The Effect of Augmented Driver Behavior on Freeway Traffic Flow

Electric vehicles provide a solution for using alternative fuels, namely, electricity. Electric vehicles are used for short distances and intercity travel over long distances, increasing the risk of accidents. Cruise Control is a technology embedded in vehicles to maintain stable speeds; this system will automatically adjust the vehicle's speed when motion changes cause changes in vehicle speed. This study aims to apply lidar sensors to detect distance in the Intelligent Cruise Control (ICC) system using the Fuzzy-PID control method. Testing results were obtained at safe distance inputs of 5, 6, and 7 meters with various object distances. All the tests were carried out; the response systems were obtained with an average settling time of 5 seconds and an average overshoot of 1.53%. Therefore, the proposed Fuzzy-PID method works well for controlling Intelligent Cruise Control systems in autonomous electric vehicle prototypes.

<div class="section abstract"><div class="htmlview paragraph">Developing a knowledge-based predictive driver-aid system requires a strategy that meets the needs and goals, as well as rigorous methods. This paper presents the strategy adopted and the first results obtained in the development of the Navigation Aided Intelligent Cruise Control (N.A.I.C.C.) system. Once the vehicle is located on the route, this new copilot can: <ol class="list nostyle"> <li class="list-item"> <span class="li-label">1.</span> <div class="htmlview paragraph">define the travel direction and the vehicle speed,</div></li> <li class="list-item"> <span class="li-label">2.</span> <div class="htmlview paragraph">determine the distance to the next bend and its characteristics,</div></li> <li class="list-item"> <span class="li-label">3.</span> <div class="htmlview paragraph">predict the optimal speed to negotiate the next bend considering the road profile, the constraints given by the driver and the information provided by the sensors mounted on the vehicle.</div></li></ol></div><div class="htmlview paragraph">Then, used in the warning mode (“Driver Alarm Mode”), N.A.I.C.C. informs the driver of the danger of the situation (excessive speed) or, in the intervention mode (“Velocity Control Mode”), N.A.I.C.C. adapts the speed to the predicted reference. In this latter operating mode, N.A.I.C.C. can be considered as an advanced intelligent cruise control system. Real experiments were carried out with the laboratory test car to validate each module described.</div></div>

Intelligent cruise control systems and traffic flow stability

This paper describes the safety evaluation results from a Field Operational Test (FOT) of an Intelligent Cruise Control (ICC) system. The primary goal of this evaluation was to determine safety effects of the ICC system. Safety surrogate measures were established and examined for normal driving situations as well as for safety-critical situations. It was found that use of the ICC system in the FOT was generally associated with safer driving compared to manual control and is projected to result in net safety benefits if widely deployed. (A) For the covering abstract see ITRD E106371.

An intelligent cruise control system based on access to the conventional cruise control system as well as to the automatic transmission ECU has been realized. The system is characterized by different states (e.g. acceleration, hold speed, deceleration). For state control classified and weighted values of distance, relative speed and vehicle speed information are used. Control strategy therefore is very similar to fuzzy control. Practical results showed high system stability.

<div class="section abstract"><div class="htmlview paragraph">The potential safety benefits of an Intelligent Cruise Control (ICC) system are assessed in terms of the number of rear-end crashes that might be avoided on U.S. freeways if all vehicles were equipped with such a system. This analysis utilizes naturalistic driving data collected from a field operational test that involved 108 volunteers who drove ten passenger cars for about 68 and 35 thousand miles in manual and ICC control modes, respectively. The effectiveness of the ICC system is estimated at about 17 percent based on computer simulations of two rear-end precrash scenarios that are distinguished by whether the following vehicle encounters a suddenly-decelerating or slow-moving lead vehicle. The ICC system has the potential to eliminate approximately 13 thousand policereported rear-end crashes on U.S. freeways, using 1996 national crash statistics.</div></div>

Ensemble of long short-term memory prediction and variable universe fuzzy control for seismic response reduction using electromagnetic dynamic vibration absorber

The existing urban traffic signal control system exhibits certain inefficiencies, including prolonged waiting times and frequent traffic congestion. Research indicates that the integration of neural networks can enhance the effectiveness of intelligent traffic control systems, potentially improving overall traffic flow and reducing delays. Neural network is a highly parallel, nonlinear and highly redundant system. Meanwhile, the self-learning and self-organizing capabilities of neural network have unique advantages for those systems that cannot establish accurate mathematical models. According to the characteristics of complex, variable and random traffic conditions at urban intersections, this paper analyzes the traffic signal control by using neural network control method. This paper introduces a design method of intelligent traffic light based on dynamic time adjustment of traffic flow. By detecting the traffic flow on site, and then allocating the green time of each lane according to the neural network algorithm, the traffic flow dynamic adjustment can be realized, and the traffic capacity of the intersection can be effectively improved. This kind of intelligent control traffic lights can effectively control traffic, and has obvious effects on dreading traffic flow, improving road capacity and reducing traffic accidents.

Обоснован перечень задач самообучения интеллектуальных систем управления автономными роботами и мультиагентными робототехническими группировками. Обсуждаются основные проблемы создания интеллектуальных самообучающихся систем управления. Показано, что один из наиболее перспективных подходов к реализации процессов самообучения в интеллектуальных системах управления автономными роботами и многоагентными робототехническими группировками связан с использованием метода автоматического построения деревьев классификации. Приводятся результаты комплексного моделирования.

The levels of driver comfort and acceptance for an autonomous intelligent cruise control (AICC) system driven in an actual highway environment are investigated. Objective measures of driving performance and behaviour are compared with participants' subjective assessments when operating under manual control, conventional cruise, and AICC. Included in the comparison are measures of driver velocity and braking behaviour. Participants drive slightly higher mean velocities under the manual condition as compared with AICC. Participants applied the brakes less frequently when driving manually. Participants rated the AICC system favorably for comfort, ease of use, and convenience. However, participants did express limited concerns associated with the use of AICC. (A) For the covering abstract of the conference see IRRD 875189.

A hybrid short-term traffic flow forecasting method based on spectral analysis and statistical volatility model

A description of a new class of organizational and technical systems is given – intelligent road-building compaction control systems, the principles of operation of which provide for ensuring a given quality of compaction of asphalt mixtures in the process of road construction. The development of systems of that class is due, in the first place, to the transition to digital and intelligent control systems in construction. A scientific problem related to the relevance of creating methods for intelligent control of compaction of asphalt mixtures that affect the quality of road surfaces was formulated. To succeed, the usage of neural network structures was proposed. The usage will allow real-time monitoring of changes in the compaction quality index and efficient controlling of road machines using both the driver's manual means and the automatic compaction control system. The properties of the system under study – which determine the principles of its functioning: intelligence, informativity, speed, interconnectedness of subsystems, controllability and modularity – were presented. The above principles of the functioning of the proposed system, which are part of the methodology for managing the quality of asphalt compaction of pavement roads, were implemented in a set of methods and algorithms. Among them should be noted a new method of intelligent continuous control of compaction in the process of laying asphalt mixtures, an advanced method of intelligent prediction of compaction quality by vibrating rollers.

Based on heat balance analysis, the dynamic heating model of asphalt tank of mixture equipment was established, the heating time and using time nodes were determined, and the trapezoidal dynamic heating process of asphalt tank was also formed to realize the intelligent control and reduce energy consumption. After analyzing different schemes, the control scheme of the combination of feed-forward and feedback to realize intelligent control system for asphalt tank was adopted, which could ensure that the asphalt in the tank is in the operating temperature and the mixing equipment works continuously when the asphalt was used completely. In addition, a simulated analysis of calculation model, which was adopted by intelligent control system, was made in combination of entitative engineering. Results showed that compared with traditional process of heating asphalt, this intelligent heating control system could reduce the heat consumption by 15.8% under the condition of continuous construction.

With the development of network communication, computer technology and artificial intelligence, it has become an inevitable development trend to promote "intelligent buildings" characterized by intelligence, comfort and safety. In order to solve the shortcomings of the existing research on intelligent building control system, this paper discusses the functional equation of CAN algorithm, artificial intelligence fuzzy controller and intelligent building, and aims at the intelligent building control system based on artificial intelligence and CAN algorithm. Hardware settings and parameter settings are briefly introduced. And the work flow design of the intelligent building control system structure based on artificial intelligence and CAN algorithm is discussed, and finally the application of the intelligent building control system based on artificial intelligence and CAN algorithm is experimentally tested. The correct number of switch control by artificial intelligence and CAN algorithm in the intelligent building control system is relatively high. The correct number of switch control in the interference environment is less than that in the humid environment, and the number of switch operations for the control system is the least in the humid environment. The error rate of 500 and up to 2500 is less than 5%, thus verifying the superiority of the application of intelligent building control system based on artificial intelligence and CAN algorithm.

With the progress of computer technology and intelligent control system, it is necessary to introduce the PLC together with the current systems. In this paper, we conduct research on the new intelligent industrial control and communication system based on PLC technique. As Industry 4.0 at the core of intelligent factory, the products made in its basic idea is integrated with dynamic digital memory, perception and communication ability, carrying the whole supply chain and all kinds of information required for life cycle. PLC biggest characteristic is to constitute the traditional relay model computer software technology, formed a unique style in relay ladder graph based image programming language, the PLC control system in the form of program to achieve its control function. In the simulation section, we implement our proposed system in detail and conduct numerical analtsis and simulation. The result is acceptable and accurate.