VIENA2: A Driving Anticipation Dataset

Action anticipation is critical in scenarios where one needs to react before the action is finalized. This is, for instance, the case in automated driving, where a car needs to, e.g., avoid hitting pedestrians and respect traffic lights. While solutions have been proposed to tackle subsets of the driving anticipation tasks, by making use of diverse, task-specific sensors, there is no single dataset or framework that addresses them all in a consistent manner. In this paper, we therefore introduce a new, large-scale dataset, called VIENA2, covering 5 generic driving scenarios, with a total of 25 distinct action classes. It contains more than 15K full HD, 5s long videos acquired in various driving conditions, weathers, daytimes and environments, complemented with a common and realistic set of sensor measurements. This amounts to more than 2.25M frames, each annotated with an action label, corresponding to 600 samples per action class. We discuss our data acquisition strategy and the statistics of our dataset, and benchmark state-of-the-art action anticipation techniques, including a new multi-modal LSTM architecture with an effective loss function for action anticipation in driving scenarios.Comment: Accepted in ACCV 201

Fusion of Data from Heterogeneous Sensors with Distributed Fields of View and Situation Evaluation for Advanced Driver Assistance Systems

In order to develop a driver assistance system for pedestrian protection, pedestrians in the environment of a truck are detected by radars and a camera and are tracked across distributed fields of view using a Joint Integrated Probabilistic Data Association filter. A robust approach for prediction of the system vehicles trajectory is presented. It serves the computation of a probabilistic collision risk based on reachable sets where different sources of uncertainty are taken into account

Building trust in autonomous vehicles: Role of virtual reality driving simulators in HMI design

The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish trust, depends on effective user-vehicle communication; thus, the importance of Human-Machine Interaction (HMI) is poised to increase. In this work, we propose a methodology to validate the user experience in AVs based on continuous, objective information gathered from physiological signals, while the user is immersed in a Virtual Reality-based driving simulation. We applied this methodology to the design of a head-up display interface delivering visual cues about the vehicle' sensory and planning systems. Through this approach, we obtained qualitative and quantitative evidence that a complete picture of the vehicle's surrounding, despite the higher cognitive load, is conducive to a less stressful experience. Moreover, after having been exposed to a more informative interface, users involved in the study were also more willing to test a real AV. The proposed methodology could be extended by adjusting the simulation environment, the HMI and/or the vehicle's Artificial Intelligence modules to dig into other aspects of the user experience

The Development of a Common Investment Appraisal for Urban Transport Projects.

In December 1990 we were invited by Birmingham City Council and Centro to submit a proposal for an introductory study of the development of a common investment appraisal for urban transport projects. Many of the issues had arisen during the Birmingham Integrated Transport Study (BITS) in which we were involved, and in the subsequent assessment of light rail schemes of which we have considerable experience. In subsequent discussion, the objectives were identified as being:- (i) to identify, briefly, the weaknesses with existing appraisal techniques; (ii) to develop proposals for common methods for the social cost-benefit appraisal of both urban road and rail schemes which overcome these weaknesses; (iii) to develop complementary and consistent proposals for common methods of financial appraisal of such projects; (iv) to develop proposals for variants of the methods in (ii) and (iii) which are appropriate to schemes of differing complexity and cost; (v) to consider briefly methods of treating externalities, and performance against other public sector goals, which are consistent with those developed under (ii) to (iv) above; (vi) to recommend work to be done in the second phase of the study (beyond March 1991) on the provision of input to such evaluation methods from strategic and mode-specific models, and on the testing of the proposed evaluation methods. Such issues are particularly topical at present, and we have been able to draw, in our study, on experience of:- (i) evaluation methods developed for BITS and subsequent integrated transport studies (MVA) (ii) evaluation of individual light rail and heavy rail investment projects (ITS,MVA); (iii) the recommendations of AMA in "Changing Gear" (iv) advice to IPPR on appraisal methodology (ITS); (v) submissions to the House of Commons enquiry into "Roads for the Future" (ITS); (vi) advice to the National Audit Office (ITS) (vii) involvement in the SACTRA study of urban road appraisal (MVA, ITS

Automates: the future of autonomous cars

El futur dels cotxes autònoms sembla brillant, tot i així, personatges com el mateix Elon Musk, entre d'altres, ens porten prometent que serien part de les nostres vides des de fa gairebé deu anys. Tot i això aquí seguim, amb els nostres vehicles que sí, que són genials, però de moment encara no es condueixen sols. Aquestes falses promeses i el concepte de que una màquina condueixi el cotxe per nosaltres encara genera rebuig a la majoria de la població, quan de fet més d'un 90% dels accidents de trànsit avui dia són a causa de l'error humà, i aquestes màquines seran moltes coses, però precisament humanes de moment no són. En aquest projecte s’indaga sobre l’estat actual d’aquests vehicles, que de fet certs serveis de cotxes autònoms ja ronden els carrers d’algunes de les ciutats més grans del món, com ara San Francisco. La clau és descobrir si els vehicles autònoms tenen el potencial real de convertir-se en el servei del futur. Per això, es recorre a les metodologies de Disseny de Futurs, analitzant les tendències del sector i així presentant una sèrie d'Escenaris Futurs. Aquestes metodologies ens permetran entreveure cap on ens porten els desenvolupaments actuals, per així descobrir els passos que hauríem de seguir i els que no per a una correcta i eficient implementació d'aquestes tecnologies en un futur més aviat proper que llunyà.El futuro de los coches autónomos parece brillante, aún así, personajes como el mismísimo Elon Musk, entre otros, nos llevan prometiendo que iban a ser parte de nuestras vidas desde hace ya casi diez años. Sin embargo aquí seguimos, con nuestros vehículos que sí, que son geniales, pero de momento aún no se conducen solos. Estas falsas promesas y el concepto de que una máquina conduzca el coche por nosotros aún genera rechazo en la mayoría de la población, cuando lo cierto es que más de un 90% de los accidentes de tráfico hoy en día son a causa del error humano, y estas máquinas serán muchas cosas pero precisamente humanas no son. En este proyecto se indaga sobre el estado actual de estos vehículos, que de hecho ciertos servicios de coches autónomos ya rondan las calles de algunas de las ciudades más grandes del mundo, como por ejemplo San Francisco. La clave es descubrir si los vehículos autónomos tienen el potencial real de convertirse en el servicio del futuro. Para ello, se recurre a las metodologías de Diseño de Futuros, analizando las tendencias del sector y así presentando una serie de Escenarios Futuros. Estas metodologías nos permitirán vislumbrar hacia dónde nos llevan los desarrollos actuales, para así descubrir los pasos que deberíamos seguir y los que no para una correcta y eficiente implementación de estas tecnologías en un futuro más próximo que lejano.The future of autonomous cars seems bright, even though, famous people like Elon Musk himself, among others, have been making promises around the fact that those cars would be part of our lives for almost ten years, but here we are, with our vehicles that are great, but for now they still don't drive for themselves. These false promises and the concept of a machine driving a car for us still generates rejection in the majority of the population, when the fact is that more than 90% of traffic accidents nowadays are due to human error, and these machines will be sort of things but not humans at all. This project investigates the current state of these vehicles, that in fact these autonomous car services already transit the streets of some of the largest cities in the world, cities like San Francisco. The key is to find out if autonomous vehicles have the real potential to become the service of the future. Therefore, Futures Design methodologies are used, analysing the trends of the sector and thus presenting a series of Future Scenarios. These methodologies will allow us to understand where current developments are leading us, so then we can understand the steps that we should follow as a society and those that we should not for a correct and efficient implementation of these technologies in the near future

Fully automated urban traffic system

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible