Toward a Safer Transportation System for Senior Road Users

Senior pedestrians and drivers (65 years and older) are among the most vulnerable road users. As the population of seniors rise, concerns regarding older adults\u27 traffic safety are growing. The advantages of using autonomous vehicles, innovative vehicle technologies, and active transportation are becoming more widely recognized to improve seniors\u27 mobility and safety. This behooves researchers to further investigate senior road users’ safety challenges and countermeasures. This study contributes to the literature by achieving two main goals. First, to explore contributing factors affecting the safety of older pedestrians and drivers in the current transportation system. Second, to examine seniors’ perceptions, preferences, and behaviors toward autonomous vehicles and advanced vehicle technologies, the main components of future transportation systems. To achieve the first objective, crash data involving senior pedestrians and drivers were collected and analyzed. Using structural equation modeling, it was found out that seniors’ susceptibility to pedestrian incidents is a function of level of walking difficulty, fear of falling, and crossing evaluation capability. Senior drivers’ risk factors were found to be driving maneuver & crash location, road features & traffic control devices, driver condition & behavior, road geometric characteristics, crash time and lighting, road class latent factors, as well as pandemic variable. To achieve the second objective, a national survey and a driving simulator experiment were conducted among seniors. The national survey investigates seniors’ perceptions and attitudes to a wide range of AVs features from the perspective of pedestrians and users. Using principal component analysis and cluster analysis, three distinctive clusters of seniors were identified with different perceptions and attitude toward different AV options. The driving simulator experiment examined drivers’ behavior and preferences towards vehicle to infrastructure warning messages. Using the analysis of covariance technique, the results revealed that audio warning message was more effective compared to other scenarios. This finding is consistent with the results of stated preferences of the participants. Female and senior drivers had higher speed limit compliance rate. The findings of this study shed light on key aspects of the current and future of transportation systems that are needed to improve the safety of senior road users

Know Your User: Building a Predictive Model of Consumer Preference for Driverless Cars

INTRODUCTION: This dissertation identifies factors significantly predicting participants\u27 preference for riding in an autonomous vehicle rather than flying on a commercial aircraft. A plethora of research has investigated these two transportation industries independently; however, scarcely any research has considered the impact these two industries will have on each other. Travelers’ preference for riding in an autonomous vehicle rather than a commercial aircraft was investigated through four different scenarios. METHOD: A regression equation was created to predict participants’ preferred travel method and validated through a two-stage process. Stage 1 involved the creation of the regression equation, and a total of 1,008 participants responded to an online survey, providing information on demographics, travel-related behavior, and their preference for riding in an autonomous vehicle rather than flying on a commercial aircraft. Stage 2 involved validation of the regression equation, and 1,008 participants responded to the same online survey. Stage 2 participants’ scores were predicted using the regression equation created in Stage 1. Then, their predicted scores and actual scores were compared to validate the equation throughout four different travel scenarios. RESULTS: In Stage 1, a backward stepwise regression assessed the twenty predictive factors (age, gender, ethnicity, social class, price, perceived value, familiarity, fun factor, wariness of new technology, personality (openness, conscientiousness, extraversion, agreeableness, and neuroticism), general vehicle affect, general airplane affect, vehicle comfort, vehicle external factors, airplane comfort, and airplane external factors). These factors were tested in four different scenarios, which varied only in the length of time participants would spend traveling. CONCLUSION: A predictive model was created for each scenario, and then all four models were validated in Stage 2 using participants’ predicted scores and actual scores. Models were validated using a t-test, correlation, and comparison of cross-validated R2. The most robust model was for the four-hour trip, with six variables significantly predicting participants’ preferred travel method, which accounted for 50.7% of the variance in the model (50.1% adjusted). Upper Social Class, Vehicle Affect, Airplane Affect, and Vehicle Comfort were the only significant predictors throughout all four scenarios. These four predictors will help other researchers and experts in the vehicle industry identify the first adopters of this new technology. The implications of the results and suggestions for future research are discussed

Factors influencing learner driver experiences [Road Safety Grant Report 2009-003]

When compared with more experienced drivers, new drivers have a higher crash risk. This study examined the experiences of learner drivers in Queensland and New South Wales in order to develop an understanding of the factors that influenced them while learning to drive. This will enable the development of more effective licensing systems. The research was informed by a number of heoretical perspectives, particularly social learning theory. Participants were recruited from driver licensing centres as soon as they passed their practical driving test to attain a provisional licence. Of those approached, 392 new drivers from capital cities and regional locations in Queensland and New South Wales completed a 35 minute telephone interview that collected information on a range of personal, social, environmental and socio-demographic factors. Participants were obtaining their licence before several changes to the licensing systems in both Queensland and New South Wales were made in 2007. Several implications for countermeasure development resulted from this research. These included ensuring licensing authorities carefully consider mandating a minimum number of hour of practice as it may inadvertently suppress the amount of practice that some learners obtain. Licensing authorities should consider the use of logbooks for learner drivers, even if there is no minimum amount of supervised practice required as it may assist learners and their supervisors structure their practice more effectively. This research also found that the confidence of learner drivers increases between when they first obtain their learner licence and when they obtain their provisional licence. This is an important issue requiring further attention by licensing authorities

Teenagers and Automated Vehicles: Are They Ready to Use Them?

ABSTRACT: Mobility needs, expectations, and concerns vary across age groups and are closely linked to users' views on the future of the road transport system. Automated vehicles are expected to have a significant impact on the future of the road transport system, and pilot deployments are increasingly being tested in Europe and beyond, which is also thanks to the evolving regulatory landscape. As a result, several studies have started to analyse citizens' attitudes towards this technology. However, very few studies have focused on teenagers' views on automated vehicles, although today's children and teenagers could be among the first users of such vehicles. Studying teenagers and the way they envisage automated vehicles in the future is of particular significance in defining transport planning strategies and supporting upcoming policy orientations. To cover this gap, the present study aims to explore teenagers' views about automated vehicles and whether and how they could fit into their future transport setting. A series of on-line and face-to-face focus groups, a demonstration of an automated vehicle prototype, supporting engagement activities, and a post-pre survey were used to collect their views on the topic. The results show that even though the teenagers acknowledged the potential advantages, they also expressed concerns in relation to the interactions with other road users, to automated driving systems' reliability, to safety, and to data privacy. In particular, these safety concerns revealed an unwillingness on the part of the teenagers to be among the first users of automated vehicles.This research has been funded by the European Commission Joint Research Centre Institutional Funds

Emerging Technologies With Potential Care and Support Applications for Older People: Review of Gray Literature

BACKGROUND:The number of older people with unmet care and support needs is increasing substantially due to the challenges facing the formal and informal care systems. Emerging technological developments have the potential to address some of the care and support challenges of older people. However, limited work has been done to identify emerging technological developments with the potential to meet the care and support needs of the aging population. OBJECTIVE:This review aimed to gain an overview of emerging technologies with potential care and support applications for older people, particularly for those living at home. METHODS:A scoping gray literature review was carried out by using the databases of 13 key organizations, hand searching reference lists of included documents, using funding data, and consulting technology experts. A narrative synthesis approach was used to analyze and summarize the findings of the literature review. RESULTS:A total of 39 documents were included in the final analysis. From the analysis, 8 emerging technologies were identified that could potentially be used to meet older people's needs in various care and support domains. These emerging technologies were (1) assistive autonomous robots; (2) self-driving vehicles; (3) artificial intelligence-enabled health smart apps and wearables; (4) new drug release mechanisms; (5) portable diagnostics; (6) voice-activated devices; (7) virtual, augmented, and mixed reality; and (8) intelligent homes. These emerging technologies were at different levels of development, with some being trialed for care applications, whereas others being in the early phases of development. However, only a few documents mentioned including older people during the process of designing and developing these technologies. CONCLUSIONS:This review has identified key emerging technologies with the potential to contribute to the support and care needs of older people. However, to increase the adoption of these technologies by older people, there is a need to involve them and other stakeholders, such as formal and informal carers, in the process of designing and developing these technologies