Automatic Speed Control System for Vehicle Approaching and Driving on a Curve

Abstract

Based on the curvature information for an upcoming road, an automatic speed control system regulates vehicle speed to improve vehicle curve following performance. The road information is extracted from a digitally stored map using the current vehicle position obtained from Global Positioning System (GPS) data. Then, a safe curve speed is determined using the lateral dynamics of vehicle in turn to ensure proper curve handling. Other factors, such as vehicle characteristics, driver preferences, and road and environment conditions are also considered so that vehicle safety and driver comfort are enhanced. An acceleration command is generated from the current vehicle speed and the desired curve speed profile. Driving mode, such as conservative, normal, or aggressive mode, can be selected from the console for a desired driving style. The gain and preview time to determine the vehicle cornering speed are selected according to driver’s preference. The functional blocks of the system include computation of the road curvature, determination of a desired curve speed profile for the best cornering performance for an upcoming curve, and regulation of vehicle speed toward the desired speed. Signal input blocks and actuator control blocks are added to interface with the bus oriented sensors and actuators. The entrance and exit conditions block checks for various vehicle status signals to enter or exit the curve speed control mode gracefully. It also generates a diagnostic message when map data is absent or an error occurs on acceleration command computation. The vehicle studies indicated that the curve speed control system is effective in regulating vehicle speed during curve following maneuvers.

Curve speed model for driver assistance based on driving style classification

“…Zhang et al [12] concluded that the curve speed was related to the drivers' preferred velocity and the initial velocity on a curved road. Lee et al [13,14] added three different gain factors associated with vehicles, roads and drivers to the curve speed model to represent how these factors affect the curve speed. However, the process of determining the appropriate gain values was carried out without any on-field experiment for further verification.…”

“…The superelevation i y = 0.04 rad and four kinds of common road adhesion coefficients are 0.4 (gravel), 0.6(wet asphalt), 0.8(dry asphalt) and 0.85(dry concrete) [27]. The curve radiuses are 100 200, 400 and 1000 m. Based on these conditions, four existing curve speed models including the simplified model [27], Glaser's model [8,9], Chen's model [10] and Lee's model [13,14] were compared with the proposed model. Fig.…”

Highly Automated Driving on Highways Based on Legal Safety

“…However, speed limits that are specified for an extended zone do not always reflect the appropriate speed on each road segment in that zone, e.g. in curves [GNL07,Lee08]. Additionally, speed limits are usually fixed, while the appropriate speed varies with day/night and weather conditions, i.e.…”

Design of Intelligent Vehicle Speed Adaption Based on Variable Road Geometry

“…Zhang (Zhang et al, 2012) designed vehicle longitudinal dynamics model using the traction force, aerodynamic force, rolling resistance and road slope. Lee (Lee, 2008) proposed curve speed control system using the upcoming curvature information. The acceleration of vehicle was generated from the current vehicle speed and the desired curve speed.…”