The extrinsic Fabry-Perot interferometer has been implemented before for the health monitoring of multi-computer communication networks. Such integrated sensor and communication system architectures can be extremely useful during the implementation of ITS traffic management centers. The same optical fiber can be modified to provide the necessary communication link, and the incorporated sensor can be used to monitor the health of the computer network, for providing a fault-tolerant architecture. However the signal to noise ratio, minimum detection reliability, and dynamic range of the interferometer are of primary concern in such an implementation. The main objective of this paper is to present an exact analytical and experimental evaluation of the extrinsic Fabry-Perot interferometer using Kirchhoff's diffraction formalism. The obtained results are compared with the conventional two-beam interference model, and proved to correlate better with the experimental results. Future applications of this optical interferometer in other ITS applications are also discussed.

The use of machine vision in electronic toll and traffic management applications has significantly increased since its commercial introduction in the 1980's. This paper will review the types of applications currently using machine vision systems. The paper will then look at the types of machine vision systems and their evolution. Finally the paper will examine some current applications of machine vision to electronic toll automatic vehicle classification and violation enforcement.

Driver vision enhancement systems provide augmented information to improve the driver's perceptual ability when visibility is reduced. Vision enhancement is a technologically- challenging mission. We surveyed two classes of technologies: imaging systems (visible and infrared) and radars (millimeter-wave and laser radars). Night (IR) vision and radar-based systems promise meaningful vision enhancement functionality to the driver. Available field test data give thermal imagers operating in the range of 8 to 12 micrometers an edge. This spectral regime has a long (miles) clear night range, adequate object discrimination and handles inclement weather conditions better than other shorter wavelength imagers. Uncooled thermal imagers, because of their potentially low-cost, are emerging as a front runner technology. All weather penetration of a radar based system is attractive for certain driving scenarios. They are not particularly adept in high resolution imaging. This combination makes them more of interest as automated warning devices. Icons replace the actual objects imaged to indicate the hazard ahead. True all-weather high-resolution vision enhancement systems are beyond near- term capabilities. Overall, vision enhancement systems under development today will have good utility with the challenge that they become `affordable'.

This paper describes fiber-optic sensor systems developed for airport ground traffic monitoring and the first steps toward their installation in an experimental surface movement guidance and control system at the Braunschweig airport. Initial results obtained with fiber- optic light barriers and vibration sensors are reported. The feasibility of employing interferometric strain gauges for this application will be discussed based on sensor characteristics obtained through measurements of dynamic load variations in an aircraft structure in flight.

Optical fiber sensors, because of their small size, low weight, extremely high information carrying capability, and immunity to electromagnetic interference, provide numerous advantages over conventional electrically based sensors. Fiber-based sensors has found numerous applications in industry for process control, and more recently for monitoring the health of advanced civil structures. This paper presents an overview of optical fiber sensors for civil structure monitoring and emerging applications of optical fiber sensors for traffic monitoring. Vehicle flow, vehicle speed and weight-in-motion measurements using fiber-based sensors are discussed, and results from field tests are presented to demonstrate the effectiveness of fiber sensors at determining traffic flow.

Most collision avoidance strategies for highway vehicles have primarily been based on control of 1 degree-of-freedom (1 DOF). Such collision avoidance strategies typically use RADAR or other range sensors as a means to servo on the distance between the controlled vehicle and the vehicle in front. However, for large inertia vehicles such as trucks, such strategies which involve engine/transmission or brake control, may likely prove inadequate for avoiding collisions with vehicles on either side or with animals. A 2 DOF strategy involving both steering and speed control conceptually offers significant advantages over 1 DOF strategies. A 2 DOF strategy is introduced that is based on the concept of a virtual bumper. As the name implies, the approach is based on surrounding the perimeter of the vehicle with a sensor-based computer controlled `bumper'. As the bumper's boundary is `deflected,' (i.e. the vehicle's `personal space' is invaded) a virtual force proportional to the amount of deflection is generated. The vehicle controller responds to this virtual force in such a way as to return the bumper to its non-deflected state. Information on the road geometry can also be used to generate a virtual force field to keep the vehicle in its lane. A number of vehicle mounted RADAR units measure the range and range rate between the sensors (mounted and oriented to cover the field around the vehicle) and the obstacle. Using this sensory information and an impedance based control algorithm, the vehicle will attempt to always move away from the obstacle in a controlled manner using both steering and speed control. By integrating local lane/shoulder information and sensor provided data on incursions into the vehicle's personal space, appropriate trajectory displacements are generated based on the virtual force summation. In this paper, we discuss a number of issues that need to be addressed in developing such virtual bumpers.

For intelligent cruise control (ICC) and forward looking collision warning systems to be successful products they must provide robust performance in a complex roadway environment. Inconveniences caused by dropped tracks and nuisance alarms will not be tolerated by consumers, and would likely result in rejection of these new technologies in the marketplace. The authors report on a low-cost automotive millimeter wave (MMW) radar design which addresses shortcomings associated with previously reported ICC system implementations. The importance of the sensor's ability to identify and separately track all obstacles in the field of view is discussed. The applicability of the MMW's FM-CW sensor implementation to collision warning systems is also discussed.

Ultra-wideband (UWB) communications is a new field of technology that has a wide range of applications from range finding to wide bandwidth communications. Ultra-wideband signals are unusual because their bandwidth to center frequency ratio is not small and can be greater than 100%. Recent developments of integrating this technology on a chip have made it versatile and low cost. A number of areas especially those in ITS can benefit by this technology including Automatic Vehicle Identification (AVI), Advanced Traveler Information Systems (ATIS), Advanced Traffic Management Systems (ATMS), Transportation Planning, Collision Avoidance, and Automated Highway Systems (AHS). This paper describes the basics of UWB technology, describes its features, provides background on the technology, and provides some possible applications of UWB to ITS. This paper is not intended to be overly detailed in any one area, but, to provide information about a technology to a wide audience.

The problem of providing an electronic warning of an impending crash to a precrash restraint system a fraction of a second before physical contact differs from more widely explored problems, such as providing several seconds of crash warning to a driver. One approach to precrash restraint sensing is to apply anticipatory system theory. This consists of nested simplified models of the system to be controlled and of the system's environment. It requires sensory information to describe the `current state' of the system and the environment. The models use the sensor data to make a faster-than-real-time prediction about the near future. Anticipation theory is well founded but rarely used. A major problem is to extract real-time current-state information from inexpensive sensors. Providing current-state information to the nested models is the weakest element of the system. Therefore, sensors and real-time processing of sensor signals command the most attention in an assessment of system feasibility. This paper describes problem definition, potential `showstoppers,' and ways to overcome them. It includes experiments showing that inexpensive radar is a practical sensing element. It considers fast and inexpensive algorithms to extract information from sensor data.

This paper presents a new approach for autonomously negotiating freeway traffic. It is based on the concept of Velocity Obstacle (VO) which maps the set of vehicle's velocities that would result in a collision with the other moving vehicles. The Velocity Obstacle is computed by measuring the relative velocities and positions of the neighboring vehicles. The vehicle then negotiates through the moving traffic by selecting velocities that are out of that set, but are directed towards the intermediate goal, which may be an exit ramp or another lane. The computation of the VO and the feasible velocity is repeated at regular time intervals, to account for the time evolution of the freeway traffic. This representation can be used to automatically plan the vehicle's motion, or to advise the driver of potential unsafe maneuvers. For automatic planning, we developed heuristics that select the safe velocity based on the location of the goal and the acceptable risk level of the maneuvering vehicle. For advisory purposes, we developed a graphic representation of the VO which clearly shows the unsafe velocities to be avoided at all times. Attempting to drive at an unsafe velocity may sound an alarm and suggest a corrective maneuver. This representation is computationally efficient, and is applicable for on-line planning and warning. The method is demonstrated in simulations for planning the trajectory of an automated vehicle in an Intelligent vehicle Highway System (IVHS) scenario.

Determination of vehicle origins and destinations, calculation of travel times and measurement of traffic congestion are the common goals of traffic surveys. In the last few years the use of machine vision has been able to increase the accuracy of these measurements, the turn around time of traffic surveys and improve the breadth and depth of the information that can be capture regarding these traffic flow parameters. This paper describes several surveys that have been conducted using machine vision, in both the United States and Europe. The paper presents the preliminary results of field trials conducted in several United States cities to calculate travel times, as well as the use of machine vision to address certain `micro survey' data requirements. The paper discusses the experience gained in conducting these surveys.

As part of the U.S. FHWA-sponsored Detection Technology for IVHS program, ultrasonic, microwave radar, infrared laser radar, nonimaging passive infrared, video image processing with visible and infrared spectrum imagery, acoustic array, high sampling rate inductive loop, conventional inductive loop, microloop, and magnetometer detector technologies were evaluated at freeway and surface street arterial sties in three states. The states were selected to be representative of extremes in climatic conditions. The detector evaluation sites were located on roadways with high traffic density and suitable structures for mounting the overhead detectors. Approximately 5.9 GBytes of digital and analog vehicle detection and signature data and more than three hundred video tapes of the corresponding traffic flow were recorded. The detector outputs were time tagged and recorded on 88 MByte magnetic cartridges by using a data logger specifically designed and built for this project. Data analysis software was written to convert the data into an easily accessible Paradox database format compatible with a Windows personal computer operating system. Traffic volume ground truth data, obtained by counting vehicles from the recorded video imagery, were compared with the counts from the detector outputs. Speed ground truth data, obtained by driving probe vehicles through the field of view of the detectors and noting the vehicle speed as measured by the vehicle instrumentation, were compared with the speed measurement from the detectors. Several types of detectors were found to satisfy current traffic management functions. However, improved accuracies and new types of information may be required from detectors for future traffic management applications.

We propose a new approach for vision based longitudinal and lateral vehicle control. The novel feature of this approach is the use of binocular vision. We integrated two modules consisting of a new, domain-specific binocular stereo algorithm, and a lane marker detection algorithm, and show that the integration results in improved performance for each of the modules. Longitudinal control is supported by detecting and measuring the distances to leading vehicles using binocular stereo. The knowledge of the camera geometry with respect to the locally planar road is used to map the images of the road plane in the two camera views into alignment. This allows us to separate image features into those lying in the road plane, e.g. lane markers, and those due to other objects which are dynamically integrated into an obstacle map. Therefore, in contrast with the previous work, we can cope with the difficulties arising from occlusion of lane markers by other vehicles. Detected vehicles are then tracked in time using a vehicle centered coordinate system. Multiple cameras can be integrated to provide full surround awareness. The detection and measurement of the lane markers provides us with the positional parameters and the road curvature which are needed for lateral vehicle control. Moreover, this information is also used to update the camera geometry with respect to the road, therefore allowing us to cope with the problem of vibrations and road inclination to obtain consistent results from binocular stereo.

Aerometrics is developing an innovative laser-diode based device that provides a warning signal when a motor-vehicle deviates from the center of the lane. The device is based on a sensor that scans the roadway on either side of the vehicle and determines the lateral position relative to the existing painted lines marking the lane. No additional markings are required. A warning is used to alert the driver of excessive weaving or unanticipated departure from the center of the lane. The laser beams are at invisible wavelengths to that operation of the device does not pose a distraction to the driver or other motorists: When appropriate markers are not present on the road, the device is capable of detecting this condition and warn the driver. The sensor system is expected to work well irrespective of ambient light levels, fog and rain. This sensor has enormous commercial potential. It could be marketed as an instrument to warn drivers that they are weaving, used as a research tool to monitor driving patterns, be required equipment for those previously convicted of driving under the influence, or used as a backup sensor for vehicle lateral position control. It can also be used in storage plants to guide robotic delivery vehicles. In this paper, the principles of operation of the sensor, and the results of Aerometrics ongoing testing will be presented.

Automated highway systems will need sensors both for longitudinal guidance (intelligent speed control) and for lateral guidance relative to the center of the traffic lane. A magnetic sensor combined with a practical magnetic highway marking system provides an all-weather, cost effective lateral guidance technique. A practical system must have robust performance under all weather operation, and be producible at a reasonable cost. Previous schemes have suffered from weather related performance problems, cost of the sensor portion on the vehicle, or the cost of the highway infrastructure. The subject system uses a high sensitivity magneto-resistive sensor and a magnetic marking tape which is a variant of existing traffic marking tapes. In addition to providing lateral position information, the system can encode ancillary data that can be received by the vehicle sensor. An important data item is the road curvature for the next segment of road. If the system operates with closed loop autonomous lateral control, such feedforward data is important for good performance at highway speeds. A preliminary feasibility demonstration illustrated that the system provides a high signal to noise ratio, and good accuracy.

In the past few years MATRA and RENAULT have developed an Autonomous Intelligent Cruise Control (AICC) system based on a LIDAR sensor. This sensor incorporating a charge coupled device was designed to acquire pulsed laser diode emission reflected by standard car reflectors. The absence of moving mechanical parts, the large field of view, the high measurement rate and the very good accuracy for distance range and angular position of targets make this sensor very interesting. It provides the equipped car with the distance and the relative speed of other vehicles enabling the safety distance to be controlled by acting on the throttle and the automatic gear box. Experiments in various real traffic situations have shown the limitations of this kind of system especially on bends. All AICC sensors are unable to distinguish between a bend and a change of lane. This is easily understood if we consider a road without lane markings. This fact has led MATRA to improve its AICC system by providing the lane marking information. Also in the scope of the EUREKA PROMETHEUS project, MATRA and RENAULT have developed a lane keeping system in order to warn of the drivers lack of vigilance. Thus, MATRA have spread this system to far field lane marking detection and have coupled it with the AICC system. Experiments will be carried out on roads to estimate the gain in performance and comfort due to this fusion.

This paper treats the use of in-vehicle imaging sensors to achieve lateral control to avoid single vehicle roadway departure crashes. Since the sensor is expected to function under a variety of weather conditions, it is important to determine the overall performance envelope of the combined sensor/image processing algorithm. Initial roadway imagery was acquired under favorable ambient conditions and subsequently transformed to specified levels of adverse weather by means of software originally developed for military sensor applications. The transformed imagery was utilized to determine the relationship between adverse weather, measured in visibility ranges, versus the ability of the sensor/image processing algorithm to maintain lateral vehicle stability.

Development of automotive collision warning systems has progressed rapidly over the past several years. A key enabling technology for these systems is millimeter-wave radar. This paper addresses a very critical millimeter-wave radar sensing issue for automotive radar, namely the scattering characteristics of common roadway objects such as vehicles, roadsigns, and bridge overpass structures. The data presented in this paper were collected on ERIM's Fine Resolution Radar Imaging Rotary Platform Facility and processed with ERIM's image processing tools. The value of this approach is that it provides system developers with a 2D radar image from which information about individual point scatterers `within a single target' can be extracted. This information on scattering characteristics will be utilized to refine threat assessment processing algorithms and automotive radar hardware configurations. (1) By evaluating the scattering characteristics identified in the radar image, radar signatures as a function of aspect angle for common roadway objects can be established. These signatures will aid in the refinement of threat assessment processing algorithms. (2) Utilizing ERIM's image manipulation tools, total RCS and RCS as a function of range and azimuth can be extracted from the radar image data. This RCS information will be essential in defining the operational envelope (e.g. dynamic range) within which any radar sensor hardware must be designed.

Many intersection accidents are related to drivers' inappropriate responses to an amber signal light, due to their misjudgment on the traffic situation and/or their aggressive behavior. To reduce intersection accidents of this nature, this paper proposes the Intersection Auxiliary Signal System (IAS). IAS can be installed at selected intersections, where information regarding signal phasing, intersection geometry and speed limit is transmitted from an ultrasonic/infra-red transmitter. An on-vehicle device receivers and processes the information, the provides the driver with explicit suggestions on the correct action to take (continue to pass or decelerate to stop), or warnings against on-going incorrect actions. IAS is expected to be more effective in suburban intersections, which are usually characterized by greater dimension, longer amber phases, and higher vehicle speeds. Both the intersection transmitters and the on-vehicle processors are expected to have simple structures and low costs. Simulation results show that IAS has a significant effect on reducing red signal violation, especially when there is no significant dilemma zones.