Risk evaluation by modeling of passing behavior on two-lane rural highways

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.     

Driving simulator for speed research on two-lane rural roads

The paper reports on a validation study of the interactive fixed-base driving simulator of Inter-University Research Center for Road Safety (CRISS) that was effectuated in order to verify the CRISS driving simulator's usefulness at a tool for speed research on two-lane rural roads. Speeds were recorded at eleven measurement sites with different alignment configurations on a two-lane rural road near Rome. The real world was reproduced in the CRISS driving simulator. Forty drivers drove the simulator. The results of the comparative and statistical analysis established the relative validity and also revealed that absolute validity was obtained in nine measurements sites. Only in two non-demanding configurations, were the speeds in simulator significantly higher than those recorded in the field. In these sites the mean speed in simulator was equal to or greater than 94 km/h. For these configurations, the higher speeds recorded in simulator appeared to stem from the different risk perception on the simulated road as opposed to that on the real road. The study's results should be considered for driving speed behavior research, in which simulator equipment with similar features of the CRISS driving simulator is used.     

Use of speed profile as surrogate measure: Effect of traffic calming devices on crosstown road safety performance

Urban road safety management is usually characterized by the lack of sufficient, good quality crash data and low budgets to obtain it even though many traffic accidents occur there. For example, 54 percent of road crashes in Spain take place in urban areas, and 10 percent of urban fatal crashes occur on crosstown roads, which are rural roads that traverse small communities. Traffic calming measures (TCMs) are often implemented on these parts of rural roads that traverse small communities in order to reduce both the frequency and severity of crashes by lowering speeds, but evaluation of their effectiveness has been limited. The objective of this study was to develop a methodology using continuous speed profiles to evaluate the safety effectiveness of TCMs on crosstown roads as part of an integrated system in the absence of historical data. Given the strong relationship between speed and crash experience, safety performance can be related to speed. Consequently, speed can be used indirectly as a surrogate safety measure in the absence of crash and speed data.     

An examination of the environmental,driver and vehicle factors associated with the serious and fatal crashes of older rural drivers

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004–2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100 km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances.     

Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia

Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements.     

Driver injury severity outcome analysis in rural interstate highway crashes: a two-level Bayesian logistic regression interpretation

There is a high potential of severe injury outcomes in traffic crashes on rural interstate highways due to the significant amount of high speed traffic on these corridors. Hierarchical Bayesian models are capable of incorporating between-crash variance and within-crash correlations into traffic crash data analysis and are increasingly utilized in traffic crash severity analysis. This paper applies a hierarchical Bayesian logistic model to examine the significant factors at crash and vehicle/driver levels and their heterogeneous impacts on driver injury severity in rural interstate highway crashes. Analysis results indicate that the majority of the total variance is induced by the between-crash variance, showing the appropriateness of the utilized hierarchical modeling approach. Three crash-level variables and six vehicle/driver-level variables are found significant in predicting driver injury severities: road curve, maximum vehicle damage in a crash, number of vehicles in a crash, wet road surface, vehicle type, driver age, driver gender, driver seatbelt use and driver alcohol or drug involvement. Among these variables, road curve, functional and disabled vehicle damage in crash, single-vehicle crashes, female drivers, senior drivers, motorcycles and driver alcohol or drug involvement tend to increase the odds of drivers being incapably injured or killed in rural interstate crashes, while wet road surface, male drivers and driver seatbelt use are more likely to decrease the probability of severe driver injuries. The developed methodology and estimation results provide insightful understanding of the internal mechanism of rural interstate crashes and beneficial references for developing effective countermeasures for rural interstate crash prevention.     

Modeling drivers’ speed selection as a trade-off behavior

This paper proposes a new model of driver-preferred speeds derived from the assumption that drivers trade-off a portion of their safety for a time gain. The risk of receiving a ticket for speeding is also considered. A trip disutility concept is selected to combine the three components of speed choice (safety, time, and enforcement). The perceived crash risk and speed enforcement are considered as speed deterrents while the perceived value of a time gain is considered as a speed enticement. According to this concept, speeds that minimize the perceived trip disutility are preferred by drivers. The modeled trade-off behavior does not have to be fully rational since it is affected by drivers’ preferences and their ability to perceive the risk. As such, the proposed framework follows the concept of bound rationality.The attractiveness of the model lies in its parameters being estimable with the observed preferred speeds and then interpretable as the factors of risk perception, the subjective value of time, and the perceived risk of speed enforcement. The proposed method may successfully supplement behavioral studies based on a driver survey.The study focuses on four-lane rural and suburban roads in Indiana, USA. The behavior of two types of drivers (trucks and cars) is modeled. The selection of test sites was such that the roads and other local characteristics varied across the studied sites while the population of drivers could be assumed as the same. The density of intersections, land development along the road, and the presence of sidewalks were the identified prominent risk perception factors. Another interesting finding is that the speed limit seems to encourage slow drivers to drive faster and fast drivers to drive slower.     

Behaviourally relevant road categorisation: a step towards self-explaining rural roads

In contrast to motorways, rural roads are characterised by a large variation in design, appearance and function which is reflected in a comparatively large number of rural road categories. Depending on these categories, a certain (normative) behaviour is usually expected from the driver. These normative behavioural expectations are conveyed to the driver either by formal cues (e.g. speed limit signs) or are expected to be inferred from the road appearance or the affordance (Gibson, J.J., 1986. The Ecological Approach to Visual Perception. Lawrence Erlbaum, Hillsdale (New Jersey)) of the respective road situation. Unsafe situations are likely to occur if the perceived message conveyed by cues or affordances does not match the normative behavioural expectations of the official road category. In order to avoid such mismatch it is important to know how drivers categorise (rural) roads and which elements are used for this subjective and behaviourally relevant road categorisation. We therefore summarized the processes behind this categorisation in a model and conducted a study in a laboratory setting during which subjects were asked to rate a variety of rural road pictures. The study revealed that drivers distinguish between three different rural road categories which can be distinguished with comparatively few objective criteria. Applying these criteria helps to categorise and design rural roads along self-explaining road principles.     

Speeding drivers' attitudes and perceptions of speed cameras in rural England

There is evidence that excessive speed leads to an increased frequency and severity of road traffic accidents, but it is not clear how speeds may be reduced. To increase understanding of why drivers exceed the speed limits, the views of a sample of road users who had been prosecuted for exceeding the speed limit in the rural county of Norfolk England were sought. Respondents were categorised into a four group driver typology comprising conformers (those who report they never exceed limits) deterred drivers (those put off speeding by the presence of cameras), manipulators (those who slow only at camera locations) and defiers (those who exceed limits regardless of cameras), and the consistency of opinions was compared between the groups. Speeding was perceived as widespread and normal, and many drivers resented camera enforcement. Indeed, some respondents considered that cameras in themselves caused dangerous driving. For many drivers, the prosecution experience resulted in distress, anger and anti-camera sentiments, predominantly because they expressed the belief that they were more skilled than other drivers. It was also apparent that many respondents displayed a lack of awareness of the link between speed and collisions. Conformers were the least likely to state that the prosecution had deterred them from further speeding behaviour, possibly because they perceived themselves as already law-abiding. The deterred drivers were most likely to express intentions to avoid further speeding and their speeding incident was found to be most likely to be accidental. Manipulators and defiers tended to report that they had deliberately chosen to infringe the speed limits. Manipulators often acknowledged that their style of driving was dangerous; however, they failed to link this to their own behaviour. It was evident that many defiers and manipulators did not perceive speeding as a serious traffic law violation. Possible implications for road safety initiatives are discussed and recommendations are given for specifically targeting different driver types.     

Quasi-induced exposure: The choice of exposure metrics

The quasi-induced exposure method is widely used to estimate exposure and risks of different groups of drivers and vehicles. Essentially, this method assumes that non-at-fault or passive parties in two-vehicle collisions represent a random sample of the populations on the road. Most previous works have used the whole sample of collisions to estimate exposure.There has been some concern about possible biases in quasi-induced estimates. In this paper, we argue that (1) biases are mainly due to differences in accident avoidance abilities, speeds and injury risks, and (2) because the influence of these three factors on the probability of being non-at-fault is not the same for every crash type, differences may arise among non-at-fault populations, in which case some crash types would provide a more accurate estimate of exposure than others.We explore the direction of biases due to speed, accident avoidance ability and injury risk in four accident types: accidents between vehicles travelling on different lanes in two-way, two-lane undivided roads; accidents between vehicles travelling on different lanes on multilane roads; intersection accidents; and accidents between vehicles travelling on the same lane. Our analysis shows that more research would be needed concerning the effect of speed on head-on crashes on undivided roads, and crashes on multilane roads.     

Modeling vehicle operating speed on urban roads in Montreal: A panel mixed ordered probit fractional split model

Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate that the proposed panel mixed ordered probit fractional split model offers promise for modeling such proportional ordinal variables.     

How does it change safety margins if overtaking is prohibited: A pilot study

Overtaking was temporarily prohibited on a 1.2km long stretch of two-lane road and the time headway for every car, passing the site in a certain direction, was measured at two points between which the prohibition sign was posted. Additionally, the lateral position of every car was recorded. Due to the prohibition, some favorable effects on safety margins were found. When passing the prohibition sign the drivers following another car very closely increased their following distance; no such change was found in the control condition. Furthermore, when overtaking prohibited, the closely following drivers reserved a bit greater safety margin with respect to the oncoming vehicles. The results suggest that waiting for an opportunity of overtaking increases the accident risk by inducing very short following distances and driving near the center line. This implies that the total accident loss due to overtaking is not wholly included in the category “overtaking acidents” but, in fact, a part of rear-end accidents should be counted on overtaking, too. This should be taken into account when estimating the pay-off of overtaking on two-lane roads.     

Effects of road geometry and traffic volumes on rural roadway accident rates

This paper revisits the question of the relationship between rural road geometric characteristics, accident rates and their prediction, using a rigorous non-parametric statistical methodology known as hierarchical tree-based regression. The goal of this paper is twofold: first, it develops a methodology that quantitatively assesses the effects of various highway geometric characteristics on accident rates and, second, it provides a straightforward, yet fundamentally and mathematically sound way of predicting accident rates on rural roads. The results show that although the importance of isolated variables differs between two-lane and multilane roads, 'geometric design' variables and pavement condition' variables are the two most important factors affecting accident rates. Further, the methodology used in this paper allows for the explicit prediction of accident rates for given highway sections, as soon as the profile of a road section is given.     

Time vs. distance as measures of exposure in driving surveys

A survey of drivers carried out in Ontario in 1988 has provided data on time spent driving as well as the distances driven for licensed drivers of both sexes in six age groups and three regions. Substantial differences were found in times, distances, and distance/time ratios among these groups. Men drove 50% greater distances, but spent only 30% more time driving than women; speed, averaged over each day's driving, was lower for older drivers than for younger drivers. Differences in speed reflect differences in the driving done in urban or rural areas, and differences in the opportunity for road crashes; such differences, whether based on units of time or distance, will also affect both the comparisons of accident rates and the perceptions of risk among different groups of drivers. A definition of exposure to risk of road crash is required that considers both time and distance appropriately.     

Driver behavior during bicycle passing maneuvers in response to a Share the Road sign treatment

The interaction of motorists and bicyclists, particularly during passing maneuvers, is an area of concern to the bicycle safety community as there is a general perception that motor vehicle drivers may not share the road effectively with bicyclists. This is a particular concern on road sections with centerline rumble strips where motorists are prone to crowd bicyclists during passing events. One potential countermeasure to address this concern is the use of a bicycle warning sign with a “Share the Road” plaque. This paper presents the results of a controlled field evaluation of this sign treatment, which involved an examination of driver behavior while overtaking bicyclists. A series of field studies were conducted concurrently on two segments of a high-speed, rural two-lane highway. These segments were similar in terms of roadway geometry, traffic volumes, and other relevant factors, except that one of the segments included centerline rumble strips while the other did not. A before-and-after study design was utilized to examine changes in motor vehicle lateral placement and speed at the time of the passing event as they relate to the presence of centerline rumble strips and the sign treatment. Centerline rumble strips generally shifted vehicles closer to the bicyclists during passing maneuvers, though the magnitude of this effect was marginal. The sign treatment was found to shift motor vehicles away from the rightmost lane positions, though the signs did not significantly affect the mean buffer distance between the bicyclists and passing motorists or the propensity of crowding events during passing. The sign treatment also resulted in a 2.5 miles/h (4.0 km/h) reduction in vehicle speeds. Vehicle type, bicyclist position, and the presence of opposing traffic were also found to affect lateral placement and speed selection during passing maneuvers.     

Close-following drivers on two-lane highways

This study was intended first to replicate, on two-lane highways, of the Evans and Wasielewski (Accident Analysis & Prevention 14, 57–64, 1982; 15, 121–136, 1983) results on the connection between close-following driving and traffic offenses and, second, to reveal reasons for close-following. A sample of close-following drivers (N= 157) and control drivers (N= 178) was picked from the flow on two-lane main highways. The driver records of the past 3 years showed retrospectively that the close-followers had accumulated 2.3 times more traffic offenses than had the control drivers and 2.0 times more when mileage was taken into account. The result is in agreement with the Evans and Wasielewski results for multi-lane highways, with the additional check for mileage in these data. However, the effect only occurred in males and was more marked in young males. Close-following females even indicated a tendency of having fewer offenses than their controls when their higher mileage was taken into account. Another sample of close-followers interviewed on the road revealed that hurry or desire to overtake the car ahead was the justification for the close-following in the majority of cases. It was suggested that on two-lane highways close-following substantially stems from overtaking needs and maneuvering connected to higher target speeds. This study partly confirms the connection between close-following and an increased number of offenses in comparisons between drivers. However, the suggested connection between close-following and accident involvement, as based on interindividual comparisons, still remains somewhat open.     

An explanatory analysis of driver injury severity in rear-end crashes using a decision table/Naïve Bayes (DTNB) hybrid classifier

Rear-end crashes are a major type of traffic crashes in the U.S. Of practical necessity is a comprehensive examination of its mechanism that results in injuries and fatalities. Decision table (DT) and Naïve Bayes (NB) methods have both been used widely but separately for solving classification problems in multiple areas except for traffic safety research. Based on a two-year rear-end crash dataset, this paper applies a decision table/Naïve Bayes (DTNB) hybrid classifier to select the deterministic attributes and predict driver injury outcomes in rear-end crashes. The test results show that the hybrid classifier performs reasonably well, which was indicated by several performance evaluation measurements, such as accuracy, F-measure, ROC, and AUC. Fifteen significant attributes were found to be significant in predicting driver injury severities, including weather, lighting conditions, road geometry characteristics, driver behavior information, etc. The extracted decision rules demonstrate that heavy vehicle involvement, a comfortable traffic environment, inferior lighting conditions, two-lane rural roadways, vehicle disabled damage, and two-vehicle crashes would increase the likelihood of drivers sustaining fatal injuries. The research limitations on data size, data structure, and result presentation are also summarized. The applied methodology and estimation results provide insights for developing effective countermeasures to alleviate rear-end crash injury severities and improve traffic system safety performance.     

What can we learn about North Dakota's youngest drivers from their crashes?

For North Dakota teens, three of every four deaths are from motor vehicle crashes. Injury crash records for teen drivers were studied to gain insight regarding driver, vehicle, and road factors for public safety policy and program discussions. Results show 14-year-old drivers are three times more likely to die or be disabled in an injury crash than 17-year-old drivers, and that male drivers are 30% less likely to incur severe injury. As expected, seat belt use is a critical factor in severe injury avoidance. The likelihood for death or disablement is 165% greater for unbelted teen drivers than for those who are properly belted. In addition, rural and gravel roads pose a risk. Teens are six times more likely to be severely injured in crashes on rural roads than on urban roads. Findings suggest that an increased licensing age and seat belt emphasis may reduce teen traffic injuries in the state. In addition, more information on exposure should be attained to better understand rural and gravel road as risks.