scholarly journals Critical values of driver response time and its impact on reducing reliability and safety in road traffic

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

Author(s):  
Vipul Mishra ◽  
Richa Ahuja ◽  
N. Nezamuddin ◽  
Geetam Tiwari ◽  
Kavi Bhalla

International standards recommend provision of one ambulance for every 50,000 people to fulfill demand for transporting patients to definitive care facilities in low and middle income countries (LMICs). Governments’ consistent attempt to build capacity of emergency medical services (EMS) in LMICs has been financially demanding. This study is an attempt to assess the feasibility of capacity building of existing EMS in Delhi, India by using taxis as an alternative mode of transport for emergency transportation of road traffic crash victims to enable improvement in response time for road traffic crashes where time criticality is deemed important. Performance of the proposed system is evaluated based on response time, coverage and distance. The system models the performance and quantifies the taxi–ambulance configuration for achieving EMS performance within international standards.


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

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.


2020 ◽  
Vol 1 (2) ◽  
pp. 01-11
Author(s):  
Mohd Firdaus Mohd Siam ◽  
Mohd Hafzi Md Isa ◽  
Abdullah Sukardi ◽  
Azhar Hamzah ◽  
Ahmad Khushairy Makhtar

The Malaysian Institute of Road Safety Research (MIROS) has embarked on the development of an instrumented vehicle that purposely to suit various driver behavioural researches. One of the studies was pertaining to driver distraction. The objectives of this study are to measure the driver distraction in terms of participants’ response time and hit rate using the instrumented vehicle. Besides, the study was also conducted to determine whether road conditions and secondary tasks are associated with the participants’ response time. The results showed that response times generally increased as a function of road segments as well as exposure to secondary tasks. In terms of road segments, longer response times were observed for the more demanding off-ramp and curvy road sections when compared with expressway driving. Furthermore, for the secondary tasks, the participants took a longer duration to respond to the tactile stimulus, particularly for the difficult n-back task.


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

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