The Feasibility of Quantitatively Characterizing the Vehicle Motion Environment (VME)

https://deepblue.lib.umich.edu/bitstream/2027.42/154108/1/ervin1990.pd

Development of rear-end collision avoidance in automobiles

The goal of this work is to develop a Rear-End Collision Avoidance System for automobiles. In order to develop the Rear-end Collision Avoidance System, it is stated that the most important difference from the old practice is the fact that new design approach attempts to completely avoid collision instead of minimizing the damage by over-designing cars. Rear-end collisions are the third highest cause of multiple vehicle fatalities in the U.S. Their cause seems to be a result of poor driver awareness and communication. For example, car brake lights illuminate exactly the same whether the car is slowing, stopping or the driver is simply resting his foot on the pedal. In the development of Rear-End Collision Avoidance System (RECAS), a thorough review of hardware, software, driver/human factors, and current rear-end collision avoidance systems are included. Key sensor technologies are identified and reviewed in an attempt to ease the design effort. The characteristics and capabilities of alternative and emerging sensor technologies are also described and their performance compared. In designing a RECAS the first component is to monitor the distance and speed of the car ahead. If an unsafe condition is detected a warning is issued and the vehicle is decelerated (if necessary). The second component in the design effort utilizes the illumination of independent segments of brake lights corresponding to the stopping condition of the car. This communicates the stopping intensity to the following driver. The RECAS is designed the using the LabVIEW software. The simulation is designed to meet several criteria: System warnings should result in a minimum load on driver attention, and the system should also perform well in a variety of driving conditions. In order to illustrate and test the proposed RECAS methods, a Java program has been developed. This simulation animates a multi-car, multi-lane highway environment where car speeds are assigned randomly, and the proposed RECAS approaches demonstrate rear-end collision avoidance successfully. The Java simulation is an applet, which is easily accessible through the World Wide Web and also can be tested for different angles of the sensor

IVHS Education Program

https://deepblue.lib.umich.edu/bitstream/2027.42/154098/1/gillespie1990.pd

Intelligent Transportation Systems Strategic Plan (Phase I Report)

This interim report on an Intelligent Transportation Systems Strategic (ITS) Plan has been developed as documentation of the process of offering a vision for ITS and recommending an outline for organizational structure, infrastructure, and long-term planning for ITS in Kentucky. This plan provides an overview of the broad scope of ITS and relationships between various Intelligent Vehicle Highway Systems (IVHS) functional areas and ITS user service areas. Three of the functional areas of ITS have been addressed in this interim report with sections devoted to mission, vision, goals, and potential technology applications. Within each of the three areas, recommendations have been made for applications and technologies for deployment. A more formalized business plan for will be developed to recommend specific projects for implementation. Those three functional areas are 1) Advanced Rural Transportation Systems (ARTS), 2) Advanced Traveler Information Systems (ATIS), and 3) Commercial Vehicle Operations (CVO). A survey of other states was conducted to determine the status of the development of ITS strategic plans. Information received from the 11 states that had completed strategic plans was used to determine the overall approach taken in development of the plans and to evaluate the essential contents of the reports for application in Kentucky. Kentucky\u27s ITS Strategic Plan evolved from an early decision by representatives of the Kentucky Transportation Cabinet (KyTC) to formalize the procedure by requesting the Kentucky Transportation Center to prepare a work plan outlining the proposed tasks. Following several introductory meetings of the Study Advisory Committee, additional focus group meetings were held with various transportation representatives to identify ITS issues of importance. Results from these meetings were compiled and used as input to the planning process for development of the Strategic Plan components of ARTS and ATIS. The development of a strategic plan for Commercial Vehicle Operations originated from a different procedure than did the other functional areas of ITS. As part of well-developed commercial vehicle activities through the ITS-related programs of Advantage I-75 and CVISN, Kentucky has become a national leader in this area and has developed a strategic plan of advanced technology applications to commercial vehicles. The strategic plan for Commercial Vehicle Operations was developed out of the convergence of several parallel processes in Kentucky. Empower Kentucky work teams had met over a two-year period to develop improved and more efficient processes for CVO in Kentucky. Their conclusions and recommendations encouraged the further activities of the Kentucky ITS/CVO working group that first convened in the summer of 1996. In an effort to conceptually organize the various ITS/CVO activities in Kentucky, and as a commitment to the CVISN Mainstreaming plan, an inclusive visioning exercise was held in early 1997. Out of this exercise emerged the six critical vision elements that guided the CVO strategic plan. The remaining functional areas to be included in the ITS Strategic Plan will be addressed in the second phase of this study. Those areas are Advanced Traffic Management Systems (ATMS), Advanced Vehicle Control Systems (AVCS), and Advanced Public Transportation Systems (APTS). It is anticipated that a process similar to that developed for the first phase of this study will continue

Intelligent Control of Vehicles: Preliminary Results on the Application of Learning Automata Techniques to Automated Highway System

We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results

The Application of Sensors on Guardrails for the Purpose of Real Time Impact Detection

The United States roadway system has deteriorated over time due to its age, increasing delays in completing preventative maintenance, and the lack of timely repairs following damage to the infrastructure. Proper asset management drives the need for generalized methods to integrate new sensing capabilities into existing Intelligent Transportation Systems in a time efficient and cost effective manner. In this thesis, we present a methodology for the deployment of new sensors into an existing ITS system. The proposed methodology employs a three phase approach that incorporates data modeling, spatial analysis in Geographic Information Systems, and cost optimization to provide enhanced decision support when deploying new sensing capabilities within an existing ITS. Additionally, we also demonstrate the usefulness of computing while integrating these new sensors using a guardrail sensor case study and focusing on data modeling. The results of the three phase methodology demonstrate an effective means for planning new sensor deployments by analyzing tradeoffs in equipment selection yielding the minimum cost solution for a given set of requirements. Furthermore, the results of the data models demonstrate necessary considerations that must be made with a systems engineering method. The data models accomplish this while accounting for asset management principles taking a systematic approach and incorporating engineering principles