Fawzi Nashashibi

Vehicle detection combining gradient analysis and AdaBoost classification

This paper presents a real-time vision-based vehicles rear detection system using gradient based methods and Adaboost classification, for ACC applications. Our detection algorithm consists of two main steps: gradient driven hypothesis generation and appearance based hypothesis verification. In the hypothesis generation step, possible target locations are hypothesized. This step uses an adaptive range-dependant threshold and symmetry for gradient maxima localization. Appearance-based hypothesis validation verifies those hypothesis using AdaBoost for classification with illumination independent classifiers. The monocular system was tested under different traffic scenarios (e.g., simply structured highway, complex urban environments, varying lightening conditions), illustrating good performance.

Real time visual traffic lights recognition based on Spot Light Detection and adaptive traffic lights templates

This paper introduces a new real-time traffic light recognition system for on-vehicle camera applications. This approach has been tested with good results in urban scenes. Thanks to the use of our generic “Adaptive Templates” it would be possible to recognize different kinds of traffic lights from various countries.

A Review of Motion Planning Techniques for Automated Vehicles

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

Cooperative Multi-Vehicle Localization Using Split Covariance Intersection Filter

Vehicle localization (ground vehicles) is an important task for intelligent vehicle systems and vehicle cooperation may bring benefits for this task. A new cooperative multi-vehicle localization method using split covariance intersection filter is proposed in this paper. In the proposed method, each vehicle maintains an estimate of a decomposed group state and this estimate is shared with neighboring vehicles; the estimate of the decomposed group state is updated with both the sensor data of the ego-vehicle and the estimates sent from other vehicles; the covariance intersection filter which yields consistent estimates even facing unknown degree of inter-estimate correlation has been used for data fusion. A comparative study based simulations demonstrate the effectiveness and the advantage of the proposed cooperative localization method.

Traffic light recognition using image processing compared to learning processes

In this paper we introduce a real-time traffic light recognition system for intelligent vehicles. The method proposed is fully based on image processing. Detection step is achieved in grayscale with spot light detection, and recognition is done using our generic “adaptive templates”. The whole process was kept modular which make our TLR capable of recognizing different traffic lights from various countries.

Vehicle to pedestrian communications for protection of vulnerable road users

Vehicle and pedestrian collisions often result in fatality to the vulnerable road users, indicating a strong need of technologies to protect such vulnerable road users. Wireless communications have potential to support road safety by enabling road users to exchange information. In contrast to vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications for avoidance of inter-vehicle collisions, very limited efforts are made on communication mechanisms for pedestrian safety. This paper addresses the issue in a concrete way. We first formulate the requirement of the minimum information exchange distance for providing road users to have the necessary amount of time to perceive the situation and react. We then report our field tests and measurement based analysis to investigate if a Wi-Fi system can satisfy the application requirement. We also introduce a pedestrian protection application, V2ProVu, which provides the functionalities of the Wi-Fi communications, risk calculation, and hazard alarming. Our study discloses several useful insights including 1) information exchange for a velocity of 80 km/h has to be made before vehicle to pedestrian (V2P) distance is below 72 meters and 2) while this requirement is not too hard for radio communications technologies, the V2P communication range is greatly reduced if the signal is blocked by a human body.

Real-time crash avoidance system on crossroads based on 802.11 devices and GPS receivers

In this paper we study the contribution of inter-vehicular communication in ADAS applications. We thus propose a collaborative system on the crossroads using our 802.11g communications tools and a low cost GPS receiver. Once the vehicles positions exchanged, the crash avoidance is performed by predicting the future positions of both cars and calculating the time to impact and the region of high risk. The prediction is biased in time and space. The time error is due to the GPS and the communication latencies. We thus propose an estimation of both latencies and integrate them in the prediction loop. The space error is caused by the uncertainty of the positions delivered by the GPS receivers. We compensate this error not by considering a deterministic position of the vehicle but by a probability of being in a region of space and by proposing a Kalman filter which first reduces noise on the positioning and second estimates the variance of error on the measurement. This approach is validated through real scenarios of road crossing. We show thus the contribution of the cooperation via the communication devices in the reduction of accidents rate on the crossroads

Real time trajectory prediction for collision risk estimation between vehicles

In this paper, we present our approach for collision risk estimation between vehicles. The vehicles are equipped with GPS receivers and communication devices. Our approach consists on using the knowledge given trough communication tool to predict the trajectories of the surrounding vehicles. Based on these trajectories, we identify the configurations of the collisions between vehicles. The risk is calculated using several indicators that are reflecting not only the possible collisions but also the dangerousness of these collisions. Our algorithm is tested on crossroads using scenarios involving real prototypes producing realistic scenarios.

Platooning control using visible light communications: A feasibility study

The major benefits of driving vehicles in controlled close formations such as platoons are that of increasing traffic fluidity and reducing air pollution. While Vehicle-toVehicle (V2V) communications is requisite for platooning stability, the existing radio communications technologies (e.g., the IEEE 802.11p) suffer from poor performance in highly dense road scenarios, which are exactly to be created by platooning. This paper studies the applicability of visible light communications (VLC) system for information exchange between the platoon members. A complete VLC model is built enabling precise calculations of Bit-Error-Rate (BER) affected by inter-vehicle distance, background noise, incidence angle and receiver electrical bandwidth. Based on our analytical model, the optical parameters suiting platooning application are defined. Finally, a SIMULINK model is developed to study the performances of a platooning longitudinal and lateral control, where VLC is used for V2V information exchange. Our study demonstrates the feasibility of VLC-based platooning control even in the presence of optical noise at significant levels and up to a certain road curvature.

Digitizing and 3D modeling of urban environments and roads using vehicle-borne laser scanner system

In this paper we present a system for three-dimensional environment modeling. It consists of an instrumented vehicle equipped with a 2D laser range scanner for data mapping, and GPS, INS and odometers for vehicle positioning and attitude information. The advantage of this system is its ability to perform data acquisition during the vehicle navigation; the sensor needed being a basic 2D scanner with opposition to traditional expensive 3D sensors. This system integrates the laser raw range data with the vehicles internal state estimator and is capable of reconstructing the 3D geometry of the environment by real-time geo-referencing. We propose a high level representation of the urban scene while identifying automatically and in real time some types of existing objects in this environment. Thus, our modeling is articulated around three principal axes: the segmentation, decimation, the 3D reconstruction and visualization. The road is the most important object for us; some road features like the curvature and the width are extracted.