• International Journal of Highway Engineering
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• v.14 no.3
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• pp.163-171
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• 2012

Demand Responsive Transit (DRT) services are becoming necessary as part of not only alternative transportation means for elderly and mobility impaired passengers, but also sustainable and flexible transportation options in urban area due to the development of communication technologies and Location Based Services (LBS). It is difficult to investigate the system performance regarding vehicle operational schemes and vehicle routing algorithms due to the lack of commercial software to support door-to-door vehicle simulation for larger area. This study proposes a simulation framework to evaluate innovative and flexible transit systems focusing on various vehicle routing algorithms, which describes data-type requirements for simulating door-to-door service on demand. A simulation framework is applied to compare two vehicle dispatch algorithms, Nearest Vehicle Dispatch (NVD) and Insertion Heuristic (IH) for real-time shared-taxi service in Seoul. System productivity and efficiency of the shared-taxi service are investigated, comparing to the conventional taxi system.

• Convergence Security Journal
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• v.23 no.2
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• pp.115-120
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• 2023

In the domestic physical security (mechanical security) market, there is an increasing variation in the expansion of security areas due to the infrastructure of large enterprises and small and medium-sized enterprises. In other words, problems related to on-site dispatch between companies are constantly being raised due to the limitation of physical security service s to the scope of dispatch according to the dispatch time. Therefore, in this study, based on the results of the criteria for the scope of dispatch as a criterion for dispatch time through simulations related to on-site dispatch, we propose a plan to activate the physical security (mechanical security) market in the future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1962-1967
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• 2009

This paper deals with a design of a platform to simulate PRT vehicle operational control algorithms using on-board embedded process board. The configuration of the platform is composed of the central control module, the station control module, man-machine interface and monitoring module. Since PRT system needs inherently very reliable vehicle operational control algorithm in order to avoid the impact between vehicles, it is very important to construct a simulation platform to test a designed vehicle operational control algorithm during the development process For the test of the proposed platform a path of the each moving vehicle is predefined in the central control system before the dispatch order is given to the vehicle. The simulation results show the effectiveness of the proposed simulation platform for test and evaluation of the PRT operational control algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.24-35
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• 2016

Emergency Vehicle Preemption(EVP) is an operation method which helps to improve response condition of Emergency Vehicle(EV) and it has not yet been introduced in Korea. In order to implement the system, it requires step-by-step plan and selecting a priority area for trial operation. Since a municipal government such as Seoul is too large so it is limited in time and cost to analyze the whole area. Therefore, quantitative and effective selection method for priority area is critical. The aim of this study is to propose a selection method of implementation area for EVP system using the dispatch data analysis. This study also determined the priority area for EVP implementation by analyzing the dispatch data in Seoul and conducted a simulation to evaluate the effects of implementing EVP.

• Fire Science and Engineering
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• v.31 no.3
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• pp.137-143
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• 2017

A sufficient number of ambulances are critical for preventing delayed vehicle dispatch for emergency patients. This study presents effective methodologies for evaluating the effects of ambulance quantities on availability. The statistical properties of the emergency requests and responses were analyzed for a city in Korea. The inter-request times were modeled by statistical distributions. The ambulance dispatch was modeled using simulation, reflecting the shared dispatch among the city districts. The simulation results revealed that the existing ambulance quantity could successfully meet the majority of the requests, but more vehicles were desirable for improvement. The locations of the additional vehicles were determined efficiently by simulations with a greedy approach. The simulations with added vehicles showed a significantly better coverage of the emergency calls. This research can help design improved emergency vehicle operations, and help save lives.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.837-844
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• 2008

In an automated container terminal, various factors affect the operation of container handling equipment such as quay cranes and AGVs, and thus calculating the exact operation time is nearly infeasible. This uncertainty makes it difficult to dispatch AGVs well. In this paper, we propose a simulation-based AGV dispatching algorithm When dispatching an AGV to an operation, the proposed algorithm conducts multiple stochastic simulation for the succeeding AGV operations for the predetermined period to collect stochastic samples of the result of the dispatching. In the stochastic simulation, the uncertainty of crane operations is represented as a simple probability distribution and the operation time of a crane is determined according to this. A dispatching option is evaluated by the total delay time of quay cranes which is estimated by averaging the quay crane delay of each simulation In order to collect a sufficient number of samples that guarantee the credibility of the evaluation, we devised a high-speed simulator that simulates AGV operation The effectiveness of the proposed algorithm is validated by simulation experiments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.64-79
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• 2023

This study reviewed the process of applying the Monte Carlo simulation technique to the traffic allocation problem of metropolitan subways. The analysis applied the assumption of a normal distribution in which the travel time information of the inter-station sample is the basis of the probit model. From this, the average and standard deviation are calculated by separating the traffic between stations. A plan was proposed to apply the simulation with the weights of the in-vehicle time of individual links and the walking and dispatch interval of transfer. Long-distance traffic with a low number of samples of 50 or fewer was evaluated as a way to analyze the characteristics of similar traffic. The research results were reviewed in two directions by applying them to the Seoul Metropolitan Subway Network. The travel time between single stations on the Seolleung-Seongsu route was verified by applying random sampling to the in-vehicle time and transfer time. The assumption of a normal distribution was accepted for sample sizes of more than 50 stations according to the inter-station traffic sample of the entire Seoul Metropolitan Subway. For long-distance traffic with samples numbering less than 50, the minimum distance between stations was 122Km. Therefore, it was judged that the sample deviation equality was achieved and the inter-station mean and standard deviation of the transport card data for stations at this distance could be applied.