• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.5
• /
• pp.1087-1096
• /
• 2011

Vehicular Ad Hoc Network(VANET) using wireless network is offering the communications between vehicle and vehicle(V2V) or vehicle and infrastructure(V2I). VANET is being actively researched from industry field and university because of the rapid developments of the industry and vehicular automation. Information, collected from VANET, of velocity, acceleration, condition of road and environments provides various services related with safe drive to the drivers, so security over network is the inevitable factor. For the secure message authentication, a number of authentication proposals have been proposed. Among of them, a scheme, proposed by Jung, applying database search algorithm, Bloom filter, to RAISE scheme, is efficient authentication algorithm in a dense space. However, k-anonymity used for obtaining the accurate vehicular identification in the paper has a weak point. Whenever requesting the righteous identification, all hash value of messages are calculated. For this reason, as the number of car increases, a amount of hash operation increases exponentially. Moreover the paper does not provide a complete key exchange algorithm while the hand-over operation. In this paper, we use a Received Signal Strength Indicator(RSSI) based velocity and distance estimation algorithm to localize the identification and provide the secure and efficient algorithm in which the problem of hand-over algorithm is corrected.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.107-116
• /
• 2002

Crash Cushion is a kind of safety facilities on roadside which acts the role of absorbing impact energy when vehicles are driven out of normal route such as Gore area of freeway off ramp. Criteria for severity index considering accident occurrence possibility are needed to have strong effect on installing the facilities. However, present criteria for establishing crash cushion design do not include such processes. Therefore, the paper presents two kinds of study to develop criteria for severity index. First of all, development of accident forecasting model on freeway off ramp is presented. The module is a relationship between accidents and road environment by negative binomial distribution (NB) which is called to reflect very well quality of accidents at Gore of crash cushion installed freeway Secondly, freeway exiting behavior model is developed because the human factor is the most important one. However, many literatures have shown between road environment and accidents which are more quantitative than human factor. The study supposed advanced process steps on actual freeway and analysed correlation between variables and accidents. The criteria for severity index is presented to determine whether to install or not by benefit cost analysis for each module. The standard for severity index will help to determine whether to install the crash cushion or not and to estimate severity for freeway and off ramp.

• Journal of Korean Society of Transportation
• /
• v.28 no.5
• /
• pp.91-106
• /
• 2010

Recently, interest in supply chain management is rising along with the increasing oil prices and traffic congestion. In particular, people started studying the issue, but realized that advantageous strategies for suppliers and retailers are not always advantageous to a carrier. Therefore, in this study the atuhors set up a simulation scenario to understand delivery vehicle routing problems under various inventory policies, namely Economic Order Quantity (EOQ) and Periodic Order Quantity (POQ) and network configurations. First, the authors made a virtual supply chain. Then they analyzed characteristics of delivery vehicle routing under various inventory policies (EOQ and POQ) and network configurations. As a result, the POQ inventory policy decreases the number of vehicles, the number of drivers, and the service time of vehicles. Also, the centralized network increases the load factor of vehicles and decreases the service time of vehicles. In other words, the centralized network and the POQ inventory policy are better for the carrier. These results show a savings of 15,556,806 won ($13,389.10) in a month: a reduction of 17%.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.10
• /
• pp.962-974
• /
• 2010

Recently, the convergence of information technology with bio-technology, nano-technology or other technologies has been creating a new paradigm. In a field of transportation, the intelligent transport systems which is a convergence of intelligent technologies and transportation systems have been studied. The Variable Speed Limit(VSL), is one of ITS technologies, is thought to improve safety and efficiency of transportation while controlling speed limit based on road conditions. Legacy studies have considered only one station for VSL algorithm. However, it is not appropriate for an urban freeway installed with many stations. In this paper, new algorithm is proposed to not only enhance effectiveness of VSL based on cooperation of stations but also reflect road conditions within 30 seconds. The proposed algorithm consists of 4 steps: the first is a "searching bottleneck station" step, the second is a "calculating a size of congestion" step, the third is a "calculating the number of controlled stations" step, the final is a "calculating VSL" step. This algorithm guarantees improved safety and minimum additional travel time. The travel time should be considered because drivers would against the VSL algorithm when the proposed algorithm occurs additional travel time. In our experiments, microscopic traffic simulator VISSIM is selected to perform a modeling work. The results show that proposed algorithm provides the improved safety and minimum increase of travel time.

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.11
• /
• pp.263-270
• /
• 2019

Vehicular cloud computing is a new emerging technology that can provide drivers with cloud services to enable various vehicular applications. A vehicular cloud is defined as a set of vehicles that share their own resources. Vehicles should collaborate with each other to construct vehicular clouds through vehicle-to-vehicle communications. Since collaborating vehicles to construct the vehicular cloud have different speeds, directions and locations respectively, the vehicular cloud is constructed in multi-hop communication range. Due to intermittent wireless connectivity and low density of vehicles with the limited resources, the construction of vehicular cloud with multi-hop communications has become challenging in vehicular environments in terms of the service success ratio, the service delay, and the transmitted packet number. Thus, we propose a multi-hop vehicular cloud construction protocol that increases the service success ratio and decreases the service delay and the transmitted packet number. The proposed protocol uses a connection time-based intermediate vehicle selection scheme to reduce the cloud failure probability of multi-hop vehicular cloud. Simulation results conducted in various environments verify that the proposed protocol achieves better performance than the existing protocol.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.7
• /
• pp.535-546
• /
• 2019

The purpose of this research was to analyze the relationship between human risk factors and evacuation behavior stages for tunnel safety. Therefore, we conducted a survey using a structured questionnaire on the relationship between safety facilities and safety behavior in order to derive an optimized interaction between the two. The research subjects were 141 tunnel users who understand the tunnel environment. The survey period was from June 24, 2018, to September 28, 2018. As data analysis methods, we employed a frequency analysis, a multiple regression analysis, and an independent-sample t-test. In the analysis of the correlation between the human risk factors and the major variables of evacuation behavior, the evacuation phases 1, 2, and 3 were all correlated with acceleration and delay, and the human risk factors were partially correlated. In the multiple regression analysis, the will to comply with laws (${\beta}=0.188$, p=0.034) and information recognition within the tunnel (${\beta}=0.220$, p=0.009) were factors that influence the relationship between human risk factors and evacuation behavior, indicating 12% explanatory power of the impact of human risk factors for the acceleration of evacuation behavior 3. The important variables between human risk factors and evacuation behavior were compliance with laws and information recognition in tunnels. Hence, it is necessary to study the elements that interact with the environment in the tunnel.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.5
• /
• pp.224-239
• /
• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• Smart Media Journal
• /
• v.12 no.11
• /
• pp.57-66
• /
• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.110-126
• /
• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.1
• /
• pp.97-104
• /
• 2016

In Korea, the number of crash accident victims per 100,000 population is three times higher than the average of OECD. In particular, 60% of it occurs on the community road. Thus, this study intends to analyze the causes of such accidents through a pedestrian and vehicle traffic survey. The purpose is to establish practical safety enhancement measures for community roads. In recent years, lots of changes have occurred in the pedestrian environment. A traffic survey shows that 65% of pedestrians walk on the right and 17% of people use smart-phones while walking. An eye camera experiment shows that the operation load of drivers on the community roads is more than 4 times higher than those in urban roads. According to a speed survey, 62% of vehicles drive at 30km/h or above. The characteristics of accidents on community roads are as follows. First, the ratio of accidents on the edge of the road is 2.3 times as high as those on other roads. Second, when people walk on the right, the ratio of accidents is 2.5 times as high as that of walking on the left. Third, it becomes more dangerous when people cross the road from the right to the left. The majority of accidents is caused by unsafe driving (84.4%). When a vehicle makes a left turn, the likelihood of accidents is 2.3 times as high as those caused by a right turn. The ratio of accidents caused by vehicles going backwards is 14% among all accidents. In community roads, the focus of drivers should be at least 4 times higher than those on urban roads. Thus, walking in the opposite direction of vehicles and careless behaviors are highly likely lead to accidents.