George Yannis

A review of the effect of traffic and weather characteristics on road safety

Taking into consideration the increasing availability of real-time traffic data and stimulated by the importance of proactive safety management, this paper attempts to provide a review of the effect of traffic and weather characteristics on road safety, identify the gaps and discuss the needs for further research. Despite the existence of generally mixed evidence on the effect of traffic parameters, a few patterns can be observed. For instance, traffic flow seems to have a non-linear relationship with accident rates, even though some studies suggest linear relationship with accidents. On the other hand, increased speed limits have found to have a straightforward positive relationship with accident occurrence. Regarding weather effects, the effect of precipitation is quite consistent and leads generally to increased accident frequency but does not seem to have a consistent effect on severity. The impact of other weather parameters on safety, such as visibility, wind speed and temperature is not found straightforward so far. The increasing use of real-time data not only makes easier to identify the safety impact of traffic and weather characteristics, but most importantly makes possible the identification of their combined effect. The more systematic use of these real-time data may address several of the research gaps identified in this research.

Effects of Urban Delivery Restrictions on Traffic Movements

Abstract This article investigates the effects of the adoption of restrictions in vehicle movements associated with urban delivery operations on traffic. A wide range of data (including land use, delivery requirements per type of service, traffic mix, traffic flows and capacities) are used within suitable models to assess the traffic and environmental effects in Athens, Greece. The findings suggest that restricting delivery to specific types of businesses during rush hours can lead to positive traffic and environmental effects. The effectiveness of urban delivery restriction policies depends on the careful selection of the time periods and types of businesses for which they will apply.

When may road fatalities start to decrease

INTRODUCTION The comparative analysis of macroscopic trends in road safety has been a popular research topic. The objective of this research is to propose a simple and, at the same time, reliable multiple regime model framework for international road safety comparisons, allowing for the identification of slope changes of personal risk curves and respective breakpoints. METHOD The trends of road traffic fatalities in several EU countries have been examined through the temporal evolution of elementary socioeconomic indicators, namely motorized vehicle fleet and population, at the country level. RESULTS Piece-wise linear regression models have been fitted, using a methodology that allows the simultaneous estimation of all slopes and breakpoints. The number and location of breakpoints, as well as the slope of the connecting trends, vary among countries, thus indicating different road safety evolution patterns. IMPACT ON INDUSTRY Macroscopic analysis of road accident trends may be proved beneficial for the identification of best examples and the implementation of appropriate programmes and measures, which will lead to important benefits for the society and the economy through the reduction of road fatalities and injuries. Best performing countries and the related programmes and measures adopted may concern several safety improvements at the processes of the road, the vehicle and the insurance industries. CONCLUSIONS Lessons from the analysis of the past road safety patterns of developed countries provide some insight into the underlying process that relates motorization levels with personal risk and can prove to be beneficial for predicting the road safety evolution of developing countries that may have not yet reached the same breakpoints. Furthermore, the presented framework may serve as a basis to build more elaborate models, including more reliable exposure indicators (such as vehicle-km driven).

On statistical inference in time series analysis of the evolution of road safety

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research.

OFF-STREET PARKING CHOICE SENSITIVITY

This article deals with the determinants of choice between on- and off-street parking. In this context, a questionnaire-based survey was conducted and the stated preference method was used to develop an explanatory model. The model assessment showed that parking cost has, as expected, the most important impact on the choice of parking alternatives. Furthermore, all other variables with a significant impact on parking choice are time related, i.e., search time for a parking space, duration of parking and walking time from the parking space to the final destination. It is also shown that parking choice decisions did not depend on driver and trip characteristics. The methodology followed can be used in other similar cases for the identification of parking choice sensitivity, thus providing valuable input to the development of appropriate parking policy in a given area.

Impact of Texting on Young Drivers' Behavior and Safety On Urban and Rural Roads Through A Simulation Experiment

PROBLEM This research aims to investigate the impact of texting on the behavior and safety of young drivers on urban and rural roads. METHOD A driving simulator experiment was carried out in which 34 young participants drove in different driving scenarios; specifically, driving in good weather, in raining conditions, in daylight and in night were examined. Lognormal regression methods were used to investigate the influence of texting as well as various other parameters on the mean speed and mean reaction time. Binary logistic methods were used to investigate the influence of texting use as well as various other parameters in the probability of an accident. RESULTS It appears that texting leads to statistically significant decrease of the mean speed and increase of the mean reaction time in urban and rural road environment. Simultaneously, it leads to an increased accident probability due to driver distraction and delayed reaction at the moment of the incident. It appeared that drivers using mobile phones with a touch screen present different driving behavior with respect to their speed, however, they had an even higher probability of being involved in an accident. DISCUSSION The analysis of the distracted driving performance of drivers who are texting while driving may allow for the identification of measures for the improvement of driving performance (e.g., restrictive measures, training and licensing, information campaigns). PRACTICAL APPLICATIONS The identification of some of the parameters that have an impact on the behavior and safety of young drivers concerning texting and the consequent results can be exploited by policy decision makers in future efforts for the improvement of road safety.

Factors Affecting Accident Severity Inside and Outside Urban Areas in Greece

Objectives: This research aims to identify and analyze the factors affecting accident severity through a macroscopic analysis, with a focus on the comparison between inside and outside urban areas. Disaggregate road accident data for Greece for the year 2008 were used. Methods: Two models were developed, one for inside and one for outside urban areas. Because the dependent variable had 2 categories, killed/severely injured (KSI) and slightly injured (SI), the binary logistic regression analysis was selected. Furthermore, this research aims to estimate the probability of fatality/severe injury versus slight injury as well as to calculate the odds ratios (relative probabilities) for various road accident configurations. The Hosmer and Lemeshow statistic and other diagnostic tests were conducted in order to assess the goodness-of-fit of the model. Results: From the application of the models, it appears that inside urban areas 3 types of collisions (sideswipe, rear-end, with fixed object/parked car), as well as involvement of motorcycles, bicycles, buses, 2 age groups (18–30 and older than 60 years old), time of accident, and location of the accident, seem to affect accident severity. Outside urban areas, 4 types of collisions (head-on, rear-end, side, sideswipe), weather conditions, time of accident, one age group (older than 60 years old), and involvement of motorcycles and buses were found to be significant. Conclusions: Factors affecting road accident severity only inside urban areas include young driver age, bicycles, intersections, and collision with fixed objects, whereas factors affecting severity only outside urban areas are weather conditions and head-on and side collisions, demonstrating the particular road users and traffic situations that should be focused on for road safety interventions for the 2 different types of networks (inside and outside urban areas). The methodology and the results of this research may provide a promising tool to prioritize programs and measures to improve road safety in Greece and worldwide.

Classification of driver-assistance systems according to their impact on road safety and traffic efficiency

The aim was to examine driver-assistance systems that seem to have a considerable potential for road safety and traffic efficiency improvement, and to propose an impact-oriented classification of these systems. A broad overview of a series of driver-assistance systems under development or in some cases already available is presented and it identifies the basic characteristics of each system and its expected impact on traffic efficiency and road safety. The latter is assessed on the basis of appropriate evaluation criteria. Expert judgement and literature evidence available are used in this context. This impact approach, in contrast with the usually adopted user or system-oriented approaches, allows for more appropriate identification of the priorities in the field of future research, development and promotion of driver-assistance systems. The proposed classification allocates the driver-assistance systems in four different categories on the basis of whether traffic efficiency and safety impact are high or low. This categorization reveals that 40% of the systems considered are expected to have a high safety and low traffic-efficiency impact, while only 15% is expected to have both impacts high.

Estimation of Fatality and Injury Risk by Means of In-Depth Fatal Accident Investigation Data

Objective: In this article the factors affecting fatality and injury risk of road users involved in fatal accidents are analyzed by means of in-depth accident investigation data, with emphasis on parameters not extensively explored in previous research. Methods: A fatal accident investigation (FAI) database is used, which includes intermediate-level in-depth data for a harmonized representative sample of 1300 fatal accidents in 7 European countries. The FAI database offers improved potential for analysis, because it includes information on a number of variables that are seldom available, complete, or accurately recorded in road accident databases. However, the fact that only fatal accidents are examined requires for methodological adjustments, namely, the correction for two types of effects on a road users baseline risk: “accident size” effects, and “relative vulnerability” effects. Fatality and injury risk can be then modeled through multilevel logistic regression models, which account for the hierarchical dependences of the road accident process. Results: The results show that the baseline fatality risk of road users involved in fatal accidents decreases with accident size and increases with the vulnerability of the road user. On the contrary, accident size increases nonfatal injury risk of road users involved in fatal accidents. Other significant effects on fatality and injury risk in fatal accidents include road user age, vehicle type, speed limit, the chain of accident events, vehicle maneuver, and safety equipment. In particular, the presence and use of safety equipment such as seat belt, antilock braking system (ABS), and electronic stability program (ESP) are protection factors for car occupants, especially for those seated at the front seats. Conclusions: Although ABS and ESP systems are typically associated with positive effects on accident occurrence, the results of this research revealed significant related effects on accident severity as well. Moreover, accident consequences are more severe when the most harmful event of the accident occurs later within the accident chain.

Mobility Patterns of Motorcycle and Moped Riders in Greece

This paper investigates the mobility patterns of powered two-wheeler riders in comparison with those of passenger car drivers in Greece, a country in which an increased rate of two-wheeler ownership and related traffic is observed. A nationwide travel survey targeted at active two-wheeler and passenger car drivers was carried out for that purpose. The results of the survey were exploited in two ways. First, the use of the vehicle types examined in Greece was investigated in relation to driver characteristics by calculation of the respective sample distributions. The results demonstrated a clear difference between vehicle ownership rates and vehicle use rates by vehicle type. Moreover, the mobility patterns of each vehicle type were compared on the basis of the average yearly mileage traveled in relation to driver (age, gender, experience), vehicle (engine size), type of trip (weekday or weekend), and road environment (area type, lighting conditions, road type). The findings indicated that driver gender, age, and experience appeared to be a stronger determinant of mobility patterns than vehicle type. But different mobility patterns among vehicle types in different road environments were identified; this suggests that mopeds and motorcycles are preferred for particular types of trips (e.g., traveling in residential areas and weekdays during the daytime), whereas passenger cars may be used in all cases.