Understanding condition of road surface is very important especially for road maintenance and asset management. There are many approaches to obtain road surface condition data, however almost all of them are either low speed with intensive human intervention techniques (visual inspection) or techniques that require advanced measurement equipment (sophisticated profilers), which usually comes with high costs and requiring skillful operators. Using smartphone to collect data is a promising alternative because of its low cost and easy to use features in addition to its potentially wide population coverage as probe devices. This paper explores features and relationship of acceleration vibration that may be useful to express or estimate road roughness condition, which is the main focusing road surface condition for this paper. Results from our experiment and analysis show that acceleration data collected by smartphone sensors at different driving speeds has different significant linear relationships with road roughness condition.

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A study to achieve high-strength, high porosity and permeability pervious concrete pavement was carried out. Mix proportions in terms of cement content, coarse aggregate-cement ratio (CA/C) and water-cement (W/C) ratio were varied. A mix proportion providing the optimal combination of strength and porosity was chosen, and polymer superplasticizers were added to examine their effect on the strength and porosity. Results showed that a water-cement ratio of 0.2 resulted in a dry and brittle mix that led to compressive strength less than 15MPa but a high permeability rate of approximately 20mm/s. A mix with w/c ratio of 0.3 and CA/C ratio of 4.25 resulted in compressive strength of 13.9MPa, flexural strength of 3MPa and high porosity of more than 20%. The use of high cement content of 495kg/m³ in the mix resulted in high compressive strengths of 51.8MPa, flexural strength of more than 4MPa, however permeability was reduced to approximately 1mm/s.

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Skid resistance and noise of roads highly depend on the characteristics of pavement texture. Therefore, the estimation of texture characteristics may give an useful information for the skid resistance and noise of road. As an indicator, MTD (Mean Texture Depth) is generally measured by the Sand Patch Test (SPT). Even though the SPT can be simply conducted with very low cost, it has some disadvantages including time-consuming and traffic interruption. There is a strong need to develop a method to quickly estimate characteristics of road surface textures without traffic interruption and implement it in the expressway pavement management system. In this study, an effective measurement way for the texture depth is developed using the MPD (Mean Profile Depth) which can obtained by the Portable Laser Profiler.

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This paper presents the theoretical study of influence of bonding condition between asphalt pavement layer on pavement structural responses based on the theoretical assumption and software based analysis. The bonding condition in this analysis are range from weak bonding to strong bonding which represent the partial bonding conditon as a realistic condition at interface between pavement layers. The standard shear spring compliance in BISAR software is used to represent this bonding condition. Applying the horizontal forces and reducing surface layer are also described. The results indicate that the better bonding condition at the interface between layers will decrease the strain responses. Hence, better structural capacity can be achieved with better bonding between layers.

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Condensation is a state change when the temperature drops below the dew point, and the moisture contained within the atmosphere forms dew on surfaces. This type of condensation caused problems on roads and road facilities. Especially, if vapors occur in the form of dew on road signs, problems in retro-reflectivity, visibility, and legibility of road signs may occur, resulting in difficulty in providing information. In order to make improvements for such problems that arise as condensation forms on road signs, dew-resistance films, illuminated road signs, and heating cables are currently being used. However there is no test method to analyze the effectiveness of anti-dew road sign method. Therefore in this research, an experiment method was developed to simulate real-world conditions and verified the performance of an anti-dew road sign using thermohygrostats in the laboratory. Comparisons were also conducted between the value of theoretic concepts and the value of the research.

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Four car-following models with artificial neural network (ANN) structure were developed with various input variables in the car-following behavior. A four-layer ANN structure was set up and a genetic algorithm (GA) and back-propagation methodology were utilized for determining the synaptic weights in the models, however the models sometimes had a difficulty in learning such enormous number of raw data points. Therefore, a methodology of data point conversion was developed with, Kohonen Feature Map (KFM), a self-organization neural network model. In order to evaluate the ANN models, the General Motors’ (GM) model was also calibrated. This paper concluded that the ANN models were successfully developed with KFM data conversion without deteriorating the original data quality. In comparing the results among the four ANN models, it was implied that the accelerations of the following vehicle and leading vehicle can also become key input variables for improving the modeling of car-following behavior.

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A dynamic feedback system is developed for estimating the headway distance and velocity in a longitudinal three-vehicle platoon. The estimation system is modeled using a particle filter (PF) and an unscented Kalman filter (UKF) that estimate them by measuring the acceleration rate and/or velocity of probe vehicle(s) in the platoon. State equations are defined as a discrete conservation equation of headway distance and velocity, whereas the measurement equation is based on a conventional car-following model. The UKF and PF have the advantage of avoiding first-order approximation when implementing a filtering process to increase the estimation accuracy. Numerical analyses using artificial simulated data as well as real car-following data showed that the PF and UKF reduce the estimation errors in most cases compared to conventional approaches such as an extended Kalman filter (EKF) or neural Kalman filter (NKF). This was significant especially in the headway estimation, where the accuracy of the EKF estimates was low.

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This paper models operating speeds on residential streets with a 30 km/h speed limit by using: (i) regression methods including Single Equation Regression (SER) and Simultaneous Equation Approach (SEA), and (ii) Neural Networks (NN) modeling technique. Free-flow profile-speed data were recorded on 99 street sections with varying characteristics which were then used to develop and validate speed models for estimating maximum speeds obtaining within a section and speeds at the entrance to the next un-signalised intersection. The results suggest that the models developed by SEA performed better than those by the conventional regression (i.e., SER). Compared to regression models, NN models showed better performance especially regarding model fitness although the resultant models are quite complicated. Based on the developed models, various street features were found as determinants of driving speeds that provided helpful information for addressing speeding issues on neighborhood streets.

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U-turn at midblock median opening is frequently provided in developing countries to facilitate the local access. Movement capacity of such u-turn is of interest for deciding the necessary traffic management. HCM 2010 contains the methodology for u-turn capacity estimation, which is based on gap acceptance theory and assumption of major traffic headway distribution. This research evaluated the gap acceptance capacity model and proposed an adjustment method by v/c balancing. Data collection at a u-turn site was conducted for validation. The results showed that the gap acceptance capacity overestimated the field capacity in case of negative exponential headway distribution and underestimated in case of Erlang-2 headway distribution. The difference in driver behavior when responding to different conflicting headway could explain the situation. The proposed adjustment could provide the estimated capacity closer to the measured field capacity. The method also incorporated the interactions between the u-turn and through traffic streams.

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This paper aims to further discuss basic elasticity models in China, using the panel data set of annual observations of China and six areas (North China, East China, Southwest China, South Central China, Northeast China and Northwest China) for the years 1990-2008. Based on the related foreign concept of induced traffic, autocorrelation model, autoregressive distributed lag model and dummy model are researched. According to the detailed analysis of empirical results, these models are available to China. Lane-kilometers are found to have a statistical relationship with VKT (vehicle-kilometers of travel) of 0.060-0.882 in short-term and 0.086-1.194 in long-term in China and six areas. These mean the necessary of considering induced traffic in China. About the basic elasticity models discussed in this paper, autoregressive distributed lag model is better suitable in China. It not only includes the time delay and cumulative effect but also brings more economic explanations than autocorrelation model.

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With the latest improvement done on North Luzon Expressway (NLEX), it is expected that the number of riders for both North Bound and South Bound will rise. For a more continuous flow of traffic, an Electronic Toll Collection (ETC) system was introduced to help alleviate traffic congestions; specifically at Toll Plazas. The paper shows how the introduction of NLEX’s ETC system helped alleviate traffic by decreasing the service times at Toll Plaza; thus increasing the capacity of motorists it can accommodate. By using Queuing Theory, the researchers were able to show the significant difference in performance of Toll Plazas when using ETC. The paper also expounds on the factors that contribute to the delays and long queues experienced at Toll Plazas and recommends ways to help improve the service.

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Incidents frequently occur in the expressway. A fast and precise detection of incidents is required to mitigate negative impacts caused by delay of traffic managements. This study proposes an incident detection method using a non-parametric model. In the proposed method, traffic incidents are detected by developing a conditional probability function of traffic state using the long term data which is observed by traffic detectors (longitudinal occupancy time-series data). The proposed method was verified empirically using actual field data, then compared with existing incident detection methods. Analysis results show that the proposed method has high applicability due to no need of complex parameter calibrations.

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It is urgent to understand the traffic performance by modelling traffic streams under mixed traffic conditions, in which motorcycles contribute to a dominant rate of the total traffic composition. This study aims to analyze the interactions between the left-turn and the opposite straight-through vehicles and estimate the capacity of both flows. An attempt is made to develop a social force model for the vehicles. The result indicates that the social force model is an appropriate approach to model the mixed traffic flow at signalized intersections. The study also outlines various aspects of integrating such a model into the existing methods for microscopic traffic flow simulation and capacity analysis.

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This research aims to develop a reliable density estimation method for signalised arterials based on cumulative counts from upstream and downstream detectors. In order to overcome counting errors associated with urban arterials with mid-link sinks and sources, CUmulative plots and Probe Integration for Travel timE estimation (CUPRITE) is employed for density estimation. The method, by utilizing probe vehicles’ samples, reduces or cancels the counting inconsistencies when vehicles’ conservation is not satisfied within a section. The method is tested in a controlled environment, and the authors demonstrate the effectiveness of CUPRITE for density estimation in a signalised section, and discuss issues associated with the method.

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The techniques developed for delay estimation in the most traffic signal design guidelines are based on the assumption that queue discharge rate at signalized intersections becomes stable after a few vehicles passes through the stop line, which is termed as saturation flow rate. This assumption has been challenged in recent times as a number of field observation in different parts of the world reported an increasing queue discharge rate observed along the back of queue. This paper proposes an empirical model that is capable of capturing the queue discharge behavior observed at signalized intersection. The model is implemented to estimate delay and compared with the existing delay models. The results revealed that the proposed model can overcome the deficiencies of the existing models and can estimate delay more accurately.

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On urban expressways, ramp metering and information provision conducted by road administrators have significant effects on mitigating traffic delay. Although these two methods are already in service, they are operated independently. To combine these beneficial methods, this paper aims to develop “Status Map” which is based on the analysis of queuing pattern on the traffic network. Simulation on radial road section consists of paralleled urban expressway and arterial shows that significant relationship exists between Status Map and delay calculated on dynamic simulator, which implies that Status Map as a static framework would still be applicable to future traffic control method.

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This paper develops the emission and dispersion model based on our previously proposed and validated mixed traffic cell-transmission model (MCTM). Additionally, the emission coefficients of various types of motor vehicles and the Gaussian puff dispersion model are integrated into the MCTM model to simulate the dynamic emission concentration along the roadway. To investigate the applicability of the proposed model, a signalized intersection under various traffic conditions and signal timing plans are simulated and compared. Taking one of pollutants, carbon monoxide (CO), as example, dynamic CO concentrations of a total of 10 spots at different distances from the intersections are analyzed and compared. Results show that the CO concentration decreases as the distance from the intersection increases. Moreover, it is interesting to note that the total CO emissions will increase as the intersection delay increases, but the CO concentration does not remarkably increase.

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Ramp metering can effect on mitigating the traffic congestion on freeway. In Taiwan, the conventional Local Traffic Responsive (LTR) ramp metering model based on the capacity and demand algorithm has been adopted for freeway ramp control since long time. For enhancing the ramp metering technology, this paper aimed at developing a new Fuzzy Logic Control (FLC) algorithm based on the real traffic situation for ramp metering control on the highway tunnel, by taking Freeway No.5 as the case, which is a freeway with the longest tunnel of 12.9km, in order to enhance the ramp metering performance on relieving traffic congestion. Through the comparative analysis using microscopic simulation, the FLC ramp metering results in higher performance on mitigating the congestion than the LTR control and no control.

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To accommodate the heavy travel demand in high-density areas, Taipei Bus Station (TBS) is developed as the first multi-level bus terminal in Taipei City. TBS also plays important roles in congestion mitigation, energy conservation and pollutant reduction. Unlike conventional single-level terminals, bus flow interruption while circulating in TBS could significantly impact the service quality and deteriorate environmental condition. Considering time-varying demand and existing Radio Frequency Identification (RFID) monitoring systems, this study constructed an adaptive signal control model combining an artificial neural network (ANN) demand forecasting model to manage bus traffic in TBS. In the case study, the self-retraining demand forecasting algorism is programmed in existing controller/computer to facilitate demand changes. The proposed model has demonstrated itself very efficient in reducing congestion within the terminal.

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Ramp metering is an effective strategy used to manage highway traffic by regulating the on-ramp traffic flow in order to avoid traffic congestion on highway networks. This study aims to investigate the impacts of fixed-time ramp metering on operational characteristics of highway networks via microscopic simulation. A fixed-time ramp meter is modelled for a highway section using Aimsun micro simulator and the traffic condition is evaluated under two ramp control scenarios: no-control and time-of-day metering plan. Three metering plans including one-car-per green, 2-vehicle-platoon releasing and 3-vehicle-platoon releasing are developed for peak and off-peak periods. The results show that ramp metering improves the highway performance, especially at peak hour. However, it leads to serious issues for the ramp and consequently for the entire system.

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An integrated taxi dispatching strategy namely the Advance Booking Chain Dispatching strategy (ABC-DS) is proposed in this paper, which aims to handle two types of commonly known taxi bookings: one is the Current Booking (CBK), the customer makes a booking call for a taxi that can reach him/her as early as possible; another is the Advance Booking (ABK), the customer makes a booking call and indicates the pickup time which is normally in half an hour or later. The microscopic traffic simulation is adopted as the modeling and testing approach for the proposed dispatching strategy, by which a sensitivity analysis in terms of different booking demands is conducted. The simulation results show that the proposed ABC-DS can give better operational performance in certain demand levels, which is potential to attract more customers to take the taxi by booking in advance and provide strategic implications for taxi operators.

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Ramp metering (RM) and variable speed limits (VSL) are two important Intelligent Transportation Systems (ITS) tools aimed at improving the performance of motorway systems. The former is widely used all around the world to regulate on-ramp traffic while the latter is still an emerging technology that can be deployed in the mainline immediately upstream side of on-ramps to create some merging space for entering traffic. This paper assesses the performances of two ramp metering algorithms namely ALINEA and HERO individually and in combination with VSL strategies for a critical bottleneck section of Auckland Motorway using AIMSUN micro-simulation. ALINEA is the most prominent local RM algorithm while HERO is a rule-based coordinated RM algorithm. Total travel time and Gini coefficient were the two important performance indicators used to measure the efficiency and equity of the motorway system respectively. Results showed strengths and weaknesses of these tools for the motorway system.

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Knowing the turning rates at an intersection can contribute to the improvement of signal control parameters and correct estimation of vehicle delays. This study proposes a methodology for estimating turning rates at an intersection under oversaturated traffic conditions. Data from detectors and infrared beacons (probe data) are used with a traffic simulator to reproduce average probe travel times for different turning ratio values. Turning rates were estimated by observing the change in the parameters describing the linear relationship between the entry time and average probe travel time for different turning rates and comparing them with the values from virtual probe and detector data. The methodology works well with simulated data.

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Data aggregation interval is important for reliable travel time predictions in probe-based systems. Where sufficient probes exist, a short interval can be used to minimize the time delay. However, in the opposite case, a short interval can cause unreliable travel time predictions due to small probes. Thus, the optimal aggregation interval may vary according to traffic flow conditions. This study suggests a methodology for selecting the optimal aggregation interval which varies according to a characteristic of probe travel time. The superiority of the proposed methodology compared to a conventional fixed interval is verified using DSRC probe data collected on a multilane highway near Seoul, Korea. The Kalman filter is adopted for a travel time prediction technique. As a consequence, the prediction accuracy is enhanced by approximately 40% compared to a fixed aggregation interval under free flow conditions.

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This study proposed a real-time inductive loop signature based vehicle reidentification approach, RTREID-2M, which improved the previously developed RTREID-2 algorithm on two aspects: (1) Develop a cubic spline data imputation approach to replace the existing linear data imputation approach in order to improve the raw signature data quality; (2) Improve the time window setting for vehicles on High-Occupancy Vehicle (HOV) lanes so that vehicles on HOV lanes traveling with free flow speeds would be considered when generating candidate vehicle sets even during congestion time periods. In addition, a stratified-random sampling method was developed to effectively perform grouth-truthing task for evaluating the performance of the proposed RTREID-2M. The evaluation results showed desired performance for vehicle reidentification and travel time estimation under both free-flow and congested flow traffic conditions. The future research will focus on the potential applications and arterial vehicle reidentification utilizing the inductive loop signature technologies.

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In Taiwan, the depressed urban streets were usually sited on intersections in urban area to bypass facilities and avoid the traffic congestion. The traffic flows of depressed urban streets were treated as the un-interrupted flows in the Chapter 10 "Depressed Urban Streets" of 2011 Taiwan Highway Capacity Manual (2011 HCM). But, the signals were usually settled in the depressed urban street upstream and downstream, and the traffic operation was affected by the signal control obviously. The analysis procedure in 2011 HCM was not realistic and practical. In order to explore the characteristics of the depressed urban streets and find the adjustment factor of slope for revising HCM, this study conducted the field data collection in 9 sites in Taipei metropolitan area. It was found that the queue discharge rates of the straight-through lanes of these streets were significantly lower than those of flat streets, and were affected by geometric design. And these findings could be useful for revising works.

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This study aims at developing a crash risk estimation model (CREM) considering the interaction of geometry, traffic flow and ambient conditions for basic segments of Nagoya Urban Expressway. A matched case-control study is firstly designed separately for three traffic conditions; low-density, high-density uncongested and congested regimes. Based on these case-control samples, conditional logistic regression is then applied and the CREM is finally developed. The results reveal that the model has statistical significance and acceptable goodness-of-fit, with 86.6%, 80.5% and 70.2% of predictive performance for each of the three traffic conditions, respectively. Regarding crash influencing factors, with the increase of traffic density, the significance of horizontal geometry affecting crash becomes lower. In contrast, the contribution of vertical geometry to crash risk is on the rise. Meanwhile, the effect of average speed on crashes gets more significant. Besides, nighttime or holiday can increase the relative risk compared to daytime or weekday, respectively.

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Using the police command center hotline ―110. as a channel, this study performed a call back interview to ask the accident reporting motorists about their perceptions on the quality of police service. A concept of fuzzy logic was introduced to measure the qualitative questions characterized with fuzziness. A total of 254 accident reporting motorists in Taipei City were interviewed. The results revealed that no less than 80% of the respondents would be satisfied and no more than 20% of them would be dissatisfied if the police response time could stay within 5 to 10 minutes and service time within 20 to 35 minutes. Both satisfaction and dissatisfaction to the police service time for A2-type accident (injury) were significantly longer than that for A3-type accident (property damage). According to our findings, the current practices of police deployment and accident investigation in Taipei City should be reexamined.

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This paper investigates motorway safety by developing accident prediction models that link accident frequencies to their non-behavioural contributing factors, including traffic conditions, geometric and operational characteristics of road, and weather conditions. The study used a sample of accidents occurred from 2004 through 2010 on a 74 km long section of Auckland motorway. A number of accident prediction models were developed and assessed for their predictive ability using negative binomial regression models under three categories: first for the whole of the motorway, second for rural and urban motorway segments separately and third for motorway segments without ramp, with on-ramp and with off-ramp separately. The results uncovered the safety impacts of different non-behavioural contributing factors, in which segment length, AADT per lane and the number of lanes always have the most profound effects on accident frequency. The validation tools were applied to examine the ability of models to predict accidents.

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How to provide accurate travel time under incidents is one of the most important premises for highway safety management. Although there was an increase in the studies of predicting incident duration recently, predicting incident duration accurately is currently still a challenging technology due to the quality of incident dataset. Additionally, the previous studies still have some limitations for empirical implication, such as pre-defined function form and strict statistical assumptions. This study employed the huge incident data, recorded accurately from Taiwan freeway systems, to develop predicting incident duration model without the disadvantages of traditional statistical techniques. The analysis results represented that the most two important variables are number of large-sized vehicles and incident type, and provided decision rules to predict incident duration. Therefore, the motorists will avoid traffic jam by changing travel route while the traffic management organization makes decisions timely to mitigate traffic congestion and clear the incident effectively.

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About 1.3 million lose their life worldwide, and this is set to double by 2030 if status quo continues. It is the developing countries which account for overwhelming part of the current fatalities, and forecasted accident fatalities. There are local as well global initiatives to address the safety issues, in developing countries in particular. However, there are emerging issues in developing countries that may result in safety trend different from that of industrialized countries. This has huge policy implication as it may make innovative measures inevitable. Therefore, to address the safety issues effectively it is necessary to grasp its nature and trend in developing countries. This paper analyses the dynamics in traffic accident trend in Asian countries, re-evaluates the current traffic safety approaches for strategic policy recommendations for emerging trends in the region.

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Black Spot Safety Management (BSM) employs identification and treatment of black spots as the two basic stages. Traditionally, these two stages base themselves mainly on recorded accidents rather than safety potential (SAPO). This paper intends to introduce an innovative BSM approach called SAPO-Based BSM which developed is based on the Network Safety Management (BASt & Sétra, 2005). There are two basic stages in this approach: SAPO calculation and accident pattern analysis. The innovation lies in the fact that SAPO-Based BSM approach takes SAPO as the main indicator of black spots; and SAPO is determined by means of the traffic volume and the severity of accidents. In order to illustrate the effectiveness of SAPO-Based BSM approach, this paper provides an empirical investigation in which SAPO-Based BSM is practically applied to the local road traffic situations in Ho Chi Minh City (HCMC).

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The study examined Measures of Effectiveness (MOE) of vehicle speeds and its comparison with posted speed limits in Advance Warning Zone (AWZ), Working Zone (WZ) and Terminal Transition Zone (TTZ) on NH-8 in India. Results indicate that (1) Except slow moving vehicles, all the fast moving vehicles exceeded the posted speed limit of 40 km/h in AWZ and WZ; (2) 85^th percentile speeds of Cars/Jeeps, Two-wheelers, Standard Trucks, Mini Trucks, and Buses are much higher than speed limit in AWZ and WZ; (3) mean speeds of fast moving vehicles are more than speed limit in AWZ and WZ; (4) there is no significant difference in the speed of vehicles in AWZ, WZ and TTZ at 95% confidence interval. This study strongly recommends the use of active traffic calming measures like Rumble Strips on Highway Work Zones.

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Recently, simple traffic safety measures such as road markings, warning signs or color pavement which mainly aim to promote drivers’ awareness have been implemented. These measures are inexpensive, thus can relatively easily be implemented. However, the effects on safety are not clear since these measures do not affect driving behavior directory. This study analyzes the effects of the simple traffic safety measures on driving behavior through a before-and-after survey at a signalized intersection where frequent right-turn-straight-run (RTSR) accidents had occurred. It was indicated that the right-turn vehicles tended to follow the intention of the guide of right-turn-start-position after the implementation. Also, by comparing the gap acceptance behavior, the judgment of gap acceptance did not only shift to safe side after the implementation, but also become more efficient long period after the implementation.

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The efficacy of an extended theory of planned behavior was evaluated in the young drivers’ (N=800) speeding behavior and intention to speed. The results show that young drivers’ speeding behavior appears to be affected by perceived behavioral control, past behavior, personal norms, intention to speed, affective and evaluative attitude towards compliance with speed limit, and social support. It also found that the impact of personal norms is greater in the intention to speed. Furthermore, the effect of socio-economic characteristics and the vehicle usage such as gender, age, income level, university type, and location of university etc. were significant factors to report that young drivers are more likely to be speeding offenders. Interestingly, racing movies and racing also make important predictors to influence drivers to drive exceeding the speed limit.

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This study applied a multidimensional item response model to measure police officers’ ability on conducting red-light running enforcement. The ability to conduct red-light running enforcement was found to consist of five component constructs, including ability on mental demands (AMD), on stopping and chasing vehicle (ASC), on psychological demands (APD), on physical demands (APHD), and under abnormal environment (AAE). The multidimensional Rasch models was then applied to assess the perceived enforcement ability of officers and item/task difficulties of conducting traffic law enforcement. The results showed that most participant police offices performed well on AMD, ASC, and APD constructs, but half of them were weak on APHD and AAE constructs. Young officers were more appropriate to conduct red-light running enforcement than the other officers. Finally, some management strategies are suggested to improve performance when conducting red-light running enforcement.

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Safety of traffic operations on roads is of utmost importance especially in developing countries like Malaysia where the rate of motorization is still increasing. Apart from the common approach of conducting safety analysis based on historical data, simulation-based traffic safety analysis is becoming more common. This paper aims to propose a new safety indicator called the minimum safe time gap (MSTG) which incorporates vehicle dynamics and gross vehicle weight (GVW). This simulation-based safety indicator is able to analyse the capability of a vehicle in a car-following situation to safely stop without hitting the vehicle in front when an emergency brake is applied by considering the braking time of the two consecutive vehicles and the perception-reaction time of the driver of the following vehicle. Results from this simulation study indicate that the MSTG is influenced by the vehicle type and GVW, hence providing a more comprehensive safety indicator for safety analysis.

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Motorcycles take a majority in road vehicle fleet of Vietnam, but there is no data on the number in current traffic circulation. This study presents a methodology to calculate this quantity (Mcir). Until now, in all existing works, the numbers of registered motorcycles are used instead of Mcir in ignoring the fact that after several years many vehicles have been excluded out of circulation. The use of correct Mcir could lead to better and more economical transport solutions. The paper also investigates the violations related to motorcycle driver license and shows that the level of such violations is serious. Furthermore, the paper shows methods to calculate the average use life, number of current users, and rate of users per one motorcycle. Especially, the short use life shows one sign for bad technical quality of existing vehicles. Last but not least, the paper presents a prediction of motorcycle number until 2020.

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In Japan lots of traffic signals have been installed even in small intersections or crosswalks at narrow basic road sections. However, it is said that signal controlling is not always the most efficient and the safest considering various situations, especially for areas with not-so-high traffic volume. In this paper, “two-step crossing” was proposed as one of the alternatives of safety measure for non-signalized crosswalk and a risk index was derived to evaluate risks of three design types of crosswalk: “do-nothing” case, “two-step crossing” case and “signalization” case. A number of incidents was considered as the risk index and pedestrians’ and drivers’ incident occurrence was formulated in stochastic way that reflects people’s perception and psychology. As a result, by defining parameters and variables arbitrarily we found that the “two-step crossing” can be a solution to improve a crosswalk in particular conditions while “signalization” has a significant effect on risk reduction.

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In this study, head-turning behavior is analyzed to determine the most appropriate location for pedestrians to confirm the approach of a vehicle while crossing a crosswalk. It was found that the head-turning frequency increases towards the entry of the crosswalk and the conflict point. Moreover, the analysis of different attributes indicated that the head-turning frequency at nighttime or by elderly people tended to be low, and that head-turning was performed more at the conflict point. These results suggest that there is a need to provide information about approaching vehicles. When a vehicle approached the subjects from behind, the head-turning frequency was low, implying the need for information for pedestrians. According to the above results, there are several important locations where pedestrians should confirm the approach of a vehicle to ensure their safety.

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The accident rate of vehicles approaching from narrow streets, and bicycles approaching from the left side on a sidewalk is high at small intersections along arterial roads. Drivers tend to gaze to the right side. On the other hand, at intersections with bad visibility, cyclist’s safety confirmation and ability to slowdown greatly differs from that of an intersection with good visibility. Thus, bicycles on a sidewalk are at risk of colliding with vehicles travelling along narrow streets. In this study, we focused on notifying the cyclist of a the vehicle’s approach from a narrow street as one of the countermeasures for supporting safe running of bicycles. The effectiveness of this system was verified by public-road experiment. It was found that cyclists’ behavior of safety confirmation improved, cyclists tended to slow-down and there was a subsequent increase in cyclists’ safety.

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Speeding contributed 60% of road crashes in Malaysia every year. The automated speed enforcement (ASE) system was piloted in 10 blackspots area across the states of Selangor, Perak, Kuala Lumpur and Putrajaya on 22 September 2012. This study was aimed to measure the drivers’ speed compliance at Lebuh Sentosa, Putrajaya where ASE camera was installed. Spot-speed studies conducted in October, November 2012 and February 2013, respectively revealed more than 70-90% compliance at the treatment site (ASE camera installed). However, less than 50% of drivers comply with the speed limit at the control site (ASE camera not installed). At treatment site, the 85^th percentile speed was less than 70km/h but it was above 70 km/h at the control site. Moreover, we found that the effect of the ASE camera increases over the time. This implies that the ASE system has successfully reduced the speeding incidents at the blackspot area.

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Illegal direction change is accounted the highest ratio for road accident causes in Hochiminh City, Vietnam. Illegal direction change is examined through separate behavioral models such theory of planned behavior, health belief model and integrated behavior model. Integrated behavior model including health belief model, theory of planned behavior variables and extended socio-cognitive variables is identified to be one of the best model (with the highest percentage of total variance) that is for applying predictive illegal direction behavior not only for HCMC but also for other cities and provinces of Vietnam. The high significant variables of the integrated behavior model as behavioral intention, perceived benefits, subjective norm and perceived severity are selected to propose the appropriate community campaigns of road safety.

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This paper examines the effects of other people’s noise-situations on an individual’s maximum acceptable flight frequency (MAFF). Two scenarios for interview questionnaires: with and without additional noise information were established under a hypothetical setting. Two MAFF models, one that tests for effect of available noise information and another testing for effect of other people living in different noise-affected zones, were estimated using data from a pilot survey based on a developed headphone interview system. Results of the first model indicated a significant effect of the available noise information on MAFF. From the second model, it was found that MAFF would increase if subjects took into account the noise-situations of people living in the high noise-affected zone, all else being held constant. For those located in the moderate noise-affected zone, the results suggest a reduction in MAFF. There was an increase in MAFF if subjects did not consider anyone else’s noise-situation.

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The study seeks to clarify the development of Indonesia’s aviation policy, primarily in relation to the proposed air transport liberalization in Southeast Asia region, ASEAN Single Aviation Market (ASAM). The study begins by reviewing aviation policy and industry development in Indonesia related to air passenger services. The study also highlights Indonesia’s progress towards ASAM. Challenges and opportunities are then identified. Indonesia is still reluctant towards full implementation of ASAM due to the issue of benefit reciprocity. Ratification of agreements is conducted in stages to give time for airlines and airport sectors to adjust. Infrastructure capacity and quality remain as the biggest challenge for Indonesia.

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This paper analyzes the vulnerability of the Straits of Malacca and Singapore (SoMS) to maritime risks. The impacts of the risk events on international cargo flows, transshipment at major ports, and domestic economies are simulated with an international cargo traffic simulation model and a spatial general equilibrium model. Both container cargos and dry/liquid cargos are covered. Three cases are analyzed: sea-lane blockade at the SoMS, stop of the service at Singapore Port, and increase of loading/unloading time at all ports in the world. Results show that the risks which occur at the SoMS impact on the economies in the whole Asia; container carriers may change transshipment ports — from littoral ports to other East Asian ports — if the risk events were to actually occur; and the economic impacts of the risk events depend on the cases and the countries. Finally, the implication to the maritime security policy is discussed.

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With today’s rather comprehensive port infrastructure and facilities information made available on public-domain Internet websites by port authorities and operators, it is possible to collect very good quality detailed data and information from such sources alone. This paper presents a case analysis based on 40 major ports in East and Southeast Asia. It demonstrates that good quality port infrastructure and container handling facilities data obtained can be used to derive a statistically significant predictive model of annual port throughputs. The derived information offers meaningful port productivity evaluation and efficiency benchmarking among the 40 ports analyzed. The analysis makes use of the commonly available technique of statistical regression to establish the predicted level of performance. The simplicity of the approach, plus the fact that all required inputs are public domain data obtainable from port websites, permits owners/operators of individual ports or any other users to perform additional analysis if required.

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The purpose of this paper is to examine the actual situation of the delay characteristics of the flights controlled by Ground-Holding which arrived at Tokyo International Airport (Haneda Airport (HND)), which is the largest hub airport in Japan. The data analyzed is the flight data of all arrivals to HND from April 2008 to March 2009 including their Estimated Time of Arrival, Expected Departure Clearance Time (EDCT) issued by Ground-Holding, Actual Time of Departure, Actual Time of Arrival, other aircraft characteristics and meteorological condition, and other related data. The results of the analysis clarify the factors that affect the flight airborne delays and the EDCT such as runway capacity fluctuations. Also the possibility of over-controlled delay by EDCT is examined through the comparison between actual airborne delay and expected airborne delay in Ground-Holding program.

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By the threat of other countries’ new or renovated airports, Taiwan Tauyuan International Airport endeavor to improve its service quality. Satisfaction has been discussed to be one of the crucial factors that influence whether passenger will repurchase on specific product. We focus on the physical surroundings and its further impact on the satisfaction. This research proposes a 2-order model and explores the relationship between servicescape and satisfaction through structural equation model (SEM). Furthermore, combining Importance-Performance Analysis (IPA) this research finds out some key items needed to be improved with high priority. Specifically, the results show that convenience of passenger traffic flow system should be improved first. Lastly, we propose some implications and suggestions for further research.

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Passenger traffic at Kaohsiung International Airport in Taiwan has seen a steady decline in the past few years due to several effects, including the establishment of the Taiwan High Speed Rail, and industry moving abroad. Because economic conditions have improved to some degree, and the Taiwanese government has permitted Chinese tourists to visit Taiwan and has allowed cross-strait direct flights, passengers are increasing. Therefore, the airport's priority should be promoting its service quality and environment. This study analyzed the importance and satisfaction of domestic and international tourists using questionnaires, and further applied an importance-performance analysis (IPA) to assess priority services that need improvement and to provide appropriate advice. The results showed that the priority services that must be improved comprise ground transportation, complaint handling, health center, speed of baggage claim, and comfort of the terminal.

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