Sebastien Glaser

Maneuver-Based Trajectory Planning for Highly Autonomous Vehicles on Real Road With Traffic and Driver Interaction

This paper presents the design and first test on a simulator of a vehicle trajectory-planning algorithm that adapts to traffic on a lane-structured infrastructure such as highways. The proposed algorithm is designed to run on a fail-safe embedded environment with low computational power, such as an engine control unit, to be implementable in commercial vehicles of the near future. The target platform has a clock frequency of less than 150 MHz, 150 kB RAM of memory, and a 3-MB program memory. The trajectory planning is performed by a two-step algorithm. The first step defines the feasible maneuvers with respect to the environment, aiming at minimizing the risk of a collision. The output of this step is a target group of maneuvers in the longitudinal direction (accelerating or decelerating), in the lateral direction (changing lanes), and in the combination of both directions. The second step is a more detailed evaluation of several possible trajectories within these maneuvers. The trajectories are optimized to additional performance indicators such as travel time, traffic rules, consumption, and comfort. The output of this module is a trajectory in the vehicle frame that represents the recommended vehicle state (position, heading, speed, and acceleration) for the following seconds.

Time to line crossing for lane departure avoidance: a theoretical study and an experimental setting

The main goal of this paper is to develop a distance to line crossing (DLC) based computation of time to line crossing (TLC). Different computation methods with increasing complexity are provided. A discussion develops the influence of assumptions generally assumed for approximation. A sensitivity analysis with respect to vehicle parameters and positioning is performed. For TLC computation, both straight and curved vehicle paths are considered. The road curvature being another important variable considered in the proposed computations, an observer for its estimation is then proposed. An evaluation over a digitalized test track is first performed. Real data are then collected through an experiment carried out in test tracks with the equipped prototype vehicle. Based on these real data, TLC is then computed with the theoretically proposed methods. The obtained results outlined the necessity to take into consideration vehicle dynamics to use the TLC as a lane departure indicator.

Highly Automated Driving on Highways Based on Legal Safety

This paper discusses driving system design based on traffic rules. This allows fully automated driving in an environment with human drivers, without necessarily changing equipment on other vehicles or infrastructure. It also facilitates cooperation between the driving system and the host driver during highly automated driving. The concept, referred to as legal safety, is illustrated for highly automated driving on highways with distance keeping, intelligent speed adaptation, and lane-changing functionalities. Requirements by legal safety on perception and control components are discussed. This paper presents the actual design of a legal safety decision component, which predicts object trajectories and calculates optimal subject trajectories. System implementation on automotive electronic control units and results on vehicle and simulator are discussed.

Road slope and vehicle dynamics estimation

Driving safely can be achieved by the prevention of risky situations which may require the knowledge of vehicle dynamic state as well as road geometry. It is thus essential to have in real-time a good estimation of the related variables and parameters. Among the parameters of the road that are influencing vehicle longitudinal motion one can find the slope which can not be measured with reduced cost sensor. Vehicle lateral motion is mainly affected by the value of the lateral speed which can not simply measured too. In this paper, an observer based method for the estimation of the vehicle dynamics using a nonlinear vehicle model is proposed. It uses a combination of Extended Kalman filter (EKF) and Luenberger Observer (LO). The observers use several standard measurements such as : the yaw rate, the steering angle and the rotational velocity of the four tires. Experimental tests conducted with a prototype vehicle prove the effectiveness of the proposed approach.

Vehicle lateral dynamics estimation using unknown input proportional-integral observers

This paper proposes a robust state and fault estimation of vehicle lateral dynamics by means of proportional integral observers. The observer is able to estimate the state and any constant or varying fault signals even in presence of road bank, sensor noise or offset. A framework for common road adhesion factor estimation and road bank angle estimation is also proposed. Field test results obtained with a prototype vehicle show the effectiveness of the approach for performing in real conditions

Speed Limitation Based on an Advanced Curve Warning System

This paper presents an integrated system to prevent driver from taking a curve with a dangerous speed. The integrated system underlines three functions developed as follows : the first function consists in knowing the geometry characteristics of the coming road; the second function has to compute a safe speed according to the road section, the vehicle and the driver; the last function must impose the speed control of the vehicle in order to achieve a safe speed in the case that the driver does not achieve it.

Low cost IMU-Odometer-GPS ego localization for unusual maneuvers

This paper presents the problem of outdoor vehicle localization during unusual maneuvers with the Interacting Multiple Model (IMM) and Extended Kalman Filter (EKF) approaches. IMM, contrary to classical methods, is based on the discretization of the vehicle evolution space into simple maneuvers. Each maneuver is represented by a simple dynamic model such as a constant velocity or a constant turning model. This allows the method to be optimized for highly dynamic vehicles. In this work, we focus on unusual vehicle maneuvers during some special driving situations, including very strong accelerations, high speed turnings or backwards driving with stop stages. The presented results are based on real measurements collected from different scenarios. Based on an EKF vs. IMM comparison, these results show a real interest of using the IMM method in order to take into account unusual maneuvers.

Automatic Parallel Parking in Tiny Spots: Path Planning and Control

This paper presents automatic parallel parking for a passenger vehicle, with highlights on a path-planning method and on experimental results. The path-planning method consists of two parts. First, the kinematic model of the vehicle, with corresponding geometry, is used to create a path to park the vehicle in one or more maneuvers if the spot is very narrow. This path is constituted of circle arcs. Second, this path is transformed into a continuous-curvature path using clothoid curves. To execute the generated path, control inputs for steering angle and longitudinal velocity depending on the traveled distance are generated. Therefore, the traveled distance and the vehicle pose during a parking maneuver are estimated. Finally, the parking performance is tested on a prototype vehicle.

Integrated Driver–Vehicle–Infrastructure Road Departure Warning Unit

In this paper, a road-departure warning unit taking into account driver-vehicle-infrastructure (DVI) interactions is proposed. The longitudinal and lateral vehicle dynamics limits are analyzed to detect the road departure on loss of control. Vehicle positioning and time to lane crossing (TLC) are used to detect the road departure on a defect of guidance. Prevention of excessive longitudinal speed is handled through the computation of a critical longitudinal speed when approaching a curve and speed profile generation in the straight road section preceding the curve. For the lateral mode, the vehicle oversteering or understeering, the yaw motion, and the lateral acceleration are analyzed. The vehicle lateral displacement and the TLC values are also examined when the vehicle dynamics are not excessive. Necessary data for detection algorithms, which are not available from measurements, are estimated using an extended Kalman filter. The system consists of several subsystems, which work in parallel and provide warning through a dedicated human-machine interface (HMI). This road-departure warning system is experimentally tested on a test track using a prototype vehicle. It is found to be efficient and robust.

Trajectory Tracking for Highly Automated Passenger Vehicles

In this paper, the design of the longitudinal and lateral controller for dynamic trajectory tracking is presented. The main objective is to follow the planned trajectories generated by a co-pilot module in the safe way despite the presence of vehicle model uncertainties and also to guarantee a passenger comfort by generating soft actions on the steering wheel and accelerations. A primary experimental implementation on the vehicle test prototype is presented.