Advance Information on the Road: A Simulator Study of the Effect of Road Markings

Author(s):  
Harald Witt ◽  
Carl G. Hoyos

Accident statistics and studies of driving behavior have shown repeatedly that curved roads are hazardous. It was hypothesized that the safety of curves could be improved by indicating in advance the course of the road in a more effective way than do traditional road signs. A code of sequences of stripes put on right edge of the pavement was developed to indicate to the driver the radius of the curve ahead. The main characteristic of this code was the frequency of transitions from code elements to gaps between elements. The effect of these markings was investigated on a driving simulator. Twelve subjects drove on simulated roads of different curvature and with different placement of the code in the approach zone. Some positive effects of the advance information could be observed. The subjects drove more steadily, more precisely, and with a more suitable speed profile.

2018 ◽  
pp. 147-176 ◽  
Author(s):  
Katie J. Parnell ◽  
Neville A. Stanton ◽  
Katherine L. Plant

2021 ◽  
Author(s):  
Mustafa Suhail Almallah ◽  
Shabna Sayed Mohammed ◽  
Qinaat Hussain ◽  
Wael K. M. Alhajyaseen

The illegal overtaking/crossing of stopped school buses has been identified as one of the leading causes of students’ injuries and fatalities. The likelihood of students in getting involved in a school bus-related crash increases during loading/unloading. The main objective of this driving simulator study was to study the effectiveness of different treatments in improving students’ safety by reducing the illegal overtaking/crossing of stopped school buses. Treatments used in this research are LED, Road Narrowing and Red Pavement. All proposed treatments were compared with the control condition (i.e., typical condition in the State of Qatar). Seventy-two subjects with valid Qatari driving license were invited to participate in this study. Each subject was exposed to three situations (i.e., Situation 1: the school bus is stopped in the same traveling direction, Situation 2: the school bus is stopped in the opposite traveling direction, Situation 3: the school bus is not present at the bus stop). Results showed that LED and Road Narrowing treatments were effective in reducing the illegal overtaking/crossing of stopped school buses. Moreover, the stopping behavior for drivers in LED and Road Narrowing was more consistent compared to the Red Pavement and control conditions. Finally, LED and Road Narrowing treatments motivated drivers to reduce their traveling speed by 5.16 km/h and 5.11 km/h, respectively, even with the absence of the school bus. Taking into account the results from this study, we recommend the proposed LED and Road Narrowing as potentially effective treatments to improve students’ safety at school bus stop locations.


Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.


2015 ◽  
Vol 27 (6) ◽  
pp. 660-670 ◽  
Author(s):  
Udara Eshan Manawadu ◽  
◽  
Masaaki Ishikawa ◽  
Mitsuhiro Kamezaki ◽  
Shigeki Sugano ◽  
...  

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270006/08.jpg"" width=""300"" /> Driving simulator</div>Intelligent passenger vehicles with autonomous capabilities will be commonplace on our roads in the near future. These vehicles will reshape the existing relationship between the driver and vehicle. Therefore, to create a new type of rewarding relationship, it is important to analyze when drivers prefer autonomous vehicles to manually-driven (conventional) vehicles. This paper documents a driving simulator-based study conducted to identify the preferences and individual driving experiences of novice and experienced drivers of autonomous and conventional vehicles under different traffic and road conditions. We first developed a simplified driving simulator that could connect to different driver-vehicle interfaces (DVI). We then created virtual environments consisting of scenarios and events that drivers encounter in real-world driving, and we implemented fully autonomous driving. We then conducted experiments to clarify how the autonomous driving experience differed for the two groups. The results showed that experienced drivers opt for conventional driving overall, mainly due to the flexibility and driving pleasure it offers, while novices tend to prefer autonomous driving due to its inherent ease and safety. A further analysis indicated that drivers preferred to use both autonomous and conventional driving methods interchangeably, depending on the road and traffic conditions.


2018 ◽  
Vol 20 (4) ◽  
pp. 597-619 ◽  
Author(s):  
Katie J. Parnell ◽  
Neville A. Stanton ◽  
Katherine L. Plant

Author(s):  
David K. Damkot ◽  
S. R. Toussie ◽  
Norman R. Akley ◽  
Henry A. Geller ◽  
David G. Whitmore

Author(s):  
Jaejoon Kim

Many visually impaired people worldwide are unable to travel safely and autonomously because they are physically unable to perceive effective visual information during their daily lives. In this research, we study how to extract the character information of the road sign and transmit it to the visually impaired effectively, so they can understand easier. Experimental method is to apply the Maximally Stable External Region and Stroke Width Transform method in Phase I so that the visually impaired person can recognize the letters on the road signs. It is to convey text information to the disabled. The result of Phase I using samples of simple road signs was to extract the sign information after dividing the exact character area, but the accuracy was not good for the Hangul (Korean characters) information. The initial experimental results in the Phase II succeeded in transmitting the text information on Phase I to the visually impaired. In the future, it will be required to develop a wearable character recognition system that can be attached to the visually impaired. In order to perform this task, we need to develop and verify a miniaturized and wearable character recognition system. In this paper, we examined the method of recognizing road sign characters on the road and presented a possibility that may be applicable to our final development.


2021 ◽  
Vol 12 (1) ◽  
pp. 56-65
Author(s):  
R. Abd Rahman ◽  
H. A. Mazle ◽  
W. M. Lim ◽  
M. I. Mohd Masirin ◽  
M. F. Hassan

This descriptive study aims to assess the knowledge and awareness of road safety among university students. The study was conducted among students in Universiti Tun Hussein Onn Malaysia by means of questionnaire disseminated online via social media with shareable link to a Google form. The respondents were self-selected to participate in this study where their responses were self-administrated. Questionnaire consisted of 3 sections included demographic information, knowledge on road signs and road safety law, and road safety awareness. 371 students participated in this study, 66% of them age 23 to 27 years old, 61% were female, 92.5% of respondents have at least one type of license with majority agreed that occurrence of accidents resulted in an increase in road safety awareness. The study found that more than half of the participants could not recognise road sign like parking totally prohibited and speed limit ends here. While, 38% of them correctly identified posted speed limit for expressway. Overall, participants have fair understanding on road safety. Therefore, road safety programmes and education are still relevant to university students as young drivers on the road which is important to increase safety awareness.


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