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Tailored countermeasures that may significantly improve road traffic safety can be proposed and implemented if the relationship between various associated factors and aggressive driving is well understood. However, this relationship remains unknown, as driving behavior is complex, and the interrelationships among variables are not easy to identify. Considering this situation, this paper constructed a model based on a structural equation model (SEM) and factor analysis (FA), which is a multivariate statistical analysis technique used to analyze structural relationships. The model is applied in a case study using data from the Shanghai Naturalistic Driving Study. In the case study, 16 variables were grouped into five latent factors in the SEM, and the model fits the data well. Compared with other variables, the results show that age had the most significant positive impact on aggressive driving behavior (older drivers exhibited high aggressive driving frequency). Adverse weather negatively impacted driver behavior (lower speed and high longitude acceleration), which in turn negatively affected aggressive driving behavior. In addition, the results show that driver factors (such as age and sex) were the main factors influencing vehicle use (such as hard acceleration), and the environment was the main factor determining risky scenarios, where safety-critical situations increase. This paper provides a reference for defining and determining aggressive driving and a model for exploring the relationship between driving safety factors and aggressive driving, which can be used in real-world applications for improving driving safety with applications in advanced driver-assistance (ADAS) and traffic enforcement safety control systems.

Although vehicle, bicycle, and pedestrian flows are considerably lower in general during the nighttime, a higher number of accidents than expected occur during this time. A highly influential factor is the lack of visibility at nighttime. Several studies have shown the negative effects of the lack of visibility on bicycle and pedestrian accident frequency and injury severity at nighttime. However, these studies considered only the presence or absence of light, which was not sufficient to evaluate road user safety. Only a limited number of studies in this field actually measured nighttime road illuminance levels. This study relied on the collection of road illuminance data on road links during the nighttime in downtown Montreal, Quebec, Canada, through the use of an illuminance sensor mounted on a scooter. Pedestrian and bicycle accident frequencies were analyzed separately with the use of the negative binomial model. Unexpectedly, the result showed that an increase in road lighting was associated with more bicycle and pedestrian accidents, which might have been explained by the decision to add or increase the amount of lighting at locations in which accidents occurred. The presence of a bike facility and arterial roads was associated with a decrease in bicycle accident occurrence. For pedestrians, the number of lanes per link and the pedestrian flow were associated with an increase in nighttime accident frequency, while the vehicle flow was associated with a decreasing number of accidents. The study called for more investigation of the precise relationship between safety and the amount of light provided by road lighting.

The review of recent research efforts in road lighting and safety shows an inconsistency in the methods to measure ambient road lighting. The importance of road lighting on improving night time safety is evident; however, the lack of actual illuminance field measurements results in a gap in the knowledge of whether installed road lighting provides adequate illuminance for clear visibility at night time or not. Previous studies considered the presence or absence of road lighting on safety without measuring actual illuminance of the road. This paper aims to propose a uniform methodology to perform a simple road lighting audit and safety screening that can be applied to any area.To perform the proposed audit, a photometric sensor, data logger and information on the city lighting standards, geo-referenced accident data and traffic flow data are needed. To collect field measurements, the data collectors cross each side of the intersection with the sensors starting and ending 15 m before and after the intersection. Information on land use, road type, location of light poles, location of trees and weather conditions is collected. Based on the collected data, average illuminance of each approach of an intersection as well as the average illuminance of the whole intersection and the uniformity ratio of the intersection was calculated. These results are then used to compare to the city lighting standard to check if the installed road lighting is performing adequately. If illuminance values of an intersection were below the standard specifications, the intersections were ranked as sub-standard.This methodology was then applied to a case study in Montréal, Québec, where 59 % of the selected sample intersections had sub-standard lighting. Statistical analysis showed that the number of night time accidents was correlated to traffic flow (or the ratio of minor to major flows) and the fact that the intersection average intersection illuminance did not meet the standard. The factors contributing to average illuminance were clear sky, hour of the night of the data collection, and presence of light poles and commercial lights. Nabavi Niaki, Saunier, Miranda-Moreno, Amador, Bruneau 2 INTRODUCTIONThe purpose of road lighting is to provide visibility, security and safety for all road users during the night (1-5). Once light poles are installed according to specification standards, they are assumed to provide adequate illumination to road users at night. However, lighting equipment might not be well maintained and there are hardly any follow-ups on the performance of lighting and its effect on safety. With time and resources constraints, there are usually few field measurements done by municipalities to check if lighting meets the specification standards. This is problematic because with the rapid change in traffic flow and land use, the amount of illumination needed for visibility also changes (6, 7). Road safety issues at night where lighting standards are not checked can be related to illumination deficiencies (1-4). Theref...

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