The autonomous car - A blessing or a curse for the future of low carbon mobility? An exploration of likely vs. desirable outcomes

Certain developed countries have experienced the ‘peak car’ phenomenon. While this remains to be confirmed longitudinally, it looks certain that future mobility in Europe and elsewhere will be shaped by a particular technological development: driverless or autonomous transport. The ‘autonomous car’ ignites the imagination, yet the research and debate on this topic largely focus on the ‘autonomous’ and not adequately on the ‘car’ element. Like any new technological development, autonomous transport presents ample opportunities to better our mobility system, but similarly it carries risks and can lead into a future mobility that exacerbates, rather than relieves, current deficiencies of our mobility systems, including its high carbon and high cost characteristics. Now it is high time to explore these, before we lock ourselves into the autonomous car future. Using Low Carbon Mobility (LCM) as a guiding framework to assess mobility patterns and based on an extensive literature review, this paper aims to explore where there is a gap between the likely and desirable outcomes when developing the autonomous car and suggest how we might reduce it. Moreover, enhancing on global empirical evidence and forecasts about the opportunities and threats emerging from ICT deployment in transport and initial evidence on the development of the autonomous car, the paper concludes that a desirable outcome will only come if technological development will be accompanied by a social change. A change where public and sharing will be seen as superior to private and individual transport, could make the autonomous car a blessing

Using Argumentation in a French Agrifood Chain Application: Technical Report

Evaluating food quality is a complex process since it relies on nu- merous criteria historically grouped into four main types: nutritional, sensorial, practical and hygienic qualities. They may be completed by other emerging preoccupations such as the environmental impact, eco- nomic phenomena, etc. However, all these aspects of quality and their various components are not always compatible and their simultaneous improvement is a problem that sometimes has no obvious solution, which corresponds to a real issue for decision making. This paper proposes a decision support method guided by the objectives de ned for the end products of an agrifood chain. It is materialized by a backward chaining approach based on argumentation

Ethical Issues in Transportation

Ethics is a discipline dealing with the set of rules, principles and beliefs used to judge the value of human actions. Ethics are relevant in the transportation sector due to the diversity and the social relevance of its effects, both positive and negative. Normative assessments of transportation plans and policies invoked by policy-makers, researchers and activists often use concepts such as equality, equity, fairness and justice, which are informed by ethical views. Despite the increased interest in these issues in policy debates and research, there are few examples of actual attempts to explicitly address them in transport planning. This entry presents contemporary perspectives around ethical question in transportation, including social understandings of accessibility, risk and environmental effects, as well as a review of transportation project evaluation methods and the implications of ethics for policy-makers, researchers, and individuals and companies making decisions in the transportation market

Fusion de données redondantes : une approche explicative

National audienceNous nous intéressons, dans le cadre du projet ANR Qualinca au trai-tement des données redondantes. Nous supposons dans cet article que cette re-dondance a déjà été établie par une étape préalable de liage de données. La question abordée est la suivante : comment proposer une représentation unique en fusionnant les "duplicats" identifiés ? Plus spécifiquement, comment décider, pour chaque propriété de la donnée considérée, quelle valeur choisir parmi celles figurant dans les "duplicats" à fusionner ? Quelle méthode adopter dans le but de pouvoir, par la suite, retracer et expliquer le résultat obtenu de façon trans-parente et compréhensible par l'utilisateur ? Nous nous appuyons pour cela sur une approche de décision multicritère et d'argumentation

An ethical assessment of low carbon vehicles using cost benefit analysis

Global concerns about climate change, as confirmed at COP21, have led to lower carbon emissions environmental policies, particularly in the road transport sector. Through an empirical analysis of low carbon vehicle (LCV) policies in California, this paper contrasts the findings from diverse distribution theories between income quintiles - used as a proxy for societal groups - to address vertical equity concerns and offer an overview of impact distribution to policy makers. Thus, it contributes in operationalising ethical theories within transport cost benefit analysis and revisiting impact distribution when promoting low carbon vehicles. Findings indicate that manufacturer penalties are the most effective policy measure to avoid cost transfer between stakeholders. Yet, the analysis shows that those purchasing small LCVs may face disproportional vehicle purchase cost increases which needs to be considered by policy makers. Thus, this paper makes a methodological contribution regarding CBA in practice as well as providing policy relevant recommendations

Optimal Serial Distributed Decision Fusion

The problem of distributed detection involving N sensors is considered. The configuration of sensors is serial in the sense that the (j - 1)th sensor passes its decision to the jth sensor and that the jth sensor decides using the decision it receives and its own observation. When each sensor employs the Neyman-Pearson test, the probability of detection is maximized for a given probability of false alarm, at the Nth stage. With two sensors, the serial scheme has a performance better than or equal to the parallel fusion scheme analyzed in the literature. Numerical examples illustrate the global optimization by the selection of operating thresholds at the sensors

Optimal Distributed Decision Fusion

The problem of decision fusion in distributed sensor system is considered. Distributed sensors pass their decisions about the same hypotheses to a fusion center that combines them into a final decision. Assuming that the semor decisions are independent from each other conditioned on each hypothesis, we provide a general proof that the optimal decision scheme that maximizes the probability of detection at the fusion for fixed false alarm probability comists of a Neyman-Pearson test (or a randomized N-P test) at the fusion and likelihood-ratio tests at the sensors

Optimal Decision Fusion in Multiple Sensor Systems

The problem of optimal data fusion in the sense of the Neyman- Pearson (N-P) test in a centralized fusion center is considered. The fusion center receives data from various distributed sensors. Each sensor implements a N-P test individually and independently of the other sensors. Due to limitations in channel capacity, the sensors transmit their decision instead of raw data. In addition to their decisions, the sensors may transmit one or more bits of quality information. The optimal, in the N-P sense, decision scheme at the fusion center is derived and it is seen that an improvement in the performance of the system beyond that of the most reliable sensor is feasible, even without quality information, for a system of three or more sensors. If quality information bits are also available at the fusion center, the performance of the distributed decision scheme is comparable to that of the centralized N-P test. Several examples are provided and an algorithm for adjusting the threshold level at the fusion center is provided