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We consider the challenge of testing lane centering ADAS control systems using a differential global positioning system localization strategy. Rather than constructing test scenarios using lane line markers or driving test vehicles on public roads, we develop a testing framework that can be used in both simulation and on open test surfaces with no lane demarcation. The primary sensor we leverage is...
Traffic congestion control is pivotal for intelligent transportation systems. Previous works optimize vehicle speed for different objectives such as minimizing fuel consumption and minimizing travel time. However, they overlook the possible congestion generation in the future (e.g., in 5mins), which may degrade the performance of achieving the objectives. In this paper, we propose a vehicle Trajectory...
Currently, the understanding of the human mobility is an important challenge that has a large number of applications, especially in the study of a nation's ability to thrive economically and socially. Some works have shown that, it is possible to observe developed and developing countries reviewing their administrative regions borders, in order to reduce costs, or to solve ethnic claims and/or independence...
This paper presents an Adaptive Nonlinear Model Predictive Controller for longitudinal motion of automated vehicles which incorporates advance information on future speed demand values, as well as on road grade changes. It is used in combination with a state and parameter estimator to adapt to a changing vehicle mass. This allows improved speed tracking capability for horizontal driving and steep...
In this paper, we propose a central coordination system to compute optimized trajectories of intelligent vehicles in a double lane road with traffic lights. The focus is to decrease travel time when comparing to human drivers traffic. First, we predict the waiting line formation order when vehicles approach traffic lights. Then, we compute a global motion plan in order to force trajectories result...
This paper discusses the time-constrained data delivery problem in vehicular ad hoc networks (VANETs). The unique characteristics of the network present great challenges to the issue. First, there are no always-connected forwarding routes between vehicles. Second, there is an intrinsic tradeoff between communication cost and delivery quality. Third, there is great uncertainty about vehicular mobilities...
Many Vehicular Ad-hoc Networks (VANETs) applications require that each vehicle knows precisely its current position in real time. The Global Positioning System (GPS) is technology most widely used to determine the positioning of vehicles in VANETs. However, the GPS has several drawbacks, one of them is the lack of accuracy of the measurement of impact is the most unacceptable disadvantage. In this...
Automated riving is becoming the focus of various research institutions and companies. In this context, road estimation is one of the most important tasks. Many works propose to realize this task by employing one or multiple of the following orthogonal information sources: road markings from optical lane recognition, leading vehicle, digital map. etc. Each of them has its own strength and drawbacks...
Reliably detecting obstacles and identifying traversable areas is a key challenge in mobile robotics. For redundancy, information from multiple sensors is often fused. In this work we discuss how prior knowledge of the environment can improve the quality of sensor fusion, thereby increasing the performance of an obstacle detection module. We define a methodology to quantify the performance of obstacle...
This paper studies car trajectory predictions desired in several active safety systems, such as automatic emergency braking (AEB) systems and lane keeping systems (LKS). In the former, the car trajectory is estimated such that objects detected within this trajectory in front of current host vehicle are taken into consideration of collision avoidance. In LKS, the trajectory predictor is utilized to...
The ability of autonomous vehicles to successfully replace human drivers depends on their capability to plan safe, efficient and usable paths in dynamically evolving traffic scenarios. This challenge gets more difficult when the autonomous vehicle has to drive through complex scenarios such as intersections which demand interactive behaviour between vehicles. Many autonomous vehicle demonstrations...
Privacy protection is critical for location-based services (LBS). A frequently proposed solution to protect location privacy suggests that the LBS users need to exchange their pseudonyms over time in protected regions called mix-zones. However, how to deploy mix-zones remains an open question and has not been well addressed in previous works. Inspired by the notion that "where you drive more...
Trajectory data contain more spatial, temporal information. So publishing such trajectory data to the public or a third party for data mining, analysis could cause more serious privacy issues. In this work, we demonstrate that the presence of road network can cause serious damage to the identity privacy of individuals. Motivated attackers can utilize the constraints information of road network to...
The development of automated vehicles brings new challenges to road safety. The behavior of the automated vehicles should be carefully designed in order to interact with the environment and other vehicles efficiently and safely. This paper is focused on the learning and decision making methods for the automated vehicles towards safe freeway driving. Based on a multi-agent traffic model, the decision...
The road curvature is an important characteristic, specially for systems tracking a target trajectory. However, in some cases, this value is not available and its dynamics is unknown and has to be estimated to be used by control. By considering vehicle lateral dynamics, the steering system and the Radar/Camera information, the standard Traffic Jam Pilot (TJP) system is presented. Current TJP solutions...
Due to high mobility and intermittent connections in vehicular networks, reliable and efficient vehicular communication is a challenging task. Previous research on Vehicle-to-Vehicle (V2V) communication mostly focuses on achieving reliable transmissions from a given source to a given destination by mining moving patterns of taxicabs. However, to the best of our knowledge, none of them considered the...
Collision on road is a classic and important problem as it brings about great loss on humans' safety and the efficiency of the traffic system. Numerous algorithms have been proposed to address the issue, and most of the existing researches are focused on rear-end, overtaking and lane change scenarios. However, due to the massive computing process, limitation of prediction time and complex layouts...
Road intersections are considered to be bottlenecks for urban transportation whose impacts are longer travel times and wasted human resources. In this paper we focus on vehicle to vehicle communications (V2V) that allow exchanging data between vehicles. Considering that vehicles are controlled by drivers (not autonomous), we do not pretend to take control of them, nor is the goal to avoid collision...
Leakage of user location and traffic patterns is a serious security threat with significant implications on privacy as reported by recent surveys and identified by the US Congress Location Privacy Protection Act of 2014. While mobile phones can restrict the explicit access to location information to applications authorized by the user, they are ill-equipped to protect against side-channel attacks...
The paper deals with the issues that have to be faced when researching a Road User Charging (RUC) in Norway based upon GNSS and with an innovative methodology especially developed to address these issues proposed by CEN-CENELEC TC5/WG1 and supported by the SaPPART COST Action. The paper presents a case study applying the methodology to a specific RUC algorithm developed by the Norwegian company Q-Free...
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