All presentations on Dynamic Map for Automated Driving
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De zelfsturende auto is in opmars, maar welke? Gaat het om een zelfstandige robotauto of coöperatieve auto? De overheid zet al jaren in op coöperatieve auto’s. Omdat ze treintje kunnen rijden, verwacht men dat de coöperatieve auto bijdraagt aan doorstroming, milieubesparing en veiligheid. Recent wint de robotauto aan terrein in het Nederlandse beleid.
If motor vehicles are to be truly autonomous and able to operate responsibly on our roads, they will need to replicate—or do better than—the human decision-making process. But some decisions are more than just a mechanical application of traffic laws and plotting a safe path.
Planning the path of an autonomous, agile vehicle in a dynamic environment is a very complex problem, especially when the vehicle is required to use its full maneuvering capabilities. Recent efforts aimed at using randomized algorithms for planning the path of kinematic and dynamic vehicles have demonstrated considerable potential for implementation on future autonomous platforms.
This report explores the impacts that autonomous (also called self-driving, driverless or robotic) vehicles are likely to have on travel demands and transportation planning.
Although recent studies of Shared Autonomous Vehicles (SAVs) have explored the economic costs and environmental impacts of this technology, little is known about how SAVs can change urban forms, especially by reducing the demand for parking.
33 The emergence of automated vehicles holds great promise for the future of transportation. While 34 it commercial sales of fully self-driving vehicles will not commence for several more years, once 35 this is possible, a new transportation mode for personal travel looks set to arrive.
This roadmap is based on surveys and consultations among major European automotive manufacturers and suppliers.
Will technological advances and shifts in social attitudes lead to our no longer owning or driving vehicles? The global auto industry's transformation has far-reaching implications for how we move from point A to point B and, in turn, affects carmakers, energy companies, insurers, health care, government funding, and more. Value shifts as a new ecosystem of mobility emerges.
We present a method for identifying drivable surfaces in difficult unpaved and offroad terrain conditions as encountered in the DARPA Grand Challenge robot race. Instead of relying on a static, pre-computed road appearance model, this method adjusts its model to changing environments.