School of Architecture and Civil Engineering

Driver behavior in the transition area from the open road to the built-up area


The dissertation deals in detail with the problem of town entrances. At this point in the road network, the decisive function of the road usually changes and at the same time the motorist is required to adapt his speed behavior to the local conditions. Often, the structural environment at the entrance to the village is not suitable to support this adaptation process, and the high speeds are maintained into the village. In this work, different empirical investigation methods are used to analyze driver behavior over longer distances. Among other things, test drives are carried out with a video measurement vehicle and test drivers, and stationary laser radar equipment is used to record the deceleration processes in the vicinity of the town sign. The evaluations show that motorists decelerate only gently in conventionally designed town entrances, where high speeds occur. The 85 % speeds were between 60 and 85 km/h, 80 to 100 % exceeded speed 50. Significant influences of individual boundary conditions could not be determined. Therefore, a systematic before/after comparison was carried out in an attempt to specifically clarify the effect of innovative redesign measures. In this trial, which ran over several years and included 26 local driveways, significant speed reductions were found after the local driveways had been redesigned (reduction of the 85 % speed by about 13 km/h). However, the analyses made it clear that only measures with elements that had an effect on driving dynamics (in particular, raising or lowering the carriageway) had noticeable effects; purely visual measures were hardly successful. Re-acceleration effects were also found. As a conclusion, it is demanded to embed the redesign measures into the immediately following inner-city section and/or to induce the motorists to initiate the deceleration process already earlier, i.e. about 150 m outside.

This Abstract was translated from German with deepL and could be faulty.

Weitere Infos über #UniWuppertal: