Presentation on theme: "Older drivers fail in intersections: speed discrepancies between older and younger male drivers 學生：董瑩蟬."— Presentation transcript:
Older drivers fail in intersections: speed discrepancies between older and younger male drivers 學生：董瑩蟬
Purpose This paper investigated the driver turning time gap. They study different age group the gap time variation. And found the driver more look direction when they turning.
Reference The older population increasing, Valkonen et al. (1987) expected there was 20% older in the 2020. The higher traffic accident for the older in many countries. (Finland et al.,1994; U.S.A., Evans,1991) Slower motor performance may increased risk at road. (Hakamies-Blomquist,1994)
Method Data collect used video at T-shaped intersections. Three cameras hidden, the first one was to collect driver head movement, the other two was to collect the car from lift and right. The driver divided into two group include turn right (turning) and turn left (opponent drivers).
Method Independence variable –Sex –Age: young, middle-aged, old –Direction the driver first look –Driver turn head number – Vehicle coming from right and left number Dependence variable –Attention –Turning time –Time gap –Time differences
Method The same method from Harrell (1993) The data analysis ANOVA and Sheffe’s test.
Result-attention Turning driver often look right (82%), and before turning was look left (99%). Turning driver turn head number depend on the passing vehicles. (F=171.99; p>0.001) The turning driver age was not difference at attention.
Result-turning time The longer turning time when the turning driver increased age. The longer turning time when the increased passing vehicle.
Result-turning time The age was effect turning time. (F=3.94; P<0.05) The number of passing vehicle was effect turning time. (F=11.1;P<0.01) When the same passing vehicle number. The Scheffe’s test found that the age was effect turning time. r=0.15 (P<0.05) The same driver age situation we can found the vehicles passing was effect turning time. r=0.20 (P<0.01)
Result-time gaps The left coming vehicle type effect the time gap. (F=15.23,P<0.001) But the right coming vehicle type no effect time gap. The left coming vehicle driver age may effect time gap. The coming vehicle was older and middle situation the turning driver time gap was longer than young. The coming vehicle type may effect turning driver time gap.
The coming vehicle from left of driver age effect time differences. (F=3.18,P<0.05) The coming vehicle type may effect the time difference. (F=13.91; P<0.001) The middle-aged has longer time difference than old. The coming motorcycle has short time differences than car.
Discussion The result showed that the attention has on different with different age group. The author has three reasons for this result. The first one was the two lane too easy. The second can’t detailed measure the attention behavior. Last was many cause effect attention.
Discussion The older driver may slower, the similar found Chipman et al.(1992) and Hakamies-Blomqvist(1996). The young has shorter headway distances and drive faster. (Evans et al.,1983; Ota et al.,1996) Blomqvist (1996) found the different age group has different drive style.
Conclusion Turning driver was look left before turning. Turning driver turn head number depend on the passing vehicles. The longer turning time when the turning driver increased age and the increased passing vehicle. The different type coming vehicle was effect time different and time gaps.
My comment This paper let me had a idea which was the pedestrian before road crossing they first look direction. The second was the pedestrian before road crossing they head move number. Third are the coming vehicle type effect the pedestrian crossing time.