Reliability of drivers in urban intersections

The concept of human reliability has been widely used in industrial settings by human factors experts to optimise the person-task fit. Reliability is estimated by the probability that a task will successfully be completed by personnel in a given stage of system operation. Human Reliability Analysis (HRA) is a technique used to calculate human error probabilities as the ratio of errors committed to the number of opportunities for that error. To transfer this notion to the measurement of car driver reliability the following components are necessary: a taxonomy of driving tasks, a definition of correct behaviour in each of these tasks, a list of errors as deviations from the correct actions and an adequate observation method to register errors and opportunities for these errors. Use of the SAFE-task analysis procedure recently made it possible to derive driver errors directly from the normative analysis of behavioural requirements. Driver reliability estimates could be used to compare groups of tasks (e.g. different types of intersections with their respective regulations) as well as groups of drivers’ or individual drivers’ aptitudes. This approach was tested in a field study with 62 drivers of different age groups. The subjects drove an instrumented car and had to complete an urban test route, the main features of which were 18 intersections representing six different driving tasks. The subjects were accompanied by two trained observers who recorded driver errors using standardized observation sheets. Results indicate that error indices often vary between both the age group of drivers and the type of driving task. The highest error indices occurred in the non-signalised intersection tasks and the roundabout, which exactly equals the corresponding ratings of task complexity from the SAFE analysis. A comparison of age groups clearly shows the disadvantage of older drivers, whose error indices in nearly all tasks are significantly higher than those of the other groups. The vast majority of these errors could be explained by high task load in the intersections, as they represent difficult tasks. The discussion shows how reliability estimates can be used in a constructive way to propose changes in car design, intersection layout and regulation as well as driver training.     

Motor-vehicle collisions involving child pedestrians at intersection and mid-block locations

We study motor-vehicle collisions involving child pedestrians walking to school in Hamilton, Ontario, Canada to understand and contrast collision risks at mid-block and intersection locations. We use a matched case–control study design and apply it to intersection and mid-block locations instead of people. Cases are intersections/mid-blocks where collisions occurred and controls are locations where collisions did not occur. We match cases to controls on geography, socio-economic status and year. We use conditional logistic regression to predict the log-odds of collision risk at intersections and mid-blocks as a function of various environmental measures while controlling for volume of child pedestrian activity. Our results suggest that child pedestrian injuries at intersections are associated with intersection control type, traffic volume, and land use characteristics. In contrast, mid-block child pedestrian collisions are not associated with small scale environmental features. The results of this study suggest that some factors associated with the risk of collision differ across location types. These findings may be useful in the planning of safer walking journeys to school.     

Distraction-induced driving error: An on-road examination of the errors made by distracted and undistracted drivers

This study explored the nature of errors made by drivers when distracted versus not distracted. Participants drove an instrumented vehicle around an urban test route both while distracted (performing a visual detection task) and while not distracted. Two in-vehicle observers recorded the driving errors made, and a range of other data were collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, etc.). Classification of the errors revealed that drivers were significantly more likely to make errors when distracted; although driving errors were prevalent even when not distracted. Interestingly, the nature of the errors made when distracted did not differ substantially from those made when not distracted, suggesting that, rather than making different types of errors, distracted drivers simply make a greater number of the same error types they make when not distracted. Avenues for broadening our understanding of the relationship between distraction and driving errors are discussed along with the advantages of using a multi-method framework for studying driver behaviour.     

Driver behavior in car-to-pedestrian incidents: An application of the Driving Reliability and Error Analysis Method (DREAM)

To develop relevant road safety countermeasures, it is necessary to first obtain an in-depth understanding of how and why safety-critical situations such as incidents, near-crashes, and crashes occur. Video-recordings from naturalistic driving studies provide detailed information on events and circumstances prior to such situations that is difficult to obtain from traditional crash investigations, at least when it comes to the observable driver behavior. This study analyzed causation in 90 video-recordings of car-to-pedestrian incidents captured by onboard cameras in a naturalistic driving study in Japan. The Driving Reliability and Error Analysis Method (DREAM) was modified and used to identify contributing factors and causation patterns in these incidents. Two main causation patterns were found. In intersections, drivers failed to recognize the presence of the conflict pedestrian due to visual obstructions and/or because their attention was allocated towards something other than the conflict pedestrian. In incidents away from intersections, this pattern reoccurred along with another pattern showing that pedestrians often behaved in unexpected ways. These patterns indicate that an interactive advanced driver assistance system (ADAS) able to redirect the driver's attention could have averted many of the intersection incidents, while autonomous systems may be needed away from intersections. Cooperative ADAS may be needed to address issues raised by visual obstructions.     

Gap acceptance of violators at signalised pedestrian crossings

Gap acceptance of violating pedestrians was studied at seven stretches of signalised pedestrian crossings in Singapore. The provision of the traffic light signals provide a ‘safer’ crossing option to these pedestrians, as compared to uncontrolled crossings and mid-block arterial roads. However, there are still people choosing to cross at the riskier period (Red Man phase). The paper discusses about the size of traffic gaps rejected and accepted by pedestrians and the behaviour of riskier pedestrians (those adapting partial gap). The likelihood of pedestrians accepting gaps between vehicular traffic as a combination of different influencing independent variables such as traffic, environmental and personal factors was studied and modelled using logistic regression.     

Surface condition and safety at signalised intersections

The study reported herein focuses on assessing the effects and contributions of pavement surface condition parameters including roughness, rut depth and skid resistance on crash frequencies and rates at signalised intersections. The assessment has been performed using graphical trend analysis and negative binomial regression. For each signalised intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of 3 and maximum of 5 years before and after treatment years. Analyses results show that before treatment, light condition (day/night), road surface moisture condition (wet/dry) and skid resistance are the significant contributors to crash occurrence. For after-treatment; light condition, road surface moisture condition and the interaction between roughness and traffic volume are the significant contributors. The study aim and approach are presented herein together with a discussion of the main findings.     

Driver decision-making in the dilemma zone – Examining the influences of clearance intervals,enforcement cameras and the provision of advance warning through a panel data random parameters probit model

In recent years, there have been a series of innovations in the field of vehicle detection at intersection approaches. Modern radar-based smart sensors make it possible to track individual vehicles in close proximity to an intersection. These advancements in technology potentially enable the provision of vehicle- and site-specific decision dilemma zone protection at the onset of the yellow indication at signalized intersections. To exploit this opportunity, it is critical to develop an in-depth understanding of those factors influencing a driver's decision to stop or go at the onset of yellow. This study investigates how signal timing strategies such as yellow interval durations, all-red clearance intervals, advance warning flashers, and automated camera enforcement affect driver decision-making. Data from 87 intersection approaches across five regions of the United States are used to develop a series of decision (i.e., probability of stopping) curves using vehicle trajectory and signal phasing data. A panel data random parameters probit model is used to account for heterogeneity across locations, as well as correlation in driver decision-making, due to unobserved factors that are unique to each signalized intersection. The results demonstrate drivers are more likely to stop at locations where enforcement cameras or flashers are present. Stopping was also more prevalent at intersections with lower speed limits, longer crossing distances, and where pedestrian crosswalks were present.     

Analysis of drivers' preparatory behaviour before turning at intersections

This study analyses naturalistic driving behaviour before making turns at intersections. Instrumented vehicles recorded drivers? preparatory behaviour, including moving the right foot to cover the brake pedal and activating the turn-signal, while approaching the turning point on public roads. Data were analysed for relations between driver preparations, different traffic conditions (with or without forward and/or following vehicles) and the intersection type and turning direction. The results suggest that braking began closer to the target intersection when driving with a vehicle in front, independent of the number of traffic lanes or the turning direction. In contrast, the onset of braking occurred further before the intersection when drivers had a forward vehicle while approaching intersections after curves, where drivers cannot readily determine the distance between their vehicle and the turning point until just before the intersection. The presentation timing of vehicle navigation systems for each traffic condition is discussed based on the road structures of turning points.     

Impact of risk attitudes and perception on game theoretic driving interactions and safety

This study employs game theory to investigate behavioural norms of interaction between drivers at a signalised intersection. The choice framework incorporates drivers’ risk perception as well as their risk attitudes. A laboratory experiment is conducted to study the impact of risk attitudes and perception in crossing behaviour at a signalised intersection. The laboratory experiment uses methods from experimental economics to induce incentives and study revealed behaviour. Conflicting drivers are considered to have symmetric disincentives for crashing, to represent a no-fault car insurance environment. The study is novel as it uses experimental data collection methods to investigate perceived risk. Further, it directly integrates perceived risk of crashing with other active drivers into the modelling structure. A theoretical model of intersection crossing behaviour is also developed in this paper. This study shows that right-of-way entitlements assigned without authoritative penalties to at-fault drivers may still improve perceptions of safety. Further, risk aversion amongst drivers attributes to manoeuvring strategies at or below Nash mixed strategy equilibrium. These findings offer a theoretical explanation for interactive manoeuvres that lead to crashes, as opposed to purely statistical methods which provide correlation but not necessarily explanation.     

Critical older driver errors in a national sample of serious U.S. crashes

Objective

Older drivers are at increased risk of crash involvement per mile traveled. The purpose of this study was to examine older driver errors in serious crashes to determine which errors are most prevalent.

Methods

The National Highway Traffic Safety Administration’s National Motor Vehicle Crash Causation Survey collected in-depth, on-scene data for a nationally representative sample of 5470 U.S. police-reported passenger vehicle crashes during 2005–2007 for which emergency medical services were dispatched. There were 620 crashes involving 647 drivers aged 70 and older, representing 250,504 crash-involved older drivers. The proportion of various critical errors made by drivers aged 70 and older were compared with those made by drivers aged 35–54.

Results

Driver error was the critical reason for 97% of crashes involving older drivers. Among older drivers who made critical errors, the most common were inadequate surveillance (33%) and misjudgment of the length of a gap between vehicles or of another vehicle’s speed, illegal maneuvers, medical events, and daydreaming (6% each). Inadequate surveillance (33% vs. 22%) and gap or speed misjudgment errors (6% vs. 3%) were more prevalent among older drivers than middle-aged drivers. Seventy-one percent of older drivers’ inadequate surveillance errors were due to looking and not seeing another vehicle or failing to see a traffic control rather than failing to look, compared with 40% of inadequate surveillance errors among middle-aged drivers. About two-thirds (66%) of older drivers’ inadequate surveillance errors and 77% of their gap or speed misjudgment errors were made when turning left at intersections. When older drivers traveled off the edge of the road or traveled over the lane line, this was most commonly due to non-performance errors such as medical events (51% and 44%, respectively), whereas middle-aged drivers were involved in these crash types for other reasons. Gap or speed misjudgment errors and inadequate surveillance errors were significantly more prevalent among female older drivers than among female middle-aged drivers, but the prevalence of these errors did not differ significantly between older and middle-aged male drivers. These errors comprised 51% of errors among older female drivers but only 31% among older male drivers.

Conclusions

Efforts to reduce older driver crash involvements should focus on diminishing the likelihood of the most common driver errors. Countermeasures that simplify or remove the need to make left turns across traffic such as roundabouts, protected left turn signals, and diverging diamond intersection designs could decrease the frequency of inadequate surveillance and gap or speed misjudgment errors. In the future, vehicle-to-vehicle and vehicle-to-infrastructure communications may also help protect older drivers from these errors.     

Novel application of red-light runner proneness theory within traffic microsimulation to an actual signal junction

Building on previous research a conceptual framework, based on potential conflicts analysis, has provided a quantitative evaluation of ‘proneness’ to red-light running behaviour at urban signalised intersections of different geometric, flow and driver characteristics. The results provided evidence that commonly used violation rates could cause inappropriate evaluation of the extent of the red-light running phenomenon. Initially, an in-depth investigation of the functional form of the mathematical relationship between the potential and actual red-light runners was carried out. The application of the conceptual framework was tested on a signalised intersection in order to quantify the proneness to red-light running. For the particular junction studied proneness for daytime was found to be 0.17 north and 0.16 south for opposing main road approaches and 0.42 east and 0.59 west for the secondary approaches. Further investigations were carried out using a traffic microsimulation model, to explore those geometric features and traffic volumes (arrival patterns at the stop-line) that significantly affect red-light running. In this way the prediction capability of the proposed potential conflict model was improved. A degree of consistency in the measured and simulated red-light running was observed and the conceptual framework was tested through a sensitivity analysis applied to different stop-line positions and traffic volume variations. The microsimulation, although at its early stages of development, has shown promise in its ability to model unintentional red light running behaviour and following further work through application to other junctions, potentially provides a tool for evaluation of alternative junction designs on proneness. In brief, this paper proposes and applies a novel approach to model red-light running using a microsimulation and demonstrates consistency with the observed and theoretical results.     

Modeling aggressive driver behavior at unsignalized intersections

The processing of vehicles at unsignalized intersections is a complex and highly interactive process, whereby each driver makes individual decisions about when, where, and how to complete the required maneuver, subject to his perceptions of distances, velocities, and own car's performance. Typically, the performance of priority-unsignalized intersections has been modeled with probabilistic approaches that consider the distribution of gaps in the major-traffic stream and their acceptance by the drivers of minor street vehicles based on the driver's "critical gap". This paper investigates the aggressive behavior of minor street vehicles at intersections that are priority-unsignalized but operate with little respect of control measures. The objective is to formulate a behavioral model that predicts the probability that a driver performs an aggressive maneuver as a function of a set of driver and traffic attributes. Parameters that were tested and modeled include driver characteristics (gender and age), car characteristics (performance and model year), and traffic attributes (number of rejected gaps, total waiting time at head of queue, and major-traffic speed). Binary probit models are developed and tested, based on a collected data set from an unsignalized intersection in the city of Beirut, to determine which of the studied variables are statistically significant in determining the aggressiveness of a specific driver. Primary conclusions reveal that age, car performance, and average speed on the major road are the major determinants of aggressive behavior. Another striking conclusion is that the total waiting time of the driver while waiting for an acceptable gap is of little significance in incurring the "forcing" behavior. The obtained model is incorporated in a simple simulation framework that reflects driver behavior and traffic stream interactions in estimating delay and conflict measures at unsignalized intersections. The simulation results were then compared against real world observations, representing an important step in validating the model of aggressive driver behavior at unsignalized intersections.     

Illegal pedestrian crossing at signalised intersections: Incidence and relative risk

Illegal pedestrian behaviour is common and is reported as a factor in many pedestrian crashes. Since walking is being promoted for its health and environmental benefits, minimisation of its associated risks is of interest. The risk associated with illegal road crossing is unclear, and better information would assist in setting a rationale for enforcement and priorities for public education. An observation survey of pedestrian behaviour was conducted at signalised intersections in the Brisbane CBD (Queensland, Australia) on typical workdays, using behavioural categories that were identifiable in police crash reports. The survey confirmed high levels of crossing against the lights, or close enough to the lights that they should legally have been used. Measures of exposure for crossing legally, against the lights, and close to the lights were generated by weighting the observation data. Relative risk ratios were calculated for these categories using crash data from the observation sites and adjacent midblocks. Crossing against the lights and crossing close to the lights both exhibited a crash risk per crossing event approximately eight times that of legal crossing at signalised intersections. The implications of these results for enforcement and education are discussed, along with the limitations of the study.     

Comparison of teen and adult driver crash scenarios in a nationally representative sample of serious crashes

Motor vehicle crashes are the leading cause of death and acquired disability during the first four decades of life. While teen drivers have the highest crash risk, few studies examine the similarities and differences in teen and adult driver crashes. We aimed to: (1) identify and compare the most frequent crash scenarios—integrated information on a vehicle's movement prior to crash, immediate pre-crash event, and crash configuration—for teen and adult drivers involved in serious crashes, and (2) for the most frequent scenarios, explore whether the distribution of driver critical errors differed for teens and adult drivers. We analyzed data from the National Motor Vehicle Crash Causation Survey, a nationally representative study of serious crashes conducted by the U.S. National Highway Traffic Safety Administration from 2005 to 2007. Our sample included 642 16- to 19-year-old and 1167 35- to 54-year-old crash-involved drivers (weighted n = 296,482 and 439,356, respectively) who made a critical error that led to their crash's critical pre-crash event (i.e., event that made the crash inevitable). We estimated prevalence ratios (PR) and 95% confidence intervals (CI) to compare the relative frequency of crash scenarios and driver critical errors. The top five crash scenarios among teen drivers, accounting for 37.3% of their crashes, included: (1) going straight, other vehicle stopped, rear end; (2) stopped in traffic lane, turning left at intersection, turn into path of other vehicle; (3) negotiating curve, off right edge of road, right roadside departure; (4) going straight, off right edge of road, right roadside departure; and (5) stopped in lane, turning left at intersection, turn across path of other vehicle. The top five crash scenarios among adult drivers, accounting for 33.9% of their crashes, included the same scenarios as the teen drivers with the exception of scenario (3) and the addition of going straight, crossing over an intersection, and continuing on a straight path. For two scenarios ((1) and (3) above), teens were more likely than adults to make a critical decision error (e.g., traveling too fast for conditions). Our findings indicate that among those who make a driver critical error in a serious crash, there are few differences in the scenarios or critical driver errors for teen and adult drivers.     

Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks

Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian–motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007–2013 pedestrian–motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian–motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.     

Prevalence of teen driver errors leading to serious motor vehicle crashes

Objectives

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors.

Methods

The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15–18 year old drivers.

Results

822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors.

Conclusions

Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training.     

Older driver distraction: A naturalistic study of behaviour at intersections

This study examined older driver engagement in distracting behaviours (secondary activities) at intersections using naturalistic driving data from a larger study based in Melbourne, Australia. Of interest was whether engagement in secondary activities at intersections was influenced by factors such as driver gender and situational variables, in particular, those relating to the complexity of the driving environment. Specifically we expected that when making left/right turns, older drivers would reduce the proportion of time engaged in secondary behaviours at intersections which required gap judgements (partly controlled or uncontrolled) compared with intersections that were fully controlled by traffic signals. Consideration was given to engagement in secondary activity with hands off the wheel and when the vehicle was moving versus stationary. Older drivers aged between 65 and 83 years drove an instrumented vehicle (IV) on their regular trips for approximately two weeks. The IV was equipped with a video camera system, enabling recording of the road environment and driver and a data acquisition unit, enabling recording of trip distance, vehicle speed, braking, accelerating, steering and indicator use. Driving experience and demographics were collected and functional abilities were assessed using the Useful Field of View (UFOV), Trail Making Test B, Mini Mental Status Examination (MMSE), visual acuity and contrast sensitivity. The study yielded a total of 371 trips with 4493 km (99.8 h) of naturalistic driving data including 1396 left and right turns. Trips were randomly selected from the dataset and in-depth analysis was conducted on 200 intersection manoeuvres (approximately 50% left turns, 50% right turns). The most frequently observed secondary activities were scratching/grooming (42.5%), talking/singing (30.2%) and manipulating the vehicle control panel (12.2%). Glances “off road” 2 s or longer were associated with reading, reaching and manipulation of the vehicle control panel. Hands off the wheel was associated with reading. Key parameters associated with the percent of intersection time that drivers engaged in secondary activities were intersection complexity, vehicle status (moving vs. stationary) and traffic density. In conclusion, older drivers appeared to engage selectively in secondary activities according to roadway/driving situations, supporting the notion that drivers self-regulate by engaging in secondary tasks less frequently when the driving task is more challenging compared with less challenging manoeuvres.     

Evaluating safety effectiveness of surface treatment at signalised intersections: a before and after study

In a metropolitan region of Melbourne, Australia, 136 signalised intersections were identified to have been resurfaced with asphalt over the period 2005–2010. In this study, the safety effectiveness of surface treatment was evaluated using Empirical Bayes (EB) approach to account for regression to the mean bias and traffic volume change through using safety performance function (SPF). Safety effects were estimated for total casualty, high severity (fatality and serious injury) and other injury crashes. For conducting EB method a reference group was selected with similar traffic volumes and site characteristics to the treated sites. Negative Binomial regression was applied to develop SPFs that were used to predict the expected number of crashes at the treated sites. The results of EB approach revealed that the treatment effect was found to be significant at 95% confidence level for all crash severity levels. The evaluation results also showed that total casualty crashes were reduced by 21.3% with a standard error of 3.13% and high severity (fatality and serious injury) crashes were reduced by 15.3% with a standard error of 5.56%. Pavement surface treatment was found to reduce other injury crashes by 21.4% with a standard error of 3.75%.     

Safety surrogate histograms (SSH): A novel real-time safety assessment of dilemma zone related conflicts at signalized intersections

Drivers’ indecisiveness in dilemma zones (DZ) could result in crash-prone situations at signalized intersections. DZ is to the area ahead of an intersection in which drivers encounter a dilemma regarding whether to stop or proceed through the intersection when the signal turns yellow. An improper decision to stop by the leading driver, combined with the following driver deciding to go, can result in a rear-end collision, unless the following driver recognizes a collision is imminent and adjusts his or her behavior at or shortly after the onset of yellow. Considering the significance of DZ-related crashes, a comprehensive safety measure is needed to characterize the level of safety at signalized intersections. In this study, a novel safety surrogate measure was developed utilizing real-time radar field data. This new measure, called safety surrogate histogram (SSH), captures the degree and frequency of DZ-related conflicts at each intersection approach. SSH includes detailed information regarding the possibility of crashes, because it is calculated based on the vehicles conflicts. An example illustrating the application of the new methodology at two study sites in Virginia is presented and discussed, and a comparison is provided between SSH and other DZ-related safety surrogate measures mentioned in the literature. The results of the study reveal the efficacy of the SSH as complementary to existing surrogate measures.     

Evaluation of bike boxes at signalized intersections

This paper presents a before-after study of bike boxes at 10 signalized intersections in Portland, Oregon. The bike boxes, also known as advanced stop lines or advanced stop boxes, were installed to increase visibility of cyclists and reduce conflicts between motor vehicles and cyclists, particularly in potential "right-hook" situations. Before and after video were analyzed for seven intersections with green bike boxes, three intersections with uncolored bike boxes, and two control intersections. User perceptions were measured through surveys of cyclists passing through five of the bike box intersections and of motorists working downtown, where the boxes were concentrated. Both the observations and survey of motorists found a high rate of compliance and understanding of the markings. Overall, 73% of the stopping motor vehicles did not encroach at all into the bike box. Both motor vehicle and bicycle encroachment in the pedestrian crosswalk fell significantly at the bike box locations compared to the control intersections. The bike boxes had mixed effects on the motorists' encroachment in the bicycle lane. The number of observed conflicts at the bike box locations decreased, while the total number of cyclists and motor vehicles turning right increased. Negative-binomial models based upon the data predict fewer conflicts with the boxes, particularly as right-turning motor vehicle volumes increase. Observations of yielding behavior at two bike box and one control intersection found an improvement in motorists yielding to cyclists at the bike box locations. Differences in the traffic volumes and location contexts make firm conclusions about the effects of green coloring of the boxes difficult. Higher shares of surveyed motorists felt that the bike boxes made driving safer rather than more dangerous, even when the sample was narrowed to respondents who were not also cyclists. Over three-quarters of the surveyed cyclists thought that the boxes made the intersection safer.