Influence of Wider Longitudinal Road Markings on Vehicle Speeds in Two-Lane Rural Highways

Does air pollution affect traffic safety? Evidence from cities in China

Does air pollution influence traffic safety? To answer this question, this paper empirically investigates the nonlinear impact of air pollution on traffic mortality by employing a balanced panel dataset for 102 Chinese cities covering 2014-2018. Also, this paper then discusses the nonlinear mediation effects of air pollution on traffic safety to test the influential mechanism between these two variables. The following three conclusions are obtained. First, air pollution has a nonlinear impact on traffic safety: a 1 μg/m3 increase in the average annual concentration of PM2.5 could lead to a 0.0439 increase in traffic fatalities per one million people, but the negative impact of PM2.5 on air pollution will be reduced in the long run. Second, heterogeneity analysis indicates that the impact of air pollution on traffic safety in northern cities of China, cities with lower levels of economic development is more serious than that in other cities. Third, air pollution may affect traffic safety by reducing transport efficiency and affecting drivers' physiological status and cognitive abilities.

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.

Investigating the Daytime Visibility Requirements of Pavement Marking Considering the Influence of CCT and Illuminance of Natural Light

Pavement marking in daylight with poor quality cannot provide a reference for drivers to specify their own position relative to nearby vehicles. Luminance and Correlated color temperature (CCT) of sunlight is of importance for daytime visibility of in-service pavement markings, which lacks detailed consideration. This paper aims to explore the daytime visibility requirements of in-service pavement markings considering the influence of natural light characteristics. Based on analyzing the mechanism and impact factors of daytime visibility of pavement markings, a subjective scale of pavement markings state in the drivers’ field of view was proposed and a short and bold line was recommended as the standard state. Thirty-six tested drivers were randomly selected to detect white and yellow markings of both 15 cm and 20 cm width under 2000 to 23,000 lx and 5500 to 8500 K for outdoor natural light environment. The luminance contrast of the pavement marking to the surrounding road surface ranged from 0 to 10. The result indicated that the natural light with 2000 to 3000 lx and 7500 to 8500 K is the most unfavorable light environment for drivers to recognize pavement markings during daytime. The detection distance is becoming longer with the increase of luminance contrast. The detection distance does not increase with the increase of luminance contrast when the luminance contrast of white markings is greater than 4 and that of yellow markings is greater than 3. The model was established expressing the relationship between luminance contrast and Q_d contrast. The preview time 3.65 s was selected to calculate the minimum requirements of Q_d at speeds of 60, 80, 100 km/h, respectively, for different types of markings. The results can provide scientific evidence for quality evaluation and maintenance management of pavement markings in service for daytime visibility.

Study on the Impact of Traffic Accidents in Key Areas of Rural Roads

In recent years, the proportion of rural road fatalities in the country is gradually increasing, among which the traffic safety problems are particularly prominent in the town-rural area and the town-center area. Based on the relevant accident data in Hunan Province in recent years, the chi-square test was conducted to obtain the correlation degree between each risk factor and accident severity based on gender stratification. Then, a binary logistic model was established to obtain the significant factors that affect the accident severity in the town-rural area and the town-center area, respectively. Based on the significant factors, relevant safety improvement measures were proposed for the key areas. The results show that severe accidents were significantly related to single-vehicle factors, motorcycle factors, and intersections factors in the town-rural area. In the town-center area, severe accidents were significantly related to elderly age, single-vehicle factors, and nighttime factors. The study obtained the risk factors in key areas, which can provide a reference for the improvement of traffic safety in key areas of rural roads, to ensure the safety and sustainability of rural traffic.

Ranking Road Sections Based on MCDM Model: New Improved Fuzzy SWARA (IMF SWARA)

Traffic management is a significantly difficult and demanding task. It is necessary to know the main parameters of road networks in order to adequately meet traffic management requirements. Through this paper, an integrated fuzzy model for ranking road sections based on four inputs and four outputs was developed. The goal was to determine the safety degree of the observed road sections by the methodology developed. The greatest contribution of the paper is reflected in the development of the improved fuzzy step-wise weight assessment ratio analysis (IMF SWARA) method and integration with the fuzzy measurement alternatives and ranking according to the compromise solution (fuzzy MARCOS) method. First, the data envelopment analysis (DEA) model was applied, showing that three road sections have a high traffic risk. After that, IMF SWARA was applied to determine the values of the weight coefficients of the criteria, and the fuzzy MARCOS method was used for the final ranking of the sections. The obtained results were verified through a three-phase sensitivity analysis with an emphasis on forming 40 new scenarios in which input values were simulated. The stability of the model was proven in all phases of sensitivity analysis.