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.

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.

Passing maneuver on rural two-lane highways is a complex task, which has a significant effect on capacity, level of service and safety. The maneuver is conditioned on the gap between two successive vehicles on the opposing lane. The minimum time to collision, defined as the remaining gap between the passing vehicle and the oncoming vehicle at the end of the passing process, expresses a measure of the risk involved in the passing maneuver. This paper develops a model that explains the minimum time to collision. The model formulation is based on the analysis of drivers' passing decisions on two-lane rural highways using an interactive driving simulator. The simulator enables the collection of vehicle speeds and positions for different road and traffic scenarios. In addition to the driver simulator, participants responded to a questionnaire which collected information about their socio-demographic characteristics. The composed dataset was analyzed and processed to develop a model that predicts the risk associated with the passing behavior. Tobit regression models were found to be more suitable, in comparison to ordinary least square models and Hazard-based Duration models. The explanatory variables tested represent road geometry, traffic conditions and drivers' characteristics. It was found that while the traffic related variables had the most important effect on the measure of risk chosen, factors related to the geometric design and the driver characteristics also had a significant contribution.

Crashes on two-lane rural highways are over-represented at horizontal curves, and speed inconsistency is a common contributing factor to these crashes. Road Consistency reflects the similarity or lack thereof of vehicle performance along an entire road segment. Consistency is measured by estimating the speed variation along successive geometric elements and evaluation of the speed deviation from the average speed. Because it has been shown in the past that speed variability has an impact on safety, it was hypothesized that design consistency is also related to safety. The purpose of this study is to examine the relationship between road design consistency and crash probability on two-lane rural highways. An enhanced consistency model is applied to examine this relationship in Israel and Germany. This consistency model is based on both the horizontal and vertical alignments and takes into account the impact of trucks and grades on road consistency. A statistically significant model that showed a reduction in average crash numbers per year with an increase in consistency is presented and discussed. It was found that the Israeli and German models have a similar trend. The enhanced-consistency model and the software may be used relatively easily to determine consistencies of different alternatives during the planning of new highways or the reconstruction of existing roads. Planners and decision-makers could be advised of potential design deficiencies during the design process and consequently, modify a proposed design and thus improve safety levels and save lives.

Overtaking maneuvers on two-lane rural roads are difficult maneuvers which involve relatively complicated decisions. The main hypothesis tested in this paper is that the frequency of overtaking maneuvers on a driving simulator is associated with a faulty decision making style in the Iowa Gambling Task (IGT), a popular decision task employed for assessing cognitive impulsivity. In a controlled study, 36 participants drove a scenario involving multiple overtaking decisions in an interactive driving simulator (STISIM) and also completed the IGT. The results show a significant negative correlation of about 0.3 between the IGT performance and the number of overtaking maneuvers, the average driving speed, and the acceleration noise. We also found a positive correlation of 0.5 between IGT performance and the percent of aborted overtaking maneuvers. A cognitive modeling analysis shows that the associations appear to be modulated by weighting of gains compared to losses obtained during repeated play. These results demonstrate that the IGT has a potential to predict risk prone behavior in overtaking maneuvers and in driving in general.

This paper presents research to evaluate drivers' passing maneuvers on two-lane rural roads using data collected with STISIM, an interactive driving simulator. In addition to the observations of driving behavior obtained in the simulator experiments, drivers' socioeconomic characteristics and indicators of their driving style were collected using self-reported questionnaires. The participants were asked to drive a 9.5 km twolane rural road section with no intersections. The positions and speeds of the subject vehicle and the other simulated vehicles were recorded at a resolution of 0.1 seconds. The data collected in the experiment was used to develop a model that explains drivers' passing decisions. The results indicate that the speed of the subject vehicle and its relations to the vehicle being passed are the most important factors affecting passing behavior. In addition, drivers' socio-demographic characteristics and driving styles also affect passing decisions.

Crash-prediction models can be used to assess road safety during highway planning and design. The main objective of this study is to develop an Infrastructure coefficient that reflects the overall safety level of a highway and can be used as an independent variable in a crash-prediction model. Infrastructure is defined as the highway and its geometric features. It includes the road alignment, roadside environment, sight distance along the highway, presence of guardrails, number of access points, roadway consistency alignment, lane and shoulder width and percentage of access points with a speed-change lane. These geometric features measure the overall quality of the highway. Two different infrastructure coefficients are developed and calibrated by two different statistical methods. The infrastructure coefficient developed by using the principal component analysis method consists of 11 infrastructure characteristics, and that developed by using the analytic hierarchy process method consists of 5 infrastructure characteristics. For each highway section, a value reflecting its infrastructure quality was calculated according to each of the infrastructure coefficients developed. The results showed a significant correlation between highway infrastructure quality and crash rates. Based on the infrastructure coefficients and crash records, two crash-prediction models are developed. It is suggested that these models can be used to evaluate the safety level of existing or planned 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.