• Title/Summary/Keyword: Travel Path

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Development of Path Travel Time Distribution Estimation Algorism (경로통행시간 분포비율 추정 알고리즘 개발)

  • Lee, Young-Woo
    • Journal of Korean Society of Transportation
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    • v.23 no.6 s.84
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    • pp.19-30
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    • 2005
  • The objective of this research is to keep track of path travel time using methods of collecting traffic data. Users of traffic information are looking for extensive information on path travel time, which is referred to as the time taken for traveling from the origin to the destination. However, all the information available is the average path travel times, which is a simple sum of the average link travel times. The average path travel time services are not up to the expectation of traffic information consumers. To improve provide more accurate path travel time services, this research makes a number of different estimates of various path travel times on one path, assuming it will be under the same condition, and provides a range of estimates with their probabilities to the consumers, who are looking for detailed information. To estimate the distribution of the path travel times as a combination of link travel times. this research analyzes the relation between the link travel time and path travel time. Based on the result of the estimation. this research develops the algorithm that combines the distribution of link travel time and estimates the path travel time based on the link travel times. This algorithm was tested and proven to be highly reliable for estimating the path traffic time.

An Expressway Path Travel Time Estimation Using Hi-pass DSRC Off-Line Travel Data (하이패스 DSRC 자료를 활용한 고속도로 오프라인 경로통행시간 추정기법 개발)

  • Shim, Sangwoo;Choi, Keechoo;Lee, Sangsoo;NamKoong, Seong J.
    • Journal of Korean Society of Transportation
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    • v.31 no.3
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    • pp.45-54
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    • 2013
  • Korea Expressway Corporation has been utilizing vehicles equipped with dedicated short range communication (DSRC) based on-board equipment (OBE) for collecting path travel times. A path based method (PBM) estimates the path travel time using probe vehicles traveling whole links on the path, so it is not always possible to obtain sufficient samples for calculating path travel time in the DSRC system. Having this problem in utilizing DSRC for travel time information, this study attempted to estimate path travel time with the help of a link based method (LBM) and examined whether the LBM can be used for obtaining reliable path travel times. Some comparisons were made and identified that the MAPE difference between the LBM and the PBM estimates are less than 3%, signaling that LBM can be used as a proxy for PBM in case of sparse sample conditions. Some limitations and a future research agenda have also been proposed.

A Path Travel Time Estimation Study on Expressways using TCS Link Travel Times (TCS 링크통행시간을 이용한 고속도로 경로통행시간 추정)

  • Lee, Hyeon-Seok;Jeon, Gyeong-Su
    • Journal of Korean Society of Transportation
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    • v.27 no.5
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    • pp.209-221
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    • 2009
  • Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

A Study on Spatial Aggregation Method for Path Travel Time Estimation using Hi-Pass DSRC System (하이패스 DSRC 기반의 경로통행시간 산정을 위한 공간적 집계방안 산정에 관한 연구)

  • Lee, Hwanpil;Shim, Sangwoo;Choi, Yuntaek;Kim, Dongin
    • International Journal of Highway Engineering
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    • v.16 no.3
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    • pp.119-129
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    • 2014
  • PURPOSES : This investigational survey is to observe a proper spatial aggregation method for path travel time estimation using the hi-pass DSRC system. METHODS : The links which connect the nodes of section detectors location are used for path travel time estimation traditionally. It makes some problem such as increasing accumulation errors and processing times. In this background, the new links composition methods for spatial aggregation are considered by using some types of nodes as IC, JC, RSE combination. Path travel times estimated by new aggregation methods are compared with PBM travel times by MAE, MAPE and statistical hypothesis tests. RESULTS : The results of minimum sample size and missing rate for 5 minutes aggregation interval are satisfied except for JC link path travel time in Seoul TG~Kuemho JC. Thus, it was additionally observed for minimum sample size satisfaction. In 15, 30 minutes and 1 hour aggregation intervals, all conditions are satisfied by the minimum sample size criteria. For accuracy test and statistical hypothesis test, it has been proved that RSE, Conzone, IC, JC links have equivalent errors and statistical characteristics. CONCLUSIONS : There are some errors between the PBM and the LBM methods that come from dropping vehicles by rest areas. Consequently, this survey result means each of links compositions are available for the estimation of path travel time when PBM vehicles are missed.

Development of the Multi-Path Finding Model Using Kalman Filter and Space Syntax based on GIS (Kalman Filter와 Space Syntax를 이용한 GIS 기반 다중경로제공 시스템 개발)

  • Ryu, Seung-Kyu;Lee, Seung-Jae;Ahn, Woo-Young
    • Journal of Korean Society of Transportation
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    • v.23 no.7 s.85
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    • pp.149-158
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    • 2005
  • The object of this paper is to develop the shortest path algorithm. The existing shortest path algorithm models are developed while considering travel time and travel distance. A few problems occur in these shortest path algorithm models, which have paid no regard to cognition of users, such as when user who doesn't have complete information about the trip meets a strange road or when the route searched from the shortest path algorithm model is not commonly used by users in real network. This paper develops a shortest path algorithm model to provide ideal route that many people actually prefer. In order to provide the ideal shortest path with the consideration of travel time, travel distance and road cognition, travel time is predicted by using Kalman filtering and travel distance is predicted by using GIS attributions. The road cognition is considered by using space data of GIS. Optimal routes provided from this paper are shortest distance path, shortest time path, shortest path considering distance and cognition and shortest path considering time and cognition.

Leveraging Visibility-Based Rewards in DRL-based Worker Travel Path Simulation for Improving the Learning Performance

  • Kim, Minguk;Kim, Tae Wan
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.5
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    • pp.73-82
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    • 2023
  • Optimization of Construction Site Layout Planning (CSLP) heavily relies on workers' travel paths. However, traditional path generation approaches predominantly focus on the shortest path, often neglecting critical variables such as individual wayfinding tendencies, the spatial arrangement of site objects, and potential hazards. These oversights can lead to compromised path simulations, resulting in less reliable site layout plans. While Deep Reinforcement Learning (DRL) has been proposed as a potential alternative to address these issues, it has shown limitations. Despite presenting more realistic travel paths by considering these variables, DRL often struggles with efficiency in complex environments, leading to extended learning times and potential failures. To overcome these challenges, this study introduces a refined model that enhances spatial navigation capabilities and learning performance by integrating workers' visibility into the reward functions. The proposed model demonstrated a 12.47% increase in the pathfinding success rate and notable improvements in the other two performance measures compared to the existing DRL framework. The adoption of this model could greatly enhance the reliability of the results, ultimately improving site operational efficiency and safety management such as by reducing site congestion and accidents. Future research could expand this study by simulating travel paths in dynamic, multi-agent environments that represent different stages of construction.

Personalized Travel Path Recommendation Scheme on Social Media (소셜 미디어 상에서 개인화된 여행 경로 추천 기법)

  • Aniruddha, Paul;Lim, Jongtae;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.19 no.2
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    • pp.284-295
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    • 2019
  • In the recent times, a personalized travel path recommendation based on both travelogues and community contributed photos and the heterogeneous meta-data (tags, geographical locations, and date taken) which are associated with photos have been studied. The travellers using social media leave their location history, in the form of paths. These paths can be bridged for acquiring information, required, for future recommendation, for the future travellers, who are new to that location, providing all sort of information. In this paper, we propose a personalized travel path recommendation scheme, based on social life log. By taking advantage, of two kinds of social media, such as travelogue and community contributed photos, the proposed scheme, can not only be personalized to user's travel interest, but also be able to recommend, a travel path rather than individual Points of Interest (POIs). The proposed personalized travel route recommendation method consists of two steps, which are: pruning POI pruning step and creating travel path step. In the POI pruning step, candidate paths are created by the POI derived. In the creating travel path step, the proposed scheme creates the paths considering the user's interest, cost, time, season of the topic for more meaningful recommendation.

Comparison of Two Methods for Measuring Daily Path Lengths in Arboreal Primates

  • Lappan, Susan
    • Journal of Ecology and Environment
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    • v.30 no.2
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    • pp.201-207
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    • 2007
  • Researchers have used a variety of methods to measure patterns of animal movement, including the use of spatial data (mapping the position of a moving animal at specified intervals) and direct estimation of travel path length by pacing under a moving animal or group. I collected movement data from five groups of siamangs (Symphalangus syndactylus) using two different methods concurrently to estimate the effects of the method of data collection on estimates of daily path length (DPL). Estimates of DPL produced from spatial data collected at 15-minute intervals were 12% lower than estimates of DPL produced by pacing under the traveling animal. The actual magnitude of the difference was correlated with the travel distance, but there was no correlation between the proportional difference and the travel distance. While the collection of spatial data is generally preferable, as spatial data permit additional analyses of patterns of movements in two or three dimensions, the relatively small difference between the DPL's produced using different methods suggests that pacing is an acceptable substitute where the collection of spatial data is impractical. I also subsampled the spatial data at increasing time intervals to assess the effect of sampling interval on the calculation of daily path lengths. Longer sampling intervals produced significantly shorter estimates of travel paths than shorter sampling intervals. These results suggest that spatial data should be collected at short time intervals wherever possible, and that sampling intervals should not exceed 30 minutes. Researchers should be cautious when comparing data generated using different methods.

Leveraging Reinforcement Learning for Generating Construction Workers' Moving Path: Opportunities and Challenges

  • Kim, Minguk;Kim, Tae Wan
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1085-1092
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    • 2022
  • Travel distance is a parameter mainly used in the objective function of Construction Site Layout Planning (CSLP) automation models. To obtain travel distance, common approaches, such as linear distance, shortest-distance algorithm, visibility graph, and access road path, concentrate only on identifying the shortest path. However, humans do not necessarily follow one shortest path but can choose a safer and more comfortable path according to their situation within a reasonable range. Thus, paths generated by these approaches may be different from the actual paths of the workers, which may cause a decrease in the reliability of the optimized construction site layout. To solve this problem, this paper adopts reinforcement learning (RL) inspired by various concepts of cognitive science and behavioral psychology to generate a realistic path that mimics the decision-making and behavioral processes of wayfinding of workers on the construction site. To do so, in this paper, the collection of human wayfinding tendencies and the characteristics of the walking environment of construction sites are investigated and the importance of taking these into account in simulating the actual path of workers is emphasized. Furthermore, a simulation developed by mapping the identified tendencies to the reward design shows that the RL agent behaves like a real construction worker. Based on the research findings, some opportunities and challenges were proposed. This study contributes to simulating the potential path of workers based on deep RL, which can be utilized to calculate the travel distance of CSLP automation models, contributing to providing more reliable solutions.

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A Study on the Improvement of Means of Egress Based on NFPA 101 (NFPA 101 피난 안정성 평가에 기초한 피난 규정 개선 방향 연구)

  • Kyeung-Ho Kang;Suck-Hwan Joung
    • Journal of the Korea Safety Management & Science
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    • v.25 no.1
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    • pp.31-38
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    • 2023
  • The object of this study is to evaluate whether the means of egress of Jechon Sports Center and Miryang Sejong Hospital, where massive fire human casualties occurred in 2017 and 2018 respectively, comply with NFPA 101(Life Safety Code), and to suggest the need for supplementation of domestic means of egress regulations. The study evaluated the number and arrangement of the means of egress, travel distance, common path of travel, dead end and discharge from exit for each building by applying the means of egress regulations of NFPA 101. As a result of the evaluation through NFPA 101, the travel distance was appropriate, but some of the other items except for the travel distance did not meet NFPA 101. The regulations that need to be supplemented are 1)occupant load calculation 2)egress capacity calculation 3)continuous concept of means of egress 4)concept of common path of travel. It is especially necessary to revise the requirement for fire door of the evacuation floor(normal 1st floor) of the stairwell in case of below the five story building.