Longitudinal control of heavy trucks in mixed traffic: environmental and fuel economy considerations

In this paper, longitudinal vehicle-following controllers for heavy trucks with different spacing policies are designed, analyzed, simulated, and experimentally tested, and their performance in mixed traffic with passenger vehicles is evaluated. A new vehicle-following controller for trucks, which has better properties than existing ones with respect to performance and impact on fuel economy and pollution during traffic disturbances, is developed. The response of trucks to disturbances caused by lead passenger vehicles is smooth due to the limited acceleration capabilities of trucks whether they are manual or equipped with adaptive cruise control (ACC) systems. Vehicles following the truck are therefore presented with a smoother speed trajectory to track. This filtering effect of trucks is shown to have beneficial effects on fuel economy and pollution. However, it creates large intervehicle gaps that invite cut-ins from neighboring lanes, creating additional disturbances. These cut-ins, under certain realistic scenarios, may reduce any benefits obtained by the smooth response of trucks as well as increase travel time. The results of this paper indicate possible benefits trucks may have in mixed traffic and also reinforces what is already known-that trucks could be detrimental to traffic flow.     

Analysis of traffic flow with mixed manual and semiautomated vehicles

The introduction of semiautomated vehicles designed to operate with manually driven vehicles is a realistic near-term objective. The purpose of this paper is to analyze the effects on traffic-flow characteristics and environment when semiautomated vehicles with automatic vehicle following capability (in the same lane) operate together with manually driven vehicles. We have shown that semiautomated vehicles do not contribute to the slinky effect phenomenon when the lead manual vehicle performs smooth acceleration maneuvers. We have demonstrated that semiautomated vehicles help smooth traffic flow by filtering the response of rapidly accelerating lead vehicles. The accurate speed tracking and the smooth response of the semiautomated vehicles designed for passenger comfort reduces fuel consumption and levels of pollutants of following vehicles. This reduction is significant when the lead manual vehicle performs rapid acceleration maneuvers. We have demonstrated using simulations that the fuel consumption and pollution levels present in manual traffic can be reduced during rapid acceleration transients by 28.5% and 1.5%-60.6%, respectively, due to the presence of 10% semiautomated vehicles. These environmental benefits are obtained without any adverse effects on the traffic-flow rates. Experiments with actual vehicles are used to validate the theoretical and simulation results.     

ACC+Stop&go maneuvers with throttle and brake fuzzy control

Research on adaptive cruise control (ACC) with Stop&Go maneuvers is presently one of the most important topics in the field of intelligent transportation systems. The main feature of such controllers is that there is adaptation to a user-preset speed and, if necessary, speed reduction to keep a safe distance from the vehicle ahead in the same lane of the road, whatever the speed. The extreme case is the stop and go operation in which the lead car stops and the vehicle at the rear must also do so. This paper presents the development of an ACC system and related experiments. The system input information is acquired by a real-time kinematic phase differential global positioning system (GPS) (i.e., centimetric GPS) and wireless local area network links. The outputs are the variables that control the pressure on the throttle and brake pedals, which is calculated by an onboard computer. In addition, the car control is based on fuzzy logic. The system has been installed in two mass-produced Citroe/spl uml/n Berlingo electric vans, in which all the actuators have been automated to achieve humanlike driving. The results from real experiments show that the unmanned vehicles behave very similarly to human-driven cars and are very adaptive to any kind of situation at a broad range of speeds, thus raising the safety of the driving and allowing cooperation with manually driven cars.     

Modeling of traffic flow of automated vehicles

With the development of near term automatic vehicles following concepts such as intelligent cruise control (ICC) and cooperative driving, vehicles will be able to automatically follow each other in the longitudinal direction. The modeling of traffic flow consisting of such vehicles is important for analyzing the effects of vehicle automation on the characteristics of traffic flow and for suggesting macroscopic control strategies to improve efficiency. Such analysis may also suggest ways for modifying the vehicle control characteristics in order to improve the macroscopic behavior of traffic. In this paper, we developed a mesoscopic and macroscopic model that describes the automated traffic-flow dynamics in a single highway lane. The mesoscopic model describes the speed and density continuously in time and space and at the same time retains the microscopic characteristics of traffic flow. The macroscopic model describes the average speed and density at each section of the lane and at each point in time. Even though the macroscopic model does not retain the microscopic characteristics of the vehicular traffic, computationally it is much simpler than the mesoscopic one. Simulations are used to demonstrate the effectiveness of these models in describing traffic-flow characteristics. The developed models indicate some similarities, but also some fundamental differences with existing traffic-flow models for manually driven vehicles.     

Lane-Change Fuzzy Control in Autonomous Vehicles for the Overtaking Maneuver

The automation of the overtaking maneuver is considered to be one of the toughest challenges in the development of autonomous vehicles. This operation involves two vehicles (the overtaking and the overtaken) cooperatively driving, as well as the surveillance of any other vehicles that are involved in the maneuver. This operation consists of two lane changes—one from the right to the left lane of the road, and the other is to return to the right lane after passing. Lane-change maneuvers have been used to move into or out of a circulation lane or platoon; however, overtaking operations have not received much coverage in the literature. In this paper, we present an overtaking system for autonomous vehicles equipped with path-tracking and lane-change capabilities. The system uses fuzzy controllers that mimic human behavior and reactions during overtaking maneuvers. The system is based on the information that is supplied by a high-precision Global Positioning System and a wireless network environment. It is able to drive an automated vehicle and overtake a second vehicle that is driving in the same lane of the road.      

Real-Time Traffic Simulation With a Microscopic Model

This paper describes a microscopic model that is able to simulate traffic situations in an urban environment in real time for use in driving simulators. Two types of vehicles are considered in the simulation, namely the user-driven vehicle at the center of the simulation model and the other vehicles that interact with it and its surroundings, which configure the developed traffic model. Simulation is performed in a reduced zone, called the control zone, surrounding the user-driven vehicle. This control zone is a mobile zone centered on the user-driven vehicle. The size of the control zone depends on the maximum number of vehicles involved simultaneously, the traffic density, and the driver's limit of visibility. The other vehicles involved in the traffic simulation are created or destroyed within the limits of the control zone. The general behavior of the traffic model is based on the following theory. Vehicles have an associated driver model that establishes several control functions for them to follow the path, while the steering, acceleration, and braking maneuvers follow certain models of behavior. A traffic light regulation is also included but only in the control area. The possibility of introducing anomalous traffic situations into the simulation is also considered, such as the presence of obstacles, abnormal maneuvers, etc. The developed model is immediately applicable to large-scale driving simulators for driver training, traffic control studies, and safety studies     

Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation

In this paper, we present a new three-stage algorithm to calibrate roadside traffic management cameras and track vehicles to create a traffic speed sensor. The algorithm first estimates the camera position relative to the roadway using the motion and edges of the vehicles. Given the camera position, the algorithm then calibrates the camera by estimating the lane boundaries and the vanishing point of the lines along the roadway. The algorithm transforms the image coordinates from the vehicle tracker into real-world coordinates using our simplified camera model. We present results that demonstrate the ability of our algorithm to produce good estimates of the mean vehicle speed in a lane of traffic.     

Position Control of a Wheeled Mobile Robot Including Tire Behavior

Advanced driver assistance systems are increasingly available on road vehicles. These systems require a thorough development procedure, an important part of which consists of hardware-in-the-loop experiments in a controlled environment. To this end, a facility called vehicle hardware-in-the-loop (VeHIL) is operated, aiming at testing the entire road vehicle in an artificial environment. In VeHIL, the test vehicle is placed on a roller bench, whereas other traffic participants, i.e., vehicles in the direct neighborhood of the test vehicle, are simulated using wheeled mobile robots (WMRs). To achieve a high degree of experiment reproducibility, focus is put on the design of an accurate position control system for the robots. Due to the required types of maneuvers, these robots have independently driven and steered wheels. Consequently, the robot is overactuated. Furthermore, since the robot is capable of high-dynamic maneuvers, slip effects caused by the tires can play an important role. A position controller based on feedback linearization is presented, using the so-called multicycle approach, which regards the robot as a set of identical unicycles. As a result, the WMR is position controlled, whereas each unicycle is controlled, taking weight transfer and longitudinal and lateral tire slip into account.     

Toward Autonomous Collision Avoidance by Steering

This paper presents a new automotive safety function called Emergency Lane Assist (ELA). ELA combines conventional lane guidance systems with a threat assessment module that tries to activate the lane guidance interventions according to the actual risk level of lane departure. The goal is to only prevent dangerous lane departure maneuvers. The ELA safety function is based on a statistical method that evaluates a list of safety concepts and tries to maximize the impact on accident statistics while minimizing development and hardware component costs. ELA runs in a demonstrator and successfully intervenes during lane changes that are likely to result in a collision and is also able to take control of the vehicle and return it to a safe position in the original lane. It has also been tested on 2000 km of roads in traffic without giving any false interventions     

Automated lane change controller design

The primary focus of study in this paper is the background control theory for automated lane change maneuvers. We provide an analytic approach for the systematic development of controllers that will cause an autonomous vehicle to accomplish a smooth lane change suitable for use in an Automated Highway System. The design is motivated by the discontinuous availability of valid preview data from the sensing systems during lane-to-lane transitions. The task is accomplished by the generation of a virtual yaw reference and the utilization of a robust switching controller to generate steering commands that cause the vehicle to track that reference. In this way, the open loop lane change problem is converted into an equivalent virtual reference trajectory tracking problem. The approach considers optimality in elapsed time at an operating longitudinal velocity. Although the analysis is performed assuming that the road is straight, the generalization of the proposed algorithm to arbitrary road segments is rather straightforward. The outlined lane change algorithm has been implemented and tested on The Ohio State University test vehicles. Some of the experimental results are presented at the conclusion of this paper.     

Lane Detection With Moving Vehicles in the Traffic Scenes

A lane-detection method aimed at handling moving vehicles in the traffic scenes is proposed in this brief. First, lane marks are extracted based on color information. The extraction of lane-mark colors is designed in a way that is not affected by illumination changes and the proportion of space that vehicles on the road occupy. Next, for vehicles that have the same colors as the lane marks, we utilize size, shape, and motion information to distinguish them from the real lane marks. The mechanism effectively eliminates the influence of passing vehicles when performing lane detection. Finally, pixels in the extracted lane-mark mask are accumulated to find the boundary lines of the lane. The proposed algorithm is able to robustly find the left and right boundary lines of the lane and is not affected by the passing traffic. Experimental results show that the proposed method works well on marked roads in various lighting conditions     

基于车底阴影的前方运动车辆检测

实时准确检测前方运动车辆的位置信息是车辆安全驾驶的前提,提出了一种在不依赖车道线检测情况下,基于车底阴影的前方运动车辆检测。阴影算法采用两次自适应阈值分割图像从而提取车底与路面的交线,生成目标假设区域,对建筑物或树的投影、光照强弱等干扰能初步有效的排除,提高检测效率;接着,利用熵值归一化的对称性测度来验证,排除虚假车辆。实验结果显示,该算法的正确识别率达到97.2%,平均处理速度为22.5帧/秒,对白天中多种环境能满足实时准确地要求。     

Basic study on traffic information system using LED traffic lights

The vehicle information and communication system (VICS) is starting to become practicable. The infrared system of a VICS detects vehicles on the road by using optical beacons to control traffic and to supply real-time traffic information. But it needs an enormous budget because the optical beacons must be located on every lane of the road throughout the country. We propose a traffic information system using existing LED traffic lights, and focus on its visible rays and power used for traffic control, the number and location of the traffic lights, and the movement toward LED traffic lights. We design the best service area not to interfere with other service areas and analyze its basic performance such as the suitable modulation, required SNR and the amount of receivable information     

The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles     

Vehicle-Component Identification Based on Multiscale Textural Couriers

This paper presents a novel method for identifying vehicle components in a monocular traffic image sequence. In the proposed method, the vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask and the calibrated-camera parameters. With these multiscale regions, textural couriers are generated based on the localized variances of the foreground vehicle image. A new scale-space model is subsequently created based on the textural couriers to provide a topological structure of the vehicle. In this model, key feature points of the vehicle can significantly be described based on the topological structure to determine the regions that are homogenous in texture from which vehicle components can be identified by segmenting the key feature points. Since no motion information is required in order to segment the vehicles prior to recognition, the proposed system can be used in situations where extensive observation time is not available or motion information is unreliable. This novel method can be used in real-world systems such as vehicle-shape reconstruction, vehicle classification, and vehicle recognition. This method was demonstrated and tested on 200 different vehicle samples captured in routine outdoor traffic images and achieved an average error rate of 6.8% with a variety of vehicles and traffic scenes.     

Methodology for assessing adaptive cruise control behavior

This paper reports on nonintrusive methods for characterizing the longitudinal performance of vehicles equipped with adaptive cruise control (ACC) systems. It reports the experimental set-up and procedures for measuring ACC system performance, followed by the modeling and simulation of the measured ACC performance. To further assess the interaction of ACC vehicles with human-controlled traffic, microscopic simulation involving both a human-driver model and an ACC model is discussed.     

A lane detection algorithm for personal vehicles

By the term “personal vehicle,” we mean a simple and lightweight vehicle expected to emerge as a personal ground transportation device. The motorcycle, electric wheelchair, and motor‐powered bicycle are examples of the personal vehicle and have been developed for personal transportation use. Recently, a new type of intelligent personal vehicle called the Segway has been developed, which is controlled and stabilized by using on‐board intelligent multiple sensors. The demand for such personal vehicles is increasing: (1) to enhance human mobility, (2) to support mobility for elderly persons, and (3) to reduce environmental load. With the rapid growth of the personal vehicle market, the number of accidents caused by human error is also increasing. These accidents are associated with driving capabilities; to enhance or support driving capabilities as well as to prevent accidents, intelligent assistance is necessary. One of the most important elementary functions for personal vehicles is robust lane detection. In this paper, we develop a robust lane detection method for personal vehicles in outdoor environments. The proposed lane detection method employs a 360° omnidirectional camera and unique robust image processing algorithm. In order to detect lanes, a combination of the template matching technique and the Hough transform is employed. The validity of the proposed lane detection algorithm was confirmed with a prototype vehicle under various types of sunshine conditions. © 2011 Wiley Periodicals, Inc. Electr Eng Jpn, 177(4): 23–32, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21193     

Ultrasonic vehicle detector for side-fire implementation andextensive results including harsh conditions

Concerns vehicle detectors, which collect passing vehicle information and traffic condition in real time. This paper develops an ultrasonic vehicle detector (UVD) system that can be implemented in a side-fire configuration. Conventionally, UVD systems are installed in overhead configurations. If these sensors can be mounted from the side of a road, the installation cost can be reduced. In addition, the aesthetic integrity of roadways will not be affected very much. However, this side-fire configuration has not been used, because of the fact that vehicles generally do not have sufficiently large oblique-angled surfaces to reflect the emitted ultrasonic wave back to the sensor for detection. This paper reports on the feasibility of a side-fire UVD system. A new low-cost instrumentation and control system for side-fire implementation was developed, and comprehensive experiments were performed at highway and downtown test sites. Experimental conditions included various traffic conditions as well as various weather conditions, including daylight, dusk, night, heavy rain, and heavy snow. Traffic data were generated for every five minutes. For the highway location, the vehicle counting error was less than 1%. For the downtown location, the error was approximately 3% during normal weather conditions and approximately 5% during a snow storm. The larger error in downtown is mainly attributed to vehicles changing lane. We believe that these side-fire implementation results are adequate for implementing advanced traveler information systems (ATIS)     

An algorithm for distinguishing the types of objects on the road using laser radar and vision

Describes a method for distinguishing the types of forward objects detected on and alongside the road using a vehicle-mounted scanning laser radar (SLR) and a camera. This method can measure the distance to a preceding vehicle in the same lane as well as to other forward vehicles in adjacent lanes. Objects are detected on the basis of SLR digital signal data and are categorized as vehicles, delineators, and signs based on their motion and positions relative to white lane markers. The motions of detected objects are judged by the relationship between the path of the host vehicle and changes in the positions of the objects. The host vehicle's path is computed using steering maneuver data and the vehicle velocity. White lane markers are detected by an image processing technique. The proposed algorithm has been validated in an experiment conducted with a simulator. Data recorded at a driving speed of more than 40 km/h on Japanese expressways were used in the simulation. The types of objects detected on the road were successfully distinguished as expected.     

隧道交通虚拟仿真系统

将虚拟现实（Vinual Reality—VR）技术与交通流仿真技术相结合,设计了虚拟交通流仿真系统应用于隧道交通流研究。该项技术也称交互式的动态虚拟实现技术,使用发车、跟车、变道等模型对隧道内的交通状况进行了仿真。为我国隧道交通工程的研究和设计提供了直观、科学的仿真手段。