In recent years, the number of accidents involving head-on collisions at the beginning of work zone has been increasing rapidly. In this study, we focused on principal signs among the various signs that exist in construction restricted areas and proposed a method of providing regulatory information within the work zone to reduce the number of collisions considering driver-road interaction. We conducted an indoor driving experiment using a driving simulator and collected data on the driver's gaze, lane change position, and the target of the decision to change lanes. Based on our analysis, we found that the risk of such accidents could be reduced by installing two each of reduced lane signs and road construction signs in that order, and installing maximum speed signs in accordance with current installation methods. We suggest that this sign arrangement, combined with regulatory information provided by a sign car that is highly visible from a distance and effective in encouraging early lane changes, as identified in a previous study, can significantly reduce the risk of collisions in work zones.

Many traffic fatalities are attributed to driver inattention, and numerous public awareness campaigns and educational initiatives have been conducted. This study posits that linking attention to driving and providing relevant information are essential to translating increased awareness into practical action. Therefore, we focused on attentional functions, for which standardized assessment methods are established, and analyzed the relationship between these functions and individual driving behaviors. Data on vehicle and driver behavior were collected through indoor driving experiments using a driving simulator, and data on attentional functions were gathered from attention assessments conducted after the driving experiments. The findings revealed that individuals with lower ability to sustain focus on a task had difficulty maintaining vehicle position. Additionally, those with reduced ability to inhibit irrelevant stimuli and maintain focus on the intended target experienced delays in recognizing signage. Furthermore, individuals with diminished capability to handle multiple tasks simultaneously demonstrated reduced rates of forward gaze.

The 11th Basic Plan for Traffic Safety in Japan promotes policing on traffic aimed at deterring traffic accidents by applying the PDCA concept, which involves analyzing traffic accident data and using that information effectively. A situation like this, previous research has developed a bayes model which predicts the daily risk of traffic accidents and an artificial intelligence model which calculates the optimal location time for policing on traffic to maximize the reduction of daily accident risks. In this study, a one-month trial operation was conducted in October 2023 at the Shinjuku Police Station of the Tokyo Metropolitan Police Department. This trial aimed to verify the validity of the model developed in the previous research and its practical usability. Following the trial, the effects of street enforcement on accident reduction, as well as the model's validity and usability, were assessed, and issues to be addressed for the full-scale social implementation of the model were summarized.

In order to further promote safety measures on residential roads, it is expected that objective data such as the number of accidents and traffic volume data can be combined and used to select locations for traffic accident countermeasures. In this study, using ETC2.0 data, DRM data, and traffic accident data, we conducted a hierarchical factor analysis of the relationship between the number of traffic accidents and various intersection characteristics for 117 representative residential intersections in Tokushima Prefecture, based on a structural equation modeling. The results revealed that poor visibility has a direct influence on the increase in traffic accidents and an indirect influence structure on traffic accidents via the non-priority side traffic volume from the degree of dependence on arterial roads. The results suggest that it is important to identify the points of high risk based on the intersection attributes such as visibility of each intersection, as well as the road traffic conditions and land use where the intersections are located.

The logistics industry is facing a driver shortage and stricter regulations on working hours, which may make stable delivery difficult. On the other hand, depopulated areas face the challenge of maintaining public transportation services due to aging and declining populations. This study aims to verify the effectiveness of mixed freight/passenger services using bus routes to address the challenges of the logistics industry and depopulated areas. Using data on nationwide carriers' offices, population, and bus routes, we identified depopulated areas where it is possible to replace trucks with route buses. Bus routes from sales offices to depopulated areas were calculated using a route search method, and the results were discussed based on the time saved in driving time. As a result, 313 depopulated areas were identified where mixed freight/passenger transportation by local buses is possible. The calculation results based on the distance from the sales office to the depopulated areas suggest that approximately 210,000 hours of driving time could be saved annually.

As promoting the change of usage style of urban roads from vehicle-centric to pedestrian-centric, it is important to clarify the application conditions of “road diet” according to the situation in Japan. In this study, the application conditions of road diet in urban areas of Japan are examined, such as traffic volume and intersection density, when introducing a road diet that reduces lanes for vehicles from a two-way four-lane road to a two-way two-lane road. Firstly, the effects and application conditions of the road diets are investigated based on cases and studies of road diets on the roads in the United States. Next, the application conditions of road diet are examined based on the intersection density and bus stop density on urban roads in Japan. Finally, the applicability of the road diet on urban roads in Kyoto City, which have many two-way four-lane roads that do not have right-turn lanes, is examined.

The objective of this study is to clarify how the provision of information about flooded roads affects driver’s decision to choose detour or flooded roads. Factors such as information provided by in-car navigation systems showing the flooding situation, caution signs indicating the depth of flooding, and oncoming vehicles running through flooded sections were reproduced in video. A questionnaire survey and experiments using a driving simulator were conducted to understand the tendency to choose a detour. The results of the questionnaire survey confirmed that the information provided by the navigation system and caution signs are effective in encouraging detours. From the questionnaire survey, about 3.6% of the respondents indicated that they enter a flooded road at a depth of 30 cm, where the risk of engine stoppage is relatively high. In addition, the results of the driving simulator showed that the effect of encouraging detours was greater among people who have less experience driving on flooded roads.

The World Health Organization constitution states that health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity. Therefore, in Japan, many studies have been made on the connection between public transport usage and mental or social health. However, few studies identify the factors influencing the impact of using public transport on health. In addition, although shared-ride taxi has been becoming highly important to meet the low demand mainly in rural areas of Japan, there have been few studies focused on the impact of shared-ride taxi on health. Consequently, it might be difficult for local authorities to consider where to introduce shared-ride taxi services and how to improve existing shared-ride taxi services, from the perspective of health improvement. This study mainly aims to identify the factors that influence the impact of shared-ride taxi on mental or social health. The results of our study clearly show the following: (1) the impact of shared-ride taxi on mental and social health is not uniform but depends on individual attributes of shared-ride taxi users, and (2) the impact of shared-ride taxi on mental health is small.

While the number of traffic accidents has been decreasing yearly, the reduction rate for accidents on residential roads is smaller compared to arterial roads. Predicting high-risk intersections on residential roads is thus a crucial challenge for reducing traffic accidents in these areas. In this study, we aim to explore the applicability of a model based on Convolutional Neural Networks (CNN), a rapidly advancing field of image recognition AI, to predict intersections with a high likelihood of traffic accidents. Additionally, we aim to identify the optimal conditions for intersection images used in the prediction model. The implementation and evaluation of the model reveal that image recognition AI is indeed applicable to predicting traffic accidents. The optimal image conditions are determined to be a resolution of 1,280×960 pixels, a sky color of uneditted, and a distance of 10 meters from the intersection. Furthermore, it is found that the presence of highly saturated buildings in the images significantly influences the recognition accuracy of the AI.

Consider vehicles visiting stores that are positioned at far-right corners. These vehicles have to make a right turn whichever route they choose to enter the store, namely, going straight at the intersection and then turn right, or turning right at the intersection and then turning left. Thus, this may have a great impact on the surrounding traffic, although the detail has not been clarified. Therefore, this study aims to analyze the factors affecting these entering route choices. First, we conducted field observations at the intersection in Kanazawa City. Then, as a basic analysis, the effects of the number of vehicles going straight, turning right and following, the number of vehicles in the opposite lane, and the signal phase on route choice were examined. Furthermore, we estimated a route choice model using these variables. The results showed that both the number of vehicles turning right and going straight had a significant impact on route choice. Also, it was suggested that heterogeneity among drivers needs to be considered.

The Moving Light Guidance System (MLGS) is used to prevent traffic congestion on freeways, but its microscopic impact on car-following behavior is not well understood. In this study, we quantitatively evaluate the variable characteristics of relative speed and parameters of car-following behavior during MLGS operations, focusing on speed differences between the MLGS lighting speed and vehicle speed. We use the all vehicle trajectory data, recording the position and speed of each vehicle every 0.1 seconds, and the MLGS operational history data, recording the lighting speed of the MLGS for each block. The results show that when the lighting speed of the MLGS is 0–5 km/h faster than the vehicle speed in the congestion section, the relative speed with the lead vehicle decreases, leading to more appropriate speed adjustments based on the distance between vehicles. Additionally, downstream of the bottleneck, there is no significant difference in car-following behavior with respect to relative speed. Therefore, the results suggest that MLGS improves speed adjustment relative to the lead vehicle when the MLGS lighting speed is operated slightly higher than the vehicle speed in the congestion sections.

This study investigated the situation of conflicts between incoming and outgoing vehicles and pedestrians and bicycles at several parking lot entrances and exits under different pedestrian traffic conditions. The survey results were used to quantitatively understand vehicle travel conditions and the occurrence of hazardous events without traffic wardens. The results of the analysis indicated that at entrances and exits located in areas with heavy pedestrian traffic in the city center, there are many cases of conflicts where vehicles pass first despite the presence of pedestrians near the entrances and exits because the pedestrian traffic is too heavy to pass easily. In both urban and suburban areas, it was also found that right-turn entrances are more frequently preceded by relatively hazardous complications with shorter gap times than left-turn entrances. In addition, the time difference between the two types of complications tended to be shorter when the vehicle enters or exits the garage before pedestrians or bicycles, compared to when the vehicle waits for pedestrians or bicycles to pass before entering or exiting the garage.

Smartphone use while walking or driving a vehicle involves the risk of traffic accidents. This study surveyed the smartphone usage and attitudes of traffic accident toward smartphone use while walking or driving of people who have experienced a smartphone use while doing so. The relationship between their personal attributes, smartphone usage, and attitudes toward smartphone use while walking or driving a vehicle was analyzed, as well as factors related to the timing of smartphone use while walking. The results showed that people in their 20s, male, and long-duration smartphone users were more likely to say that it is acceptable to use a smartphone while walking so long as no accidents occur. This study has revealed that the personal factors associated with engaging in smartphone while walking and driving were identified as follows: 20s–40s, viewing a smartphone as “very difficult without it,” low awareness of traffic rules, and allowing smartphone use while walking or driving depending on the situation.

The majority of the fatalities in pedestrian traffic accidents in Japan occur while crossing the road, and ensuring safety while crossing is a major issue. One of the measures to address this issue is the introduction of bulb-outs. A bulb-out is a type of pedestrian crossings that shortens the crossing distance for pedestrians by widening the sidewalk to the side of the roadway. The advantages of introducing bulb-outs include the reduction of conflicting opportunities between pedestrians and vehicles. In this study, we conducted a walking experiment using a head-mounted display for three types of unsignalized pedestrian crossing facilities (standard type, two-stage type, bulb-out type), and conducted a comparative analysis of each crossing facility in terms of both pedestrian's walking behavior and awareness. The results showed that the introduction of bulb-outs at unsignalized crosswalks improved pedestrian safety and facilitation while crossing the road, and was an effective measure to show drivers the presence of pedestrians clearly.

A moving light guide system (MLGS) is increasingly being installed on expressways to alleviate traffic congestion. The mechanism of MLGS can be interpreted as influencing drivers' vection (visually induced illusory self-motion), which may subsequently alter their driving behavior. However, the specific impact of vection on human behavior, including driving, remains unclear. In this study, we focused on walking behaviors as a fundamental human activity rather than driving behaviors and conducted experiments in Augmented Reality (AR) environments, where optical objects moved along the walking direction to induce vection in the participants. We then analyzed the relationship between the speed of these optical objects and walking speed. The results revealed that (i) the perceived strength of adherence to vection-inducing objects affects the perception of one's walking speed, and (ii) walking speed increases when the objects move at a slightly faster pace than the individual's normal walking speed and decreases when the objects move at a slower pace.

Recently in Japan, the occurrence of traffic accidents cause to erroneous or dangerous driving has become a serious social problem. While the development of automated driving technology that does not require the driving operation for the vehicle is underway, there are many issues that need to be resolved, and it will take some time before the technology can be introduced. Therefore, it is essential to promote prevention safety technologies that support driver operation. In this study, the anomaly driving detection method was proposed and verified the effectiveness of this method, based on the concept that when driving is likely to lead to accidents, the driver's driving behavior tend to anomaly. The proposed method was applied with two different approaches. The effectiveness of the proposed method was verified by setting up a scene of inattention to safety at an intersection, and the detection results suggested that the application of the proposed method may lead to a reduction in accidents.

In recent years, the number of fatal and serious bicycle-related accidents has been decreasing because of law revisions and advances in public information for the safe use of bicycles. However, the rate of fatal bicycle accidents in Japan is higher than in other advanced countries, therefore, it is still necessary to take measures for bicycle-related accidents. In this study, bicycle-related accidents were selected from open traffic accident data, organized the characteristics of bicycle-related accidents. In addition, the conditions under which bicycle-related accidents are most likely to occur were clarified using association analysis. As a result, we showed that ; bicycle-related fatalities are more likely to occur under the conditions that “locations without traffic signals” and “the bicycling party is 65 years old or older”; for accidents involving pedestrians are more likely to occur under the conditions that “single road”, “locations without traffic signals”, “the bicycling party is 24 years old or younger” and “the collision site was in front” ; and single-pedestrian accidents are more likely to occur under the conditions that “single road”, “locations without traffic signals” and “the bicycling party is 65 years old or older”.

Natural disasters have frequently occurred across Japan, leading to significant damage to the road transportation network in recent years. When assessing the impact of these disasters and evaluating disaster prevention and mitigation measures, it is crucial to accurately estimate traffic flow characteristics on specific road sections, such as the relationship between speed and density, and the resulting traffic capacity. Data from vehicle detectors can aggregate traffic volume and average speed per unit time. However, in rural areas with low traffic density, observational constraints may exist, which can potentially introduce bias into the aggregated data. Consequently, it becomes challenging to accurately evaluate traffic flow characteristics using standard regression analyses, such as ordinary least squares. This study proposes using weighted least squares and hierarchical Bayesian models to address these observational constraints. Furthermore, observations made on a national highway in Niigata City, Japan, during the winter of 2023 have been used to validate the proposed models.

It is known that elderly drivers often encounter accidents at unsignalized intersections, and measures are being taken to raise awareness, such as coloring intersections where accidents occur and dangerous intersections. Although it is hoped that these measures will confirm brain activity linked to safe driving behavior, the actual situation is not clear. Therefore, in this study, we would like to clarify the brain activity of elderly drivers when driving at unsignalized intersections in order to understand the biological reaction factors that lead to more accidents among elderly drivers. Specifically, we created a VR space of a deformed intersection where elderly people are more likely to cause accidents, and measured their brain activity while driving in a driving simulator. Although no clear increase in brain activity due to colored pavement was observed, it was confirmed that brain activity in the elderly group tended to decrease after passing through an intersection compared to the non-elderly group.

Information facilities such as signboards have been set up on highways to alert drivers to potential hazards. However, the visual attention of drivers tends to be strongly focused on the direction of travel, and not enough visual attention is captured by information-providing facilities, resulting in the delay in detection of such facilities. To relieve the delay in detection, it is effective to release the captured visual attention by visual stimuli and to direct visual attention to the target by visual cues. In the present study, the hypothesis that visual stimuli and visual cues can alleviate the delay in target detection was formulated and tested in an indoor experiment using a driving simulator, with a dual task in which the main task was highway driving and the secondary task was a visual search task. The results of the experiment showed that the visual stimuli disengaged visual attention and the visual cues induced visual attention, and supported the hypothesis.

It is necessary to consider how to ensure the safety of bicyclists at intersections to promote cycling on the road. The purpose of this study is to evaluate safety measures at intersections by using a cooperative driving and cycling simulator that both bicycles and cars can navigate same virtual spaces. We compared the TTC, approach speed, and subject's anxiety indexes from the experiment at intersections with different safety measures, focusing on the bicycle dangerous behaviors such as running alongside a blind spot and turning to front of vehicles. The results showed that, at conventional intersections, the improvement of danger was found to be due to the improvement of bicycle running space and the reduction of the size of corner areas. Furthermore, the evaluation of protected intersections, which are being introduced in other countries, revealed that improvements in safety and sense of uneasiness can be expected.

Street surface decoration is a method of pedestrian-vehicle coexistence in which specific designs are applied to the street surface to create a sense of pedestrian priority and vehicle driving behavior. The speed suppression and attention-enhancing effects of street surface decorations have been verified, but only for specific designs. In this study, therefore, a driving simulator was used to verify whether different designs of street surface decoration have an effect on driving speed and whether the effect differs from existing non-statutory sign. Based on the dot design, which was shown to be effective in previous research, we conducted a comparative analysis of driving speeds across six different patterns—where the dot arrangement, circle size and shape, installation area, and installation location within a block were varied—as well as when existing non-statutory sign was installed. As a result, depending on the placement, it was shown that Street surface decorations have a speed suppression effect greater than existing non-statutory sign. In addition, depending on the placement and location, some designs were found to be more effective in speed suppression than previous studies.

Street surface decoration, in which specific designs are applied to the road surface, has been shown in previous research to be effective in fostering awareness and driving behavior of pedestrian-priority among drivers. However, this research has only been conducted in an experimental environment, and verification on public roads is essential for the generalization of the results. Therefore, in this study, driving experiments were carried out on a residential street in Fukui Prefecture to verify the effectiveness of Street surface decoration. A questionnaire survey was conducted to evaluate the effect on fostering an awareness of Pedestrian priority, while data on visual behavior collected using an eye tracker and driving speeds were compared before and after the experiment to determine the effect on driving behavior. The results of the verification confirmed that Street surface decoration is effective in making drivers aware of Pedestrian priority and encourages pedestrian-aware driving, such as enhancing spatial awareness at street entries and reducing driving speed on single-road sections.

The actual speed on Japan's ordinary roads is lower than the speed limit, and there is a discrepancy between the travel speeds on expressways and ordinary roads, as there are many signalized intersections on arterial roads that should provide higher traffic functions. In addition, congestion on arterial roads causes various problems, such as reduced smoothness of medium-distance travel and reduced safety on residential roads, and it is necessary to construct a road network with a functional hierarchy to improve the quality of the road network. In foreign countries, a new type of intersection called Alternative Intersections has been introduced, which is less expensive than a multi-level intersection, and has the effect of improving the smoothness and safety of intersections. This study focuses on a control method called RCUT, which is a type of Alternative Intersections, and compares and analyzes conventional and RCUT control methods using simulation to clarify the effects of reducing travel time and increasing travel speed on arterial roads by introducing RCUT in Japan as a new option for intersection improvement.

One of the most prevalent patterns of severe accidents at signalized intersections is a collision between a bicycle and a vehicle making a left turn. The objective of this study is to gain fundamental insights into the design of intersection corners with the aim of enhancing the safety of bicycle traffic. To this end, the characteristics of several bicycles and a left-turning vehicle at four different intersections under various bicycle traffic conditions were observed. Video footage was captured at the study intersections. Deep learning methods were employed for the detection and tracking of objects, and the resulting trajectory data were subjected to analysis. The results demonstrated that the trajectories of left-turning vehicles and bicycles entering the intersection exhibited variability contingent on the intersection geometry. Moreover, these discrepancies were found to be significantly correlated with the speed and turning radius of the left-turning vehicle, which in turn influenced the safety index, namely the collision margin time.

Videos captured by roadside cameras is considered to contribute to understand of process and factors of the accident and to select of effective measures for road safety because videos can continuously record the process of traffic accidents and traffic incidents from a bird's-eye view angle. And it may contribute to reduce traffic accidents on arterial roads. However, it is tough to extract traffic accidents and traffic incidents from the vast amount of videos. Therefore, this study aims to construct an efficient method to extract videos using AI image recognition technology. We attempted to detect and track objects in videos taken at hazardous spots and automatically extract traffic incidents based on the positional relationship between objects. We verified the accuracy by comparing it with the results of visual judgment. From the viewpoint of accident analysis, we found no difference in accuracy by traffic accident / incident type and the characteristics of daytime and nighttime. Furthermore, we identified false positives and negatives and organized points for improvement.

In order to expand the Zone 30 Plus initiative, it is important to accumulate knowledge and expertise on physical devices that can be useful to road administrators. Humps (smooth crosswalks) at the intersections of arterial roads and residential roads are effective not only in controlling the speed of passing vehicles, but also in alerting drivers by showing them where the residential road begins and ends and the entrance to the zone. However, local conditions do not allow for the length of the sloping section, making it difficult to adopt a hump with a standard structure. Therefore, driving experiments were conducted with smooth crosswalks with different lengths of inclined sections, longitudinal slopes, and heights of flat sections from the standard structure, and the structure of non-standard smooth crosswalks was examined through objective evaluation by vehicle behavior and subjective evaluation by questionnaire surveys to the subjects. The results suggest the possibility of smooth crosswalks with steeper gradients than the standard structure, which could be expected to be as effective as the standard structure.

Collisions between U-turn vehicles and oncoming vehicles have become a problem on intercity national highways in Thailand. The objective of this study is to develop an image processing technique to extract trajectories from videos taken by UAVs, and to quantitatively express and evaluate collision risks. In Thailand, many behaviors were observed in which the oncoming vehicle decelerates after recognizing a U-turn vehicle. Since the collision risk changes significantly depending on whether the oncoming vehicle decelerates or not, this study proposed an indicator to express these behaviors. The indicators were proposed to express the collision risk caused by a U-turn vehicle not slowing down and the collision risk caused by the oncoming vehicle misjudging the start of the U-turn. The combination of the indices showed the frequency of collision risk by vehicle type and by lane.

In recent years, various types of mobility have been promoted and popularized, and e-scooters, which are rapidly gaining popularity, are particularly promising as a sustainable and convenient transportation service. While the development and diffusion of micromobility that meets diverse needs is essential for future society, it is also important to quantitatively evaluate the social, economic, and environmental impact of each type of mobility in a road space where various types of mobility are intermingled. Therefore, the purpose of this study is to conduct a comprehensive social, economic, and environmental evaluation of micromobility, including e-scooters, in order to contribute to the formulation of guidelines for the diffusion of various types of mobility. The results of this study, walking is the most beneficial transportation mode, followed by bicycles, which offer the greatest benefits. In addition, the benefits of e-scooters were lower than those of the above modes of transportation as well as electric bicycles and bicycles, indicating that policies focusing on bicycles and electric bicycles rather than e-scooters may be more beneficial in improving road space.

In this study, we aim to evaluate a framework for microscopic car-following behavior models, considering the limitations of traffic flow prediction methods based on macroscopic traffic analysis. We conducted driving experiments using On-Board Diagnostics (OBD) on the Tomei and Shin-Tomei Expressways, where we processed the large amount of data obtained through image processing to create a database of the relative coordinates of vehicles in front of and behind the subject vehicle. In our analysis, we treated the positions of the vehicle groups as relative graphs and conducted a comparative study of Long-Short Term Memory (LSTM) and Graph Neural Network (GNN) models as methods for predicting phase transitions in time series data. Compared to conventional methods that assume a set of macroscopic physical laws for traffic prediction among sensors, detectors, and cameras, we found that it is challenging to reproduce speed reduction based on emergent mechanisms within vehicle groups using LSTM. In contrast, the reproducibility of the GNN model, which models the phase relationships within the vehicle group, was significantly improved.

This study developed a method that can aggregate the detailed road network of DRM to an arbitrary size and also calculate the aggregated link capacities. The developed method first assigns capacity to each link in the DRM, performs simple aggregation such as unbranched links, and sets the link capacity to be assigned between exogenously given representative node pairs using the route selection probabilities of the logit model. The aggregated link capacity between representative node pairs is then calculated by solving the maximum flow problem. We applied the proposed method to a small area in the Kagoshima metropolitan area and confirmed that the composite capacity differs depending on how link capacity is allocated between representative node pairs, and inferred the cause of this difference. We further applied the proposed model to the entire area of Kagoshima metropolitan network, and then confirmed that the aggregated capacity is fairly independent of the value of the dispersion parameter in the logit model.

This study develops a method to determine traffic flow conditions at signalized intersections using probe travel time. Then, based on these conditions, a real-time traffic signal control method is developed that sequentially updates signal control parameters such as split times of each traffic signal phase. The proposed method categorizes traffic flow into three states: oversaturated, near-saturated and unsaturated, and these are dealt with state variables. The near-saturated and unsaturated states are distinguished using the green time utilization rate defined in this study. The control method leverages this categorization to make dynamic adjustments that optimize signal timing in response to real-time traffic states. In order to evaluate the effectiveness of this method, a traffic simulation experiment using actual traffic volumes at an actual intersection is carried out. The results show that the proposed signal control method significantly reduces total travel time, demonstrating its potential for reducing traffic congestion in urban areas.

Smartphones have become an indispensable part of modern life, and many people carry them with them. Wireless communications such as Wi-Fi and Bluetooth are used in these devices, and research has been conducted on human flow analysis using data obtained from Wi-Fi packet sensing. In recent years, however, privacy protection of Wi-Fi addresses has become more important, making it difficult to identify MAC addresses, which are unique identifiers of terminals. On the other hand, Bluetooth functionality has been installed in various devices, and its MAC address has become a standard that does not change for about 15 minutes. In this study, we summarize the current status of data that can be obtained from hybrid Wi-Fi and Bluetooth sensors, show the characteristics of data obtained from Bluetooth packet sensors, and verify the possibility of reproducing pedestrian traffic volume. We also examine the potential of Bluetooth data for pedestrian path analysis.