Haneen Farah

A Passing Gap Acceptance Model for Two-lane Rural Highways

Passing manoeuvres on rural two-lane highways significantly affect highway capacity, safety and level of service. This article presents an analysis of data on drivers’ passing decisions on two-lane rural highways that were collected with an interactive driving simulator. Measurements of the speeds and positions of all vehicles in several different scenarios were collected and processed to generate observations of gap acceptance behaviour. In addition, participants responded to a questionnaire which collected information on their socio-demographic and driving styles characteristics. These data were utilised to develop a model that explains the decision whether to pass or not, using variables that capture the impact of the road geometry, traffic conditions and drivers’ characteristics. It was found that while the traffic related variables had the most important effect on passing decision, factors related to the geometric design and the driver characteristics also had a significant effect on these decisions.

Age and Gender Differences in Overtaking Maneuvers on Two-Lane Rural Highways

For decades researchers have been pointing out significant differences in the driving behavior between young and old and between male and female drivers. There are many studies concerning age and gender differences in risk perception, traffic accident involvement, traffic violations, alcohol consumption, and risky driving. However, little effort has been focused on studying the behavioral differences in overtaking maneuvers on two-lane highways. A considerable percentage of the fatal accidents on two-lane highways is directly related to overtaking maneuvers. Therefore, the main focus of this study is to understand better the overtaking behavior of different drivers classified by their age and gender. Data on the overtaking behavior of 100 drivers were collected with an interactive driving simulator. Several scenarios of two-lane rural highways with different geometric and traffic conditions were developed. The results show interesting and significant differences in the overtaking behavior of drivers depending on their age and gender. These differences are mainly in the frequency of overtaking maneuvers, overtaking time duration, following distances, critical overtaking gaps, and desired driving speeds. Geometric and traffic conditions were also found to have a significant impact on drivers’ overtaking behavior. The findings of this study contribute to the understanding of the overtaking behavior of different groups of drivers and thus have implications for road safety intervention programs and the development of effective risk reduction strategies adapted and targeted for different age and gender groups.

Impact of Infrastructure Characteristics on Road Crashes on Two-Lane Highways

Objective. The main purpose of this study is to estimate and quantify the contribution of the infrastructure to highway crashes and to develop an infrastructure coefficient, that represents the overall characteristics of the highway and could be used as an independent variable in a crash-prediction model. Methods. The infrastructure is defined in this study as the highway and its geometric features, including alignment, road-side elements, sight-distances, presence of guardrails, access-points, roadway consistency, and additional variables that measure the overall quality of the highway alignment and elements. The analysis and developments are conducted for two-lane rural highways. The approach taken is to identify the high crash-rate roads, those with crash rates above 0.25 crashes per million vehicle-km, by Smallest Space Analysis. This type of analysis allows the aggregation of higher crash-rate roads versus lower-crash-rate roads only by their infrastructure coefficients, without consideration of their crash records. Results. Crash rates that are attached by Smallest Space Analysis to the group of roads that had less desirable infrastructure features show a high correlation between the same roads and high crash rates vs. identified better infrastructures and low crash rates. Further analysis shows that low crash-rate infrastructure, as defined in this study for two-lane rural highways, can reduce the crash rate by 44% versus high crash-rate infrastructure, at the 99% confidence level, which is almost a certainty. A model for the prediction of crash rates based on a proposed infrastructure coefficient is calibrated and presented. Conclusions. It is suggested that this model be used in evaluating alternatives for new highways or in improving the alignment and road features of existing highways.

Alternative Definitions of Passing Critical Gaps

A substantial proportion of the road network in most countries consists of two-lane highways. Available gaps for passing are a fundamental element in the operation of such highways. Providing passing opportunities is important for reducing the formation of vehicle platoons in the traffic flow, increasing the level of service, and improving safety. Passing opportunities also affect fuel consumption and emissions. Despite the importance of passing on two-lane highways, few studies have focused on exploring passing gap definitions when modeling passing behavior. Research was done to investigate various definitions of passing gaps, and these definitions were used to develop passing gap acceptance models. Data on passing maneuvers collected with a driving simulator were used to develop and calibrate three models. The generic structure of these models was composed of the drivers’ desire to pass and their gap acceptance decisions. The impact of traffic characteristics, road geometry, and driver characteristics was included in these models. The results show that the passing gap definition has a significant impact on the models’ ability to explain passing behavior. Moreover, the estimation results show that modeling a drivers desire to pass the vehicle ahead has a statistically significant contribution in explaining passing behavior. Variables that capture the impact of the traffic conditions, geometric characteristics of the road section, driver characteristics, and the unobserved heterogeneity in the driver population were found to have a significant impact on drivers’ desire to pass and their gap acceptance decisions.

dEVElOpMEnT OF an inFRaSTRucTuRE cOEFFiciEnT BY an analYTic hiERaRchY pROcESS and iTS RElaTiOnShip TO SaFETY

This paper describes a study which had as its primary objectives to develop a numerical Infrastructure Coefficient (IC) representing the overall infrastructure characteristics of a highway and to develop a crash prediction model correlating the IC with crash rates on two-lane rural highways. The first phase of the study, involving the development of the IC, examined the correlation between different infrastructures characteristics and crash rate. The Analytic Hierarchy Process (AHP) was also used to develop the IC. Its function was to attribute a specific weight to each infrastructure characteristic in order to reflect its relative importance to road safety when compared with other characteristics considered in the study. Finally, a model predicting crash rates based on the proposed IC was calibrated and presented. The study concluded that a well-built and maintained highway could reduce crashes by an average of 44% as compared to a highway with poor infrastructure.

Drivers’ Irrationality in Evaluating Risks on Two-Lane Highways

Head-on collisions on two-lane rural highways might result from failed passing maneuvers. This article investigates the hypothesis that drivers do not always estimate the required passing gap correctly, and their decision to overtake is made under a particular, even if small, probability that a crash will occur; this is the associated risk. The research investigates drivers’ irrationality in evaluating the risks of different passing gaps and develops a risk-taking measure. This measure provides a tool for classifying drivers into different groups: risky, partially cautious, and cautious drivers. A comparison of the sociodemographic averages, driving style, and crash history parameters for these groups showed significant differences. The measure developed can be used for risk evaluation and as a measure of safety. It further provides a tool for classifying drivers into groups based on their risk-taking characteristics. This is particularly useful for safety education programs.