Surrogate safety measures and traffic conflict observations.

The chapter primarily focuses on observing traffic conflicts (also known as near-accidents) as a site-based road safety analysis technique. Traffic conflicts are a type of surrogate safety measure. The term surrogate indicates that non-accident-based indicators are used to assess VRU safety instead ofthe more traditional approach focusing on accidents (see chapter 2). The theory underpinning surrogate safety measures is briefly described, followed by a discussion on the characteristics of the traffic conflict technique. Next, guidelines for conducting traffic conflict observations using trained human observers or video cameras are presented. Chapter 4 concludes with examples of the use of the traffic conflict technique in road safety studies focusing on VRUs

Functional failure sequences in traffic accidents

This thesis examines the interactions between road users and the factors that contribute to the occurrence of traffic accidents, and discusses the implications of these interactions with regards to driver behaviour and accident prevention measures. Traffic accident data is collected on a macroscopic level by local police authorities throughout the UK. This data provides a description of accident related factors on a macroscopic level which does not allow for a complete understanding of the interaction between the various road users or the influence of errors made by active road users. Traffic accident data collected on a microscopic level analysis of real world accident data, explaining why and how an accident occurred, can further contribute to a data driven approach to provide safety measures. This data allows for a better understanding of the interaction of factors for all road users within an accident that is not possible with other data collection methods. In the first part of the thesis, a literature review presents relevant research in traffic accident analysis and accident causation research, afterwards three accident causation models used to understand behaviour and factors leading to traffic accidents are introduced. A comparison study of these accident causation coding models that classify road user error was carried out to determine a model that would be best suited to code the accident data according to the thesis aims. Latent class cluster analyses were made of two separate datasets, the UK On the Spot (OTS) in-depth accident investigation study and the STATS19 national accident database. A comparison between microscopic (in-depth) accident data and macroscopic (national) accident data was carried out. This analysis allowed for the interactions between all relevant factors for the road users involved in the accident to be grouped into specific accident segmentations based on the cluster analysis results. First, all of the cases that were collected by the OTS team between the years 2000 to 2003 were analysed. Results suggested that for single vehicle accidents males and females typically made failures related to detection and execution issues, whereas male road users made diagnosis failures with speed as a particularly important factor. In terms of the multiple vehicle accidents the interactions between the first two road users and the subsequent accident sequence were demonstrated. A cluster analysis of all two vehicle accidents in Great Britain in the year 2005 and recorded within the STATS19 accident database was carried out as a comparison to the multiple vehicle accident OTS data. This analysis demonstrated the necessity of in-depth accident causation data in interpreting accident scenarios, as the resulting accident clusters did not provide significant differences between the groups to usefully segment the crash population. Relevant human factors were not coded for these cases and the level of detail in the accident cases did not allow for a discussion of countermeasure implications. An analysis of 428 Powered Two Wheeler accidents that were collected by the OTS team between the years 2000 to 2010 was carried out. Results identified 7 specific scenarios, the main types of which identified two particular looked but did not see accidents and two types of single vehicle PTW accidents. In cases where the PTW lost control, diagnosis failures were more common, for road users other than the PTW rider, detection issues were of particular relevance. In these cases the interaction between all relevant road users was interpreted in relation to one another. The subsequent study analysed 248 Pedestrian accidents that were collected by the OTS team between the years 2000 to 2010. Results identified scenarios related to pedestrians as being in a hurry and making detection errors, impairment due to alcohol, and young children playing in the roadside. For accidents that were initiated by the other road user s behaviour pedestrians were either struck after an accident had already occurred or due to the manoeuvre that a road user was making, older pedestrians were over-represented in this accident type. This thesis concludes by discussing how (1) microscopic in-depth accident data is needed to understand accident mechanisms, (2) a data mining approach using latent class clustering can benefit the understanding of failure mechanisms, (3) accident causation analysis is necessary to understand the types of failures that road users make and (4) accident scenario development helps quantify accidents and allows for accident countermeasure implication discussion. The original contribution to knowledge is the demonstration that when relevant data is available there is a possibility to understand the interactions that are occurring between road users before the crash, that is not possible otherwise. This contribution has been demonstrated by highlighting how latent class cluster analysis combined with accident causation data allows for relevant interactions between road users to be observed. Finally implications for this work and future considerations are outlined

The role of visual information in the steering behaviour of young and adult bicyclists

In a first series of experiments, the visual behaviour during different steering tasks, and under different constraints, was investigated in an indoor environment. Young learner, and experienced adult bicyclists were asked to steer through narrow lanes, a curved lane, and a slalom. Participants directed their gaze to the future path about one to two seconds ahead, and moved forward using optokinetic nystagmus-like eye movements. Both cycling speed and task demand were found to affect the visual behaviour of bicyclists. Although these shifts of visual attention were in line with earlier findings in pedestrians and car drivers, they did not seem to be entirely in line with the two-level model of steering behaviour. Therefore, a redefined version of this model was proposed as the ‘gaze constraints model for steering’. During a simple linear steering task, the visual behaviour of children (between 6 and 12 years of age) was similar to that of adults. However, in a more demanding slalom task children adopted a different visual-motor strategy. Whereas adults made more use of anticipatory fixations and often looked at the functional space between two cones, children mainly focussed on the upcoming cone. These findings suggest that adults plan their route through the slalom whereas children focus on steering around one cone at the time. In a second series of experiments, the distribution of visual attention was investigated in an actual traffic environment and the influence of a low quality cycling track on visual behaviour was studied. Results showed that children direct their gaze more to the environment and less to the path than adults. However, both adults and children made an apparent shift of visual attention from distant environmental regions towards more proximate road properties on the low quality cycling track. In general, the current thesis provides insights into how visual attention of young and adult bicyclists is distributed during different steering tasks and how this is affected by individual, task, and environmental constraints. Based on the current results, a gaze constraints model for steering was proposed. Furthermore, it seems that children adapted their visual behaviour to their limited capabilities, but that children’s visual behaviour changes in a similar way to changing task constraints as the visual behaviour of adults. These findings suggest that traffic rules, road infrastructure and traffic education should take into account the limited capabilities of children. However, it should be noted that this work only focussed on the lane-keeping task. Future research should therefore study the integration of these findings in the visual control of other traffic tasks such as hazard perception. A better understanding of the development of information processing of young learner bicyclists could potentially lead to better traffic education and more appropriate road infrastructure. Additionally, a new fixation-by-fixation analysis method to analyze head-mounted eye tracking data was tested in this thesis. This method was found to be a good alternative to the time-consuming frame-by-frame method, provided that the areas of interest were large, and the analysis is done over an extended period of time

DO TRANSPORTATION NETWORK COMPANIES AFFECT ROAD SAFETY OUTCOMES: A SPATIALLY DETAILED ANALYSIS IN SAN FRANCISCO

US traffic fatal deaths have steadily risen since 2010, with the past few years witnessing an unusual trend increase. To reverse such a dangerous trend, one must understand how and why road crashes occur and which factors are causing them. Emerging transportation technologies have shown the potential to improve mobility and safety. However, such technologies are not inherently beneficial and could worsen road safety if not effectively implemented. One such transportation technology that warrants investigation is the rise of ridesharing services, also called Transportation Network Companies (TNCs). The primary goal of the dissertation is to explore the statistical relationship between road safety outcomes and TNC service components like curbside pick-ups and drop-offs (PUDO) or through the TNC-involved vehicles miles traveled (VMT). It evaluates the relationship between TNC service components like PUDO and Tot TNC VMT with four main types of road crash frequency: the total number of road crashes, fatal and severe injury crashes, crashes involving pedestrians and bicyclists, and crashes involving drink-driving using San Francisco (SF) county data. A fixed-effect Poisson Regression Model with a robust covariance matrix compares San Francisco (SF) county\u27s 2010 safety outcomes when TNCs were negligible to safety outcomes for the exact locations in 2016 for which spatially detailed TNC data is available. Dependent variables like Total Crashes, Fatal and Injury Crashes, Pedestrian and Bicyclist Crashes, Alcohol-involving (DUI) Crashes, and Property Damage Only (PDO) Crashes are evaluated using the model, controlling for vehicle speed, Total VMT, and TNC service components, namely TNC VMT and PUDO. We apply that model to 2010 and 2016 scenarios and counterfactual scenarios that estimate what would have occurred in 2016 without specific aspects of TNC operations. The results show that TNCs indirectly increased total crashes by 4% due to higher exposure and 7% due to changes in vehicle speeds. The direct effect of TNCs on crashes offsets these increases, reducing crashes by 14%, but this effect depends upon the model specification and is insignificant in other specifications tested. The results for other types of crashes are similar in direction but lower in significance. Overall, the results suggest that TNCs are a minor factor in road safety outcomes, at least within the limits of what we can measure with the available data. This finding is broadly consistent with past research on the topic. These results interest engineers, planners, and policymakers seeking to improve road safety. Those aiming to reduce traffic crashes would be well-advised to avoid getting distracted by TNCs in one direction or another and instead focus on known solutions, including road design, vehicle technology, and reducing exposure through reducing vehicle miles traveled

Identification of road user related risk factors, deliverable 4.1 of the H2020 project SafetyCube.

Safety CaUsation, Benefits and Efficiency (SafetyCube) is a European Commission supported Horizon 2020 project with the objective of developing an innovative road safety Decision Support System (DSS). The DSS will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures, and cost-effective approaches to reduce casualties of all road user types and all severities. This document is the first deliverable (4.1) of work package 4 which is dedicated to identifying and assessing human related risk factors and corresponding countermeasures as well as their effect on road safety. The focus of deliverable 4.1 is on identification and assessment of risk factors and describes the corresponding operational procedure and corresponding outcomes. The following steps have been carried out: Identification of human related risk factors – creation of a taxonomy Consultation of relevant stakeholders and policy papers for identification of topic with high priority (‘hot topics’) Systematic literature search and selection of relevant studies on identified risk factors •Coding of studies •Analysis of risk factors on basis of coded studies •Synopses of risk factors, including accident scenarios The core output of this task are synopses of risk factors which will be available through the DSS. Within the synopses, each risk factor was analysed systematically on basis of scientific studies and is further assigned to one of four levels of risk (marked with a colour code). Essential information of the more than 180 included studies were coded and will also be available in the database of the DSS. Furthermore, the synopses contain theoretical background on the risk factor and are prepared in different sections with different levels of detail for an academic as well as a non-academic audience. These sections are readable independently. It is important to note that the relationship between road safety and road user related risk factors is a difficult task. For some risk factors the available studies focused more on conditions of the behaviour (in which situations the behaviour is shown or which groups are more likely to show this behaviour) rather than the risk factor itself. Therefore, it cannot be concluded that those risk factors that have not often been studied or have to rely more indirect and arguably weaker methodologies, e.g. self-reports , do not increase the chance of a crash occurring. The following analysed risk factors were assessed as ‘risky’, ‘probably risky’ or ‘unclear’. No risk factors were identified as ‘probably not risky’. Risky Probably risky Unclear • Influenced driving – alcohol • Influenced Driving – drugs (legal & illegal) • Speeding and inappropriate speed • Traffic rule violations – red light running • Distraction – cell phone use (hand held) • Distraction – cell phone use (hands free) • Distraction – cell phone use (texting) • Fatigue – sleep disorders – sleep apnea • Risk taking – overtaking • Risk taking – close following behaviour • Insufficient knowledge and skills • Functional impairment – cognitive impairment • Functional impairment – vision loss • Diseases and disorders – diabetes • Personal factors – sensation seeking • Personal factors – ADHD • Emotions – anger, aggression • Fatigue – Not enough sleep/driving while tired • Distraction – conversation with passengers • Distraction – outside of vehicle • Distraction – cognitive overload and inattention • Functional impairment – hearing loss (few studies) • Observation errors (few studies) • Distraction – music – entertainment systems (many studies, mixed results) • Distraction – operating devices (many studies, mixed results) The next step in SafetyCube’s WP4 is to identify and assess the effectiveness of measures and to establish a link to the identified risk factors. The work of this first task indicates a set of risk factors that should be centre of attention when identifying corresponding road safety measures (category ‘risky’)

Sustainable urban transport in Kuala Lumpur - A backcasting scenario approach.

Urban transport trends and issues in Kuala Lumpur have indicated that they are moving away from sustainability. Besides the conventional problems such as congestion, accidents, urban air pollution, there are signs showing mat social inequality and institutional problems are confronting the transport system in Kuala Lumpur. The above issues are not the natural outcome of development instead, they are related to specific social, economic and political policies. In view of the complexity and the great number of uncertainties, a backcasting scenario methodology has been adopted in this study to analyse the means of breaking the present trend. The overall aim of the research is to explore a wider perspective of possible future opportunities and policy options in order to achieve sustainable urban transport objectives in Kuala Lumpur. The sustainable urban transport policy has been formulated in four major steps (the central structure of scenario backcasting methodology). Firstly, the vision of the urban transport system in Kuala Lumpur has been defined, i.e. the one that provides affordable access to all levels of the community, and does so in an economically viable, environmentally sound and equitable manner. Secondly, policy targets have been identified in accordance with the vision. Then, three Images of the Future have been constructed to represent the alternative images. Finally, measures and policy packages have been developed to bridge the gap between the present and the future images. At every stage of the methodology, local transport experts were invited to contribute their inputs to the study as part of the validation process. The thesis concludes with an assessment of the three Images in relation to sustainability achievement and also their practicality in terms of implementation. It also recommends basic conditions and common measures to achieve a sustainable transport system in Kuala Lumpur. The contributions of this research are twofold. Firstly, it extends the frontiers of the existing transport policy considerations and formulation in Kuala Lumpur, and secondly, it demonstrates a novel application of backcasting scenario methodology to the sustainable urban transport field at the city level