42,254 research outputs found
Vision-based analysis of pedestrian traffic data
Reducing traffic congestion has become a major issue within urban environments. Traditional approaches, such as increasing road sizes, may prove impossible in certain scenarios, such as city centres, or ineffectual if current predictions of large growth in world traffic volumes hold true. An alternative approach lies with increasing the management efficiency of pre-existing infrastructure and public transport systems through the use of Intelligent Transportation Systems (ITS). In this paper, we focus on the requirement of obtaining robust pedestrian traffic flow data within these areas. We propose the use of a flexible and robust stereo-vision pedestrian detection and tracking approach as a basis for obtaining this information. Given this framework, we propose the use of a pedestrian indexing scheme and a suite of tools, which facilitates the declaration of user-defined pedestrian events or requests for specific statistical traffic flow data. The detection of the required events or the constant flow of statistical information can be incorporated into a variety of ITS solutions for applications in traffic management, public transport systems and urban planning
Driving with Style: Inverse Reinforcement Learning in General-Purpose Planning for Automated Driving
Behavior and motion planning play an important role in automated driving.
Traditionally, behavior planners instruct local motion planners with predefined
behaviors. Due to the high scene complexity in urban environments,
unpredictable situations may occur in which behavior planners fail to match
predefined behavior templates. Recently, general-purpose planners have been
introduced, combining behavior and local motion planning. These general-purpose
planners allow behavior-aware motion planning given a single reward function.
However, two challenges arise: First, this function has to map a complex
feature space into rewards. Second, the reward function has to be manually
tuned by an expert. Manually tuning this reward function becomes a tedious
task. In this paper, we propose an approach that relies on human driving
demonstrations to automatically tune reward functions. This study offers
important insights into the driving style optimization of general-purpose
planners with maximum entropy inverse reinforcement learning. We evaluate our
approach based on the expected value difference between learned and
demonstrated policies. Furthermore, we compare the similarity of human driven
trajectories with optimal policies of our planner under learned and
expert-tuned reward functions. Our experiments show that we are able to learn
reward functions exceeding the level of manual expert tuning without prior
domain knowledge.Comment: Appeared at IROS 2019. Accepted version. Added/updated footnote,
minor correction in preliminarie
Towards Full Automated Drive in Urban Environments: A Demonstration in GoMentum Station, California
Each year, millions of motor vehicle traffic accidents all over the world
cause a large number of fatalities, injuries and significant material loss.
Automated Driving (AD) has potential to drastically reduce such accidents. In
this work, we focus on the technical challenges that arise from AD in urban
environments. We present the overall architecture of an AD system and describe
in detail the perception and planning modules. The AD system, built on a
modified Acura RLX, was demonstrated in a course in GoMentum Station in
California. We demonstrated autonomous handling of 4 scenarios: traffic lights,
cross-traffic at intersections, construction zones and pedestrians. The AD
vehicle displayed safe behavior and performed consistently in repeated
demonstrations with slight variations in conditions. Overall, we completed 44
runs, encompassing 110km of automated driving with only 3 cases where the
driver intervened the control of the vehicle, mostly due to error in GPS
positioning. Our demonstration showed that robust and consistent behavior in
urban scenarios is possible, yet more investigation is necessary for full scale
roll-out on public roads.Comment: Accepted to Intelligent Vehicles Conference (IV 2017
Approaching delivery as a service
This paper explores the new logistics business model of Delivery as a Service, a concept aiming at a more efficient, fast and customer-oriented practice, linking IT solution development, urban logistics operations, supply chain efficiency and new business models. Delivery as a Service (DaaS) is defined as a service-oriented delivery and business processes in line with customer expectations and needs in the on-demand economy. The approach of this paper is an industry report based on evidence collected in multiple exploratory European projects integrating ambitious and strategic findings on Internet of Things, urban planning, consolidation centres, transport optimisation, and clean vehicle use. It contributes to a future scenario of urban logistics business models
Smart mobility: opportunity or threat to innovate places and cities
The concept of the “smart mobility” has become something of a buzz phrase in the planning and transport fields in the last decade. After a fervent first phase in which information technology and digital data were considered the answer for making mobility more efficient, more attractive and for increasing the quality of travel, some disappointing has grown around this concept: the distance between the visionarypotentialthatsmartness is providingis too far from the reality of urban mobility in cities. We argue in particular that two main aspects of smart mobility should be eluded: the first refers to the merely application to technology on mobility system, what we called the techo-centric aspect; the second feature is the consumer-centric aspect of smart mobility, that consider transport users only as potential consumers of a service.
Starting from this, the study critics the smart mobility approach and applications and argues on a“smarter mobility” approach, in which technologies are only oneaspects of a more complex system. With a view on the urgency of looking beyond technology and beyond consumer-oriented solutions, the study arguments the need for a cross-disciplinary and a more collaborative approach that could supports transition towards a“smarter mobility” for enhancing the quality of life and the development ofvibrant cities. The article does not intend to produce a radical critique of the smart mobility concept,denying a priori its utility. Our perspectiveisthat the smart mobility is sometimes used as an evocativeslogan lacking some fundamental connection with other central aspect of mobility planning and governance.
Main research questions are: what is missing in the technology-oriented or in the consumers-oriented smart mobility approach? What are the main risks behind these approaches? To answer this questions the paper provides in Section 2 the rationale behind the paper;Section 3 provides a literature review that explores the evolution on smart mobility paradigm in the last decades analysing in details the “techno-centric”and the “consumer-centric” aspects. Section 4proposes an integrated innovative approach for smart mobility, providing examples and some innovative best practices in Belgium. Some conclusions are finally drawnin Section 5, based on the role of smart mobility to create not only virtual platforms but high quality urban places
New Technologies for Sustainable Urban Transport in Europe
In the past few years, the European Commission has financed several projects
to examine how new technologies could improve the sustainability of European
cities. These technologies concern new public transportation modes such as
guided buses to form high capacity networks similar to light rail but at a
lower cost and better flexibility, PRT (Personal Rapid Transit) and cybercars
(small urban vehicles with fully automatic driving capabilities to be used in
carsharing mode, mostly as a complement to mass transport). They also concern
private vehicles with technologies which could improve the efficiency of the
vehicles as well as their safety (Intelligent Speed Adaptation, Adaptive Cruise
>.Control, Stop&Go, Lane Keeping,...) and how these new vehicles can complement
mass transport in the form of car-sharing services
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