Pedestrian safety training via smartphone-based VR provides children the repeated practice needed to learn the complex skills required to cross streets safely, and also helps them improve self-efficacy to cross streets. Given rapid motorization and global smartphone penetration, plus epidemiological findings that about 75,000 children die annually worldwide in pedestrian crashes, smartphone-based VR could supplement existing policy and prevention efforts to improve global child pedestrian safety.

Background Pedestrian injuries are a leading cause of paediatric injury. Effective, practical and cost-efficient behavioural interventions to teach young children street crossing skills are needed. They must be empirically supported and theoretically based. Virtual reality (VR) offers promise to fill this need and teach child pedestrian safety skills for several reasons, including: (A) repeated unsupervised practice without risk of injury, (B) automated feedback on crossing success or failure, (C) tailoring to child skill levels: (D) appealing and fun training environment, and (E) most recently given technological advances, potential for broad dissemination using mobile smartphone technology. Objectives and methods Extending previous work, we will evaluate delivery of an immersive pedestrian VR using mobile smartphones and the Google Cardboard platform, technology enabling standard smartphones to function as immersive VR delivery systems. We will overcome limitations of previous research suggesting children learnt some pedestrian skills after six VR training sessions but did not master adult-level pedestrian skills by implementing a randomised non-inferiority trial with two equal-sized groups of children ages 7–8 years (total N=498). All children will complete baseline, postintervention and 6-month follow-up assessments of pedestrian safety and up to 25 30-min pedestrian safety training trials until they reach adult levels of functioning. Half the children will be randomly assigned to train in Google Cardboard and the other half in a semi-immersive kiosk VR. Analysis of Covariance (ANCOVA) models will assess primary outcomes. Discussion If results are as hypothesised, mobile smartphones offer substantial potential to overcome barriers of dissemination and implementation and deliver pedestrian safety training to children worldwide.

Various programs effectively teach children to cross streets more safely, but all are labor- and cost-intensive. Recent developments in mobile phone technology offer opportunity to deliver virtual reality pedestrian environments to mobile smartphone platforms. Such an environment may offer a cost- and labor-effective strategy to teach children to cross streets safely. This study evaluated usability, feasibility, and validity of a smartphone-based virtual pedestrian environment. A total of 68 adults completed 12 virtual crossings within each of two virtual pedestrian environments, one delivered by smartphone and the other a semi-immersive kiosk virtual environment. Participants completed self-report measures of perceived realism and simulator sickness experienced in each virtual environment, plus self-reported demographic and personality characteristics. All participants followed system instructions and used the smartphone-based virtual environment without difficulty. No significant simulator sickness was reported or observed. Users rated the smartphone virtual environment as highly realistic. Convergent validity was detected, with many aspects of pedestrian behavior in the smartphone-based virtual environment matching behavior in the kiosk virtual environment. Anticipated correlations between personality and kiosk virtual reality pedestrian behavior emerged for the smartphone-based system. A smartphone-based virtual environment can be usable and valid. Future research should develop and evaluate such a training system.

Research was conducted to review and develop minimum levels for pavement marking retroreflectivity to meet nighttime driving needs. A previous study performed in the 1990s using a computer model called the Computer-Aided Road-Marking Visibility Evaluator resulted in a table of minimum levels of pavement marking retroreflectivity values that FHWA used to develop its initial set of minimum pavement marking retroreflectivity levels. Since then, additional research has been completed as well as development of a newer, more feature-intensive computer model called the Target Visibility Predictor (TarVIP). The research presented used TarVIP to study pavement marking retroreflectivity needs while using the most recently available information pertaining to driver, vehicle, and headlamp trends in the United States. In this research, previous pavement marking research efforts that included findings or recommendations related to minimum retroreflectivity are summarized. Next, a comprehensive survey on the factors that affect pavement marking visibility and minimum RL levels was performed, with key factors identified. They included pavement marking configuration, pavement surface type, vehicle speed, vehicle type, and presence of raised reflective pavement markers. From findings of the key factor reviews, the TarVIP model was used to generate preliminary results that could then be analyzed by sensitivity analysis. The research resulted in a set of recommended minimum pavement marking retroreflectivity levels for typical conditions on U.S. roadways. Limitations of the research were listed as well as concepts for future work.

This paper presents an approach to modeling and simulation of vehicles interacting with the environment (terrain) in a realistic, three-dimensional setting and to assess vehicle mobility based on simulation results. To reliably predict vehicle performance under realistic off-road conditions, lumped-parameter models commonly used in vehicle dynamics are not adequate. In this work, high fidelity, multibody dynamics approach is employed to capture vehicle nonlinear dynamic characteristics. Because all vehicle control forces/moments are generated at the patch where tire and terrain interacts, tire modeling, soil modeling, and tire-soil interaction modeling are critical. In this work, tire is modeled as multiple-input-multiple-output system with parameters determined via high-fidelity physical-based finite element model and/or test data; soil is modeled using the Bekker-Wong approach with parameters determined using high-fidelity physical-based finite element soil model and/or test data. Although the Bekker-Wong approach is relatively old, effective implementation to achieve its fully potential is possible only recently, with the advent of the so-called dynamic terrain database. A computational algorithm for such an implementation is presented. Dynamic terrain allows natural treatment of the multiple-pass problem in spatial and dynamic fashion, as opposed to the approaches found in the literature that can only deal with planar, steady-state rolling in an ad hoc fashion. Tire-terrain interaction is modeled using a hybrid approach of empirical and semi-empirical models. A complete simulation environment can be constructed by integrating all the models and mobility analysis of vehicles be perform on soft terrain. An example is presented to demonstrate the approach. Conclusions and future research directions are presented at the end of the paper.