Behaviour Of Other Road Users Research Articles

Assessing the determinants of crash propensity using structural equation modeling: Role of distractions caused by fellow drivers

IntroductionAggressive behavior of drivers is a source of crashes and high injury severity. Aggressive drivers are part of the driving environment, however, excessive aggressive driving by fellow drivers may take the attention of the recipient drivers away from the road resulting in distracted driving. Such external distractions caused by the aggressive and discourteous behavior of other road users have received limited attention. These distractions caused by fellow drivers (DFDs) may agitate recipient drivers and ultimately increase crash propensity. Aggressive driving behaviors are quite common in South Asia and, thus, it is necessary to determine their contribution to distractions and crash propensity. MethodOur study aimed to evaluate the effects of DFDs using primary data collected through a survey conducted in Lahore, Pakistan. A total of 801 complete responses were obtained. Various hypotheses were defined to explore the associations between the latent factors such as DFDs, anxiety/stress (AS), anxiety-based performance deficits (APD), hostile behavior (HB), acceptability of vehicle-related distractions (AVRD), and crash propensity (CP). Structural Equation Modeling (SEM) was employed as a multivariate statistical technique to test these hypotheses. ResultsThe results supported the hypothesis that DFDs lead to AS among recipient drivers. DFDs and AS were further found to have positive associations with APDs. Whereas, there was a significant negative association between DFD, AS, and AVRD. As hypothesized, DFD and AS had positive associations with CP, indicating that distractions caused by aggressive behaviors leads to stress and consequently enhances crash propensity. Practical applicationsThe results of this study provide a statistically sound foundation for further exploration of the distractions caused by the aggressive behaviors of fellow drivers. Further, the results of this study can be utilized by the relevant authorities to alter aggressive driving behaviors and reduce DFDs.

Recognition of typical driving stressors and driver stress level in a Chinese sample

Drivers are adversely affected in decision-making and behavior under excessive stress, thus increasing road crash risks. In this study, the Driver Stress Inventory (DSI) was used to identify typical driving stress scenarios and explore the characteristics of drivers among different stress levels. A total of 1881 drivers took part in the survey. The Precedence Chart was used to rank the importance of driving stressors involved in the scale. K-means cluster was adopted to classify drivers’ stress into three levels, namely low, medium and high-stress. Finally, the Kruskal-Wallis test and Mantel-Haenszel test were employed to analyze the similarities and differences of demographic statistical characteristics under different stress levels. The results of the study indicate that various unexpected scenarios caused by the abnormal behavior of other road users are the most typical stressors. Drivers in the high-stress group tended to be younger and less experienced. Professional drivers reported higher stress than nonprofessional drivers. In addition, high-stress drivers were more prone to be involved in traffic crashes.

New needs to consider during accident analysis: Implications of autonomous vehicles with collision reconfiguration systems

Autonomous vehicles are equipped with advanced vehicle technology (AVT) that will improve road traffic safety and reduce accidents. However, due to the uncertain behavior of other road users, collisions can never be completely eliminated. Collision reconfiguration systems offer a solution by, for instance, changing where vehicles are hit and how the impact force is directed towards them. Unfortunately, the logic behind the decision-making of collision reconfiguration systems is fundamentally different from that of other AVTs. Fundamentally different feedback might thus be required from accident analyses to ensure the successful design of collision reconfiguration systems. Through simulations, this study explores decision-making strategies of collision reconfiguration systems to ascertain the implications of which feedback is required from accident analyses. Results show that different strategies can be statistically significantly different from each other in the way they affect severity; and that a new source of unobserved heterogeneity could easily be small variations in the algorithms used by collision reconfiguration systems. Based on this, three new needs to consider during accident analysis are put forth: firstly, new safety surrogate measures (SSMs) that consider severity are required; one such SSM is proposed; secondly, to identify new unobserved heterogeneity as a result of collision reconfiguration systems, the trajectories of traffic near-collisions should be recorded, and statistical tools to identify comparable scenarios developed. Thirdly, new collision patterns will make it difficult to analyze the implications of reconfigured collisions, which suggests that collision configurations must be carefully recorded to provide early feedback.

A Cross-Sector Framework to Boost the Sustainable Implementation of Integrated Transport and Spatial Strategies to Improve Safety and Mobility of Moto-Taxi Riders

Globally, motorcycle riders make up the biggest percentage of vulnerable road user fatalities. The percentages are higher in African cities where moto-taxi transport is not only the most readily available mode of transport but also a source of income for many especially the youth. Many African cities are re-strategizing on how to sustainably deal with problems like traffic congestion, unplanned development, flooding, air and noise pollution. The authors carried out a questionnaire survey targeting a variety of road safety stakeholders to identify road safety solutions that they think best fit the current situation. Another questionnaire survey targeting moto-taxi riders was carried out, and the data analyzed by SEM to identify how different solutions interact to affect the behavior of riders. Results show that education and training programs have the biggest effect on improving behavior of riders as they adapt to new city regulations such as zoning. Other aspects such as presence of customers, behavior of other road users, road environment were also explored. Currently, city authorities in some developing nations are looking to introduce spatial regulations such as zoning and traffic management strategies such as exclusive lanes. Therefore, the contribution of this study is a proposal of a combination of solutions that different road safety stakeholders in developing countries can contribute toward the sustainable improvement of the safety of riders.

A two-layer switching based trajectory prediction method

Safety-critical situations in road traffic often result from incorrect estimation of the future behavior of other road users. Therefore, many Advanced Driver Assistance Systems (ADAS) need prediction models to ensure safety. Physical prediction models offer the advantage of general use and work quite well for short prediction horizons, while for longer periods of time, maneuver-based models offer better performance which, however, strongly depends on the data used to train them. An additional challenge for prediction is the fact that the surrounding traffic can change its path, i.e. for safety not only one maneuver should be considered but regular updates are required. Against this background, we propose a method that uses three physics-based predictions – corresponding to different prediction assumptions and models – combined with possible maneuver-based trajectories derived from environmental knowledge. Continuous monitoring is used to select the most likely of the three physics-based models. This choice then influences the environment-based prediction and the output of both models is fused afterwards. The output of the resulting Multiple Model Trajectory Prediction (MMTP) has been validated with measured data from two different scenarios – a city junction and a highway – with a good prediction performance and without the need for special measurements as commonly required for maneuver-based prediction.

The Pilot Study of the Hazard Perception Test for Evaluation of the Driver’s Skill Using Virtual Reality

Background: Although various technologies are used to evaluate driving skill, there are some limitations such as the limited range of the monitor and the possible risk of causing cybersickness. The purpose of this study is to investigate differences in the hazard perception and cybersickness experienced between novice and experienced drivers measured in a VR hazard perception test with a head-mounted display (HMD). Methods: The novice (n = 32) and the experienced drivers (n = 36) participated in the hazard perception test through the VR of an HMD. Results: The total number of identified hazards was 1071 in the novice drivers and 1376 in the experienced drivers. Two of the hazards appeared to be only identifiable through the HMD. A chi-square test revealed that experienced drivers were more likely to identify the hazards than the novice drivers (p < 0.05). The novice drivers appeared to identify “hazard prediction of the current behavior of other road users” more than other hazard types, unlike the experienced group. The Simulator Sickness Questionnaire scores indicated no significant difference in the different age or gender groups (p > 0.05). Conclusion: Our results suggest that the VR hazard perception test may be useful for evaluating patients’ driving skills.

Driving (and) Attention – Does Directional Illumination Support Driver’s System Supervision When Driving Automatically?

Partially automated driving changes the driving task into supervising the automation with occasionally a necessity to intervene. Due to this changing role, drivers of partially automated vehicles have need for interfaces that help them to supervise system operation, support detection of relevant events, as well as provide cues about system’s intentions. This study assessed to what extent directional illumination supports drivers in gaining mode awareness, i.e. in perceiving and understanding what the automation does and whether counter actions are necessary. An internet survey with video-clips of directional illumination within circumstances representative for partially automated driving measured respondents’ understanding of automation-mode and their understanding of required action. Measurements were compared with results from a base-concept, which provided cues for automation mode, but without directional illumination. Results showed that directional illumination raised perception and understanding of automation-mode noticeable when attention was requested for hazards located in the driver’s side-views. Compared to the base-concept, directional-illumination did not improve driver’s understanding of required actions. Development of explanatory instructions was recommended especially for events when changing road-situations interplayed with behaviour of other road-users. To attract attention to situations outside the vehicle, directional illumination was perceived significantly more suitable than the base-concept. The results of this study contribute to further development of directional illumination as a supporting interface while supervising partially automated driving.

Passenger opinions of the perceived safety and interaction with automated shuttles: A test ride study with ‘hidden’ safety steward

Abstract A necessary condition for the effective integration of automated vehicles in our daily lives is their acceptance by passengers inside and pedestrians and cyclists outside the automated vehicle. 119 respondents experienced an automated shuttle ride with a ‘hidden steward on board’ in a mixed traffic environment in Berlin-Schoneberg. A mixed-method approach was applied gathering qualitative interview data during the ride and quantitative questionnaire data after the ride. Responses were classified into three main categories: (1) Perceived safety, (2) interactions with automated shuttles in crossing situations, and (3) communication with automated shuttles. Respondents associated their perceptions of safety with the low speed, dynamic object and event identification, longitudinal and lateral control, pressing the emergency button inside the shuttle, their general trust in technology, sharing the shuttle with fellow travellers, the operation of the shuttle in a controlled environment, and the behaviour of other road users outside the shuttle. Respondents pressed the emergency button inside the automated shuttle on 28 out of 62 test rides in order to test its behavior. They further expected to be more cautious in crossing the road before an automated shuttle due to the lack of eye contact with the human driver and a lack of trust in the behavior of the automated shuttle, and expected road users testing the automated shuttle due to the conservative driving behavior of automated shuttles. We recommend future research into the hypothesis that the acceptance of automated shuttles will be associated with the perceived safety of and their effective and intuitive interaction and communication with both passengers and other road users.

Attention Based Vehicle Trajectory Prediction

Self-driving vehicles need to continuously analyse the driving scene, understand the behavior of other road users and predict their future trajectories in order to plan a safe motion and reduce their reaction time. Motivated by this idea, this paper addresses the problem of vehicle trajectory prediction over an extended horizon. On highways, human drivers continuously adapt their speed and paths according to the behavior of their neighboring vehicles. Therefore, vehicles’ trajectories are very correlated and considering vehicle interactions makes motion prediction possible even before the start of a clear maneuver pattern. To this end, we introduce and analyze trajectory prediction methods based on how they model the vehicles interactions. Inspired by human reasoning, we use an attention mechanism that explicitly highlights the importance of neighboring vehicles with respect to their future states. We go beyond pairwise vehicle interactions and model higher order interactions. Moreover, the existence of different goals and driving behaviors induces multiple potential futures. We exploit a combination of global and partial attention paid to surrounding vehicles to generate different possible trajectory. Experiments on highway datasets show that the proposed model outperforms the state-of-the-art performances.

Using Walk-Along Interviews to Identify Environmental Factors Influencing Older Adults' Out-of-Home Behaviors in a High-Rise, High-Density Neighborhood.

Older adults’ out-of-home behaviors (OOHBs) are critical for maintaining health and quality of life. Taking Singapore’s Yuhua East as a case, this study applied a qualitative approach to explore what neighborhood environmental factors influence older adults’ OOHBs. Twelve older adults were recruited for walk-along interviews through the use of purposeful convenience sampling. A content analysis was conducted using NVivo 11 via an inductive approach. Research results revealed 12 categories of environmental factors that affected older adults’ OOHBs: access to facilities (shops and services, public transit, and connectivity), pedestrian infrastructure (sidewalk quality, sheltered walkways, universal design, crossings, benches, and public toilets), aesthetics (natural elements, buildings, noise, and cleanliness), traffic safety (behavior of other road users and road width), safety from crime, wayfinding, familiarity (long-term residency and routine activities), weather, social contact, high-rise, high-density (lifts, population density, flat size, and privacy), affordability (shops and services, as well as transportation), and maintenance and upgrading. This analysis concluded that access to facilities and pedestrian infrastructure are important for older adults’ OOHBs. Considering Singapore’s weather, sheltered walkways, the proximity of facilities and connectivity should be given serious emphasis. In addition to physical factors, social contacts and the affordability of shops and services are also important.

INFLUENCE OF A CARRIAGEWAY WIDTH ON THE CAR SPEED UNDER URBAN CONDITIONS

Problem. The car speed is the most important indicator of the traffic organization level. A priori it is obvious that the value of the car speed in a particular place and at a particular time is random. The randomness of speed is due to the influence on it of too many factors that cannot be taken into account analytically - from the driving style of each driver, which in itself is made up of individual actions, which are difficult to predict, to a large number and individual behavior of other road users. Establishing a car speed distribution in various conditions is an urgent task, whose solution is the basis for improving the accuracy of traffic forecasts that are formed using analytical or simulation models of transport networks and their elements. Goal. The goal is obtaining patterns of changes in the car speed in limited road conditions, with the narrow carriageway. Methodology. The methods include development of a valid hypothesis regarding the type of distribution of the car speed in limited road conditions and its experimental verification using the example of an urban street with parked cars. Results. The hypothesis about the possibility of using gamma distribution to describe the car speed in any driving conditions, i.e. for any average car speed, was not denied by experimental observations of the movement of vehicles on a narrow section of the urban street 5.45 m wide for two directions. Originality. New hypothesis was promoted and tested about the kind of car speed distribution, not in free, but in limited road conditions. Practical value. The obtained result is the basis for improving the accuracy of traffic forecasts that are formed using analytical or simulation models of transport networks and their elements in transport consulting.

A statistical assessment of temporal instability in the factors determining motorcyclist injury severities

This study explores the temporal instability of factors affecting motorcyclist-injury severities in single-vehicle motorcycle crashes in Florida. Two data sources are used; one covers the 2012 to 2016 crash histories of Florida motorcyclists who were newly licensed in 2012, and the second covers motorcycle crashes that occur on horizontal curves in Florida from 2005 to 2015. In the first dataset (2012 new riders), temporal changes may result from riders gaining experience as well as general temporal shifts. In the second dataset, rider experience is unknown (thus becoming a source of potential unobserved heterogeneity) but the temporal changes will be largely from general temporal shifts. With three possible motorcyclist injury severity outcomes (no visible injury, minor injury, and severe injury), random parameters multinomial logit models, that allow for heterogeneity in means and variances, were estimated for all possible annual time periods in each dataset. Likelihood ratio tests were conducted to examine the overall stability of model estimates across time periods, and marginal effects of each explanatory variable were also considered to investigate the temporal instability of the effect of individual parameter estimates on motorcyclist injury-severity probabilities. A wide range of variables was considered including motorcyclists’ attributes (such as ethnicity and age), roadway and environmental conditions (such as light and road surface conditions), motorcycle characteristics (such as motorcycle make and type of motorcycle), rider actions (such as speeding and improper driving actions), and roadway conditions (such as obstacles on the road and speed limits). The results show significant temporal instability in motorcyclist-injury severity models, which likely result from changes in motorcycle technology and performance, changes in macroeconomic conditions, changes induced by how riders respond to the changing behavior of other road users (whose behavior may be changing as a result of technology changes in their vehicles, evolving use of personal technologies in their vehicle, such as cell phones, etc.), and the changes in riders’ behavior and skills over time.

“What Makes a Cooperative Driver?” Identifying parameters of implicit and explicit forms of communication in a lane change scenario

An automated vehicle needs to learn how human road users communicate with each other in order to avoid misunderstandings and prevent giving a negative outward image during interactions. The aim of the present work is to develop an autonomous driving system which communicates its intentions to change lanes based on implicit and explicit rules used by human drivers. To reach this goal, we aimed at gaining a deeper understanding of which aspects of lane change behaviour makes them cooperative from the perspective of other drivers. Therefore a vehicle used various lane change announcement strategies by varying combinations of driving parameters in a static driving simulator. (First study: Start indicator signal, Waittime, lane change duration; Second study: Longitudinal acceleration). It’s impact on the perception and behaviour of other road users was observed in two studies (N = 25 per study). The results showed that the earlier the merging vehicle was indicating its intentions, the more cooperative it was perceived. When turning on the indicator at a later time participants considered it as more cooperative to merge with a slower or faster lane change duration or to wait longer in the lane before starting to move to the other lane. An early longitudinal acceleration when starting to change lanes is perceived more cooperative. These findings can be used to model a lane change strategy based on human behaviour, which will eventually lead to more acceptable and safer interactions between automated and non-automated road users.

Looking to the future of visual assessment using driving simulation

Visual function is considered uniquely important for driving because it provides multiple critical sources of information that when combined ensures successful steering. There are, however, additional cognitive functions that are essential for the driver to be able to dynamically respond to the world and make predictions about the scene, as well as the behaviour of other road users. Given the complexity of driving through a busy urban environment it should be no surprise that simple tests of visual acuity seem to have weak explanatory power in terms of increased crash risk when driving. Despite this, fitness to drive still includes a formal assessment of visual acuity, with poor scores being used to revoke the driving licence. The 'gold standard' measure of driving ability remains the on-road driving test but compared to visual tests they are fairly uncontrolled, susceptible to great variation depending on the road conditions, and are unable to reliably detect subtle visual deficits. To address some of the limitations of these existing tests we use examples from two simulator settings (steering control and hazard detection) that highlight the merits of using driving simulation in order to control the visual conditions and probe specific functional capabilities of drivers. When used in conjunction with visual tests these methods will not only determine whether the core functions of driving are intact but also be able to provide richer feedback to individuals about the nature of their deficits. There are many exciting possibilities using simulation techniques to establish predictive relationships between routine visual testing and driving performance, ultimately aiming for better, more reliable assessment of fitness to drive.

Memory for everyday driving

As drivers, we often have the sense that we can recall very little about our everyday trips, particularly on familiar roads when nothing untoward occurs. The failure to recall incidental events from a routine drive is not surprising if these drives are performed at a fairly automatic or preconscious level of engagement. Some researchers have suggested that danger, difficulty, and consequentiality are what make events and actions memorable for drivers. To investigate what drivers remember from a routine trip, we asked participants (n=75) to drive familiar local roads on a 15km urban route either on-road in an instrumented car, or in the University of Waikato driving simulator (with and without a passenger). At ten predetermined locations on the drive participants were asked to provide ratings of perceived risk, difficulty and anxiety. At the end of the drive, participants were asked a free recall question about what they remembered from the drive, followed by cued recall questions about six of the locations from the drive prompted by photographs. In general, participants recalled very similar things from the drive, notably what they saw as the poor behaviour of other drivers. The participants’ recall accuracy was rather poor, with memory for whether they had stopped at a particular location having the highest accuracy. Memory of whether there were vehicles ahead and whether they had stopped had a high number of recall false alarms, adding to the suggestion that participants remembered the locations and what usually happens there rather than detailed recollections of a particular occasion. There were no observed relationships between recall accuracy and perceptions of driving risk, difficulty, or anxiety. The results indicated that memories of everyday driving are combinations of examples of bad behaviour of other road users and our recollections of what typically happens at familiar locations.

Autonomous vehicles in the pro peloton: opportunities and threats

Introduction There is a need for motor vehicles to operate in close proximity to riders in professional races; there is a need for professional cyclists to move unpredictably in order to gain sporting advantage.  Are collisions between cyclists and cars / motos therefore inevitable?  There is an ongoing controversy over the number and action of motos and other support vehicles, including ‘classic’ incidents such as Hoogerland’s crash at the 2011 TdF where a media collided with the riders; race affecting incidents such as the ‘Blockhaus’ incident affecting Thomas, Yates and Landa at 2017 Giro d’Italia where a stationary motorcycle caused an incident (Mansfield, 2017) and a similar incident involving Peter Sagan at the 2015 Vuelta a Espana.  Other incidents have led to more serious outcomes.  The automotive industry have made great improvements in vehicle safety and have invested increasing amounts of attention to protecting other road users.  One leader has been Volvo who currently promote ‘Vision 2020’: Our vision is that by 2020 no one should be killed or seriously injured in a new Volvo car (HA¥kan Samuelsson, President and CEO, Volvo Cars, 2014).  This paper seeks to outline opportunities and threats from automotive technologies and whether they might have scope to improve safety in the pro peloton.   Autonomous vehicle systems are set to revolutionise the transport environment across the world. There are enormous potential environmental benefits from autonomous vehicles including the ability to minimise emissions through smart engine management, minimising congestion through smart routing / parking, and reducing road collisions through elimination of distracted, intoxicated or tired drivers.  Autonomous vehicles are classified using six levels of autonomy (SAE, 2014). The most advanced autopilot systems currently operate at Level 2.  These use radar and optical sensors to generate virtual situation awareness.  Experimental systems (e.g. Google / Uber) use LIDAR laser scanning to support Levels 3-5.  Currently automotive manufacturers are prioritising technology to safely control the vehicle and to detect (and avoid) obstacles. Autonomy has not only been developed in cars but has also been demonstrated by major motorcycle manufactures. Some low-level autonomous systems are already standard equipment in many models of and are well accepted due to clear improvements in safety (e.g. anti-lock braking, traction control).  More sophisticated ‘standard’ autonomy such as lane-assist and adaptive cruise control will inevitably be present in some support vehicles but mostly de-activated.  If Volvo’s ‘Vision 2020’ and similar ambitious targets are to be achieved then high-level automatic safety systems will no longer be optional.   The challenge of mixing autonomous technologies with riders and fans In cycle sport autonomous technologies will need to be reviewed in order to mandate / prohibit for support vehicles at road races.  On the one hand, potential for improved performance exists in terms of collision avoidance with athletes, spectators, road furniture / debris and other support vehicles.  It could minimise the risks associated with team directors / managers to multi-task through following the race on-screen, using race radio, and driving simultaneously.  On the other hand there are many scenarios where autonomous systems may not perform as intended due to them being optimised for public roads with mixed transport systems rather than closed roads.  Autonomous vehicles are currently ‘hard wired’ to be passive when it comes to pedestrian safety and therefore will stop if a human obstacle is detected.  The reality of cycling fan behaviour means that this will not be acceptable on slow speed sections (i.e. mountain stages) where fans enjoy close engagement with athletes.  In situations where spectators are close to riders, the autonomous vehicle will need to balance safety and assertiveness; this is a use-case that is low priority for automotive manufacturers. There has been little consideration of the change in the behaviour of other road users in response to autonomous vehicles. If a cyclist recognises that a vehicle at a junction is autonomous they may choose to take an assertive approach and deliberately cross in front of it, expecting it to stop; alternatively if vulnerable road users feel unsafe with the perceived behaviour of autonomous vehicles they may be discouraged from using such forms of transport.  One advantage for the professional rider is that the behaviour of the will be predictable.  A conservative approach from the vehicle artificial intelligence (AI) programmer could result in autonomous vehicles being an easy target for criminals and this will need to be considered.  The problem of over-enthusiastic fans (e.g. Ventoux TdF 2016) could be exacerbated by those recognising that particular models and brands of will incorporate collision-avoidance and therefore be tempted to step into the path of the vehicle. Current autopilot systems work through using a high-level of data analytics and data sharing.  This means that details of road conditions can be shared to other vehicles in the fleet and effectively dictate a maximum speed that can be comfortably used.  During race descents, these limitations on speed are likely to be exceeded by the most proficient riders.  If such safety systems cannot be de-activated unintended consequences and vehicle behaviour could occur.  Similarly, the usual use of roads in their reverse directions (e.g. driving on the ‘wrong’ side, driving against the standard flow of traffic that would exist if the road was not closed) could cause the vehicle to prevent access to the race route.   Conclusion In summary, there are many aspects of autonomy that should be welcomed by the cycle race community.  However, teams and organisers should be cautious in selection and specification of vehicles that might include hard-wired automation and safety features.  It is highly likely that safety systems designed to keep road users safe under ‘normal’ driving will be counter-productive when used in close proximity to cycle races on closed roads. 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Motorcyclists’ Perceptions and Experiences of Riding and Risk and Their Advice for Safety

Objective: To examine the knowledge, observations, and perceptions of motorcycle riders on the risks of on-road motorcycling and potential safety measures to give insight and guidance in developing policies, programs, and legislation to improve the safety of motorcyclists.Methods: Individual and focus group interviews were conducted with dealers and a cross section of motorcyclists from selected regions across New Zealand. The interviews were analyzed and coded to identify common themes and diverse perspectives on why people rode motorcycles, riders’ perceptions on risk, and possible safety strategies for on-road motorcycling.Findings and Discussion: Motorcycling has major benefits for riders, although most riders perceived that the risks could be severe and they were susceptible to injury. Their observations on the threats and barriers to safety focused on 3 components: the rider, the motorcycle, and the environment. Risks included inexperience, not riding to the conditions, choice of motorcycle, protective clothing and conspicuity, and speed. The underlying risk of being on 2 wheels was accentuated by the availability of high-power motorcycles. The threats perceived in the environment included the behavior of other road users, especially car drivers, and the poor road conditions and surrounds encountered.Conclusions: Riders identified risks that have been recognized in the road safety literature as well as risks for which there are no engineering or scientific solutions. To effectively increase motorcyclist safety, recognition of the commonalities and the differences between motorcyclists’ perspectives and proposed strategies is needed. This approach is more likely to engage riders and thus support positive behavior change among riders and drivers.

Knowing their place on the roads: What would equality mean for walking and cycling?

Trials and dangers faced by pedestrians and cyclists have not only created an impression of undesirable conditions, but have promoted arguments of injustice and inequality. High rates of death and injury coupled with reporting of poor infrastructure and fear of the behaviour of other road users point to a plausible prima facie concern that pedestrians and cyclists suffer inequalities. Yet this appearance masks uncertainty about what factors are relevant in judging inequality and how these should be treated against potentially competing claims. This article develops a framework assessing conditions for walking and cycling according to a theoretical conception of political and social equality, and so providing a basis on which to make arguments for change in transport policy, planning and law. In developing the framework we examine the relevance to equality of a range of factors, including measurement of road casualties, questions of responsibility to increase walking and cycling as means of contributing to pollution and carbon reduction, matters of fault and responsibility for road safety, and the economic impacts of improving conditions for walking and cycling.

“Teaching them a lesson?” A qualitative exploration of underlying motivations for driver aggression

Aggressive driving is increasingly a concern for drivers in highly motorised countries. However, the role of driver intent in this behaviour is problematic and there is little research on driver cognitions in relation to aggressive driving incidents. In addition, while drivers who admit to behaving aggressively on the road also frequently report being recipients of similar behaviours, little is known about the relationship between perpetration and victimisation or about how road incidents escalate into the more serious events that feature in capture media attention. The current study used qualitative interviews to explore driver cognitions and underlying motivations for aggressive behaviours on the road. A total of 30 drivers aged 18–49 years were interviewed about their experiences with aggressive driving. A key theme identified in responses was driver aggression as an attempt to manage or modify the behaviour of other road users. Two subthemes were identified and appeared related to separate motivations for aggressive responses: ‘teaching them a lesson’ referred to situations where respondents intended to convey criticism or disapproval, usually of unintended behaviours by the other driver, and thus encourage self-correction; and ‘justified retaliation’ which referred to situations where respondents perceived deliberate intent on the part of the other driver and responded aggressively in return. Mildly aggressive driver behaviour appears to be common. Moreover such behaviour has a sufficiently negative impact on other drivers that it may be worth addressing because of its potential for triggering retaliation in kind or escalation of aggression, thus compromising safety.

Visual attention and the transition from novice to advanced driver

Inexperienced drivers are particularly vulnerable to road traffic accidents, and inattention emerges as a factor in these accidents. What do these drivers attend to and how can their observation skills be developed? When drivers scan the road around them, differences are observed as function of driving experience and training, with experienced drivers increasing their visual scanning on roadways of increasing complexity. Trained police drivers showed this effect of increased scanning even more than experienced drivers. This suggests that the driver's understanding of the task develops with experience, such that roads that demand increased monitoring (e.g. interweaving traffic on a multi-lane highway) receive more extensive scanning than roads that are simpler (e.g. light traffic on a straight rural road). Novice drivers do not show this sensitivity to road complexity, suggesting that they fail to attend to potential dangers involving the behaviour of other road users. Encouragingly, a simple training intervention can increase the visual scanning of novices.