AdaptIVe - Automated Driving Applications and Technologies for Intelligent Vehicles

Project manager
Martin Sanfridson
Period
2014-01-01 - 2017-06-30

AdaptIVe will enhance the performance and improve the acceptance of automated driving of cars and trucks. The project develops new and integrated automated functions to improve traffic safety by minimizing the effects of human errors and to enhance traffic efficiency by smoother flows and reduced congestion. The approach is based on a shared control concept, assuring proper collaboration between the driver and the automation system. This is realised using cooperative vehicle technologies, advanced obstacle sensors and adaptive schemes where the level of automation dynamically responds to the situation and driver status. The project will demonstrate and evaluate eight advanced vehicles – seven cars and one truck – with various combinations of automated functions. These implementations will be based on the needs of different environments and levels of traffic complexity, including motorways, urban scenarios and close-distance manoeuvres. Several common features developed in these vehicles will establish fundamental building blocks for the future exploitation of automated driving, in terms of architecture, fault-tolerance, and human factors. Communication technologies will be employed as a key enabler of highly automated schemes supporting cooperative traffic and improving road safety. In addition to the technological and ergonomic aspects, AdaptIVe will address important legal issues that might impact on the successful market introduction of automated systems; in particular product liability and road traffic laws. It will identify the legal implications for manufacturers and drivers and examine the need for corresponding changes in regulation. By demonstrating these results, AdaptIVe will significantly improve the knowledge base for automated driving and strengthen the position of European industries in the area of Intelligent Vehicles and road safety.

Short facts

Project title: AdaptIVe - Automated Driving Applications and Technologies for Intelligent Vehicles
Project type:
Research area:
Road user behaviour
Financier(s):
EU
Partner(s):
AB Volvo, VCC, Chalmers, Lund University, European project partners
Period:
-

Project publications

In this thesis a decision making algorithm for automated cars in lane change situations is presented. The algorithm accounts for situations when all objects detected by the sensor system cannot be classified. The algorithm is partially
Author(s)
Malin Nilsson
Published in
Chalmers tekniska högskola, ISSN 99-2747920-4; EX054/2014, 2014.
Year of publication
2014
We study the problem of optimally controlling autonomous vehicles to safely cross an intersection. The problem is approached by solving an optimal control subproblem for all permutations of crossing sequences. For a chosen crossing sequence, we
Author(s)
Gabriel Rodrigues de Campos, Paolo Falcone, Jonas Sjöberg
Published in
54th IEEE Conference on Decision and Control (CDC), Osaka, Japan, Dec 15–18, 2015 p. 4708-4713.
Year of publication
2015
Methods for how to keep the driver in-the-loop in highly automated vehicles is a research area that gets more and more attention while cars, trucks etc. are evolving to more complex vehicles that can operate on
Author(s)
Kristoffer Andersson, Gábor Szaló
Year of publication
2015
We propose a combined longitudinal and lateral control approach for vehicle platooning within a designated lane. We combine linear frequency and time domain methods, to design longitudinal control that ensures string stability while enforcing safety, comfort
Author(s)
Roozbeh Kianfar, Mohammad Ali, Paolo Falcone, Jonas Fredriksson
Published in
Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, October 2014, Qingdao
Year of publication
2014
Project
AdaptIVe - Automated Driving Applications and Technologies for Intelligent Vehicles

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