This paper presents a laboratory study of highly modified bitumen (HiMB) incorporating styrene butadiene styrene (SBS) and low-density polyethylene (LDPE). Due to economic and environmental concerns, there is a demand for developing sustainable alternatives that include reclaimed polymers. Recycled LDPE plastomer was mixed with base bitumen and virgin SBS elastomer to produce the HiMB binders. The total polymer concentration was fixed at 7% by weight of the HiMB binder. The morphology of the HiMB binder was captured by optical microscopy while the physical behavior and the rheological properties were measured by the traditional asphalt tests and the multiple stress creep recovery (MSCR) test. The addition of reclaimed LDPE polymer increased the softening point and complex modulus, and reduced the phase angle and tenacity. The HiMB binders showed limited improvement in storage stability and elastic recovery when mixed with recycled LDPE. All HiMB binders met the specification requirement of non-recovery compliance for the E-grade asphalt and provided a satisfactory solution in the MSCR test. The HiMB binder was shown to derive its strength and elasticity from a three-dimensional SBS network. At the same time, reclaimed LDPE exhibited a rigid and tough system which could be resistant to deformation. Flexible and resilient HiMB binders could result when the combination of SBS and LDPE polymers was used for modifying base bitumen. Test results showed the potential of using recycled LDPE polymer as a promising alternative to commercial styrene-butadiene polymers as it improved the viscoelastic properties of the neat bitumen.

This study was aimed to investigate the effects of polyethylene terephthalate fiber (PET) and carbonized wood particles (CWPs) in hot mix asphalt (HMA). First, an experimental study was conducted using 240 Marshall specimens to determine the Marshall properties and retained Marshall stability. To measure properties and optimize the materials, predictive models were developed and validated using nonlinear regression with response surface analysis. According to the models, CWPs content had a higher influence on bulk specific gravity, while PET played a higher significant role in Marshall stability in both conditioned and unconditioned stages. However, CWPs and asphalt contents were found to be the dominating factors on Marshall flow of modified HMA. Optimum binder contents of modified HMAs were significantly varied from 4.9% to 5.2% as PET and CWPs content increased. The maximum replacement rates of fine aggregate with CWPs and PET contents in HMA were found as 18% and 10% respectively.

Hydroelectric power generates electricity with the potential energy of water flow. A penstock diameter over a range of several centimeters to several meters, one of the length over a range of several meters to several kilometers. A regular maintenance method of penstock needs a worker to approach penstock and check its surface by their eye. Maintenance workers must walk the distance from one end to the other of penstock to check the whole. This method needs a lot of time and cost. We propose an automatic maintenance method using a drone and an image processing method. This method uses the penstock picture taken by a drone to check the surface of the penstock. This picture is used as an input of a deep learning-based image processing method to extract the damaged area on the penstock. In this paper, we explain the overview of the proposed method, evaluate the damage extract method, discuss the remaining problems to realize the proposed method.

Pavement maintenance management system is one of the most important aspects of road infrastructure development. Unavailability of pavement condition indication models give a big challenge for the pavement maintenance sector to come up with a decision at a particular surface. Pavement Condition Index (PCI) is one of the basic components of the pavement management system. A research study was initiated to develop PCI modeling for asphalt pavements in Sri Lanka. 15 asphalt pavements constituting 65km (both sides) were selected for model simulation and 20 asphalt pavements were selected for validation. Each pavement was separated into 32 meters segments and distresses in pavements were observed and measured. Distress indices were calculated and visual judgment values from engineering professionals were recorded for developing Surface Condition Rating (SCR) index. Finally, all these indices were combined together with Roughness Condition Index to develop a PCI model. Further methodology included the statistical and operational validation of developed SCR and PCI model. Models are validated by using compared mean t-test method for field data and compared with already established performance models in other regions. The proposed index is expected to be a good indicator of pavement condition and performance. The developed PCI can be used to select the maintenance strategy to enhance the pavement management systems of asphalt pavements in Sri Lanka.

Microscopic traffic simulation models are useful tools for decision support systems to evaluate transportation scenarios and transportation system performances. However, parameter identifications of microscopic driving models are difficult because the behavior parameters are generally not directly observable from the conventional data collection approach. This paper proposes a novel method for calibrating and validating car-following models using top-view trajectory data. The vehicle trajectory data is high-fidelity and provides detailed information on the driving characteristics. The trajectory data were extracted using deep-learning-based computer vision technologies from aerial video footage collected using an unmanned aerial vehicle (UAV). The methodology is applied for the parameter estimation with PTV VISSIM using 2,871 trajectories obtained from an intersection in Taiwan. For the validation, trajectory-level measures of performances are also proposed, including speed distribution, acceleration and deceleration distribution, and discharge headway. The results indicate that the realism of traffic simulation models is improved.

Colored crosswalks were designed to enhance the safety of pedestrians. This study examined the effects of the colored crosswalks at two sites. Results found that the effect of the colored crosswalks on drivers’ behavior was varied depending on the vehicle and turning movement types. The interactions between vehicles and pedestrians increased after the colored crosswalks were in place. Pedestrians suffered less severe conflict from right-turning cars at both sites, while this effect was noted from right-turning motorcycles at one site. Pedestrians suffered more conflicts with left-turning motorcycles. The number of pedestrians per vehicle yield increased for either cars or motorcycles and turning left or right. However, drivers’ yielding behaviors had not significantly changed. These results indicate that the colored crosswalks could encourage pedestrians to step onto the crosswalks. Accordingly, more pedestrians may suffer severe conflicts with vehicles if drivers are not willing to yield to pedestrians.

This research explores the impacts of automated vehicles on the capacity of signalized intersections under various automation degrees and penetration levels of automated vehicles. We perform simulation and analysis of mixed traffic flows, including automated vehicles, cars, trucks, buses, and scooters. The effects are assessed by simulating two representative signalized intersections in Taoyuan, Taiwan, using actual data considering the intersection geometry, the signal control, and the traffic volume. Three metrics, average stopped delay, average queue length, and average travel time were adopted as performance indicators. Our study shows that automated vehicles with the automation degree of AV caution will not positively impact traffic flows, especially in mixed traffic. If exclusive lanes are provided for such a level of AVs, this intersection’s performance would be improved. Introducing automated vehicles with automation degrees of AV Normal and AV Aggressive will positively affect a signalized intersection’s vehicle flows even under mixed traffic flows.

For heterogeneous traffic with weak lane discipline (2D mixed traffic), a quantitative investigation of the arrangement of vehicle types is necessary to understand and accurately simulate traffic phenomena. This study accordingly directly detected the vehicle groups observed frequently in 2D mixed traffic footage collected in Mumbai, India to investigate vehicle herding behavior via leader–follower networks. These networks were extracted as frequent sub-networks in standardized traffic (FSSTs) that assume standardized numbers of vehicles and network structures. The results showed that specific vehicle types tend to herd, FSSTs comprising unique vehicle types or certain sets of vehicle types were predominant, and FSSTs exhibited mutual exclusion of motorcycles and auto-rickshaws. An analysis of FSSTs with unique vehicle types clarified the difference in formations according to vehicle type. These phenomena were discussed based on the segregation and formation generation of pedestrian groups in previous research.

U-turn median openings are locations where traffic congestion and traffic crashes are likely to occur. Understanding gap acceptance and driver behavior at these locations are crucial to reduce traffic congestion and traffic crashes. This paper tried to consider the geometry (i.e., median width and opening distance) in the analyses of gap acceptance. In addition, an inverse Time-to-Collision was introduced to analyze the gap acceptance from a safety viewpoint. Our result indicated that when the U-turning vehicles perceive a possible collision, they are likely to reject the gap. We concluded that the narrower median width and longer opening distance significantly result in a higher probability of gap acceptance. Based on these findings, our paper proposed some suggestions to road designers and managers at the U-turn locations, which can minimize the likelihood of traffic crashes at this facility.

In winter Hokkaido, poor visibility occurs due to snowstorm. It is required to develop a smart system to monitor visibility on the road to minimize traffic accidents. Thus, we create an enable system to assess visibility widely on the road using the on-board video cameras. The weighted intensity of the power spectrum (WIPS) was applied to identify poor visibility from images recorded by the on-board video cameras. First, we conducted the experiment to show driver’s subjective visibility assessment values regarding poor visibility conditions compared with the values of WIPS. Next, we investigated the changes of the values of WIPS under adverse weather conditions could reflect poor visibility along the road. As a result, values of driver’s subjective visibility assessments were close to the values of WIPS. The changes of the values of WIPS indicated changes of visibility widely on the road caused by meteorological conditions and road environments.

Urban road network is deteriorated in congestion at transportation and to mitigate the congestion conditions. It needs management and implementation for the lane management and highway design at the study area. Commuters are facing with congestion impacts such as spending extra travel time, fuel wasting and crashes for traffic queuing. This study is to analyze the congestion level of two roundabouts and signalized intersection. Traffic data were collected by video and manual record and speed data are counted by hand-held GPS. Traffic congestion level is evaluated NCHRP-572 for roundabouts, HCM-2010 guideline for signalized intersections and VISSIM simulation for proposed improvement. This study analyzes to mitigate the conversion of roundabouts to simple signalized intersections, retiming the existing signalized intersection and modification of lane configuration. It is expected that simulation of signalized intersection from roundabouts is obviously changed the nature of traffic flow and the link also reduces congestion in scenario.

The land-access function for motor vehicles provides a direct connection between a street and an abutting property. Although the impact of the land-access function on pedestrians is significant, it has not been extensively studied yet, considering both pedestrians and vehicular traffic conditions. This study aims to quantify the interaction between egress vehicles and pedestrians at the driveway exit on urban streets. For this purpose, a simulation considering the blockage of pedestrians by egress vehicles was developed, assuming the two-stage gap acceptance of egress vehicles. The results show that land-access function deteriorates with an increase in the pedestrian volume; conversely, pedestrians are negatively impacted through longer delays and more frequent exposure to vehicles, with an increase in the egress vehicle volume. This study also shows the importance of reducing traffic in the main street to prevent the negative impact on both the land-access function and the walkability.

Weaving segments can be one of the crucial road facilities in terms of efficiency and safety on urban expressways. The traffic operation in weaving segment is different from the basic segment due to the crossing of multiple traffic streams. Also, quality of service (QOS) varies among lanes due to different lane utilization rate (LUR). Therefore, this study aims at establishing a lane-based evaluation procedure of QOS through developing LUR estimation models. With the data from two urban expressway sections in Nagoya and Tokyo, Japan, LUR is found to be significantly affected by cross-section flow, merging ratios, diverging ratios, and cross-section position. The model validation reveals that the model can reproduce traffic distribution. Lane-based average speed and density are adopted as measure of effectiveness (MOE), and level of service (LOS) criteria is determined by cluster analysis. Case study shows that the procedure can reflect QOS in each lane at every cross-section.

Mixed traffic with high motorcycle traffic composition is the specific feature of the road traffic in Taiwan and in most Southeast Asian countries. For planning and managing the road traffic, it is usually to convert motorcycles into Passenger Car Unit (PCU) by the Passenger Car Equivalent (PCE) of the motorcycle The PCE of the motorcycle will be different because of different traffic composition and different geometric layouts. This paper used a regression model to investigate the relationship of the PCE of the motorcycle with the lane allocation, and the location characteristics of intersections under various traffic flow situations. According to the modeling results, the passenger car equivalent of the motorcycle can be given with different mixture rates for different lane layouts. The result can be applied for designing the signal time and enhancing intersection performance using the more suitable PCE of the motorcycle.

Traffic lights play main role nowadays in urban traffic. One effective way to solve congestion is to adjust traffic signal timings, especially when the infrastructure investments are limited. This research developed two nonlinear objective optimization models that minimize the average traffic delay in isolated signalized intersection with several constraints, with a precondition that the degree of saturation must be under 0.9. Microscopic simulations are performed to simulate an isolated signalized intersection according to the traffic signal timing calculated by the developed models. Verification of the developed nonlinear objective optimization models is performed based on the simulation results. The simulation results show a 27% decrease of the average loss time and 24% decrease of the average waiting time for all vehicles if apply the signal timing calculated by the second developed model, compared with the simulation results of the fixed signal timing calculation method recommended in Japan from 2018.

This study focuses on the development and application of a queue-based custom signal optimization model (Q-SOM) to an isolated intersection in managing traffic at oversaturated conditions. The key parameter to this model is the Temporal Oversaturation Severity Index (TOSI) which is characterized by a residual queue at the end of a cycle. The traffic signals are timed such that green time wasted is minimized by reallocating these from unsaturated phases to serve oversaturated ones, reducing the residual queue. The Q-SOM algorithm is applied to a calibrated and validated microsimulation model to evaluate its effectiveness using the following MoEs: intersection throughput, average stop delay, total network travel time, average speed, and average delay. Depending on the constraints and configurations applied to the algorithm, Q-SOM can significantly improve performance compared to a prevailing fixed signal control, and an optimized signal control using the critical movement analysis method (CMA).

Due to the increasingly complex and tedious work of traffic data analysis, various traffic simulation software was developed to increase efficiency and convenience when conducting traffic analysis. In the Philippines, the Intelligent Transport Systems of the University of the Philippines Diliman also developed a traffic simulation software known as Philippine Local Traffic Simulator (LocalSim). This study aims to assess the effectiveness of the implementation of signal lights at the National Highway-Lopez Avenue intersection located at Los Baños, Laguna. The traffic data used was obtained from 2014 and 2019 for the unsignalized and signalized intersection, respectively. A simulation model for the intersection was created for both unsignalized and signalized scenarios. Based on the results of the paired t-test, the implementation of signal lights worsened the traffic condition, increasing average travel time and decreasing average travel speed in the road links of the intersection.

Full signalized traffic circles are operating in some countries to serve the heavy turning traffic flows at large-sized road junctions. Their capacities are influenced by many factors, such as the traffic conditions, signal control types and geometric layouts. The objective of this study is to find out the specified traffic demand conditions that signalized traffic circles are preferred in different cases of the number of lanes and lane configurations. A signal optimization model for the traffic circles is proposed for investigating five cases of signalized traffic circles under various traffic demand conditions. The results showed that signalized traffic circles have higher capacity than signalized intersections in some specific cases, e.g. when the total number of approach lanes reaches five or when more than one right-turn lanes are required. Besides, an analysis on the relationship between the capacity and the occupied area is conducted to further consider the geometric influence.

This article described the details of the travel time prediction model on urban roadways using the Artificial Neural Networks (ANNs) technique by integrating data from the neighboring road sections as the candidates for model inputs. The multilayer feedforward neural network model was selected as the main structure for the travel time prediction model. The candidate inputs for the travel time prediction model were historical travel times of the target section and its neighboring sections including; upstream, downstream and signal sharing sections. The real Bluetooth dataset obtained from BMS systems installed on urban roadway networks in Bangkok CBD was used in verifying the applicability of the proposed technique. Results indicated the proposed technique was superior to the baseline models in all test scenarios. Furthermore, in the case that data from target section was missing, the ANN(Miss) model that does not require historical data of target section could be a good solution for use as a travel time prediction model with acceptable results.

Deep learning methods have recently been applied to the prediction field with high accuracy. However, the processes involved in deep learning represent a kind of “black box” that can be difficult to interpret. In addition, the recently proposed attention mechanism provides both the same level of accuracy and interpretability as deep learning models. In this study, we propose a long short-term memory (LSTM) approach with an attention mechanism framework, which we call the attention LSTM model that completes a traffic flow sequence and learns the temporal features of the traffic network. Empirical results demonstrated that the proposed model performs better than classical ARIMA model, the random forest and a conventional LSTM model, both of which already produce good results. This higher level of performance is reflective of fewer errors, faster convergence, and more accurate prediction. Furthermore, the proposed model provides a possible explanation for the high accuracy of traffic flow prediction. The attention mechanism illustrates that in addition to the morning and evening peaks, some periods in the afternoon also have a greater impact on subsequent traffic flow, suggesting new possibilities for traffic flow prediction. This finding helps us to understand the trends and patterns of expressway traffic flow.

The safety of a highway can be assessed easily using speed consistency criteria. The 85^th percentile speed (V₈₅) values used to measure consistency is obtained from speed prediction models. So far, the majority of speed prediction models are regression models. Machine-learning techniques have recently been explored to develop speed models but have not yet fully explored. Further, it is also known that speed distribution plays a vital role in V₈₅. Thereby in this study, a speed distribution function is developed using Back Propagation Neural Network with naturalistic speed data. The developed model yields better results with R² of 0.91 and RMSE of 2.8 in predicting various percentile speeds on speed distribution at the center of the curve. The profile method sensitivity analysis conducted on the developed model revealed that the parameters superelevation and radius have the most significant influence on the speed over the curve. One of the significant advantages of the developed model over the existing speed models is its capability of predicting any percentile speed.

Model based ramp metering systems have long been in use to alleviate congestion in freeways. However, data driven ramp metering systems potentially offer improved performance and greater flexibility in usage. An end-to-end data driven model for ramp metering using multi-layer feedforward neural networks is presented. The proposed model is trained using traffic and metering data from the M3 freeway in Brisbane, Australia, where a coordinated ramp metering algorithm is currently used to generate metering rates. The results indicate that the proposed model has the capacity to learn the underlying metering scheme from the data, thereby enabling a shift from a model based system to a data driven one. Further work such as training models to learn more complex metering systems and using feedback mechanisms to create continually improving models are also discussed.

Recent developments in sensor technology have transformed the ways in which traffic surveys are conducted. This study investigates students’ characteristic walking behaviors while walking to and from school by using data acquired with an eyeglass-type eye-tracking device. The three main findings were as follows: when school routes (the roads used by students for their commute) are familiar, the traffic mirror receives the most gaze, and the number of safety checks is at its least; when school routes are unfamiliar, the space on the side of the traveling direction receives the most gaze; and people with driver’s licenses tend to gaze at the traffic mirror the most and increase the number of safety checks.

Excess and inappropriate speed is a core contributory factor in road crashes. In 2018, over speeding alone has claimed the lives of 97,588 people in India, which accounts for 64.4% of the total road deaths. Horizontal curves on two-lane highways contribute to a large share of these fatalities resulting from over speeding. In general, restricted sight distance and inadequate superelevation mostly impact on the safety associated with horizontal curves. The existing geometric design guides provide deterministic design criteria for highway elements. However, in developing countries like India, due to land constraints or road encroachment, the safe sight distance is often compromised. Moreover, due to poor workmanship the superelevation and extra widening is also neglected. As a result, often the negotiating speed on a horizontal curve is not compatible and safe. Thus, in the present study, the concept of reliability was used as a tool to account for the uncertainty and evaluate the risk associated with the negotiating speed on a horizontal curve on two-lane highway. A new methodology was proposed to determine safe speed for negotiating horizontal curve under restricted sight distance for allowable maximum superelevation. The insights obtained from the study can guide practitioner in setting up competent speed limits or design effective traffic calming measures.

The implications of Philippines being a developing country indicate that Filipino children may be facing safety risks going to and from school due to poorly built environments. In this study, three public elementary schools located along highways in Quezon City were assessed using Star Rating for Schools. The Star Ratings of the selected school zones were obtained, and improvements were correspondingly identified to improve the obtained Star Ratings to at least three out of five stars. Aside from the importance of communicating results and impacts in an effective, measurable manner to involved stakeholders through tools such as Star Rating for Schools, great importance must also be placed in involving the users themselves in conducting the pedestrian safety assessments. This is for designers to have considerable knowledge and understanding of a built environment's day-to-day use and thus, come up with apt and ergonomically designed solutions.

Historical statistics show that the number of accidents involving trucks is not many compared to those involving other vehicle types, yet the crash rate and the casualty rate of truck crashes are much higher than those of sedans. Truck crashes also cause huge financial losses and traffic jams. Therefore, truck companies must manage drivers by implementing cost-effective measures. This study proposed a revised approach based upon previous studies assessing driving risk of commercial vehicles. Combining Jenks natural breaks optimization and fuzzy logic has increased the logicality and flexibility of the evaluation system. Moreover, to illustrate the impact of each driving behavior on the risk level from the perspective of decision-making, this study established decision tree models. These tree models provide a quick and visible tool to grade the driving risk levels of drivers.

This study aims to employ the negative binomial model and empirical Bayes model to estimate the accident risk for vulnerable road users at the road intersections in Toyohashi, Japan. A comprehensive dataset including 831 pedestrians and 3874 bicycle accidents at 16,283 intersections over a 10-year period (previous five years and next five years) from 2009–2018 is utilized. The obtained results indicate that accident estimation with the empirical Bayes model is highly correlated (r = 0.882) with the previous accidents and moderately correlated (r = 0.445) with the future accidents, which are considerably better than those assessed by the negative binomial model (r = 0.269 and r = 0.266), for bicycle as well pedestrian accidents. Moreover, the empirical Bayes model reveals the effect of “intersection angle deviation” alone on each intersection by exposing the high-risk intersections, which is insignificant in the negative binomial model.

This study uses the tool developed by the International Road Assessment Programme (iRAP) called “Star Rating for Schools” or SR4S. It is a systematic and evidence-based tool for assessing and managing the risks children are exposed to during their school journeys. In line with the 2^nd Decade of Action for Road Safety’s target for new roads to be at least 3-star or better, this study assesses 25 and 41 schools in Zamboanga City and Valenzuela City respectively, using SR4S tool. The process starts with on-site survey of the chosen road sections that serve as access points for students going to their respective schools. Critical points are coded and analyzed using the SR4S web application. Star ratings are then generated. After which, critical road attributes are identified. Interventions are then virtually simulated, whether they would improve a road’s star rating and score or not, using the system demonstrator feature.

The present study aimed to clarify the effects of deceleration of the leading vehicle and time-gap setting of ACC on the driver's subjective risk feeling (RF). We measured the RF toward the deceleration of leading vehicle in the field experiments and proposed a RF model using 1/TTC based on results of the field experiments. Also, we developed a car-following simulation model to simulate the car-following behavior for the driving with the ACC when the leading vehicle decelerates. The car-following simulation model was verified by comparing results of the field experiments with those of the field experiments based on the relationship between 1/TTC and THW. In addition, the driver's risk feeling was examined under various conditions corresponding to results of the car-following simulation using the RF model. It is supposed that these findings are effective in expanding the use of ACC under various road conditions and traffic conditions.

In this study, the factors affecting the acceptability of the limited license for elderly drivers are organized from various viewpoints, such as residence and the actual situation of car use. We consider three types of limitation conditions: "time limitation," which limits the driving time, "Area limitation," which limits driving area, "vehicle limitation," which limits driving vehicles equipped with advanced safety technology. The survey was conducted on 1240 drivers over 60 years old. As a result, it became clear that "Area-limited license" was relatively challenging to accept, and "vehicle-limited license" tended to be acceptable. It was also found that the place of residence did not affect the acceptability of the limited licenses. Furthermore, it was found that the acceptability of "time-limited license" and "Area-limited license" would be enhanced if alternative means of transportation were available.

Apart from infrastructure development in the transportation sector, many developed nations have heavily invested in data collection and technology integration which eventually helped them enhance the safety and efficiency of their transportation sector. In contrast, the developing and underdeveloped nations are still struggling to cater to the fundamental safe, efficient, and reliable mobility needs of the people. The essential difference lies in the inability to directly adopt the norms, methodologies, approaches, practices employed by the advanced countries by the lagging nations. In this study, a framework for crash risk assessment of unsignalized intersections in absence of safety-critical data, such as crash, conflict, etc. is being proposed to do the needful effectively. Safety of 242 4-leg and 386 3-leg intersections were evaluated, and the results were cross-validated through field investigations. The improvised framework is flexible in terms of data requirements, application, and software implication.

In serious traffic congestion, boredom causes high stress and drowsiness, which in turn reduces the attention and increases the risk of traffic accidents. However, in traffic congestion, it is not possible to take a break and easily relieve stress and fatigue. Under severe traffic congestion, where the driving task is greatly reduced, there is a possibility of reducing the risk of accidents by imposing secondary tasks that reduce the sense of boredom. In this study, we conducted an experiment under the assumption of traffic congestion conditions to investigate the effects of active secondary tasks on drivers' attention and perceived time under traffic congestion conditions. The results of the study showed that the active secondary task shortened perceived time and contributed to maintaining attention.

Characteristics of crashes have been extensively analyzed. Some of them focused on analyzing "at-fault" drivers for identifying the risk level of specific driving populations. However, it requires different skills to prevent at-fault and not-at-fault crashes. This study adopts the decision tree method and Taiwan roadway crash data for extracting older drivers at-fault and not-at-fault crash scenarios. Distinctions between these two types of crashes are found. Older motorcyclists have difficulties maintaining situational awareness against motorcycles and bicycles and obeying the right of way. Thus, older drivers and motorcyclists are more likely at-fault with other motorcycles and bicycles in opposite or intersected directions. Additionally, older drivers and motorcyclists are more likely not-at-fault in rear-end crashes in non-signalized intersections owing to frequent speed adjustments to compensate for their degenerated information processing capability. Results of this study could be valuable for developing training materials for driving safety improvements.

This study aims to explore the range of driving patterns exhibited by passenger car drivers. The driving data is collected for 42 drivers using instrumented vehicles, in a naturalistic environment. An algorithm is developed for data segmentation and total 7548 acceleration events, 6156 braking events and the corresponding driving performance features are extracted. The similar patterns of events are identified using K-means clustering technique in combination with PCA. Total four patterns of acceleration and braking behavior each, characterized by the level of acceleration/braking behavior, speed behavior and the event duration are identified. The results show that, each driving pattern represents a unique driving behavior and each driver is found to exhibit different driving patterns. No driver constantly shows a single driving pattern and the proportion of patterns are changing among individuals showing inter-driver behavioral variability. The insights from the study aids in developing driver specific safety models for driver assistance.

In developing countries, road safety is an issue of prime concern. In this context, the present study has utilized road traffic crash data of the state of West Bengal, in India. Statistical models are developed to identify the key attributes influencing crash severity as well as collision types (i.e., head-on, hit from back or side, overturn, run-off). The study findings indicate that road geometrics, pavement condition, inadequate visibility, absence of appropriate speed enforcement, presence of undivided carriageway, are some of the major risk factors influencing the crash severity as well as the collision type. The study also highlights the deficiencies in ‘post-crash responses’ as a significant contributor to crash severity. The derived knowledge of risk factors is advantageously utilized to recommend specific countermeasures and road safety policies to improve the present road safety scenario in India and other developing nations.

Traffic Accident is a major problem all over the world. Traffic accident costs also become an important impact in the economy aspects of country. In this study, it is examined the blackspots and traffic accident costs of Yangon-Bago-Phayargyi highway in 2017 and 2018. The accident data are collected from six police stations. The accidents are analyzed to estimate the accident costs based on their severity by human capital method. The accident costs are categorized as four types such as fatality costs, major injured costs, minor injured costs and property damage only costs. In this study, there are fatality costs with US$ 10158157.1, serious injured costs with US$ 3754648.8, slight injured costs with US$ 92812 and PDO costs with US$ 307149.9. The total costs of traffic accident in this highway for 2017 and 2018 are estimated as 14.313 million USD and GDP losses of country for these traffic accidents is 0.02%.

Recently in Japan, traffic accidents caused by elderly drivers have attracted public attention. Elderly drivers are judged whether they can continue driving based on the results of the cognitive test at the renewal of their driver's license. However, it has not been to lead the reduction of accidents. Therefore, it is important to understand the relationship between driving ability and cognitive impairment for elderly drivers.In this study, we analysis on the relationship between driving ability and cognitive impairment for elderly drivers. The driving ability evaluates using the driving behavior at intersections where driving operations are difficult. In conclusion, a model for evaluating the cognitive impairment of an elderly driver can be constructed from the results of driving ability. On the other hand, a model for evaluating the driving behavior of an elderly driver from the result of cognitive test cleared that it needs further improvement.

In recent years, the technology development related to automobiles has been remarkable. In particular, ADAS (Advanced Driver Assistance System) is a technology that improves the safety and convenience of drivers. In order to improve the performance of ADAS, it is important to identify the driver. By identifying the driver, appropriate support and information can be given to the driver. In particular, the technology of identifying a driver using the driving behavior has many advantages over identifying the driver using biometric authentication.In this study, we considered that the driving operation at intersections is complicated　and individual differences are likely to appear. Therefore, we constructed a driver identification method using the driving behavior of intersections, which has not yet been focused on in previous studies. It was shown that the driver can be identified with high accuracy by applying LSTM (Long Short-Term Memories) to the driving behavior at the intersection.

Speeding is the vitally important traffic problem as it is one of the most-reported factors associated with crashes. Traffic calming is an ideal solution, especially the hump. But, in some places, over-speed at the hump is happening on roads. To lessen the speed, using hump signs can offer net positive benefits as they would be a practical and the most cost-effective method. However, Asian countries do not have a standard manual for hump signs, therefore, this study designs new hump signs and assesses their effectiveness. Total of 172 respondents in some Asian countries were involved in this research by answering online questionnaire after watching 3D videos. This research found that with the presence of hump signs, they affected positively on the feeling of respondents about the minor road, so drivers would think to drive carefully, slowly, and give priority to pedestrians on the minor road.

With the improvement of loading facilities and management technical of coal export terminal (CET), shipment speed at CET has increased rapidly. However, due to the restrictions of ship stability and discharge equipment, ballast water discharge speed cannot match the speed up process of shipment. Therefore, ships have to spend additional waiting time in CET for ballast water discharge, which aggerated the port congestion problem and affecting port efficiency. Dealing with this bottleneck problem, this research proposes a simulation-based method for scheduling ship ballast water discharge in CET. A multi-agent model has been established to investigate the influence of the pre-discharge of ballast water on terminal through capacity. An optimal combination for the proportion of pre-discharged ballast water by ship type has been explored. The effectiveness of the optimization method has been verified through a large CET in North China, where the annual throughput has increased by 2.96% in this study.

Traditional motorboats, known locally as kelotoks, are the main inland waterway transport (IWT) modes in Banjarmasin, Indonesia. Historically, they served as river taxis ferrying local and regional commuters from origin to destinations, including markets, schools, or workplaces, mainly on the Martapura and Barito rivers' riverbanks. However, the increased dependence on land-transport modes has adversely affected kelotok ridership, and subsequently IWT jobs. However, there were a few kelotok drivers/workers who persisted in this occupation. Using information drawn from the thematic analysis of 21 semi-structured remote interviews, this study investigates these remaining drivers/workers' motivations in participating and persisting amidst their precarious conditions and ongoing dynamics happening within the sector. It provides new insights for the study of informal transport in a way that may challenge common accounts of how the workers fare under the absence of government regulation and support, particularly within an understudied sector of IWT.

Flight surface movement is an important element in schedule block-time because every minute flight spends on ground adds cost to the airline. Study aims to determine how Taxi-Out, Taxi-In time vary with runway configuration. We consider runway type and length for analysis. In literature, researchers have selected airports randomly and have failed to find generalized results, caused less flexibility on practical applicability. After thorough literature review, we developed airport categorization method which starts from runway configurations. We analyzed one-year data belongs to two seasons and six operation days of five North American airports. Sample size is one thousand flights per airport per month per operation day. Altogether, 144,000 flights were analyzed with two sets of hypotheses using nonparametric method Kruskal-Wallis test. We found impact on taxiing process varies with runway configuration significantly. These findings will open a new path to develop one model to calculate taxiing time at any airport.

This paper measures the relative efficiencies of select major domestic ports in the Philippines for the year 2018. This study applies the non-parametric model called Data Envelopment Analysis (DEA) to provide the efficiency scores of the eight identified ports. An output-oriented analysis approach was applied for both the DEA constant return to scale model (DEA-CRS) and DEA variable return to scale model (DEA-VRS) to compute for the overall technical efficiency and pure technical efficiency of the ports. Two inputs and three outputs were used in calculating for the relative efficiency scores. Based on the results, the ports of Calapan, Ozamiz, and Panay were proved to be consistently efficient. The ports of Tagbilaran and Batangas were efficient using DEA-VRS but were deemed inefficient in DEA-CRS. On the other hand, the ports of Dumaguete, Puerto Princesa, and Surigao were identified to be relatively inefficient.

The aircraft boarding process is one of the main activities in the aircraft turnaround process. Improving the reliability of the boarding process has been a major concern of airlines as well as airport service providers. This paper focuses on the activities inside the boarding process and the factors that affect the boarding time and its variability. A Discrete Event Simulation Model is used to analyze these identified factors such as the boarding strategy, the number of luggage, arrival rate, and walking speed of passengers in different stages of the boarding process. The model is then used to compare the impact on average boarding time and its variability by changing these model parameters. Recommendations are given in the conclusion as to what methods would lead to minimizing average time and variability under different circumstances. Further, the new procedures incorporated in the boarding process under COVID-19 regulations are also evaluated.

Abrupt airport outages resulting from natural disasters can cause operational interruptions in airports and airlines. In this study, we investigate aircraft evacuation to shelter airports prior to typhoons. Considering different aircraft allocation strategies in airport aprons, we establish a model for aircraft allocation in an apron with two objectives: maximum number of evacuated aircraft in an apron and maximum possible utilization of the apron. Further, we develop a heuristic to determine optimal aircraft evacuation schemes corresponding to different priorities. We simulate aircraft evacuation to the available airports during Typhoon 19 in 2019 and compare different aircraft allocation schemes based on different priorities. The findings of this study can provide useful guidelines for practitioners.

This research aims to develop a multi-subsidy system using the mechanism of blockchain. With the functions of blockchain, the user ID and user’s trip detail information can be identified that will allow service providers to process faster and easier when facing payment requests. At current situation, there are many ministries of center government in Taiwan subsidy residents to improve the service of mobility. However, due to the capacity of administrations, each subsidy project has its own operation system such that user’s unsatisfied need will not be able to switched to another system. In addition, the process of receiving the subsidy of mobility service request several prolong stages of accounting reviews. It is undoubtedly a heavy burden for small business, and local service providers. The proposed multi-subsidy system provides a more effective mechanism for use, service providers and government agencies.

This paper proposes the market equilibrium model of RS service (especially on shared taxi). The system is described as the model proposed by Daganzo and Ouyang (2019). The user’s behaviour is formulated by a logit-based mode choice model and the supplier behaviour is formulated by the profit maximization problem. Since some variables on the user’s model and the supplier’s model are common, the market equilibrium condition is given by a fixed-point problem. This paper focus on individual mode choice behaviour. For considering individual behaviour, we propose the calculation method of travel time of RS service. We carry out a numerical experiment for demonstrating the proposed model. The result shows that travel time and travel cost of RS service is in trade-off and there is the social optimal service design.

Vehicles make unnecessary idling at the intersection cause large amount of fuel wastage and vehicular emissions. This is caused by making unnecessary idling at the intersection due to lack off signal timing information and lengthy signal cycle. It is important to study the vehicle behavior and traffic flow by proving signal information like required speed and signal timing to drivers. This paper examines the microsimulation model to assess the potential impacts of the speed control as per signal timing on mobility and environment under heterogeneous traffic flow and indiscipline lane behavior and comparative study with vehicles switch engine to off when they are waiting during red phase. The results demonstrate the potential of speed control concerning signal time to improve mobility, fuel consumption, and vehicular emission. While the presented results show a positive impact on mobility by 89% and the environment by 10%.

From the analyzing of the master data of the 3rd and 4th Kumamoto metropolitan area Household Travel Surveys, this paper clarified the below points. The moving time of private cars existing in the Kumamoto metropolitan area is only about 3% of a day, and they are parked most of the day. Except for the central areas of the city, most of the zones that were inflow excess type in 1997 changed to inflow excess type in 2012. Additionally, when an appropriate parking capacity corresponding to the current parking demand was calculated by a parking simulation model and a queuing theory, it became clear that the number of parking spaces currently supplied is quite large. These results give useful suggestions for future parking policies.