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Mobility profiles of users play a crucial role in a wide range of context-aware computing and services. Travel mode choice, as a representative feature of mobility profiles, is one of the important components in travel demand and future planning of transportation systems. Transportation mode choice has been widely studied based on the random utility model and decision making methods which haven't...
This work addresses the general problem of risk evaluation in traffic scenarios for the case of limited observability of the scene due to a restricted sensory coverage. Here we especially concentrate on intersection scenarios, which are visually difficult to access. To distinguish the area of sight, we employ publicly available digital map data which includes, besides the general road geometry, information...
Accidents at intersections are highly related to the driver's mis-decision while performing turning and merging maneuvers. This paper proposes a merging/turning controller for an automated vehicle, called the ego vehicle, which avoids collisions with surrounding (target) vehicles. An optimization-based control problem is defined based on receding horizon control, that parameterizes the system trajectory...
This paper considers the problem of controlling an autonomous vehicle that must share the road with human-driven cars.We present proactive collision avoidance algorithms that take into account the expressed intent of human driven cars and minimize the need for sudden braking or other purely reactive sudden actions. The presented algorithm utilizes multi-stage Gaussian Processes (GPs) in order to learn...
This work addresses two topics. On one hand we study the problem of general measures for spatio-temporal trajectory similarity based on the evaluation of longitudinal and lateral spatio-temporal distance. On the other hand we employ trajectory similarity measures to general situation classification problems for traffic scenarios, which include the well-known problem of lane assignment and driving...
This paper presents an efficient model for combining automotive trajectory planning with predicted environment interactions, named progressively interacting trajectories (PITRA). It allows to plan trajectories for fully-automated vehicles by actively considering how other traffic participants will react to the trajectory, while retaining many of the advantages of variational trajectory optimization...
This paper assesses the predictability of individual vehicle's mobility in Beijing expressway system using Electronic Toll Collection (ETC) data records. By examining the uncertainties of movements using entropy, considering both the frequencies and sequential correlations of vehicles' trajectories, we draw to the conclusion that the average limit of predictability of expressway vehicles mobility...
We consider the task of accurately controlling a complex system, such as autonomously sliding a car sideways into a parking spot. Although certain regions of this domain are extremely hard to model (i.e., the dynamics of the car while skidding), we observe that in practice such systems are often remarkably deterministic over short periods of time, even in difficult-to-model regions. Motivated by this...
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