Global climate agreements call for action and an integrated perspective on mobility, energy and overall consumption. Municipalities in dense, urban areas are challenged with facilitating this transition with limited space and energy resources, and with future uncertainties. One important aspect of the transition is the adoption of electric vehicles, which includes the adequate design of charging infrastructure. Another important goal is a modal shift in transportation. This study investigated over 80 urban mobility policy measures that are in the policy roadmap of two of the largest municipalities of the Netherlands. This analysis consists of an inventory of policy measures, an evaluation of their environmental effects and conceptualizations of the policy objectives and conditions within the mobility transitions. The findings reveal that the two municipalities have similarities in means, there is still little anticipation of future technology and policy conditions could be further satisfied by introducing tailored measures for specific user groups.
BACKGROUND: Mobility is a key determinant and outcome of healthy ageing but its definition, conceptual framework and underlying constructs within the physical domain may need clarification for data comparison and sharing in ageing research. This study aimed to (1) review definitions and conceptual frameworks of mobility, (2) explore agreement on the definition of mobility, conceptual frameworks, constructs and measures of mobility, and (3) define, classify and identify constructs.METHODS: A three-step approach was adopted: a literature review and two rounds of expert questionnaires (n = 64, n = 31, respectively). Agreement on statements was assessed using a five-point Likert scale; the answer options 'strongly agree' or 'agree' were combined. The percentage of respondents was subsequently used to classify agreements for each statement as: strong (≥ 80%), moderate (≥ 70% and < 80%) and low (< 70%).RESULTS: A variety of definitions of mobility, conceptual frameworks and constructs were found in the literature and among respondents. Strong agreement was found on defining mobility as the ability to move, including the use of assistive devices. Multiple constructs and measures were identified, but low agreements and variability were found on definitions, classifications and identification of constructs. Strong agreements were found on defining physical capacity (what a person is maximally capable of, 'can do') and performance (what a person actually does in their daily life, 'do') as key constructs of mobility.CONCLUSION: Agreements on definitions of mobility, physical capacity and performance were found, but constructs of mobility need to be further identified, defined and classified appropriately. Clear terminology and definitions are essential to facilitate communication and interpretation in operationalising the physical domain of mobility as a prerequisite for standardisation of mobility measures.
In the Interreg Smart Shared Green Mobility Hubs project, electric shared mobility is offered through eHUBs in the city. eHUBs are physical places inneighbourhoods where shared mobility is offered, with the intention of changing citizens’ travel behaviour by creating attractive alternatives to private car use.In this research, we aimed to gain insight into psychological factors that influence car owners’ intentions to try out shared electric vehicles from an eHUB in order to ascertain:1. The psychological factors that determine whether car owners are willing to try out shared electric modalities in the eHUBs and whether these factors are identical for cities with different mobility contexts.2. How these insights into psychological determinants can be applied to entice car owners to try out shared electric modalities in the eHUBs.Research was conducted in two cities: Amsterdam (the Netherlands) and Leuven (Belgium). An onlinesurvey was distributed to car owners in both cities inSeptember 2020 and, additionally, interviews wereheld with 12 car owners in each city.In general, car owners from Amsterdam and Leuven seem positive about the prospect of having eHUBs in their cities. However, they show less interest inusing the eHUBs themselves, as they are satisfied with their private car, which suits their mobility needs. Car owners mentioned the following reasons for notbeing interested in trying out the eHUBs: they simply do not see a need to do so, the costs involved with usage, the need to plan ahead, the expected hasslewith registration and ‘figuring out how it works’, having other travel needs, safety concerns, having to travel a distance to get to the vehicle, and a preferencefor ownership. Car owners who indicated that they felt neutral, or that they were likely to try out an eHUB, mentioned the following reasons for doing so:curiosity, attractive pricing, convenience, not owning a vehicle like those offered in an eHUB, environmental concerns, availability nearby, and necessity when theirown vehicle is unavailable.In both cities, the most important predictor determining car owners’ intention to try out an eHUB is the perceived usefulness of trying out an eHUB.In Amsterdam, experience with shared mobility and familiarity with the concept were the second and third factors determining car owners’ interest in tryingout shared mobility. In Leuven, pro-environmental attitude was the second factor determining car owners’ openness to trying out the eHUBs, and agewas the third factor, with older car owners being less likely to try one out.Having established that perceived usefulness was the most important determinant for car owners to try out shared electric vehicles from an eHUB, weconducted additional research, which showed that, in both cities, three factors contribute to perceived usefulness, in order of relevance: (1) injunctive norms(e.g., perceiving that society views trying out eHUBs as correct behaviour); (2) trust in shared electric mobility as a solution to problems in the city (e.g., expecting private car owners’ uptake of eHUBs to contributeto cleaner air, reduce traffic jams in city, and combat climate change); and (3) trust in the quality and safety of the vehicles, including the protection of users’privacy. In Amsterdam specifically, two additional factors contributed to perceived usefulness of eHUBs: drivers’ confidence in their capacity to try out anunfamiliar vehicle from the eHUB and experience of travelling in various modes of transport.Drawing on the relevant literature, the results of our research, and our behavioural expertise, we make the following recommendations to increase car users’ uptake of shared e-mobility:1. Address car owners’ attentional bias, which filters out messages on alternative transport modes.2. Emphasise benefits of (trying out) shared mobility from different perspectives so that multiple goals can be addressed.3. Change the environment and the infrastructure, as infrastructure determines choice of transport.4. For Leuven specifically: target younger car owners and car owners with high pro-environmental attitudes.5. For Amsterdam specifically: provide information on eHUBs and opportunities for trying out eHUBs.
MULTIFILE
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Automated driving nowadays has become reality with the help of in-vehicle (ADAS) systems. More and more of such systems are being developed by OEMs and service providers. These (partly) automated systems are intended to enhance road and traffic safety (among other benefits) by addressing human limitations such as fatigue, low vigilance/distraction, reaction time, low behavioral adaptation, etc. In other words, (partly) automated driving should relieve the driver from his/her one or more preliminary driving tasks, making the ride enjoyable, safer and more relaxing. The present in-vehicle systems, on the contrary, requires continuous vigilance/alertness and behavioral adaptation from human drivers, and may also subject them to frequent in-and-out-of-the-loop situations and warnings. The tip of the iceberg is the robotic behavior of these in-vehicle systems, contrary to human driving behavior, viz. adaptive according to road, traffic, users, laws, weather, etc. Furthermore, no two human drivers are the same, and thus, do not possess the same driving styles and preferences. So how can one design of robotic behavior of an in-vehicle system be suitable for all human drivers? To emphasize the need for HUBRIS, this project proposes quantifying the behavioral difference between human driver and two in-vehicle systems through naturalistic driving in highway conditions, and subsequently, formulating preliminary design guidelines using the quantified behavioral difference matrix. Partners are V-tron, a service provider and potential developer of in-vehicle systems, Smits Opleidingen, a driving school keen on providing state-of-the-art education and training, Dutch Autonomous Mobility (DAM) B.V., a company active in operations, testing and assessment of self-driving vehicles in the Groningen province, Goudappel Coffeng, consultants in mobility and experts in traffic psychology, and Siemens Industry Software and Services B.V. (Siemens), developers of traffic simulation environments for testing in-vehicle systems.
More and more aged people are joining the traffic, either using a passenger car or through a special low speed two-seater for in-city use. For elderly people, self-management in staying mobile is an essential part of their quality of life. However, with increased involvement of elderly in traffic, the risk of serious accidents increases, especially in cities. Fortunately, a rapid development of innovative technology is shown in vehicle design, with focus on advanced driver support, herewith referred to as ‘ambient intelligence’. This holds a promise to improve the safety situation, under the condition that adaption to the elderly driver’s need is accounted for. And that is not a straightforward issue, since ‘no size fits all’. With increasing age, we see an increased variety in driving skills with emphasis on cognitive, perceptual and physical limitations. In addition, people may suffer from diseases with a neurological background or other (cardiopulmonary disease, obesity or diabetes). The partners in this project have expressed the need to survey the feasibility of ‘ambient intelligence’ technology for low-speed vehicles also addressing E-Health functions to bring people safely home or involve medical help in case of health-critical situations. The MAX Mobiel make their vehicle available for that, and will help to guard the elder customer demand. The HAN Automotive Research team carries out the research, in cooperation with the HAN professorship on E-Health. Hence, both the automotive technology part of the HAN University of Applied Sciences as well as expertise from the Health oriented part of the HAN are included, being essential to successfully extend the relevant technologies to a fully integrated elderly driver support system, in the future. Noldus Information Technology is involved on the basis of their knowledge in human monitoring (drive lab) and data synchronization. The St. Maartenskliniek (Nijmegen) brings in their experience with people being restricted in physical or neurological sense.
