Driver Response Time to Left-Turning Vehiclesat Traffic Signal Controlled Intersections

Author(s):  
Shady Attalla ◽  
Ryan Toxopeus ◽  
Sam Kodsi ◽  
Michele Oliver
2016 ◽  
Vol 19 (1) ◽  
pp. 142-148
Author(s):  
Andrzej Kornacki ◽  
Jacek Wawrzosek ◽  
Andrzej Bochniak ◽  
Andrzej Szymanek ◽  
Halina Pawlak

2018 ◽  
Author(s):  
Ryan Toxopeus ◽  
Shady Attalla ◽  
Sam Kodsi ◽  
Michele Oliver

2017 ◽  
Vol 111 (5) ◽  
pp. 401-410
Author(s):  
Eugene A. Bourquin ◽  
Robert Wall Emerson ◽  
Dona Sauerburger ◽  
Janet Barlow

Introduction A new market trend offers long canes for individuals with visual impairments in a variety of colors; however, the impact of these colors is unknown to orientation and mobility (O&M) specialists and individuals who are blind or who have low vision. The authors examined the impact of cane color on drivers’ yielding behaviors; also, cane display effectiveness was assessed. Methods At traffic signal–controlled intersections, drivers’ yielding responses (yield–no yield and seconds to crosswalk) were recorded by two raters when a pedestrian presented one of two conditions (display and flagging) with four differently colored long canes (white, black, yellow, and green). Results In trials where the pedestrian used a flagging cane technique, the white cane achieved 290% more yielding than the green cane, 100% more yielding than the yellow cane, and 40% more yielding than the black. Statistical differences were found between the white-with-red cane and the yellow and green canes. The measure of drivers’ latency for moving forward was not statistically different between trials in which a pedestrian displayed a white cane at the crosswalk and trials in which no pedestrians were present. Discussion Cane color appears to have a substantial effect on drivers’ yielding responses. The results also indicate only a slight driver response to a highly visible cane display, confirming the results of previous studies that recommended more potent pedestrian movements to mitigate the threat from turning vehicles. Implications for practitioners O&M specialists and cane travelers need to consider the options for cane color when using a cane to cross streets. A white cane, flagged at the onset of the walk signal, can achieve more desirable responses from drivers than can the long canes of other colors. More effective cane behaviors exhibited by pedestrians who are visually impaired should always be considered by O&M instructors in order to influence drivers.


Author(s):  
Mike Blommer ◽  
Reates Curry ◽  
Dev Kochhar ◽  
Rads Swaminathan ◽  
Walter Talamonti ◽  
...  

Blommer et al. (2015) reported on a simulator study that investigated a driver engagement (DE) strategy designed to keep the driver-in-the-loop during automated driving in the face of two different types of secondary tasks. The method, first reported by Carsten et al. (2012), involved driving in fully automated driving mode for 6 minutes followed by 1 minute of manual driving, after which this fixed schedule was repeated several times throughout the drive. This scheduled strategy was compared to a reference condition in which different participants experienced continuous automated driving without interruptions. For each condition, some participants watched a video and others listened to the radio. All drives ended in automated driving mode with a surprise forward collision (FC) hazard to which the participant had to manually intervene. Compared to video watchers, radio listeners responded faster, looked to the road scene more, and they were more often looking forward at FC event onset. The DE strategy had no effect on radio listeners. In contrast, video watchers responded to the hazard more quickly with the scheduled strategy than without it. However, there was no reliable statistical difference between DE conditions in percent-eye-glance-time looking to the forward road scene during automated driving or in the number of drivers looking forward at FC event onset. This paper presents additional analyses of off-road eye glance behavior and finds no relationship between how long people were looking away prior to receiving a Forward Collision Warning (FCW) and driver response time (RT). About 95% of all video watching drivers glanced back to the road within 20 sec regardless of the automated driving condition. Approximately 85% of glances away from the road in the scheduled mitigation condition were 7 sec or less.


Author(s):  
Yilmaz Hatipkarasulu ◽  
Brian Wolshon

The car-following process consists of a stimulus-response relationship between vehicles in which the driver of the following vehicle reacts to the actions of the lead vehicle after a time lag. Since the 1950s, the car-following phenomenon has been studied and analyzed, resulting in various models and algorithms. Throughout this period, driver response time lag has always been assumed to be a constant value for the driver at all times, regardless of the approach and level of detail of the model. The primary shortcoming of a constant time lag is that it introduces a number of strong assumptions that do not concur with human nature. To address the problems associated with constant time lag, an independent response time lag module was developed that can be used in any car-following model or algorithm without changing its fundamental mathematical structure. One of the most appealing aspects of this module is its flexible and transparent structure that can easily be adapted to and calibrated for any model or simulation algorithm. The development and structure of the module are described, including the fuzzy definitions of driving states, fuzzy rule extraction, and fuzzy time lag assignment. Statistical and graphical evaluations of the module performance are also included by integrating the module to a proportional car-following model. In the graphical evaluation, the module improved the model performance significantly by providing more precise timing for the driver response. Both Kolmogorov–Smirnov and root-mean-square error tests confirmed that the use of the module improves the car-following model performance.


2018 ◽  
Author(s):  
Ryan Toxopeus ◽  
Shady Attalla ◽  
Sam Kodsi ◽  
Michele Oliver

2019 ◽  
Vol 22 (4) ◽  
pp. 721-731
Author(s):  
Philippe Rauffet ◽  
Assaf Botzer ◽  
Christine Chauvin ◽  
Farida Saïd ◽  
Camille Tordet

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