Yordphol Tanaboriboon

Multiple Car-Following Data with Real-Time Kinematic Global Positioning System

The real-time kinematic differential Global Positioning System (GPS) has facilitated a new horizon in traffic engineering. Multiple car-following experiments conducted with a real-time kinematic GPS with 10 vehicles participating in a probing field gave high-quality results in headway, speed, relative speed, and acceleration. The expected accuracies for measuring position and speed were 10 mm and 0.16 km/h, respectively. The vehicles were driven in a loop consisting of two parallel straight sections connected by two semicircular curves. Different driving conditions were induced in the platoon by instructing the leading driver to follow predetermined speed variations. The experiments yielded sets of continuous observations. Headway, speed, and acceleration were measured using conventional equipment for the purpose of comparing accuracy. The accuracy of the data obtained using the GPS was superior to that of the same data obtained using conventional measurements. The variation in driving characteristics down the stream of vehicles was studied using the experimental data. The results showed that the reaction time between a change in relative speed and the corresponding change in acceleration varies during the driving process. The reaction time of individual drivers also changes along the platoon. The good-quality data were able to give high-resolution plots of acceleration and relative speed illustrating that both the reaction time and the functional relationship between acceleration and relative speed do not remain constant.

TRAFFIC ACCIDENTS IN THAILAND

This paper presents an overview of traffic accident situations in Thailand. It highlights the transformation of road accident problems in Thailand, from the past to present, with the focus on the situation of the most accident prone mode of transport in the country, motorcycle accidents. Relating problems and contributing causes of motorcycle accidents are also detailed in this paper. Subsequently, this paper recommends several measures to curb the alarming increases in motorcycle accidents.

Dynamic estimation of origin-destination travel time and flow on a long freeway corridor : Neural Kalman filter

A model was formulated for estimating dynamic origin-destination (O-D) travel time and flow on a long freeway with a neural Kalman filter originally developed by the authors. The model predicts O-D travel times and flows simultaneously by using traffic detector data such as link traffic volumes, spot speeds, and off-ramp volumes. The model is based on a Kalman filter that consists of two equations: state and measurement. First, the state and measurement equations of the Kalman filter were modified to consider the influence of traffic states for some previous time steps. Then artificial neural network models were integrated with the Kalman filter to enable nonlinear formulations of the state and measurement equations. Finally, a macroscopic traffic flow simulation model was introduced to simulate traffic states on a freeway in advance and predict traffic variables such as O-D travel times, link traffic volumes, spot speeds, and off-ramp volumes. The new model was compared with a regression Kalman filter in which the state and measurement equations are defined by regression models. The numerical analysis indicated that the new model was capable of estimating nonlinearity of dynamic O-D travel time and flow and helped to improve their estimation precision under free-flow traffic states as well as congested flow states.

Helmet Use and Effectiveness in Reducing the Severity of Head Injuries in Thailand

Head injuries due to motorcycle accidents are the main cause of death and disability among motorcycle users in Thailand. It is well known that wearing a helmet is one of the most effective ways to reduce the severity of head injuries due to motorcycle crashes. Although the helmet act for motorcyclists was enacted in Thailand in 1994, the rate of helmet use has not increased, and the rate of head injuries and fatalities due to motorcycle accidents has not been reduced. In this study, a field survey was conducted to observe helmet use in Bangkok and three other major regional provinces. The observation shows that the rate of helmet use is significantly low across the study areas. Age, location, time of day, and seating position significantly affect helmet use, whereas gender and the day of the week do not show any effect. The logit model was also used to evaluate the factors affecting helmet use on the basis of the injury surveillance data of motorcycle accident victims. Results indicate that the victims in the pillion, or passenger, position are less likely to use a helmet and those who ride during the nighttime, regardless of seating position, tend not to wear a helmet. To evaluate the effectiveness of helmet use and other related ways to reduce the severity of head injuries, the ordered logit regression technique was applied to the hospital-based data, using the data on patients suffering from head injuries due to road crashes. It is found that helmet use can reduce the severity of head injuries for motorcycle crash victims. The probability of fatality due to head injuries is reduced by 38% for motorcyclists wearing helmets. For motorcycle riders, helmets are found to be effective in protecting against head injuries, particularly for those riding under the influence of alcohol; the probability of death could be reduced by 43%. Those in the passenger position without helmets are more likely to sustain either serious or fatal head injuries than are riders without helmets. Results also indicate that a 58% reduction in the probability of fatality from head injuries is associated with the use of helmets by motorcycle passengers.

Applying Public Participation Approach to Black Spot Identification Process: A Case Study in Thailand

A black spot treatment program is one type of safety improvement program that can deal with accident occurrences reactively. However, implementation of such program requires relevant accident data, which are normally unavailable or limited in developing countries. Thus, this paper proposes a supportive approach (public participation approach) to overcome this hindrance. The objective is to demonstrate how a public participation approach can be used to assist in identifying black spot locations through the framework of an Accident Public Participation Program (APPP). The real world applications of such a program are presented through a selected case study in Khon Kaen City, Thailand. By contrasting the findings obtained from the proposed framework with those obtained from the classical approach in this field, feasibility, validity, and effectiveness of the program are revealed. The findings indicate statistically significant agreements between the two datasets. This implies that residence can identify locations where accidents occurrences are unusually high and their input is potentially useful for the identification process. In addition, besides the indirect benefits to creating public awareness, the proposed methodology is potentially useful as a means for both speeding up and economizing the black spot locations identification process. The paper is unique because the merits of several professionals in fields such as social science, engineering, and medicine are harmonized to achieve success in a safety improvement program.

Effect of Seat Belt Use on Road Accidents in Thailand

This research was conducted to investigate the factors influencing seat belt use in Thailand. An additional aim was to analyze the effect of seat belt use in motor vehicle crashes with the use of injury data from hospitals. Significant factors influencing seat belt use were determined through field observations and a questionnaire survey. Seat belt use was observed to be higher in passenger cars than in pickups; lower seat belt use was observed for females, and drivers’ use of seat belts was considerably higher than that of front seat passengers and passengers in the rear seat position. Statistical analysis from the questionnaire survey found that the sex, age, education, income, vehicle type, seating position, seat belt installation, and average travel time and the interaction between age and seating position, education and income, and vehicle type and seating position significantly affect seat belt use. Probability of survival and severity index analysis found that unbelted car users could have a severity rate 67.5% higher than those who are belted. From the odds ratio analysis, car users who are unbelted have a higher fatality risk than those who are belted, as shown in the odds ratio 1.54. Fatality reduction analysis shows that with seat belt use, 35 of every 100 crash fatalities could be prevented. This study shows that by maximizing seat belt use, lives lost due to road crash injuries could be reduced annually.