Investigating Visual Recognition of Color and Safe Driving in Color-Weak Drivers

2021 ◽  
pp. 036119812110363
Author(s):  
Qingzhou Wang ◽  
Hongyu Wang ◽  
Te Luo ◽  
Lei Shi ◽  
Xin Fan
Keyword(s):  
Eye Movement ◽  
Color Vision ◽  
Recognition Test ◽  
Visual Recognition ◽  
Road Traffic ◽  
Error Rates ◽  
Dominant Factor ◽  
Normal Vision ◽  
Safe Driving ◽  
Traffic Lights

This study examined the visual characteristics of drivers with color weakness to improve their safety while driving. Significantly affected by the traffic environment, drivers with color weakness are not able to recognize traffic lights rapidly and accurately, which endangers traffic safety. In the first part of the research, through a static visual recognition test of color vision using the orthogonal method, the study explored the influence of light intensity, visual recognition distance, and color weakness type on the perception of traffic light colors by participants with color weakness. In the second part, a dynamic visual recognition test of color vision was conducted through simulating the driving environment of urban roads. Eye movement indexes between participants with color weakness and those with normal vision were analyzed by means of different vehicle speeds and time periods. The results indicated that the type of color weakness was the dominant factor affecting visual recognition of traffic lights. The eye movements of participants with deuteranomaly were close to those of people with normal vision, whereas the eye movement index of those with protanomaly and dyserythrochloropsia were significantly different. Distraction, slower responses, and higher color recognition error rates for the traffic lights were major characteristics—all representing risks that increase at night. To reduce the probability of road traffic injury, the driving safety of people with color weakness should be addressed.

Modeling Interstation Travel Speed of Hybrid Bus Rapid Transit within A Bayesian Framework

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Ji-hua Hu ◽  
Jia-xian Liang
Keyword(s):  
Road Traffic ◽  
Travel Speed ◽  
Bayesian Framework ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Important Indicator ◽  
Main Road ◽  
Traffic Lights ◽  
Speed Distribution ◽  
Hybrid Bus

Interstation travel speed is an important indicator of the running state of hybrid Bus Rapid Transit and passenger experience. Due to the influence of road traffic, traffic lights and other factors, the interstation travel speeds are often some kind of multi-peak and it is difficult to use a single distribution to model them. In this paper, a Gaussian mixture model charactizing the interstation travel speed of hybrid BRT under a Bayesian framework is established. The parameters of the model are inferred using the Reversible-Jump Markov Chain Monte Carlo approach (RJMCMC), including the number of model components and the weight, mean and variance of each component. Then the model is applied to Guangzhou BRT, a kind of hybrid BRT. From the results, it can be observed that the model can very effectively describe the heterogeneous speed data among different inter-stations, and provide richer information usually not available from the traditional models, and the model also produces an excellent fit to each multimodal speed distribution curve of the inter-stations. The causes of different speed distribution can be identified through investigating the Internet map of GBRT, they are big road traffic and long traffic lights respectively, which always contribute to a main road crossing. So, the BRT lane should be elevated through the main road to decrease the complexity of the running state.

LIGHT REGULATION SYSTEMS IMPROVEMENT ANALYSIS TO FORECAST THE TRANSPORT FLOWS IN ALMATY

2021 ◽  
Vol 116 (1) ◽  
pp. 299-304
Author(s):  
Assel Aliyadynovna Sailau
Keyword(s):  
Environmental Pollution ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Light Regulation ◽  
Transport Network ◽  
Traffic Flows ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Transport Telematics

The number of vehicles on the roads of Almaty, Kazakhstan is growing from year to year. This brings about an increasing intensity and density of traffic flows in the streets which leads to congestion, decreasing speed of the traffic flow, increasing environmental pollution caused by car emissions, and which can potentially lead to the road traffic accidents (RTA), including fatalities. While the number of injuries grows up mainly due to drivers’ non-compliance with the speed limit, the environmental pollution is caused by longer traffic jams. Therefore, to reduce the level of road traffic injuries and emissions into the environment it is necessary to ensure the uniform movement of traffic flows in cities. Currently, one of the effective ways to do it is the use of transport telematics systems, in particular, control systems for road signs, road boards and traffic lights. The paper presents an analysis of existing systems and methods of traffic light regulation. The  analyses of the systems and methods are based on the use of homogeneous data, that is the data on standard parameters of traffic flows. The need in collecting and analyzing additional semi-structured data on the factors that have a significant impact on the traffic flows parameters in cities is shown as well. The work is dedicated to solving the problem of analysis and forecast of traffic flows in the city of Almaty, Kazakhstan. GPS data on the location of individual vehicles is used as the initial data for solving this problem. By projecting the obtained information onto the graph of the city's transport network, as well as using additional filtering, it is possible to obtain an estimate of individual parameters of traffic flows. These parameters are used for short-term forecast of the changes in the city's transport network.

Traffic Signal Color Recognition Is a Problem for Both Protan and Deutan Color-Vision Deficients

2003 ◽  
Vol 45 (3) ◽  
pp. 495-503 ◽  
Author(s):  
David A. Atchison ◽  
Carol A. Pedersen ◽  
Stephen J. Dain ◽  
Joanne M. Wood
Keyword(s):  
Color Vision ◽  
Response Times ◽  
Reaction Times ◽  
Error Rates ◽  
Traffic Signal ◽  
White Background ◽  
Signal Design ◽  
Traffic Light ◽  
Light Signals ◽  
Signal Color

We investigated the effect of color-vision deficiency on reaction times and accuracy of identification of traffic light signals. Participants were 20 color-normal and 49 color-deficient males, the latter divided into subgroups of different severity and type. Participants performed a tracking task. At random intervals, stimuli simulating standard traffic light signals were presented against a white background at 5° to right or left. Participants identified stimulus color (red/yellow/green) by pressing an appropriate response button. Mean response times for color normals were 525, 410, and 450 ms for red, yellow, and green lights, respectively. For color deficients, response times to red lights increased with increase in severity of color deficiency, with deutans performing worse than protans of similar severity: response times of deuteranopes and protanopes were 53% and 35% longer than those of color normals. A similar pattern occurred for yellow lights, with deuteranopes and protanopes having increased response times of 85% and 53%, respectively. For green lights, response times of all groups were similar. Error rates showed patterns similar to those of response times. Contrary to previous studies, deutans performed much worse than protans of similar severity. Actual or potential applications of this research include traffic signal design and driver licensing.

scholarly journals Cooperative Adaptive Driving for Platooning Autonomous Self Driving Based on Edge Computing

2019 ◽  
Vol 29 (2) ◽  
pp. 213-225 ◽  
Author(s):  
Ben-Jye Chang ◽  
Ren-Hung Hwang ◽  
Yueh-Lin Tsai ◽  
Bo-Han Yu ◽  
Ying-Hsin Liang
Keyword(s):  
Shock Waves ◽  
Traffic Flow ◽  
Road Traffic ◽  
Edge Computing ◽  
Traffic Information ◽  
Velocity Variation ◽  
Traffic Density ◽  
Cruise Control ◽  
Safe Driving ◽  
Butterfly Effect

Abstract Cooperative adaptive cruise control (CACC) for human and autonomous self-driving aims to achieve active safe driving that avoids vehicle accidents or traffic jam by exchanging the road traffic information (e.g., traffic flow, traffic density, velocity variation, etc.) among neighbor vehicles. However, in CACC, the butterfly effect is encountered while exhibiting asynchronous brakes that easily lead to backward shock-waves and are difficult to remove. Several critical issues should be addressed in CACC, including (i) difficulties with adaptive steering of the inter-vehicle distances among neighbor vehicles and the vehicle speed, (ii) the butterfly effect, (iii) unstable vehicle traffic flow, etc. To address the above issues in CACC, this paper proposes the mobile edge computing-based vehicular cloud of the cooperative adaptive driving (CAD) approach to avoid shock-waves efficiently in platoon driving. Numerical results demonstrate that the CAD approach outperforms the compared techniques in the number of shock-waves, average vehicle velocity, average travel time and time to collision (TTC). Additionally, the adaptive platoon length is determined according to the traffic information gathered from the global and local clouds.

scholarly journals Developing Hybrid Simulation Model to Improve Road Traffic Management

2020 ◽  
Vol 4 (01) ◽  
pp. 56-65
Author(s):  
Hayati Mukti Asih
Keyword(s):  
Simulation Model ◽  
Urban Areas ◽  
Traffic Management ◽  
Road Traffic ◽  
Hybrid Simulation ◽  
Simulation Method ◽  
Vital Role ◽  
Light Cycle ◽  
Traffic Light ◽  
Traffic Lights

Yogyakarta has increasing trends in the number of vehicles and consequently intensifying the traffic volume and will effect to higher emission and air pollution. Traffic lights duration plays a vital role in congestion mitigation in the critical intersections of urban areas. This study has objective to minimize the number of vehicles waiting in line by developing the hybrid simulation method. First of all, the MKJI and Webster method were calculated to determine the green traffic light. Then, the simulation model was developed to evaluate the number of vehicles waiting in line according to different duration of green traffic lights from MKJI and Webster method. A case study will then be provided in Pelemgurih intersection located in Yogyakarta, Indonesia for demonstrating the applicability of the developed method. The result shows that the duration of green traffic lights calculated by Webster method provides lower number of vehicles waiting in line. It is due to the short duration of green traffic light resulted by Webster method so that the traffic light cycle becomes shorter and it effects the number of vehicles waiting in line which is lower than MKJI method. The results obtained can help the generating desired decision alternatives that will important for Department of Transportation, Indonesia to enhance the road traffic management with low number of vehicles waiting in line.

The role of driver reliability in road safety

2020 ◽  
Keyword(s):  
Road Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Research Work ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs ◽  
Psychophysiological State ◽  
Road Data

The driver of an automobile is the key part of the “driver–car–road–environment” system, the stable functioning of which determines the efficiency and safety of road traffic. The driver as the operator of the “driver –car–road–environment” system receives most of the information from the road, data from moving and standing objects, road signs, traffic lights, surface conditions and traffic conditions. An analysis of most traffic accidents shows that the weakest part of the “driver–car–road–environment" system, restricting its effectiveness and dependability, is the person. To ensure the necessary dependability and safety, the driver of any vehicle must be careful. This is supported by an appropriate psychophysiological state, which, in turn, depends on many factors. The article presents an analysis of research work taking into account the influence of various factors on the dependability of a vehicle driver. Means and methods of research are described. Recommendations are given on creating a stand for studying the influence of the psychophysiological state of the driver on road safety. Keywords Driver dependability; road traffic; automobile; traffic environment; road accidents; road safety

scholarly journals Change-Point Analysis of Eye Movement Characteristics for Female Drivers in Anxiety

2019 ◽  
Vol 16 (7) ◽  
pp. 1236 ◽  
Author(s):  
Yongqing Guo ◽  
Xiaoyuan Wang ◽  
Qing Xu ◽  
Feifei Liu ◽  
Yaqi Liu ◽  
...  
Keyword(s):  
Least Squares ◽  
Eye Movement ◽  
Change Point ◽  
Traffic Accidents ◽  
Least Squares Method ◽  
Road Traffic ◽  
Change Point Analysis ◽  
Road Traffic Safety ◽  
Movement Characteristics ◽  
Point Analysis

Driver hazard perception is highly related to involvement in traffic accidents, and vision is the most important sense with which we perceive risk. Therefore, it is of great significance to explore the characteristics of drivers’ eye movements to promote road safety. This study focuses on analyzing the changes of drivers’ eye-movement characteristics in anxiety. We used various materials to induce drivers’ anxiety, and then conducted the real driving experiments and driving simulations to collect drivers’ eye-movement data. Then, we compared the differences between calm and anxiety on drivers’ eye-movement characteristics, in order to extract the key eye-movement features. The least squares method of change point analysis was carried out to detect the time and locations of sudden changes in eye movement characteristics. The results show that the least squares method is effective for identifying eye-movement changes of female drivers in anxiety. It was also found that changes in road environments could cause a significant increase in fixation count and fixation duration for female drivers, such as in scenes with traffic accidents or sharp curves. The findings of this study can be used to recognize unexpected events in road environment and improve the geometric design of curved roads. This study can also be used to develop active driving warning systems and intelligent human–machine interactions in vehicles. This study would be of great theoretical significance and application value for improving road traffic safety.

scholarly journals Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

2020 ◽  
Vol 14 (02) ◽  
pp. 196 ◽  
Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Aberrahim Hasbi
Keyword(s):  
Road Traffic ◽  
Green Light ◽  
Optimal Solution ◽  
Ant Colony ◽  
Traffic Data ◽  
Traffic Light ◽  
Traffic Lights ◽  
The Road ◽  
Real Time Traffic ◽  
On The Road

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.

scholarly journals Performance Analysis of V2V and V2I LiFi Communication Systems in Traffic Lights

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Gerardo Hernandez-Oregon ◽  
Mario E. Rivero-Angeles ◽  
Juan C. Chimal-Eguía ◽  
Arturo Campos-Fentanes ◽  
Jorge G. Jimenez-Gallardo ◽  
...  
Keyword(s):  
Mobile Communications ◽  
Communication Systems ◽  
Vehicular Networks ◽  
Low Cost ◽  
Red Light ◽  
Green Light ◽  
Mathematical Expression ◽  
Traffic Light ◽  
Safe Driving ◽  
Traffic Lights

Vehicular networks is a key technology for efficiently communicating both user’s devices and cars for timely information regarding safe driving conditions and entertaining applications like social media, video streaming, and gaming services, among others. In view of this, mobile communications making use of cellular resources may not be an efficient and cost-effective alternative. In this context, the implementation of light-fidelity (LiFi) in vehicular communications could be a low-cost, high-data-rate, and efficient-bandwidth usage solution. In this work, we propose a mathematical analysis to study the average throughput in a road intersection equipped with a traffic light that operates as a server, which is assumed to have LiFi communication links with the front lights of the vehicles waiting for the green light. We further assume that the front vehicle (the car next to the traffic light) is able to communicate to the car immediately behind it by using its own tail lights and the front lights of such vehicle, and so on and so forth. The behavior of the road junction is modeled by a Markov chain, applying the Queueing theory with an M/M/1 system in order to obtain the average queue length. Then, Little’s theorem is applied to calculate the average waiting delay when the red light is present in the traffic light. Finally, the mathematical expression of the data throughput is derived.

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