Tactical-level simulation for intelligent transportation systems

The most difficult but important problem in advance driver assistance system development is how to measure and model the behavioral response of drivers with focusing on the cognition process. This paper describes driver's deceleration and acceleration behavior based on driving situation awareness in the car-following process, and then presents several driving models for analysis of driver's safety approaching behavior in traffic operation. The emphasis of our work is placed on the research of driver's various information process and multi-ruled decisionmaking mechanism by considering the complicated control process of driving; the results will be able to provide a theoretical basis for intelligent driving shaping model.

Section: Driver's Deceleration and Acceleration Behaviormentioning

confidence: 99%

Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model

Wang¹,

Mao²,

Jin³

et al. 2011

“…These systems aim to monitor the current traffic situation it is involved in, and assess the criticality of the situation, which in turn can be used to make informed decisions, avoid risks, and, in general, improve the performance of the system. Besides, human factors are also critical to the successful implementation of ITS 3,[9][10] . These assistant systems may make false 14 use a Bayesian framework to support a braking assistant by assessing the braking probability and the probability that the driver intends to perform a braking action.…”

Section: Introductionmentioning

confidence: 99%

Driver Intention Recognition Method Using Continuous Hidden Markov Model

Hou¹,

Jin²,

Niu³

et al. 2011

In order to make Intelligent Transportation System (ITS) work effectively, a driver intention recognition method is proposed. In this research, three different recognition models were developed based on Continuous Hidden Markov Model (CHMM), and could distinguish left and right lane change intention from normal lane keeping intention. Subjects performed lane change maneuvers and lane keeping maneuvers with driving simulator which simulated highway scenes, parameters that highly correlated with lane change behavior were collected and analyzed. A series of testings and comparisons were done to obtain the optimal model structure and feature set. Results show that, taking the steering wheel angel, steering wheel angle velocity and lateral acceleration as the optimal observation signals, the accuracy can achieve up 95%, and it proved very effective in terms of early intention recognition.

“…7 At present, there are many literatures applying the new theory to study alignment of freeway and mountainous highway, most literatures focus on studying curve's radius and gradient, [8][9][10][11][12][13] and physiological index heart rate is frequently studied. [8][9][10][11]14,15 Vehicle monitoring system, as portion of the Intelligent Transportation Systems which applies state-of-the-art information technologies to provide more efficient and effective solutions to current traffic congest and traffic safety problems, [16][17][18] detects road environment, vehicle condition and driver condition, and alert the driver under potential safety hazard. The maximum straight line length could be an input to vehicle monitoring system, i.e.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Maximum Straight Line Length for Prairie Highway using Driver's Heart Rate Variability

Huo¹,

Li²,

Zhao³

et al. 2011

The attention of driver traveling along a long straight line of prairie highway is easy to be distracted. In this paper, the correlation of straight line length and driver's attention is studied through laboratory simulation experiment and regression analysis. It can be theoretically concluded that the maximum straight line length for prairie highway within which the driver could travel with proper attention is 5km. This study is significant both for prairie highway construction and Intelligent Transportation System.