Transportation
Results for CTPS 2 are listed in CTPS2.docx.
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Experiments about satisfaction from ridesharing, from mturk
The first two experiemtns asked which explanations are likely to increase user satisfaction
The third experiment ask for satisfaction (1-7) given a scenario and some explanations. It's divided to three:
- pbe: explanations are all known info
- random: explanatiitons are random subset of knwon info
- axis: smart choosing of subset of the known info
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This dataset provides a dataset of high resolution image-grade LiDAR SLAM in .bag format.
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This repository shares some simultaneous localization and mapping (SLAM) datasets and detection datasets for railroad application. In the first stage, we decide to realease some LiDAR, visual, IMU sequence for freight-traffic railways. The ground truth cannot be provided due to safety regulations. Please infer https://github.com/YushengWHU/Railroad-dataset for detailed information.
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The number of private vehicles is still increasing from year to year. In order to limit environmental damage, a proper way of dealing with this trend is the introduction of intelligent automotive infrastructure. Besides traffic management solutions, smart parking guidance systems are important for reducing unnecessary traffic. For this, a key prerequisite are sensor networks that provide information about the occupancy state of every single parking spot in the parking infrastructure of high traffic targets e.g. nearby an airport or shopping mall.
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This dataset contains the vehicular traces from a location in Jeju-si, South Korea. The dataset contains 8,495,739 traces of vehicles. It comprises of major areas/junctions of which one is the intersection from where the Jeju International Airport and Jeju Seaport traffic passes on daily. Jeju International Airport is one of the busiest airpots in the world. Four types of vehicles were considered in the simulation of dataset, i.e., buses, trucks, passenger-cars, taxies. Each trace contains:
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time (timestep in seconds)
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This dataset contains segmented taxi trajectories with passengers within Bangkok, which are extracted from taxi GPS data during the Songkran Festival period (April 11–17, 2019), published by the ITIC Foundation (https://org.iticfoundation.org/).
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This repository contains the problem instances for the paper "Communication-aware Drone Delivery Problem".
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A commonly used definition of spatial disorientation (SD) in aviation is "an erroneous sense of one’s position and motion relative to the plane of the earth’s surface". There exists a wide range of SD use-cases dictated by situational factors, therefore SD has been predominantly studied using reduced motion detection experimental contexts in isolation. The study of SD by use-case makes it difficult to understand general SD occurrence and thus provide viable solutions. To investigate SD in a generalized manner, a two-part Human Activity Recognition (HAR) study was performed.
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