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In recent years, there has been growing interest in the design of intelligent transportation systems (ITS) using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. These systems allow vehicles to share GPS-based information, such as latitude, longitude, speed and heading, as well as important vehicle data such as brake events, throttle position, turn signal status,...
We propose a method for ego-lane estimation that can robustly determine the currently used lane as required by future lane-precise navigation systems. It employs a lane-level map-matching on a digital road map through least-squares optimization and only requires sensors available in current production vehicles, such as GPS, odometry, visual lane-marking detection and radars. Radar data is used in...
The detection of lane layout in the surroundings of the ego-vehicle is a key issue for modern ADAS and autonomous driving. Most modern systems rely on annotated spatial maps to provide lane information. However, these maps are not available everywhere, and thus have to be often supported by direct detection systems (e.g. cameras, lasers). Such systems detect lane boundaries by directly observing lane...
Cyber-Physical System (CPS, shortly) is a fusion systems of computing and physical processes. It is a highly integration of computation, communication and control in the framework of networked embedded system. In this paper, we analyze the concept and feature of CPS and propose a graphical hierarchical architecture for CPS. It is a graphic network structure within the same layer and a hierarchical...
An overview on state of the art automotive radar usage is presented and the changing requirements from detection and ranging towards radar based environmental understanding for highly automated and autonomous driving deduced. The traditional segmentation in driving, manoeuvering and parking tasks vanishes at the driver less stage. Situation assessment and trajectory/manoeuver planning need to operate...
A prime requirement for autonomous driving is a fast and reliable estimation of the motion state of dynamic objects in the ego-vehicle’s surroundings. An instantaneous approach for extended objects based on two Doppler radar sensors has recently been proposed. In this paper, that approach is augmented by prior knowledge of the object’s heading angle and rotation center. These properties can be determined...
Automotive Radar has already found its way into nearly all car manufacturers portfolio, even for small car platforms. Over the decades, the performance requirements increased steadily from simple detector tasks in blind spot monitoring systems to multi range smart environment perception sensors. The utmost push in performance requirement is initiated with the trend towards highly automated driving...
The interaction of a cyber-physical system (CPS) may impose additional constraints upon cyber aspects of the system. For instance, sensing and actuation often require nonpreemption to ensure “accuracy” in data acquisition (e.g., radar sensors in automotive a cruise control system). Furthermore, CPS may require that a system adapts to changing environment which requires support for multiple operating...
Over the last years, radar based driver assistance and active safety systems have found wide spread application in nearly all vehicle brands all over the world. With the market introduction of the 2014 Mercedes-Benz S-Class vehicle equipped with six radar sensors covering the vehicles environment 360° in the near and far range, autonomous driving has become a reality even in low speed highway scenarios...
Long-term and continuous non-invasive driver's health monitoring has shown that it is the most important to measure driver's fatigue level and personal health status. Currently, there are many preferable methods, including ECG, EEG and EOG, to get the physiological parameters of driver. However, the size of the machine is large and the operation of monitors is difficult. The measurement procedure...
This paper presents a lane-level localization algorithm based on situational awareness fusing radar, vision, GPS, and digital map on highway. Under the assumption that the maximum number of lanes is known by both GPS and digital map, the position of a vehicle is determined in a term of lane-level position via situational awareness on highway. The situational awareness aims at recognizing maneuver...
Packet loss in block erasure channels creates a randomly switching networked system that impacts control performance significantly. This paper employs safety of highway vehicle platoons as a platform to study such impact. By autonomous inter-vehicle coordination, a platoon can potentially enhance safety, improve highway utility, increase fuel economy, and reduce emission. By comparing different information...
Based on high-resolution radars a new approach for determining the full 2D-motion state (yaw rate, longitudinal and lateral speed) of an extended rigid object in a single measurement is proposed. The system does not rely on any model assumptions and is independent of the exact position, expansion and orientation of the object. In comparison to related methods it is not based on temporal filtering,...
In the research on autonomous vehicles, self-localization is an important problem to solve. In this paper we present a localization algorithm based on a map and a set of off-the-shelf sensors, with the purpose of evaluating this low-cost solution with respect to localization performance. The used test vehicle is equipped with a Global Positioning System receiver, a gyroscope, wheel speed sensors,...
As the proportion of older people in the population is growing, the demand for older driver safety is increasing sharply because their driving abilities are lowered. In this paper, we propose an autonomous emergency stop system to support older people. It activates an autonomous driving mode when the driver cannot control his vehicle any more, and stops the vehicle safely. It recognizes situation...
Autonomous ground vehicles have evolved a lot in the past decade. Several prototypes have been presented and tested in different conditions. A major challenge for such vehicles is the fact that they depend on advanced sensing technologies to perceive the environment and make real-time decisions. The complexity of this task typically requires multiple sensing devices, which is both a technical challenge...
In this paper, the target recognition system using 24GHz radar for intelligent vehicle is represented. Several kind of radar measurement features are included to get performance. The proposed method is verified by experiments. The support vector machine based classification system is implemented. The result of the system is compared with other previous methods.
Establishing an effective observing system for the urban estuary presents oceanographic and operational challenges beyond those common to the continental shelf and open ocean. Examples are used from the Middle Atlantic Bight estuaries to illustrate that, while emerging technologies are facilitating efforts to establish these systems on a sustainable basis, cooperative efficiencies are likely to be...
We present a system able to predict the future left lane change behavior of the ego-vehicle on highway, depending on detected information about the preceding vehicles. Our system learns the mapping between the current perceived scene (information about the ego-vehicle and the preceding vehicles) and the future driving behavior of the ego-vehicle.
For over a decade avoiding runway incursions (RI), events where two or more vehicles create a conflicting situation by using the same runway, have been a top ten priority of the National Transportation Safety Board (NTSB). Only the recent technological response in form of area wide deployment of Runway Incursion Prevention and Alerting Systems (RIPAS) improved the situation in the USA and safety seems...
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