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Map Data for ADAS

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Handbook of Intelligent Vehicles

Abstract

From their beginnings in the car as a tool for A-to-B navigation, digital maps are experiencing an evolution process that will see them at the forefront of new applications designed to improve active safety and manage fuel consumption. These maps will, in effect, become a new vehicle sensor, with a range exceeding that of camera and radar systems, and an ability to work in all weathers and at night. These new maps will need to be more accurate than those used for navigation, and be fused with a minimized set of map attributes to create new vehicle-interpreted precision maps. This chapter will look at the applications that would benefit from these new maps, which in terms of both safety and energy management applications, provide precise knowledge of the road ahead. This allows the vehicles and drivers to be informed of potentially dangerous situations, and take actions based on exact knowledge of future slopes and curves in the road. In energy management terms, the knowledge of road slope will allow the most fuel-efficient routes to be chosen, and can be used to determine the range of Electric and Hybrid Electric Vehicles (EV/HEV), as well as optimizing engine and transmission for fuel efficiency. We will consider how such maps can be created using a number of different technologies, and how this collection methodology impacts their characteristics. As maps evolve and become more “connected,” the possibilities to update them, and access further geographic data and services, will further increase their usefulness.

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Correspondence to John Craig .

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© 2012 Springer-Verlag London Ltd.

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Craig, J. (2012). Map Data for ADAS. In: Eskandarian, A. (eds) Handbook of Intelligent Vehicles. Springer, London. https://doi.org/10.1007/978-0-85729-085-4_33

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