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

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

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Managing Autonomous Transportation Demand

“Today we are well underway to a solution of the traffic problem.” This claim, made by Robert Moses in 1948, is as true today as it was then. Which is to say, not at all. In the middle of the last century, the preferred solution to “the traffic problem” was more cement: new highways, bridges, and lanes. Today, the sensible solution includes more sensors and better computers: highly automated vehicles that use existing roadways and roadway networks much more efficiently. This automation, we are told, will make vehicular congestion a “thing of the past.” As in the past, however, this prediction presumes that more capacity necessarily means less congestion. Today’s transportation planners recognize that the relationship between these two concepts is much more complex. This Article argues that automation could significantly increase motor vehicle travel and that this increase could have important consequences for the physical and legal infrastructures in which tomorrow’s vehicles will operate. The next part discusses four key traffic engineering concepts: vehicle miles traveled (VMT), capacity, demand, and the time-cost of travel. Part II explains why automation could increase VMT and then shows how this increase could undermine some of the claims made with respect to congestion and emissions. Part III identifies the potential effects of increased VMT on rural and urban land use and argues that the law can help manage these effects by better internalizing the costs and benefits of motor vehicle travel. Part IV offers preliminary recommendations. A more cautious appraisal of these likely costs and benefits in no way diminishes the immense value of the coming transportation revolution. All transportation and communication innovations — whether cars, carriages, canals, or cables — have involved great uncertainty. Innovation invites speculation