scholarly journals Driver Assistance System using in-vehicle Traffic Lights and Signs

2018 ◽  
Vol 7 (2.24) ◽  
pp. 527
Author(s):  
Vaibhav Jain ◽  
Tanay . ◽  
Saransh Gangele ◽  
K Kalimuthu
Keyword(s):  
Traffic Congestion ◽  
Driver Assistance System ◽  
Road Traffic ◽  
Obstacle Detection ◽  
Assistance System ◽  
Vehicular Communication ◽  
Driver Assistance ◽  
Traffic Light ◽  
Traffic Lights ◽  
Road Signs

In recent years, with the advancement of vehicular communication, it is possible to detect various road signs and provide traffic light information to the driver inside the vehicle with the application of heads-up display (HUD). It detects road signs, does basic classifications and accordingly directs the driver to slow down or stop the vehicle. The vehicle’s heads-up display keeps the driver focused by providing road warnings, speed limit, traffic signals and some vital navigation information in the driver’s line of sight(LOS). This system has 4 phases, Image recognition, wireless communication, obstacle detection and driver mechanism. This system aims to create a prototype of a smart driver assistance system which provides better road traffic and driver’s safety in countries with high traffic congestion where fully automated vehicles cannot function effectively. This system can be easily implemented in real time scenarios to reduce accidents and enhance the convenience of driving. 

Smart Cities: Study and Comparison of Traffic Light Optimization in Modern Urban Areas Using Artificial Intelligence

2018 ◽  
Vol 8 (2) ◽  
pp. 10
Author(s):  
Mustapha Kabrane ◽  
Salah-ddine Krit ◽  
Lahoucine El Maimouni
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Road Network ◽  
Smart Cities ◽  
Optimization Techniques ◽  
Traffic Light ◽  
Large Cities ◽  
Traffic Lights ◽  
The Road ◽  
Road Signs

In large cities, the increasing number of vehicles private, society, merchandise, and public transport, has led to traffic congestion. Users spend much of their time in endless traffic congestion. To solve this problem, several solutions can be envisaged. The interest is focused on the  system of road signs: The use of a road infrastructure is controlled by a traffic light controller, so it is a matter of knowing how to make the best use of the controls of this system (traffic lights) so as to make traffic more fluid. The values of the commands computed by the controller are determined by an algorithm which is ultimately, only solves a mathematical model representing the problem to be solved. The objective is to make a study and then the comparison on the optimization techniques based on artificial intelligence1 to intelligently route vehicle traffic. These techniques make it possible to minimize a certain function expressing the congestion of the road network. It can be a function, the length of the queue at intersections, the average waiting time, also the total number of vehicles waiting at the intersection

scholarly journals Driving-Induced Neurological Biomarkers in an Advanced Driver-Assistance System

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 6985
Author(s):  
Iqram Hussain ◽  
Seo Young ◽  
Se-Jin Park
Keyword(s):  
Resting State ◽  
Driver Assistance System ◽  
Driving Simulator ◽  
Road Traffic ◽  
Mental Workload ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance ◽  
Multi Class Classification ◽  
Prediction Approach

Physiological signals are immediate and sensitive to neurological changes resulting from the mental workload induced by various driving environments and are considered a quantifying tool for understanding the association between neurological outcomes and driving cognitive workloads. Neurological assessment, outside of a highly-equipped clinical setting, requires an ambulatory electroencephalography (EEG) headset. This study aimed to quantify neurological biomarkers during a resting state and two different scenarios of driving states in a virtual driving environment. We investigated the neurological responses of seventeen healthy male drivers. EEG data were measured in an initial resting state, city-roadways driving state, and expressway driving state using a portable EEG headset in a driving simulator. During the experiment, the participants drove while experiencing cognitive workloads due to various driving environments, such as road traffic conditions, lane changes of surrounding vehicles, the speed limit, etc. The power of the beta and gamma bands decreased, and the power of the delta waves, theta, and frontal theta asymmetry increased in the driving state relative to the resting state. Delta-alpha ratio (DAR) and delta-theta ratio (DTR) showed a strong correlation with a resting state, city-roadways driving state, and expressway driving state. Binary machine-learning (ML) classification models showed a near-perfect accuracy between the resting state and driving state. Moderate classification performances were observed between the resting state, city-roadways state, and expressway state in multi-class classification. An EEG-based neurological state prediction approach may be utilized in an advanced driver-assistance system (ADAS).

scholarly journals Driver Assistance System Based on Vehicular Communication

IJARCCE ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 139-146
Author(s):  
Somaskandan M ◽  
Avinash B ◽  
Sanjay Raj D
Keyword(s):  
Driver Assistance System ◽  
Assistance System ◽  
Vehicular Communication ◽  
Driver Assistance

scholarly journals Development and testing of braking and acceleration features for vehicle advanced driver assistance system

2022 ◽  
Vol 12 (2) ◽  
pp. 2047
Author(s):  
Johann Carlo Marasigan ◽  
Gian Paolo Mayuga ◽  
Elmer Magsino
Keyword(s):  
Traffic Congestion ◽  
Fuzzy Logic Controller ◽  
Driver Assistance System ◽  
Control Unit ◽  
Assistance System ◽  
Advanced Driver Assistance System ◽  
Driver Assistance ◽  
Safe Distance ◽  
Distance Information ◽  
Urban Planning And Development

<span lang="EN-US">Traffic congestion is a constant problem for cities worldwide. The human driving inefficiency and poor urban planning and development contribute to traffic buildup and travel discomfort. An example of human inefficiency is the phantom traffic jam, which is caused by unnecessary braking, causing traffic to slow down, and eventually coming to a stop. In this study, a brake and acceleration feature (BAF) for the advanced driver assistance system (ADAS) is proposed to mitigate the effects of the phantom traffic phenomenon. In its initial stage, the BAF provides a heads-up display that gives information on how much braking and acceleration input is needed to maintain smooth driving conditions, i.e., without sudden acceleration or deceleration, while observing a safe distance from the vehicle in front. BAF employs a fuzzy logic controller that takes distance information from a light detection and ranging (LIDAR) sensor and the vehicle’s instantaneous speed from the engine control unit (ECU). It then calculates the corresponding percentage value of needed acceleration and braking in order to maintain travel objectives of smooth and safe-distance travel. Empirical results show that the system suggests acceleration and braking values slightly higher than the driver’s actual inputs and can achieve 90% accuracy overall.</span>

Driver Assistance Systems with Communication to Traffic Lights - Configuration of Assistance Systems by Receiving and Transmission and Field Experiments -

2010 ◽  
Vol 22 (6) ◽  
pp. 737-744 ◽  
Author(s):  
Shin Kato ◽  
◽  
Naohisa Hashimoto ◽  
Takeki Ogitsu ◽  
Sadayuki Tsugawa ◽  
...  
Keyword(s):  
Field Experiments ◽  
Driver Assistance System ◽  
The State ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Lights ◽  
Assistance Systems

We propose some driver assistance systems with communication to traffic lights. It proposes the driver assistance system that uses information from the traffic lights with the state of the signal and time of the cycle. The demand traffic lights systems are also proposed. In addition, a consideration of the configuration and the construction of the experiment systems, and some field experiments for driver assistance are described.

scholarly journals Integrated Context-Aware Driver Assistance System Architecture

2013 ◽  
Vol 9 (3) ◽  
pp. 225-240 ◽  
Author(s):  
Elhadi M. Shakshuki ◽  
Wael Alghamdi ◽  
Tarek Sheltami
Keyword(s):  
System Architecture ◽  
Communication Systems ◽  
Driver Assistance System ◽  
Response Times ◽  
Knowledge Exchange ◽  
Assistance System ◽  
Context Aware ◽  
Vehicular Communication ◽  
Driver Assistance ◽  
Hazard Detection

Recently, significant improvements have been made in the area of vehicular communication systems. Furthermore, vehicle-to-vehicle communication is considered a key concept for keeping roads safe. An efficient implementation of these systems is necessary to ensure the safety of driving situations and to reduce the collision rates. This paper proposes a Context-Aware Driver Assistance System that links drivers with the physical environment surrounding them using multiple types of sensors and traffic systems as well as considering the senior driver's difficulties and the system processing time. This is achieved by developing a warning system that assists drivers to avoid collisions and improve their response times. The proposed system architecture consists of a set of components to process the user's request such as parking assistance, and to provide responses and advices when needed. These components include communication, knowledge exchange, knowledge update, and context-history. Also, it includes other processes such as context-history manipulation, hazard detection, and hazard detection control. The main goal of the proposed system is to reduce the number of car accidents and improve driver's decisions. The NXT Robotic environment is used to demonstrate the feasibility of the proposed system.

Microcontroller-Based Intelligent Traffic Signal Controller Design

2014 ◽  
Vol 998-999 ◽  
pp. 621-625
Author(s):  
Hong Ke Xu ◽  
Jia Yu Yang ◽  
Ming Qiang Song ◽  
Yong Zhao Qu ◽  
Xiao Hong Wang
Keyword(s):  
Traffic Congestion ◽  
Road Traffic ◽  
Traffic Signal ◽  
Input Device ◽  
Traffic Light ◽  
Two Phase ◽  
Traffic Condition ◽  
Display Module ◽  
Traffic Lights ◽  
Manual Input

With the road traffic congestion problems become more and more serious, and the current traffic lights don’t possess the function of revising timely and flexible, it can't meet the requirements of real-time controlling and make the traffic in intersection more efficient. The design of Microcontroller-based traffic signal controller fixes this problem. It based on STC90C51 as CPU solutions; LED lights and digital pipe were used as display module; 8 independent keyboards were used as the only manual input device; Software used the C programming language. The intelligent traffic light system covered the multi-phase and multi-period. So we could choose two-phase/four-phase/six-phase according to the particular road and traffic condition. Besides, it took the special status of emergency vehicles into account. It also had a manual input keyboard so that you could adjust the signal at any time. This design can effectively improve the traffic congestion problem.

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