Benoit Vanholme

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.

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.

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.

Controller design for trajectory tracking of autonomous passenger vehicles

This paper presents controllers design procedure for dynamic trajectory tracking of a highly automated vehicle. 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 decoupled design approach of longitudinal and lateral controller is adopted. For the longitudinal controller, a proportional including a feedforward terms is adopted. On the other hand, an adaptive backstepping approach is used in lateral case to deal with model nonlinearities and parameter uncertainties. The developed controller is integrated and tested in simulation environment. Performance of this controller are presented to demonstrate the effectiveness of the proposed controllers.

Fast prototyping of a Highly Autonomous Cooperative Driving System for public roads

This paper presents a framework for a fast prototyping of Advanced Driving Assistance Systems (ADAS). The simulation tool SiVIC is proposed for drastically reducing development time and costs of a vehicle system design. RTMaps® is used as a platform for easily encapsulating the system component algorithms and for effortlessly transferring them from a simulation environment to a physical vehicle. With these tools a Highly Autonomous Cooperative Driving System (HACS) has been designed. A perception component uses a combination of sensors to map the environment. In this paper a cooperative, extended perception with infrastructure-to-vehicle communication (I2V) will be proposed. A co-pilot integrates a fast Total Trajectory Exploration (TTE) method that finds a trajectory that is optimal with respect to the sensed environment. A simple controller on the vehicle actuators is used for guiding the vehicle on this trajectory. The cooperation between human and automation is managed by a Driving Mode Selection Unit (MSU) and a Human Machine Interface (HMI). In this paper a vehicle system which allows highly autonomous driving with human cooperation is called a co-system.

Simulation of automatic vehicle speed control by transponder-equipped infrastructure

A huge amount of research has been done to improve the safety of road environments and reduce the risk of unsafe traffic areas. Initially this research was mainly focused on the perception surrounding a vehicle (local perception with embedded sensors) and its potential reaction on hazardous situation. Since a few years, it has become clear that a local perception is not sufficient. Its extension is essential to minimize risk and maximize the security of the road traffic. To achieve such extension, additional works is required as well as implementation of a lot of devices often very expensive. Therefore, in early design stage, it becomes necessary to have a simulation environment dedicated to prototyping and evaluating these extended and enriched driving assistance systems. For such virtual platform it is mandatory to provide physic-driven road environments, virtual embedded sensors, embedded and virtual communicating devices and physic-base vehicle models. In this publication, we present the prototyping of a speed control application by using beacons put on the road side. The SiVIC simulation platform is used to generate the virtual world (the environment, sensors, beacons, and vehicle). The framework platform RTMaps is used for prototyping the automatic speed control algorithm. The seamless coupling of these platforms allows subsequently embedding the prototyped application directly on a real vehicle.