green bonds leads to a reduction of 0.306% or 0.331% in carbon emission intensity. It shows that green bonds have the potential to substantially reduce carbon intensity. Additionally, the intensity of emissions in the current period is driven by the intensity of emissions in the previous period. Secondly, the analysis of mediated transmission suggests that green bonds can ultimately reduce carbon emission intensity by changing the energy consumption structure or improving the efficiency of green technology innovation. Thirdly, the analysis of heterogeneity shows that the inhibitory effect of green bond issuance on carbon emissions is stronger in less economically developed regions than in economically developed regions. There is a significant inhibitory effect of green bond issuance in neighboring provinces on local carbon emission intensity. This effect is present only in provinces in less economically developed regions and not in economically developed regions.

The effects of various auditory takeover requests: A simulated driving study considering the modality of non-driving-related tasks.

With the era of automated driving approaching, designing an effective auditory takeover request (TOR) is critical to ensure automated driving safety. The present study investigated the effects of speech-based (speech and spearcon) and non-speech-based (earcon and auditory icon) TORs on takeover performance and subjective preferences. The potential impact of the non-driving-related task (NDRT) modality on auditory TORs was considered. Thirty-two participants were recruited in the present study and assigned to two groups, with one group performing the visual N-back task and another performing the auditory N-back task during automated driving. They were required to complete four simulated driving blocks corresponding to four auditory TOR types. The earcon TOR was found to be the most suitable for alerting drivers to return to the control loop because of its advantageous takeover time, lane change time, and minimum time to collision. Although participants preferred the speech TOR, it led to relatively poor takeover performance. In addition, the auditory NDRT was found to have a detrimental impact on auditory TORs. When drivers were engaged in the auditory NDRT, the takeover time and lane change time advantages of earcon TORs no longer existed. These findings highlight the importance of considering the influence of auditory NDRTs when designing an auditory takeover interface. The present study also has some practical implications for researchers and designers when designing an auditory takeover system in automated vehicles.

The effect of font boldness, noise disturbance and time pressure on human error in the context of cloud change operation.

This study investigated the number of operator errors, task completion time, and workload of subjects at different levels by imposing conditions such as focused text boldness, noise disturbance, and time pressure to simulate a realistic cloud change business process in the laboratory. Results of the study showed that the text bolding of important content reduced the number of errors, whereas noise interference increased the number of errors. Text boldness only reduced the number of corrected errors, and noise interference only increased the number of uncorrected errors. Moreover, bolding was found to have different effects on the number of errors under different noise levels and time pressure levels, with text boldness significantly reducing the number of total errors only in quiet or low time pressure states. Time pressure had no effect on cloud change task error counts, but high time pressure resulted in higher subjective workload.

Operator error is one of the main causes of service failure, and reducing operator error in cloud change operations is of practical importance. In this study, we found focused text boldness could reduce operator errors, while noise could increase the number of errors. High time pressure would lead to a high workload.

Enhanced Electrochemical Performance of a Ti-Cr-Doped LiMn1.5Ni0.5O4 Cathode Material for Lithium-Ion Batteries.

Ti, Cr dual-element-doped LiMn1.5Ni0.5O4 (LNMO) cathode materials (LTNMCO) were synthesized by a simple high-temperature solid-phase method. The obtained LTNMCO shows the standard structure of the Fd3®m space group, and the Ti and Cr doped ions may replace the Ni and Mn sites in LNMO, respectively. The effect of Ti-Cr doping and single-element doping on the structure of LNMO was studied by X-ray diffraction (XRD), Fourier transform infrared (FT-IR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) characteristics. The LTNMCO exhibited excellent electrochemical properties with a specific capacity of 135.1 mAh·g-1 for the first discharge cycle and a capacity retention rate of 88.47% at 1C after 300 cycles. The LTNMCO also has high rate performance with a discharge capacity of 125.4 mAh·g-1 at a 10C rate, 93.55% of that at 0.1C. In addition, the CIV and EIS results show that the LTNMCO showed the lowest charge transfer resistance and the highest diffusion coefficient of lithium ions. The enhanced electrochemical properties may be due to a more stable structure and an optimized Mn3+ content in LTNMCO through TiCr doping.

Inattentional blindness to unexpected hazard in augmented reality head-up display assisted driving: The impact of the relative position between stimulus and augmented graph.

OBJECTIVE: An augmented reality head-up display (AR-HUD) is a promising technology in assisted driving. It provides additional information in the driving environment. However, considering the registration problem related to the limitations of interactive technology, we suspect that an AR-HUD may not be able to recognize unpredictable stimuli in a timely manner, inducing inattentional blindness to these non-augmented stimuli. Actually, non-augmented stimuli may accidentally have a brief superimposition to AR graphics. This condition may also influence the rate of inattentional blindness accordingly. Thus, this study examined the problem of inattentional blindness in AR-HUD systems that may result from the immaturity of AR technology. METHOD: We investigated the impact of AR graphic position (peripheral AOI v.s. central AOI) and the relative position of the AR graphic on unpredictable stimuli (on-HUD hazard v.s. off-HUD hazard) on the occurrence of inattentional blindness. Thirty Participants watched an AR-augmented driving video that included four augmented conditions. Participants were instructed to respond to four critical events (speeding, running of red lights, unexpected pedestrians or motorcycles). The rate of inattentional blindness and response time were recorded. We only analyzed data on unexpected pedestrian and motorcycle incidents. RESULTS: The relative position of the AR graphic on unpredictable stimuli and AR graphic positions significantly affected the rate of inattentional blindness and response time. Drivers had a higher rate of inattentional blindness to the unpredictable stimulus briefly superimposed on the AR graphic (i.e., on-HUD hazard) in the peripheral visual field (i.e., peripheral AOI). Also, drivers exhibited a higher rate of inattentional blindness to the unpredictable stimuli outside the AR graphic (i.e., off-HUD hazard) in the central visual field (i.e., central AOI). CONCLUSION: The study is expected to be beneficial for furthering the design of an AR-HUD-assisted system to reduce inattentional blindness in driving. Our results found that in the peripheral visual field, unpredictable stimuli accidentally superimposed on the AR graphic (i.e., on-HUD hazard) lead to a higher probability of ignoring the accidental events and seemed to require a longer response time for drivers. This study illustrated that inattentional blindness to non-augmented stimuli is also influenced by the AR graphic position when AR technology fails to augment them in a timely manner. An important recommendation emerging from this work is to consider the design of AR graphics according to the AR graphic positions and stimulus types to reduce the occurrence of inattentional blindness.

When to use vibrotactile displays? A meta-analysis for the role of vibrotactile displays in human-computer interaction.

OBJECTIVE: This study aims to investigate the benefits of unimodal tactile displays relative to other modal displays and the performance gains of adding redundant tactile displays by integrating empirical studies. BACKGROUND: Tactile displays have attracted increasing attention in recent years due to their unique advantages. Synthesizing experimental data is necessary to analyze the performance benefits of tactile displays for participants and better help practitioners in utilizing them. METHOD: Five meta-analyses were conducted. Two meta-analyses compared the participants' performance between tactile and other modal displays (visual vs. tactile and auditory vs. tactile). Three meta-analyses examined the performance gains of adding redundant tactile displays based on other modal displays (visual vs. visual + tactile, auditory vs. auditory + tactile, and visual + auditory vs. visual + auditory + tactile). The related moderator variables, the types of presented information and concurrent tasks, were analyzed. RESULTS: Little evidence shows the performance difference between tactile and auditory displays. Tactile displays are more beneficial than visual displays for presenting alert information or in the situation with a visual concurrent task. The performance gains of adding redundant tactile displays to other modal displays also depend on the specific type of presented information and the concurrent task. CONCLUSION: When using tactile displays to convey information, interface designers should consider the specific type of presented information and the concurrent tasks. APPLICATIONS: The present study's findings can provide some implications for designers to utilize tactile displays when they construct and implement information displays.

Which accuracy levels of positioning technologies do drivers really need in connected vehicle settings for safety?

Based on Global Navigation Satellite Systems (GNSS) and Internet of Vehicles (IoV), collision warning systems can provide drivers specific warning information such as the position of hazardous vehicles. However, positioning technologies vary in accuracy. Highly accurate positioning technologies are theoretically favorable for driving safety but are relatively difficult to use widely due to the high cost. While many researchers compared accuracies of different positioning technologies or explored methods to improve accuracy, few directly investigated the effect of different positioning accuracies for hazardous vehicles on driving safety. The present study conducted a laboratory experiment to explore the effect of four positioning accuracies of hazardous vehicles (i.e., highest: 1.5 m, high: 5 m, medium: 8.5 m, and low: 20 m, each value represented the radius of a circle and the estimated positions of hazardous vehicle were within this circle) and different traffic densities (high: one car per 150 m and low: one car per 1500 m) on driver behaviors. Thirty participants were distributed into high and low traffic density groups. Each participant received auditory warning information, which provided positions of hazardous vehicles relative to the ego vehicle concerning four accuracy levels. Driving safety (i.e., number of collisions and min TTC), driving performance (i.e., brake onset reaction time, steer onset reaction time, and mean deceleration), and subjective workload for warnings with different positioning accuracies of hazardous vehicles were recorded and analyzed. Results suggested the following: 1) Under low traffic density, four positioning accuracies showed no significant differences on driving safety and performance as well as subjective workload. 2) Under high traffic density, the medium positioning accuracy (8.5 m) exerted no significant differences on driving safety and performance compared with the highest positioning accuracy (1.5 m), which had the fastest brake onset reaction time, the least number of collisions, and the largest mean deceleration. Moreover, when traffic density was high, warnings with the highest (1.5 m), high (5 m), and medium (8.5 m) positioning accuracies generated a significantly lower workload than the warning with low (20 m) positioning accuracy. In conclusion, low positioning accuracy (20 m), which was a general accuracy of A-GNSS (no added cost) or GNSS (SPP) (relatively low cost) in dense urban area, was feasible for providing warnings under low traffic density. Medium positioning accuracy (8.5 m), which was the accuracy of A-GNSS (no added cost) in open-sky area, was acceptable for supporting warning systems under high traffic density. These findings have implications for promoting the application of positioning technologies to realize warnings in the near future.

Optimal Time Intervals in Two-Stage Takeover Warning Systems With Insight Into the Drivers' Neuroticism Personality.

Conditional automated driving [level 3, Society of Automotive Engineers (SAE)] requires drivers to take over the vehicle when an automated system's failure occurs or is about to leave its operational design domain. Two-stage warning systems, which warn drivers in two steps, can be a promising method to guide drivers in preparing for the takeover. However, the proper time intervals of two-stage warning systems that allow drivers with different personalities to prepare for the takeover remain unclear. This study explored the optimal time intervals of two-stage warning systems with insights into the drivers' neuroticism personality. A total of 32 drivers were distributed into two groups according to their self-ratings in neuroticism (high vs. low). Each driver experienced takeover under the two-stage warning systems with four time intervals (i.e., 3, 5, 7, and 9 s). The takeover performance (i.e., hands-on-steering-wheel time, takeover time, and maximum resulting acceleration) and subjective opinions (i.e., appropriateness and usefulness) for time intervals and situation awareness (SA) were recorded. The results showed that drivers in the 5-s time interval had the best takeover preparation (fast hands-on steering wheel responses and sufficient SA). Furthermore, both the 5- and 7-s time intervals resulted in more rapid takeover reactions and were rated more appropriate and useful than the 3- and 9-s time intervals. In terms of personality, drivers with high neuroticism tended to take over immediately after receiving takeover messages, at the cost of SA deficiency. In contrast, drivers with low neuroticism responded safely by judging whether they gained enough SA. We concluded that the 5-s time interval was optimal for drivers in two-stage takeover warning systems. When considering personality, drivers with low neuroticism had no strict requirements for time intervals. However, the extended time intervals were favorable for drivers with high neuroticism in developing SA. The present findings have reference implications for designers and engineers to set the time intervals of two-stage warning systems according to the neuroticism personality of drivers.

Promote or inhibit: An inverted U-shaped effect of workload on driver takeover performance.

OBJECTIVE: In conditional automated driving (SAE Level 3), drivers are required to take over their vehicles when the automated systems fail. Non-driving related tasks (NDRTs) can positively or negatively affect takeover safety, but the underlying reasons for this inconsistency remain unclear. This study aims to investigate how various workload levels generated by NDRTs may influence the takeover performance of drivers and the lead time they require. METHOD: Fifty drivers were randomly distributed into five groups, which corresponded to five workload levels (1-4 levels generated by Tetris game; control level generated by monitoring). Each driver completed vehicle takeover tasks upon receiving takeover requests with various lead times (3, 5, 7, 9, and 11 s) while engaging in NDRTs. The drivers' takeover performance and subjective opinions were recorded. RESULTS: Drivers in the moderate workload condition (i.e., level 3) had significantly shorter takeover times and better takeover quality than those in the lower (i.e., level 1 and level 2) or higher (i.e., level 4) workload conditions. They also subjectively required less lead time in the moderate condition. Moreover, the drivers rated 7 s as the most appropriate lead time despite the improvement in their overall takeover performances with increased lead time. CONCLUSIONS: This study found an inverted U-shaped relationship between the drivers' workload generated by NDRTs and takeover performance. The moderate workload level (rather than the lower or higher workload level) led to a faster and better takeover performance, and it seemed to require minimal lead time for drivers. These findings help understand the relationship of drivers' workload during the automation and takeover performance in conditional automated driving. An important recommendation emerging from this work is to investigate what should be the most efficient method to detect the drivers' workload state real-time and give feedback to them when it comes to overload or underload during the automated driving.

Effect of highway directional signs on driver mental workload and behavior using eye movement and brain wave.

The rapid development of expressways has led to an increasing number of place names that must be displayed on road guide signs. As a result, multi-board guide signs have been increasingly set up on expressways. The main aim of this study was to analyze the effect of the directional road sign displayed on multi and single-board signs on driver mental workload and behavior. 32 participants including 16 females (mean age = 24.7 years, standard deviation = 1.9 years) participated in the experiment and completed 3 driving simulation scenes. The setting of each scene-sign board was different: 1 board, 2 boards, and 3 boards. The driver needed to reach the designated destination according to the guidance of the road signs. Eye tracker was used to measure the fixation, saccade and electroencephalogram (EEG) was used to measure the alpha (8-13 hz) band absolute power in different signage scenarios. There are two major findings of the study. First, when the number of place names is less than or equal to 7, the multi-board sign generates more mental workload than the single-board sign does. The alpha band power of the driver's frontal area under the multiple boards is lower and affects driving performance (the deceleration is greater). Second, when the number of place names is more than 7, there is no significant difference in the effect on mental workload whether multi or single-board sign is used. However, compared to the single-board sign, drivers in the case of multi-board sign are likely to reduce the fixation duration and increase the number of saccades. The results suggest that it is not necessary to use multi-board signs when the number of place names is less than 7. These findings provide more safety considerations for the setting of multi-board guide signs in the future.

Structural Equation Modeling of Drivers' Situation Awareness Considering Road and Driver Factors.

Driver's situation awareness (SA) is one of the key elements that affect driving decision-making and driving behavior. SA is influenced by many factors, and previous studies have focused only on individual factors. This study presents a comprehensive study to explore the path relationships and influence mechanism between SA and all influential factors, including road characteristics, driver characteristics and states, distracting elements, and cognitive ability. A structural equation model that relates SA to its influential factors is developed. A total of 324 valid questionnaires were collected to analyze and identify the relationships between the factors. The results show that the preceding influential factors have significant effects on SA, which is consistent with previous research. Based on path coefficients, positive effects were: cognitive abilities (0.500), driver state (0.360), age (0.277), driving experience (0.198), and gender (0.156). Negative effects were: distracting elements (-0.253) and road characteristics (-0.213). The results of this comprehensive study provide a valuable reference for the development of driver training programs and driving regulations.

Impact of Learning Methods on Spatial Knowledge Acquisition.

Research on the acquisition of spatial knowledge not only enriches our understanding of the theory of spatial knowledge representation but also creates practical value for the application of spatial knowledge. The aim of this study is to understand the impact of different learning methods on the acquisition of spatial knowledge, including the role of 2D maps, the difference between physical interaction and virtual interaction, and whether passive learning can replace active learning in virtual environments. One experiment was conducted, in which landmark knowledge and configurational knowledge were measured. Results indicate that 2D maps play a supporting role in acquiring both landmark knowledge and configurational knowledge. In addition, physical learning was associated with better spatial knowledge representation compared with virtual learning. An analysis of observational data in the third comparison found no significant difference between passive learning and active learning using virtual street view maps. However, with high-quality learning materials, passive learning can contribute to the acquisition of spatial knowledge more efficiently than active learning.

Type 2 diabetes can undermine driving performance of middle-aged male drivers through its deterioration of perceptual and cognitive functions.

It has been widely agreed that it is risky for patients with diabetes to drive during hypoglycemia. However, driving during non-hypoglycemia may also bring certain safety hazards for some patients with diabetes. Based on previous studies on diabetes-related to early aging effect, as well as gender differences in health belief and driving behavior, we have hypothesized that middle-aged male drivers with type 2 diabetes, compared with the control healthy ones, may experience a decline in driving performance without awareness. And the decline is caused by impaired perceptual and cognitive driving-related functions. To verify these hypotheses, we recruited 56 non-professional male drivers aged between 40 and 60 (27 patients with type 2 diabetes and 29 healthy controls) to perform a simulated car-following task and finish behavioral tests of proprioception, visual search, and working memory abilities during non-hypoglycemia. They also reported their hypoglycemia experience and perceived driving skills. We found that the patients had equal confidence in their driving skills but worse driving performance as shown in larger centerline deviation (t = 2.83, p = .006), longer brake reaction time (t = 3.77, p = .001) and shorter minimum time-to-collision (t = -3.27, p = .002). Such between-group differences in driving performance could be fully mediated by proprioception, visual search ability, and working memory capacity but not by hypoglycemia experience. Regarding the effect sizes of the mediation, the visual search ability played the most important role, and then followed the working memory and the proprioception. This initial study provides original and first-hand evidence demonstrating that the middle-aged male drivers with type 2 diabetes have deteriorated driving performance, but they are unaware of it. We will also discuss the possible measures to identify people of the highest risk and improve their safety awareness by using the findings of the current study.

Looking for an optimal pedal layout to improve the driving performance of patients with diabetic peripheral neuropathy.

Diabetes can undermine people's ability to drive safely, but most previous studies have focused on its deterioration of the central nervous system. This study sought to investigate how diabetic peripheral neuropathy (DPN), a common complication of diabetes characterized by reduced sensitivity of the limbs, can influence people's braking behavior and other safety-related measures of driving. In addition, it also tested how such a deteriorating effect can be reduced by using certain pedal layout designs. In total, 29 healthy drivers and 31 drivers of type 2 diabetes matched in demographic variables were invited to participate in this study. The participants with type 2 diabetes (they are from here on out referred to as "patients")were then split into two subgroups based on the severity of DPN using the median of the Semmes-Weinstein monofilaments Examination (SWME) scores. All three groups of participants finished a series of vehicle-pedestrian conflict tasks in a driving simulator using nine different types of pedal layouts. These layouts varied in the lateral distance between the accelerator and the brake (45 mm, 60 mm, and 75 mm) and the width of brake pedals (50 mm, 70 mm, 90 mm). The results showed that patients with serious DPN had longer brake reaction times (BRT) and shorter minimum distance-to-collision (DTC) as compared to the other two groups. However, the effects of such a disadvantage varied across different pedal layouts. When the accelerator-brake distance was 45 mm, patients with serious DPN showed no compromised driving performance as compared to other two groups. In conclusion, we found the DPN could undermine driving performance of participants with type 2 diabetes, and a closer accelerator-brake lateral distance (45 mm) may be an optimal choice for them to counteract such a negative influence.

The effects of warning characteristics on driver behavior in connected vehicles systems with missed warnings.

With emerging new technologies, the vehicles in the future with connected vehicle systems (CVS) will be equipped with the ability to communicate with each other and aim to provide drivers with information in a timely and reliable way to improve driver safety. This study was designed to investigate the interaction effects of warning lead time (2.5 s vs. 4.5 s), warning reliability (73% vs. 89%), and speech warning style (command vs. notification) on driver performance and subjective evaluation of warnings in CVS. A driving simulator study with thirty-two participants was designed to simulate a connected vehicle environment with missed warnings due to failures in the communication network of the CVS. With regard to the response types, the results showed that notification warnings led to a lower probability of braking response and a higher probability of braking and steering response compared with command warnings. The results showed command warnings led to a smaller collision rate compared to notification warnings with the warning lead time of 2.5 s, whereas no significant difference of collision rates was found between two warning styles when the warning lead time is 4.5 s. These results suggest notification warnings should be selected when the warning lead time is longer and the warning systems are highly reliable, which resulted in higher safety benefits and higher subjective rating. Command warnings could be selected when the warning lead time is shorter since they led to more safety benefits, but such selection has to be made with caution since command warnings may limit drivers' response type and were perceived as less helpful than notification warnings.

The Five Key Questions of Human Performance Modeling.

Via building computational (typically mathematical and computer simulation) models, human performance modeling (HPM) quantifies, predicts, and maximizes human performance, human-machine system productivity and safety. This paper describes and summarizes the five key questions of human performance modeling: 1) Why we build models of human performance; 2) What the expectations of a good human performance model are; 3) What the procedures and requirements in building and verifying a human performance model are; 4) How we integrate a human performance model with system design; and 5) What the possible future directions of human performance modeling research are. Recent and classic HPM findings are addressed in the five questions to provide new thinking in HPM's motivations, expectations, procedures, system integration and future directions.

Display of required crossing speed improves pedestrian judgment of crossing possibility at clearance phase.

At crosswalks with countdown timers, pedestrians arriving at the clearance phase tend to start crossing when the remaining time is too short. It is unclear whether this phenomenon is due to errors in judging the possibility to finish crossing before signal lights turning red. This study evaluated and compared pedestrians' accuracy in judgment of crossing possibility based on two cues: the amount of remaining time, and the minimum required speed to finish crossing within clearance phase (road width / remaining time). The results showed that pedestrians overestimated crossing possibility when they made judgments based on remaining time, especially when the road was narrow. By contrast, the display of required speed resulted in higher overall accuracy and lower false alarm rate, due to higher sensitivity to different crossing possibilities and more conservative set of response criterion. This advantage is consistent across different road widths. These findings suggest that pedestrians' risky decisions based on the countdown timers are partly induced by overestimation of crossing possibilities. The advantages of required-speed display over traditional countdown timers indicate a strong possibility to improve pedestrian judgments by information design.

Cross or wait? Pedestrian decision making during clearance phase at signalized intersections.

Pedestrians arriving at clearance phase (Flashing Don't Walk) face different levels of risk depending on behavioral choice afterwards. However, few studies have focused on the choices pedestrians make during this phase. This field study analyzed pedestrian choices after arrival, evaluated safety of the choices, and built a model to identify the predictors of pedestrian choices. It was found that pedestrians arriving during clearance phase made dynamic decisions based on the changing contexts. Specifically, the majority made the decision to "cross" as opposed to "wait" (85.2% vs. 14.8% respectively), although only the latter choice is legal. Seventy-nine percent of the pedestrians did not finish crossing the intersection before the traffic light turned red, and they walked 41% of the road width during a red light. For those waited, roughly half of them waited until green or crossed at an intersecting crosswalk, while others finally started on red light. Nevertheless, the waited pedestrians still faced lower risk than those crossed prematurely in terms of running behaviors, and conflicts with vehicles. Pedestrians are more likely to cross immediately after arrival when they are younger, are not engaged in secondary tasks, arrived at a position farther from approaching vehicles at the near side of the road, or arrived at a time when there are more pedestrians crossing the road. Although fewer pedestrians choose to cross when the required speed is higher (due to a wider road or less remaining time), the required speed they choose to cross at is far higher than their actual speed. These findings are essential for realistic pedestrian simulations and targeted safety countermeasures. They also imply the need for changes to certain traffic regulations and signal design to facilitate safe decision making at clearance phase.

An investigation of perceived vehicle speed from a driver's perspective.

PURPOSE: Speed estimation of drivers' own vehicles and other vehicles on the road is an important task for drivers and is also crucial to the roadway safety. The objective of the study was to examine the effects of multiple factors such as image scale, speed, road type, driving experience, and gender on the speed perception of drivers' own vehicles. METHODS: Thirty participants consisted of 17 males and 13 females, including 13 without driving experience. All participants estimated the driving speed of 192 5-second video clips, which were selected from naturalistic driving recordings. The recorded driving speeds were evenly distributed across the entire range from 5mph to 65mph. Half of the selected video clips were recorded on wide roads and another half were recorded on comparatively narrow roads. Video clips were played on a large screen, with each clip shown in one of 4 image scales (100%, 75%, 50%, and 38% of the actual field of view in the real world). RESULTS: Speed estimates were most accurate for the smallest image size (38% of the actual field of view). As the image size increased, the driving speed was increasingly underestimated. Participants with driving experience accurately estimated the driving speed on both wide and narrow roads whereas those without driving experience had greater underestimates on wider roads. Speeds were most accurately estimated within the range 25-35mph, but the speeds slower than the range tend to be overestimated and the speeds faster than the range are more likely to be underestimated. While males and females showed the same pattern across speed groups, females have greater estimation errors at the highest and lowest speed groups. Participants without driving experience showed increasing underestimation of speed as driving speed increased whereas participants with driving experience primarily underestimated the highest speeds. CONCLUSIONS: The present study shows the effect of multidimensional influential factors on perceived vehicle speed from drivers' perspective. The results also have implications for driving simulation scenario design, driving simulator setup, and the assessment of speed control in simulated and naturalistic environments.

Drinking and driving behavior at stop signs and red lights.

Alcohol is one of the principal risk factors for motor vehicle crashes. One factor that contributes to vehicle crashes is noncompliance with stop signs and red lights. The present experiment investigated the effects of alcohol and drinking patterns on driving behavior at stop signs and red lights. 28 participants participated in drinking and simulated driving sessions during which they received a moderate dose of alcohol (0.08% BAC) or a placebo. Simulated driving tasks measured participants' driving performance at stop signs and red lights in response to each dose. Results suggested that alcohol impaired the driver control of speed and direction and prolonged their simple and complex reaction time, which were exhibited by impaired speed and lateral control, longer reaction time when the lights turned yellow, and lower deceleration towards stop signs and red lights. Visual degradation may also occur under alcohol intake. It was also suggested that alcohol impaired non-binge drinkers more severely. To be specific, higher acceleration was observed in impaired non-binge drinkers.