In most levels of vehicle automation, drivers will not be merely occupants or passengers of automated vehicles. Especially in lower levels of automation, where the driver is still required to serve as a fallback level (SAE L3) or even as a supervisor (SAE L2), there is a need to communicate relevant system states (e.g., that the automated driving system works reliably or that there is a need for manual intervention) via the Human-Machine Interface (HMI). However, there are currently no agreed-upon guidelines that apply specifically to HMIs for automated driving. In this paper, we summarize design recommendations for visual-auditory and visual-vibrotactile HMIs derived from empirical research, applicable standards and design guidelines pertaining to in-vehicle interfaces. On this basis, we derive an initial set of principles and criteria for guiding the development and design of automated vehicle HMIs. A heuristic evaluation methodology consisting of an itemized checklist evaluation that can be used to verify that basic HMI requirements formulated in the guidelines are met is also presented. The heuristic evaluation involves an inspection of the HMI during typical use cases, judging their compliance with the proposed guidelines and documentation of identified instances of non-compliance. Taken together, the combination of the proposed guidelines and the heuristic evaluation methodology form the basis for both design and validation recommendations of automated vehicle HMIs, that can serve the industry in the important evolution of automation within vehicles.

The dynamics of demand responsive ride pooling (DRRP) systems is considered in a mean-field framework. The relevant dimensionless quantities determining the performance and viability of the system are identified. In the presence of an already established dominant market participant with comparable service quality (like, e.g., the private car), the mutual interaction of the actors (i.e., the customers sharing rides) by virtue of the route assignment algorithm gives rise to a discontinuous transition between two strongly different modes of operation. One of them represents the typical (unfavorable) performance of current ride pooling systems, while the other represents a new mode of operation in which virtually all customers use DRRP.

This paper describes a driving simulation experiment, executed on the Daimler Driving Simulator (DDS), in which a filter-based and an optimization-based motion cueing algorithm (MCA) were compared using a newly developed motion cueing quality rating method. The goal of the comparison was to investigate whether optimization-based MCAs have, compared to filter-based approaches, the potential to improve the quality of motion simulations. The paper describes the two algorithms, discusses their strengths and weaknesses and describes the experimental methods and results. The MCAs were compared in an experiment where 18 participants rated the perceived motion mismatch, i.e., the perceived mismatch between the motion felt in the simulator and the motion one would expect from a drive in a real car. The results show that the quality of the motion cueing was rated better for the optimization-based MCA than for the filter-based MCA, indicating that there exists a potential to improve the quality of the motion simulation with optimization-based methods. Furthermore, it was shown that the rating method provides reliable and repeatable results within and between participants, which further establishes the utility of the method.

Aviation contributes significantly to anthropogenic climate change, and one promising possibility for mitigation is eco-efficient flight planning by avoiding climate sensitive regions with only small changes in the aircraft trajectories. Climate sensitive regions result from strong spatial variation of the global climate impact of local non-CO2 emissions, which are expressed by so-called climate change functions. Previous research established high-fidelity climate change functions (CCFs) for aviation water vapour and NOx emissions, and contrail formation with a climate model as inputs for air traffic optimisation. The mitigation potential in this case study is promising but the climate change function simulations are too computationally intensive for real-time calculation and thus cannot be applied operationally. In this study we show for the first time that this problem can be overcome by formulating algorithmic approximations of the global climate impact. Here we approximate water vapour concentration changes from local aviation water vapour emissions, ozone changes from local NOx emissions and methane changes from local NOx emissions (i.e. algorithmic climate change functions; aCCFs) from instantaneous model weather data using regression analysis. Four candidate algorithms are formulated per chemical species and traded off. The final adjusted regression coefficients, indicating how well the aCCFs represent the CCFs, are 0.59, 0.42, and 0.17 for water vapour, ozone and methane. The results show that the meteorology at the time of emission largely controls the fate of the emitted species, where the quality of the aCCF degrades with increasing lifetime of the respective species.

The provision of an adequate liability regime for ADAS technologies is an essential prerequisite for its roll out over the coming decade. Facing to the challenge of future highly automated vehicles, this paper proposed a Human-Machine Transition (HMT) approach as a common conceptual framework for considering Human Machine Interaction (HMI), liability and ethical issues in a unified way. The issues that arise are interrogated from a legal perspective, more specifically liability regimes and that of applied ethics. The paper highlights the issue of the handover/takeover. Potential consequences for insurance companies are then identified accordingly, with the aim to progress towards the sustainable deployment of automated vehicles on public roads.

In high-motorisation, car-dependent countries, transport affordability is intimately linked to the price of oil derived motor fuels, which may become increasingly volatile in the future due to global oil price movements and environmental taxation. The negative impacts of fuel price spikes in terms of increased household expenditure and economic stress are unevenly spatially and socially distributed. Previous research has found that vulnerability to fuel price increases is higher in peripheral, peri-urban and rural areas, and that low income tends to be co-located with high car dependence and low vehicle fuel efficiency, with a compounding effect on vulnerability. The goal of this article is to test these hypotheses for England, providing new evidence on spatial patterns of vulnerability to fuel price increases at the small-area level. We propose a composite vulnerability indicator combining data on income, accessibility, vehicle inspection and vehicle registration for 2011. Within English city-regions, we find little evidence of the socially regressive patterns previously identified in the literature. This is explained by the persistent concentration of poverty in urban cores, as well as by the poor fuel economy of the vehicle fleet in wealthier areas, due to the prevalence of powerful vehicles there. On the other hand, our analysis suggests that the impacts of fuel price increases would be very unequal between city-regions, as the least sensitive metropolitan area (Greater London) is also characterised by high levels of adaptive capacity. We conclude by setting out an agenda for future research on spatial vulnerability to fuel price increases.

For a successful market take-up of plug-in electric vehicles, fast-charging stations along the highway network play a significant role. This paper provides results from a first study on estimating the minimum number of fast-charging stations along the European highway network of selected countries (i.e., France, Germany, the Benelux countries, Switzerland, Austria, Denmark, the Czech Republic, and Poland) and gives an estimate on their future profitability. The combination of a comprehensive dataset of passenger car trips in Europe and an efficient arc-cover-path-cover flow-refueling location model allows generating results for such a comprehensive transnational highway network for the first time. Besides the minimum number of required fast-charging stations which results from the applied flow-refueling location model (FRLM), an estimation of their profitability as well as some country-specific results are also identified. According to these results the operation of fast-charging stations along the highway will be attractive in 2030 because the number of customers per day and their willingness to pay for a charge is high compared to inner-city charging stations. Their location-specific workloads as well as revenues differ significantly and a careful selection of locations is decisive for their economic operation.

The effects of demographic change and the lack of acceptance represent some of the main problems for the public transport infrastructure in rural areas. As a consequence, the development of new transport service options becomes especially relevant for rural communities. The Max-Planck-Institute for Dynamics and Self-Organization developed a new form of Demand Responsive Transport the EcoBus to examine the viability of new DRT systems in rural Germany. Our work draws on customer satisfaction data during the trial runs of the EcoBus. Based on the survey data, this paper develops regression models to explain the determinants of DRT customer satisfaction. Our main findings include the importance of waiting times and the ease of entry for overall customer satisfaction. Nevertheless, we found no evidence that the presence of other guests in the vehicle had any negative impact on customer satisfaction. Findings of other works that women are significantly more likely to use DRT services could not be validated from our data.

Plug-In electric vehicles (PEV) are in an early market phase in almost all markets. Still, the lack of public charging infrastructure is a barrier to PEV adoption. The assessment of future charging infrastructure needs is often based on key figures, mainly the ratio of PEV to public charging points. However, countries differ regarding their framework conditions, e.g. the availability of home charging, and the question of how much public charging infrastructure is needed cannot be answered equally for all countries. Yet, studies analyzing the framework conditions for the medium- to long-term demand for charging infrastructure are rare. Here, we review the existing literature and summarize the evidence for the importance of framework conditions on charging infrastructure needs. Furthermore, we illustrate the literature evidence by comparing the framework conditions for charging infrastructure in different countries based on a comprehensive dataset of framework parameters. We find public charging infrastructure as alternative to home charging is only needed in some densely populated areas. However, framework conditions vary largely among countries. Accordingly, findings from literature for specific countries can only be transferred to other countries to a limited extent.

Objective: Active safety systems, of which antilock braking is a prominent example, are going to play an important role to improve powered two-wheeler (PTW) safety. This paper presents a systematic review of the scientific literature on active safety for PTWs. The aim was to list all systems under development, identify knowledge gaps and recognize promising research areas that require further efforts. Methods: A broad search using “safety” as the main keyword was performed on Scopus, Web of Science and Google Scholar, followed by manual screening to identify eligible papers that underwent a full-text review. Finally, the selected papers were grouped by general technology type and analyzed via structured form to identify the following: specific active safety system, study type, outcome type, population/sample where applicable, and overall findings. Results: Of the 8,000 papers identified with the initial search, 85 were selected for full-text review and 62 were finally included in the study, of which 34 were journal papers. The general technology types identified included antilock braking system, autonomous emergency braking, collision avoidance, intersection support, intelligent transportation systems, curve warning, human machine interface systems, stability control, traction control, and vision assistance. Approximately one third of the studies considered the design and early stage testing of safety systems (n. 22); almost one fourth (n.15) included evaluations of system effectiveness. Conclusions: Our systematic review shows that a multiplicity of active safety systems for PTWs were examined in the scientific literature, but the levels of development are diverse. A few systems are currently available in the series production, whereas other systems are still at the level of early-stage prototypes. Safety benefit assessments were conducted for single systems, however, organized comparisons between systems that may inform the prioritization of future research are lacking. Another area of future analysis is on the combined effects of different safety systems, that may be capitalized for better performance and to maximize the safety impact of new technologies.