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Electrification of the automobile is a growing trend and will create both challenges and opportunities for the vehicle manufacturer, road network infrastructure and driver. In addition to innovative fundamental battery and power transfer technologies, electric vehicles will integrate unique driver interfaces, road intelligence, traffic awareness and wireless data communication to provide a complete support system. This networked vehicle will improve efficiency, increase cruising range and contribute to the overall driving enjoyment of an electric or plug-in hybrid-electric vehicle. Through tailored applications created by content and service providers the driver will identify the most efficient travel routes, learn efficient driving behaviors, avoid energy-wasting situations, locate charging stations and have confidence in reaching a destination and returning home.

The economic challenges and environmental imperatives facing the trucking and automobile industries today all point to a pressing need to improve fuel efficiency. Due to increasing volatility of fuel supplies, prices and a growing interest in reducing greenhouse gas emissions, fuel efficiency has taken on new urgency. In the long-haul trucking industry this is especially important given the fact that fuel accounts for a significant share of fleet operating costs. To this end Daimler and NAVTEQ have developed a system to improve fuel economy and reduce CO₂ emissions through the integration of digital map data into Advanced Driver Assistance Systems or ADAS. Digital road map attributes, especially road slope have been demonstrated to enable powertrain controls to anticipate road inclination changes and use this information to predictively enhance load management optimization versus the reactive approach afforded by current technology.

Digital maps are being linked to Advanced Driver Assistance Systems (ADAS) in numerous ways. Digital map data effectively provides a road predictive capability with a quasi-infinite range. We study the use of digital map attribute data in the enhancement of Electronic Stability Control (ESC). An offline study was conducted using real-world steering input records from participants in a prior ESC study at the National Advanced Driving Simulator (NADS). In all cases, the RMS yaw rate error was significantly reduced using the map-enhanced algorithm over the traditional ESC system. Additionally, many cases also showed improvements in other measures, such as lane deviation.