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In most of the traffic safety studies, both the identification of high-risk locations and the assessment of safety improvement solutions are done through the use of historical crash data. This study proposes an alternative approach that makes use of traffic conflicts extracted from traffic video recordings for safety assessment. State-of-the-art computer vision techniques are used to extract vehicle...
The objective of this paper is the application and statistical analysis of a methodology that allows the estimation of Signal Phase and Timing (SPaT) information like cycle length and green time intervals for time-dependent fixed-time controlled or traffic actuated intersections based on low-frequency and sparse vehicular probe data, so called Floating Car Data (FCD). To infer SPaT, the applied approach...
Human mobility is known to follow simple reproducible patterns, i.e., humans tend to travel a few known places. Early detection of those “significant journeys” has a prospect for emerging smart applications like real-time traffic route recommendation and automated HVAC (heating, ventilating, and air conditioning) systems. In this paper, we design, implement, and evaluate a mobile system that effectively...
This paper concerns optimally controlling an autonomous vehicle to perform safe and comfortable overtaking of a slower moving leading vehicle using model predictive control. The contribution of this paper is to further analyze the convex relaxation that was introduced in [1] in order to see how it compares with the standard formulation. The main difference between the formulations is that the sampling...
Plug-in hybrid electric vehicles (PHEVs) are a promising step toward reaching a fully green passenger vehicle with large pre-chargeable batteries which offer a very good fuel economy. Many researchers are now focussing on making vehicles safer and more efficient by improving vehicles' interaction with their environment and assisting drivers to make better decisions with less errors. Adaptive Cruise...
Real-time path planning constitutes one of the hot topics when developing automated driving. Different path planning techniques have been studied in both the robotics and automated vehicles fields trying to improve the trajectory generation and its tracking. In this paper, a novel local path planning algorithm combining both off-line and real-time generation for automated vehicles in urban environments...
JAMSTEC has proposed an operation of multiple AUVs using an ASV (Autonomous Surface Vehicle) to improve survey efficiency. For this purpose, an ASV “MAINAMI” with a length of 6 meters has been developed since 2013. The vehicle is equipped with an acoustic communication device and a satellite one, in order to relay information between an AUV and operators on a ship or on land. In February 2016, its...
The paper at hand proposes a real-time capable approach to combined trajectory planning and control. One single prediction model is used to plan a feasible trajectory and to perform lateral guidance of the vehicle at the same time. Nonlinear model predictive control (NMPC) methods are applied to solve the optimal control problem, which incorporates environmental constraints leading to a model predictive...
Autonomous driving in urban environments depends on the ability to interpret the current situation and to react accordingly. This means to continuously make decisions for certain comfort-optimized maneuvers under the constraints of traffic rules and feasibility. This work presents a novel, longitudinal driving strategy formulated as a discrete planning problem. Instead of designing an algorithm for...
We propose a method for ego-lane estimation that can robustly determine the currently used lane as required by future lane-precise navigation systems. It employs a lane-level map-matching on a digital road map through least-squares optimization and only requires sensors available in current production vehicles, such as GPS, odometry, visual lane-marking detection and radars. Radar data is used in...
Dynamic on-road driving scenarios require robust methods for planning a safe and feasible vehicle motion coping with both static and dynamic obstacles. Many of the different approaches which have been proposed to tackle this challenge are based on optimal control and employ local continuous or discrete optimization schemes. While discrete methods possess the ability to find reasonable solutions in...
This article presents a path planning concept for automated driving. It builds upon existing approaches using quintic polynomials for path planning in structured environments. The contribution of this work are analytical solutions to evaluate selected properties of quintic polynomial based paths such as maximum acceleration and jerk or overshooting behavior. In addition, a concept for generating asymmetrical...
In many traffic situations there are times where interaction with other drivers is necessary and unavoidable in order to safely progress towards an intended destination. This is especially true for merge manoeuvres into dense traffic, where drivers sometimes must be somewhat aggressive and show the intention of merging in order to interact with the other driver and make the driver open the gap needed...
One of the key factors to ensure the safe operation of autonomous and semi-autonomous vehicles in dynamic environments is the ability to accurately predict the motion of the dynamic obstacles in the scene. In this work, we show how to use a realistic driver model learned from demonstrations via Inverse Reinforcement Learning to predict the long-term evolution of highway traffic scenes. We model each...
The research community has shown significant improvements in both vision-based detection and tracking of vehicles, working towards a high level understanding of on-road maneuvers. Behaviors of surrounding vehicles in a highway environment is found as an interesting starting point, of why this dataset is introduced along with its challenges and evaluation metrics. A vision-based multi-perspective dataset...
Global Positioning System (GPS) which is a part of the Geographical Information System(GIS) is used for the efficient mapping of the traffic trajectories in the real world scenario.It uses GPS logs of roadways which is useful in the routing applications like Smart Maps. The historical GPS logs which is a collection of numerous GPS points are provided to find the landmark graph. Beyond that the live...
In this paper, the performance of the well-known Generalized Adaptive Smoothing Method (GASM) as online traffic speed estimator with Floating Car Data (FCD) as single source of data is assessed. Therefore, the main challenges originating from the sparseness and delay in collecting FCD are addressed and a procedure using the GASM is proposed that allows estimating traffic velocities continuously. In...
The goal of the work in this paper is to use occupancy grid in integrating safety distances with the planning strategy for autonomous vehicle navigation. The challenge is to avoid static and dynamic obstacles at high speed with respect to some specific road rules while following a global reference trajectory. Our local trajectory planning algorithm is based on the method of clothoid tentacles. It...
This paper considers the problem of optimal trajectory generation for autonomous driving under both continuous and logical constraints. Classical approaches based on continuous optimization formulate the trajectory generation problem as a nonlinear program, in which vehicle dynamics and obstacle avoidance requirements are enforced as nonlinear equality and inequality constraints. In general, gradient-based...
Modeling of decision-making behavior for discretionary lane-changing execution (DLCE) is fundamental to both movement simulation and controlling design of automatic vehicles. The existing gap acceptance models ingored the nonlinearity of drivers' DLCE decision-making behavior. Therefore, this study tries to analyze and simulate the DLCE decision-making behavior using the real trajectory data. First,...
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