Using road markings as a continuous cue for speed choice

Optimization of colored pavement considering driving behavior and psychological characteristics under dynamic low-visibility conditions related to fog-a driving simulator study

OBJECTIVE

Colored pavement is commonly used to reduce the road traffic risk and promote road traffic safety, but its performance in foggy environments has not been fully assessed. The goal of this research is to explore the effectiveness and optimization of colored pavement in a dynamic low-visibility environment.

METHODS

A driving simulation experiment is conducted. Three road risk sections in which collisions are common, including a long straight section, a sharp bend section, and a long downslope section, are considered, and three forms of colored pavement are used in five different visibility environments. The effectiveness of the colored pavement is explored by collecting and analyzing driving behavior and physiological characteristic data for 30 drivers in the established driving environment, and information is obtained through a subjective colored evaluation questionnaire. Eight evaluation indexes are selected from the perspectives of driving behavior and physiological characteristics, and the gray premium evaluation method is applied to evaluate the effectiveness of different forms of colored pavement considering the influence of visibility. Finally, the optimal colored pavement under various visibility and road alignment conditions is proposed.

RESULTS

The results show that reasonably selecting colored pavement can effectively improve drivers' behaviors and physiological characteristics under foggy conditions. For different road alignments and visibility conditions, different forms of colored pavement should be used to ensure road traffic safety.

CONCLUSIONS

The findings provide a theoretical reference for the optimization of colored pavement in foggy conditions.

Synthesis of a Room-Temperature Curable Acrylic-Urethane Polymer Binder for Road Markings with High Transmittance

Triol acrylic-urethane (t-AU) was synthesized from an addition reaction using trimethylolpropane, hexamethylene diisocyanate, and 2-hydroxyethyl methacrylate. The novel acrylic-urethane polymer was applied to a high-performance binder to prepare a reliable road marking paint. Acrylic-urethane polymer binder formulations were designed to optimize the effect of t-AU on the physical properties. The t-AU content in the formulation affected the adhesion and optical properties. The improvement in the adhesive performance and transparency ability for road markings was attributed to the optimal chemical structure or design of the acrylic-urethane polymer. The synthesis of t-AU was confirmed by Fourier transform infrared spectroscopy, and molecular weight and polydispersity index (PDI; PDI = M_w/M_n) measurements. The tensile and shear strength, hardness, gel fraction, crosslink density, contact angle, and transmittance of the acrylic-urethane polymer binder (AUP) were evaluated by curing at room temperature using a redox initiator system. An optimized AUP by adding 5 wt.% t-AU provides a viable alternative to high-performance binders in road marking paints.

Using multicolor perceptual markings as a rear-end crash risk mitigator: A field investigation

Perceptual markings on roadways are prevailing countermeasures with substantial effectiveness for accident prevention, and a variety of alternatives and derivatives of them are developed to expect to receive an augmented performance of behavioral intervention and crash risk mitigation. However, the proper use of colors as a way of developing effective and innovative perceptual markings is seldomly recognized in-depth from the perspective of visual perceptual mechanism in behind. Given this, in this study, we introduced a kind of multicolor perceptual markings (MCPMs) pattern, i.e., one red marking follows one yellow marking ("1Y + 1R"), two red markings follow two yellow markings ("2Y + 2R"), and three red markings follow three yellow markings ("3Y + 3R"), and evaluated their effects on longitudinal and lateral driving behaviors and real-time safety benefits in car-following via a series of field investigation on a real-world expressway in China. The statistical analyses of the relative differences of speed (θ_v), distance headway (θ_d), time headway (θ_h), lateral movement (θ_p), and crash risk (η_mTTC and η_DRAC, developed from time-to-collision (TTC) and deceleration rate to avoid crash (DRAC)) suggest that, 1) the MCPMs could lead to substantial increases in car-following time and distance headways, and reduction in speed. The maximum time headway increase (0.61 s), speed reduction (1.42 m/s), and distance increase (3.6 m) were found in the condition of "1Y + 1R" compared with the baseline; 2) the MCPMs stabilized the lateral movement of vehicles on the lane at each observation section, and "1Y + 1R" yielded the best performance of lane-keeping; 3) the MCPMs yielded applaudable real-time safety benefits, which were believed to afford the drivers a better chance to accommodate their behaviors to a safer car-following status. The findings of this study suggest the MCPMs could be an especially applaudable form of perceptual markings, and could also be a critical reference of how to use colors in a better way for developing augmented perceptual markings.

A knowledge elicitation approach to traffic accident analysis in open data: comparing periods before and after the Covid-19 outbreak

Extracting knowledge from open data of traffic accidents has been attracting increasing attention to policymakers responsible for road safety. This article presents a knowledge elicitation approach to exploring the determinants of traffic accidents from open government data of an urban area in Taiwan. The collected open dataset contains 34 decisional attributes and one predictive attribute (i.e., type of injury, including head, breast, leg), and 47,974 cases. Prediction models using a classification-oriented mechanism and generated rules that considered datasets from before (B-dataset; 30,116 cases) and after (A-dataset; 17,868 cases) beginning to combat the Covid-19 pandemic in an urban area of Taiwan were compared. The findings showed that prediction accuracy was acceptable but not high, at 70.73% for B-dataset and 74.77% for A-dataset. Determinants in the human and vehicle categories revealed higher classification ranks than those in the temporal and environment categories. Traffic accidents involving motorcycles were 5.13% higher in A-dataset, whereas those involving cars were 4.11% lower. Injury on leg or foot was 3.46% higher in A-dataset, whereas other types of injury were up to 1.00% lower. The average support for rules in the A-dataset rule base and the simplicity of the A-dataset decision tree were higher than those of B-dataset. The research demonstrates the value of open government data in prediction model development and knowledge elicitation to support policymaking in the traffic safety domain.

Driver Behavioral Classification on Curves Based on the Relationship between Speed, Trajectories, and Eye Movements: A Driving Simulator Study

Horizontal curves of rural highways are prone to a considerably high number of fatalities because an erroneous perception can lead to unsafe driving. This generally occurs when a driver fails to notice the highway geometry or changes in the driving environment, particularly curved segments. This study aimed to understand the geometric characteristics of curved segments, such as radius and approach tangents, on the driving performance towards minimizing vehicle crashes. Speed profiles and lateral position, the most common indicators of successful negotiation in curves, and eye movements were recorded during an experiment conducted in a fixed-base driving simulator equipped with an eye-tracking system with a road infrastructure (a three-lane highway) and its surroundings. A driving simulator can faithfully reproduce any situation and enable sustainable research because it is a high-tech and cost-effective tool allowing repeatability in a laboratory. The experiment was conducted with 28 drivers who covered approximately 500 test kilometers with 90 horizontal curves comprising nine different combinations of radii and approach tangent lengths. The drivers’ behavior on each curve was classified as ideal, normal, intermediate, cutting, or correcting according to their trajectories and speed changes for analyses of the performance parameters and their correlation conducted by factorial ANOVA and Pearson chi-square tests. The cross-tabulation results indicated that the safest behavior significantly increased when the curve radius increased, and the performance measures of curve radii were greatly affected. However, the driving behavior was not affected by the approach tangent length. The results revealed segments of the road that require a driver’s closer attention for essential vehicle control, critical information, and vehicle control in different parts of the task.

Quantifying effects of reverse linear perspective as a visual cue on vehicle and platoon crash risk variations in car-following using path analysis

Road markings are prevalent in practice as perceptual countermeasures to crashes, and a great deal of them have been used for speed reduction. However, there is rare seen any equivalent measures especially for distance control. More importantly, the visual perceptual mechanism of road markings on driving behaviors and crash risk is still blur. Given this, in the present study, we comprehensively quantified the effects of reverse linear perspective (RLP) from its origin as a visual cue, produced by a kind of transverse line markings on road, and explored the effects on car-following behaviors and crash risk variations by path analyses imbedded in a structural equations model, which was approximated with naturalistic driving and traffic flow data. In the model, multiple sources of observed factors in visual perception, driver behaviors, and traffic flow characteristics, and exogenous unobserved factors of distance risk perception, speed risk perception, and platoon risk status were comprehensively structured to explain the vehicle crash risk variation and the platoon crash risk variation. The results indicate that (1) distance risk perception, speed risk perception, and platoon risk status were well explanatory and predictive to vehicle crash risk variation and platoon crash risk variation; (2) the effects of reverse linear perspective as a visual cue on driving behaviors and crash risk variations in car-following were adequately quantified by its geometrical characteristics concerning distance perception; (3) the visual cue of reverse linear perspective in addition with initial distance, stopping sight distance, and the type of leading vehicles explained 33 % of the variance in distance risk perception; the temporal frequency, initial speed, and the type of following vehicles explained 23 % of the variance in speed risk perception; distance risk perception, speed risk perception, and platoon risk status combinedly explained 25 % and 22 % of the total variance in vehicle crash risk variation and platoon crash risk variation, respectively; (4) vehicle crash risk variation and platoon crash risk variation were equivalently specified by those observed explanatory factors. The findings of this study suggest the usefulness and importance of understanding the contribution of psychological factors on crash risk, and emphasize that the road markings can be an effective and readily practical countermeasure in easing traffic safety issues.

Long-term effectiveness of reverse linear perspective markings on crash mitigation in car-following: Evidence from naturalistic observations

Perceptual markings on roads are verified with short-term effectiveness for accident prevention. However, the long-term performance of them is seldomly investigated, which unintentionally impedes its more widely recognition and application as a low-cost and readily achievable countermeasure. Also, the previous perceptual markings were only tested for speed reduction effect, little is known concerning their influence on headway adjustment. Given this, in this study, we investigated the short-, medium-, and long-term performance of the reverse linear perspective markings (RLPMs) on driving behaviors and safety benefits in car-following. The RLPMs were a form of markings pattern that can produce reverse linear perspective visual information on the lane and lead to distance underestimation. The RLPMs were permanently installed on a straight and a curve segment of a freeway in China, and the naturalistic vehicle flow data one day, four months, one year, two years, and three years after the installation of the RLPMs were collected. The statistical analyses of general and sectional relative differences of speed, distance headway and time headway suggest that 1) the speed reduced and distance and time headways increased in short-, medium-, and long-term as compared with the baseline on both the straight and curve segments; 2) the long-term performance of RLPMs significantly weakened as compared with the short-term performance, yet sustained to 0.50 m/s in speed reduction, 3.77 m in distance headway increase, and 0.097 s in time headway increase on average within the observations in one year and above on the straight segment; similar sustained performance of 0.47 m/s in speed reduction, 2.60 m in distance headway increase, and 0.072 s in time headway increase were observed on the curve segment; 3) the RLPMs were tested to have positive and relatively endured effectiveness on mitigating crash risk in car-following measured by two surrogate safety indicators based on time-to-crash (TTC) and deceleration rate to avoid a crash (DRAC). The findings of this study suggest the RLPMs could be an especially applaudable form of perceptual markings as they are relatively effective in the long-term and are multifunctional in intervening speed, distance, headway, and crash risk. This study also emphasizes the challenge of more field tests and observations on the long-term performance of the perceptual markings, and the thorough considerations of the visual perception mechanism behind the markings to achieve an alternative solution to the long-term issue.

Do detection-based warning strategies improve vehicle yielding behavior at uncontrolled midblock crosswalks?

Pedestrians being the most vulnerable road users account for a large proportion of injuries and fatalities from road traffic crashes. Pedestrians are involved in around one-third of the whole fatalities coming from the road traffic crashes in the state of Qatar. In areas with uncontrolled midblock crosswalks, it is very crucial to improve drivers' alertness and yielding behavior. The objective of this driving simulator study is to investigate the impact of pedestrian detection strategies and pavement markings on driving behavior at high-speed uncontrolled crosswalks. To this end, an untreated condition (i.e. Control) was compared with three treatment conditions. The three treated conditions included two detection strategies, i.e., advance variable message sign (VMS) and LED lights, and road markings with pedestrian encircled. Each condition was tested with a yield/stop controlled marked crosswalk for two situations, i.e. with vs. without a pedestrian present. The experiment was conducted using the driving simulator at Qatar University. In total, 67 volunteers possessing a valid Qatari driving license participated in the study. Different analyses were conducted on vehicle-pedestrian interactions, driving speed, variations in acceleration/deceleration and lateral position. The results showed that both the LED and VMS conditions were helpful in increasing yielding rates up to 98.4 % and reducing the vehicle-pedestrian conflicts significantly. Furthermore, both treatments were effective in motivating drivers to reduce vehicle speed in advance. Considering the findings of this study, we recommend LED and VMS conditions as potentially effective solutions to improve safety at yield/stop controlled crosswalks.

Low-cost road marking measures for increasing safety in horizontal curves: A driving simulator study

Statistics show that horizontal curves, especially those of radii less than 200 m, present an increased road accident risk mainly due to inappropriate speed and failure to maintain proper lateral position. This simulator study aims to analyse how two low-cost road marking measures (red median and horizontal warning signs), alone or combined with a vertical warning sign, affect driver behaviour (driving speed, lateral movement, acceleration/deceleration) before and throughout dangerous horizontal curves on a two-way rural road. With GIS-supported mapping of traffic accidents, we identified the most dangerous curves on the main rural road in Croatia and replicated them on the driving simulator. Based on the driving runs of 43 participants, the study concluded that both measures, used either alone or combined with a vertical warning sign, significantly reduced the speed compared to the control condition (vertical warning sign alone). Additionally, the use of a red median prompted the lateral movement of the vehicle closer to the edge line. The paper also defines the potential use of the measures for dealing with specific types of curve-related accidents.

Optical pavement treatments and their impact on speed and lateral position at transition zones: A driving simulator study

Transition zones are a road section where posted speed drops from higher to lower limits. Due to the sudden changes in posted speed limits and road environment, drivers usually do not adapt to the posted speed limits and underestimate their traveling speed. Previous studies have highlighted that crash rates are usually higher in these sections. This study aims at improving the safety at transition zones by introducing perceptual measures that are tested using a driving simulator. The proposed measures are speed limit pavement markings with a gradual increase of brightness and/or size that were placed at transition zones in simulation scenarios replicating the real-world environment of the Doha Expressway in Qatar. These innovative measures aim to produce the impression of increased speed that could stimulate drivers to better adapt speed limits. The driving behavior of 81 drivers possessing a valid Qatari driving license was recorded with a driving simulator interfaced with STISIM Drive® 3. Results showed that pavement markings combining size and brightness manipulations were the most effective treatment, keeping drivers' traveling speed significantly below the traveling speed recorded in the untreated control condition. In this regard, the maximum mean speed reductions of 5.3 km/h and 4.6 km/h were observed for this treatment at the first transition (120 to 100 km/h) and second transition (100 to 80 km/h) zones, respectively. Regarding the variations in drivers' lateral position, the results showed that the proposed pavement markings did not negatively influence drivers' lateral control on the road as the maximum observed standard deviation of lateral position was around 0.065 m. This study shows that the proposed pavement markings are recommended for improving the speed adaptation of drivers in the transition zones.

Effect of Road Markings and Traffic Signs Presence on Young Driver Stress Level, Eye Movement and Behaviour in Night-Time Conditions: A Driving Simulator Study

The study investigates how the presence of traffic signalling elements (road markings and traffic signs) affects the behaviour of young drivers in night-time conditions. Statistics show that young drivers (≤30 years old) are often involved in road accidents, especially those that occur in night-time conditions. Among other factors, this is due to lack of experience, overestimation of their ability or the desire to prove themselves. A driving simulator scenario was developed for the purpose of the research and 32 young drivers took two runs using it: (a) one containing no road markings and traffic signs and (b) one containing road markings and traffic signs. In addition to the driving simulator, eye tracking glasses were used to track eye movement and an electrocardiograph was used to monitor the heart rate and to determine the level of stress during the runs. The results show statistically significant differences (dependent samples t-test) between the two runs concerning driving speed, lateral position of the vehicle, and visual scanning of the environment. The results prove that road markings and traffic signs provide the drivers with timely and relevant information related to the upcoming situation, thus enabling them to adjust their driving accordingly. The results are valuable to road authorities and provide an explicit confirmation of the importance of traffic signalling for the behaviour of young drivers in night-time conditions, and thus for the overall traffic safety.

Innovative countermeasures for red light running prevention at signalized intersections: A driving simulator study

The change interval, which includes the yellow and all-red times, plays a crucial role in the safety and operation of signalized intersections. During this interval, drivers not only need to decide to stop or go but also have to interact with drivers both in front and behind, trying to avoid conflicting decisions. Red light running and inconsistent stopping behavior may increase the risk for angular and rear-end crashes. This study aims to investigate the effect of different innovative countermeasures on red light running prevention and safe stopping behavior at signalized intersections. Five different conditions were tested inviting sixty-seven volunteers with a valid driving license. The conditions include a default traffic signal setting (control condition), flashing green signal setting (F-green), red LED ground lights integrated with a traffic signal (R-LED), yellow interval countdown variable message sign (C-VMS), and red light running detection camera warning gantry (RW-gantry). Drivers in each condition were exposed to two different situations based on the distance from the stop line. In the first situation, drivers were located in the indecision zone while in the second situation they were located in the likely stopping zone. A series of logistic regression analyses and linear mixed models were conducted to investigate the overall safety effects of the different countermeasures. The probability of red light running (RLR) was significantly reduced for R-LED in both analyses (i.e. in the total sample, and in the sample of crossed vehicles). Moreover, a clearly inconsistent stopping behavior was observed for the flashing green condition. Furthermore, a unit increase in speed (kph) at the onset of yellow interval significantly increases the probability of RLR by 5.3 %. The study showed that R-LED was the most effective solution for improving red light running prevention and encouraging a consistent stopping behavior at the intersection. In conclusion, the R-LED and the RW-gantry treatments are recommended as effective tools to improve safety at signalized intersections.

Evaluating the effectiveness of perceptual treatments on sharp curves: a driving simulator study

Objective: Speed has been identified as a key risk factor in road crashes, influencing the occurrence of a road crash and its severity. Excessive speeding is particularly dangerous on highway curves, and under critical traffic and environmental conditions. Various measures have been identified to be effective in managing and controlling vehicle speed. Among these, low-cost perceptual measures have been considered to be effective tools, as they generally increase the risks perceived by drivers, or alter speed perception, and consequently lead the drivers to reduce their speeds. The overall aim of this study is 1) to investigate the effectiveness of a set of perceptual treatments in reducing the driver's speed along a sharp curve of an existing rural road that is characterized by high crash rates, and 2) to identify the most effective measure(s) to implement in the field to counteract the problem of speeding.Methods: A driving simulator study was developed and four speed-reducing measures (white and red peripheral transverse bars (PTB), optical speed bars (OSB) and chevrons) were tested on a sample of forty-two drivers. The driving speeds recorded using the treatments tests were compared to a baseline condition (treatments were not applied). Subjective measures were also collected; these included the driver's evaluation of the desired speed, risk perception, road legibility, and markings comprehension, as based on screenshot pictures that represented the simulated configurations of the treatments.Results: The outcomes demonstrated an overall effectiveness of the perceptual treatments. Particularly, red PTB were associated with a speed-reduction of up to 12 km/h along the curve under study. An analysis of the questionnaires revealed that drivers did not fully comprehend the relevant message of PTB. Despite that, the drivers did unconsciously reduce their speeds; this confirms the effectiveness of such perceptual treatments based on the optical illusion that entices drivers to reduce their speeds.Conclusions: The findings demonstrated the effectiveness of the perceptual treatments, especially red PTB, in enticing drivers to reduce their speeds whilst approaching the sharp curve under study or driving through the curve.

Impact of perceptual countermeasures on driving behavior at curves using driving simulator

OBJECTIVE

The probability of crash occurrence on horizontal curves is 1.5 to 4 times higher than that on tangent sections. A majority of these crashes are associated with human errors. Therefore, human behavior in curves needs to be corrected.

METHODOLOGY

In this study, 2 different road marking treatments, optical circles and herringbone patterns, were used to influence driver behavior while entering a curve on a 2-lane rural road section. A driving simulator was used to perform the experiment. The simulated road sections are replicas of 2 real road sections in Flanders.

RESULTS

Both treatments were found to reduce speed before entering the curve. However, speed reduction was more gradual when optical circles were used. A herringbone pattern had more influence on lateral position than optical circles by forcing drivers to maintain a safe distance from opposing traffic in the adjacent lane.

CONCLUSION

The study concluded that among other low-cost speed reduction methods, optical circles are effective tools to reduce speed and increase drivers' attention. Moreover, a herringbone pattern can be used to reduce crashes on curves, mainly for head-on crashes where the main problem is inappropriate lateral position.

Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy

Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level. Using multichannel whole-head high density functional near-infrared spectroscopy (fNIRS) brain activation measurements, we aimed to predict driving difficulty level, both separate for each WML level and with a combined model. Participants drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. In half of the time, the course led through a construction site with reduced lane width, increasing visuospatial attentional demands. Concurrently, participants performed a modified version of the n-back task with five different WML levels (from 0-back up to 4-back), forcing them to continuously update, memorize, and recall the sequence of the previous 'n' speed signs and adjust their speed accordingly. Using multivariate logistic ridge regression, we were able to correctly predict driving difficulty in 75.0% of the signal samples (1.955 Hz sampling rate) across 15 participants in an out-of-sample cross-validation of classifiers trained on fNIRS data separately for each WML level. There was a significant effect of the WML level on the driving difficulty prediction accuracies [range 62.2-87.1%; χ2(4) = 19.9, p < 0.001, Kruskal-Wallis H test] with highest prediction rates at intermediate WML levels. On the contrary, training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46.8%). Activation changes in the bilateral dorsal frontal (putative BA46), bilateral inferior parietal (putative BA39), and left superior parietal (putative BA7) areas were most predictive to increased driving difficulty. These discriminative patterns diminished at higher WML levels indicating that visuospatial attentional demands and WML involve interacting underlying brain processes. The changing pattern of driving difficulty related brain areas across WML levels could indicate potential changes in the multitasking strategy with level of WML demand, in line with the multiple resource theory.