GAIN (2012-2014)

The aim of the GAIN, GAlileo for INteractive driving, project is to develop and finalize the Enhanced Active Green Driving (EAGD) system for real time optimization and reduction of CO2 emission and fuel consumption.

The final system will automatically regulate the vehicle speed according to the vehicle position, legal speed limitation and lane geometry. Within the GAIN project, a refined positioning algorithm which is based on EGNOS/EDAS data will be developed. Further, the concept of position integrity is introduced and used to innovatively detect multipath in urban areas. Furthermore, communication through Vehicle-to-Vehicle standards will be used to improve the Electronic Horizon to also contain dynamic information about other vehicles present on the road.

The steadily increasing road traffic density in Europe is causing considerable negative effects such as traffic congestion, accidents and increasing CO2 emissions. Mobility accounts for a large share of resource consumption, pollution and greenhouse gas emissions. In particular, road transport is responsible for more than 70% of all transport related CO2 emissions, which increased by 30% since 1990 [12]. This trend is expected to continue in the following years.

Today, many efforts are made to reduce energy consumption of vehicles. Research of Daimler has demonstrated that fuel consumption could potentially be reduced up to 30% by driving a vehicle in an economical way. Anticipation of the road ahead allows a smooth driving style resulting in a decreased consumption. Information about the road layout ahead is obtained from advanced digital map data that contain curvature and slope information. For instance, the study shows a consumption decrease from 13.1l/100km to 9.8l/100km at 60km/h by selection of the correct gear ratio [11]. Thus, systems which actively intervene into the driving process in order to achieve decreased fuel consumption—so called Active Green Driving (AGD) systems—yield an enormous potential for significantly improving traffic efficiency.

 

ss

 

Figure 1 – Example of how current positioning systems may handle uncertain measurements. The solid car is driving along a highway. Due to a biased GPS measurement, the estimated vehicle position is mapped to the exit ramp. As the system cannot detect this error due to an inappropriate integrity concept, the speed will be lowered to 40 km/h. Such erroneous warnings or interventions are reducing the end-user acceptance of the AGD application and have to be eliminated before market introduction.

From a public perspective, there is a strong need for the deployment of such systems. In addition, an improvement of traffic efficiency is also strongly required from the user’s perspective. As mobility is a common requirement for present day professional activities, many people have to rely on efficient and economic transportation in their daily lives. Taking this into account, there is a significant demand (and consequently also a market) for AGD products which decrease fuel consumption and maintenance. This is particularly true for the professional market where fuel consumption is one of the most important expense factors.

Further information are available on the GAIN website.

Status: 
Terminated
Funding: 
FP7 Project