Probability-Based Decision Making for Automated Highway Driving

Niehaus, Axel; Stengel, Robert F.

doi:10.4271/912869

Cited by 3 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For each value of the time constant, we can calculate the requirements on the sensor noise as follows. From (13), we obtain Iy-rL<rInL (14) Now, in order to satisfy a desired bound s on the error, we can choose TInL(e (15) which gives us the desired sensor noise bound as InLl(e/y (16) For LTI systems, we can analyze the effect on gain margin and phase margin by the inclusion of sensor dynamics and noise. By looking at the system stability marns without the sensor, we can calculate how much can the margins be allowed to reduce in order to have final acceptable values with the sensor.…”

Section: Analysis To Determine Sensor Parametersmentioning

confidence: 99%

“…In fact, traditional solutions of expanding road capacity do not always relieve congestion, and in some cases can even make the condition worse. The research community has done considerable work in the areas related to MIS, especially in the past few years [2][3][4][5][6][7][8][9][10][11][12][13][14]. Some of the aspects of MIS are described as follows:…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

<title>Sensor requirements for control systems with an example of longitudinal headway control of vehicles in automated highway systems</title>

Krishen

Kachroo

1997

SPIE Proceedings

View full text Add to dashboard Cite

There is a need for developing a methodology for obtaining sensor requirements for control systems. This study is an attempt at developing a methodology for specifying sensor needs as part of the design process of dynamic control systems in general, and Automated Highway System (AHS) in particular. Such approaches have not been advanced to-date. The current practice is to assume sensor parameters from available sensors and devise control strategies. That does not in general produce optimal designs. This paper provides a discussion on the sensor requirements needed for longitudinal headway control ofvehicles in an ABS.

show abstract

Section: Analysis To Determine Sensor Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

<title>Sensor requirements for control systems with an example of longitudinal headway control of vehicles in automated highway systems</title>

Krishen

Kachroo

1997

SPIE Proceedings

View full text Add to dashboard Cite

show abstract

Driving Cars by Means of Genetic Algorithms

Sáez

Pérez

Sanjuán

et al. 2008

Parallel Problem Solving From Nature – PPSN X

View full text Add to dashboard Cite

Abstract. The techniques and the technologies supporting Automatic Vehicle Guidance are an important issue. Automobile manufacturers view automatic driving as a very interesting product with motivating key features which allow improvement of the safety of the car, reducing emission or fuel consumption or optimizing driver comfort during long journeys. Car racing is an active research field where new advances in aerodynamics, consumption and engine power are critical each season. Our proposal is to research how evolutionary computation techniques can help in this field. As a first goal we want to automatically learn to drive, by means of genetic algorithms, optimizing lap times while driving through three different circuits.

show abstract

Rule-Based Guidance for Highway Driving in the Presence of Uncertainty

Niehaus

Stengel

1994

Journal of Dynamic Systems, Measurement, and Control

Self Cite

View full text Add to dashboard Cite

The principal objective of this research is to study the feasibility of a real-time, rule-based guidance system for an automobile on a limited-access highway. The inputs to the system are parameters describing the traffic situation, road geometry, vehicle state, and a driver selected goal. The output of the system consists of guidance parameters that command control logic governing the throttle, steering angle, and brakes. During our past research, a dynamic expert system accomplished this guidance task under the assumption that all inputs were available deterministically, i.e., without error. This paper investigates the types and effects of uncertainties encountered in a more realistic environment, and it proposes a stochastic methodology to extend the expert system to handle information that is known only in a probabilistic way.

show abstract

Probability-Based Decision Making for Automated Highway Driving

Cited by 3 publications

References 11 publications

<title>Sensor requirements for control systems with an example of longitudinal headway control of vehicles in automated highway systems</title>

<title>Sensor requirements for control systems with an example of longitudinal headway control of vehicles in automated highway systems</title>

Driving Cars by Means of Genetic Algorithms

Rule-Based Guidance for Highway Driving in the Presence of Uncertainty

Contact Info

Product

Resources

About