Autonomous Intelligent Cruise Control Systems Research Articles

Linear Acceleration Car-Following Model Development and Validation

A linear acceleration car-following model has been developed for realistic simulation of traffic flow in intelligent transportation systems (ITS) applications. The new model provides continuous acceleration profiles instead of the stepwise profiles that are currently used. The brake reaction times of the drivers are simulated effectively and are independent of the simulation time steps. Chain-reaction times of the drivers are also simulated and perception thresholds are incorporated in the model. The preferred time headways are utilized to determine the simulated drivers’ separation during car-following. The features of the model and the realistic vehicle simulation in car-following and in stop-and-go conditions make this model suitable to ITS, especially to autonomous intelligent cruise-control systems. The car-following algorithm is validated at microscopic and macroscopic levels by using field data. Simulated versus field trajectories and statistical tests show very strong agreement between simulation results and field data.

Driver- and Situation-Specific Effects on Assistance Systems for Speed and Distance Control

AICC (Autonomous Intelligent Cruise Control) systems, as investigated in the European PROMETHEUS and DRIVE projects, should support the driver in longitudinal vehicle control. The presented study analyzed driver- and situation-specific effects, which have to be considered when developing or evaluating AICCs. The investigations focused on assistance systems, which inform or warn a driver in case of inadequate speed or distance. Messages to the driver are transferred either acoustically or visually or via active control devices, such as an “active gas-pedal”. Driving experiments were performed, whereby subjects' distance keeping behavior was monitored. As a first step before experimental evaluation, relevant traffic situations for AICC application were identified and classified. The results of the subsequent situation analysis reveal driver- and situation-specific characteristics. Typical effects are found in frequency and duration of various AICC situations, in distance distribution when following, and in minimum distance when approaching a preceding vehicle. From situation analysis, first consequences were derived showing off capabilities and limitations of AICC systems on principle and of an “active gas-pedal” in particular.

Intelligent cruise control and roadside information

An onboard autonomous intelligent cruise control system which controls a vehicle's speed according to the driver's desire and the speed of and distance to the preceding vehicle is discussed. The system offers a one-directional short-range system for vehicle-vehicle and roadside-vehicle communication and considerations for recommended speed, limits, and traffic signals. It is a potential key element in linking and integrating the driver-vehicle-infrastructure in future intelligent transportation systems. Two field trials undertaken to determine the feasibility of the system are described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Autonomous intelligent cruise control

Vehicle following and its effects on traffic flow has been an active area of research. Human driving involves reaction times, delays, and human errors that affect traffic flow adversely. One way to eliminate human errors and delays in vehicle following is to replace the human driver with a computer control system and sensors. The purpose of this paper is to develop an autonomous intelligent cruise control (AICC) system for automatic vehicle following, examine its effect on traffic flow, and compare its performance with that of the human driver models. The AICC system developed is not cooperative; i.e., it does not exchange information with other vehicles and yet is not susceptible to oscillations and slinky effects. The elimination of the slinky effect is achieved by using a safety distance separation rule that is proportional to the vehicle velocity (constant time headway) and by designing the control system appropriately. The performance of the AICC system is found to be superior to that of the human driver models considered. It has a faster and better transient response that leads to a much smoother and faster traffic flow. Computer simulations are used to study the performance of the proposed AICC system and analyze vehicle following in a single lane, without passing, under manual and automatic control. In addition, several emergency situations that include emergency stopping and cut-in cases were simulated. The simulation results demonstrate the effectiveness of the AICC system and its potentially beneficial effects on traffic flow. >