Usability of Local Traffic Density as Basis for Advanced Driver Assistance Systems

Abstract

Advanced driver assistance systems’ objective is to support the driver in traffic by enhancing driving comfort and safety. In order to achieve optimal results, all relevant factors retroacting on the drivers’ needs and expectations have to be included in the system design. State-of-the-art systems do not introduce traffic conditions as an input parameter. Since traffic is one of the main external factors influencing human driving behaviour, user acceptance and usability are limited. This paper describes the first steps of a development process leading to a traffic adaptive assistance system, taking Adaptive Cruise Control as an example. All the works are done based on a data set of a simulator study conducted in the DLR motion driving simulator. Two main objectives are addressed in the paper. First, human driving behaviour is analysed regarding the two driving tasks of following and approaching a vehicle in the same lane. This is done by statistically evaluating dynamic data. Various influences of subjective perceived traffic density can be found which can be used for adapting systems’ characteristics. Concerning the approach task, an additional experiment should be performed in the future to verify the portrayed findings. In the second part of the paper, the results for improving the estimation of perceived traffic density are presented based on the concept of coverage level. The proposed algorithms show good estimation performance with the capability of online processing.