Young-Tae Oh

FUZZY-NEURAL NETWORK TRAFFIC PREDICTION FRAMEWORK WITH WAVELET DECOMPOSITION

The framework of a traffic prediction model that could eliminate noise caused by random travel conditions is investigated. This model also can quantitatively calculate the influence of special factors. The framework combined several artificial intelligence technologies, such as wavelet transform, neural network, and fuzzy logic. The wavelet denoising method is emphasized and analyzed.

Effectiveness of Speed-Monitoring Displays in Speed Reduction in School Zones

Speeding is one of the major causes of the frequent and severe traffic accidents that occur in school zones. Two field studies were conducted to assess the short-term and long-term effectiveness of speed-monitoring displays (SMDs) for speed reduction in school zones. The performance difference is discussed according to several dependent variables, including the average speed, the 85th percentile speed, and the distribution of speeds. The short-term study results showed that the speed of vehicles began to be reduced when the driver recognized the presence of an SMD, and the average speed was reduced by about 17.5% (8.2 km/h) at the SMD location. This speed reduction was observed throughout the day, regardless of the time of day. A similar performance trend was identified from the long-term study results, but the average speed reduction was slightly reduced to 12.4% (5.8 km/h) at the SMD location. However, statistical analyses showed that the speed differences were statistically significant. In addition, an...

Study of the Effect of the Point-to-Point Speed Enforcement System Using a Comparison-Group Method

In order to reduce traffic accidents at long road sections involving high risks of traffic accidents, including tunnels, bridges or curves, the National Police Agency have decided a tentative installation and operation of an automated point-to-point speed enforcement system based on cameras at January, 2007. The first system was established at the direction to Kangreung of Dunnae Tunnel at December, 2007. Currently, the automated point-to-point speed enforcement system operates at 11 sections including eight sections on expressways and three sections on national highways. However, there have been few researches on the effects of the system upon the reduction of traffic accidents in a scientific way. To this end, this research effort was initiated to evaluate the effect of the automated point-to-point speed enforcement system on traffic safety by comparing the number of traffic accidents before and after the installation of the system using a comparison-group(C-G) method. Three-year-long traffic accident data for the expressways were collected in order to evaluate the system. As a result, the installation of the system was found to reduce traffic accidents by 49.97% in average.

A Study on the Safety of Passing-type Climbing Lanes in Expressways using C-G Method

PURPOSES: Climbing lanes on expressways managed by the Korea Expressway Corporation (KEC) have been hot potatoes due to conflicts between slow-moving vehicles such as trucks and other vehicles at the merging section as well as the less popularity with the slow-moving vehicles. In order to resolve such problems, KEC has altered existing climbing lanes to passing-type climbing lanes in 1999. The new type of climbing lanes showed an apparent improvement in mobility. For example, the speeds of vehicles using both climbing lane and other lanes improved a lot. However, there has been no clear evidence about improved safety. METHODS : This research effort was initiated to evaluate the safety of the new passing-type climbing lanes using the comparison-group(CG) method based on three-year-long traffic accident data sets before and after the change, respectively. RESULTS : The passing-type climbing lanes showed twice increased traffic accidents even though the traffic accidents on old type climbing lanes increased 1.1% during the same periods. In addition, in-depth study, the merging area of the passing-type climbing lanes was found out to be the weakest section where 43.8% traffic accidents out of total traffic accidents happened. It is noted that the merging area of the old type climbing showed only 25.0% traffic accidents. CONCLUSIONS : The new passing-type climbing lanes were found to be weak in terms of safety when compared with the old type climbing lanes. Especially, the merging area should be improved to reduce the risk of traffic conflicts between slow-moving vehicles and other vehicles.

Analysis Period of Input Data for Improving the Prediction Accuracy of Express-Bus Travel Times

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

Traffic Crash Prediction Models for Expressway Ramps

PURPOSES: Using the collected data for crash, traffic volume, and design elements on ramps between 2007 and 2009, this research effort was initiated to develop traffic crash prediction models for expressway ramps. METHODS: Three negative binomial regression models and three zero-inflated negative binomial regression models were developed for individual ramp types, including direct, semi-direct and loop, respectively. For validating the developed models, authors compared the estimated crash frequencies with actual crash frequencies of twelve randomly selected interchanges, the ramps of which have not been used for model developing. RESULTS: The results show that the negative binomial regression models for direct, semi-direct and loop ramps showed 60.3%, 63.8% and 48.7% error rates on average whereas the zero-inflated negative binomial regression models showed 82.1%, 120.4% and 57.3%, respectively. CONCLUSIONS: Conclusively, the negative binomial regression models worked better in traffic crash prediction than the zero-inflated negative binomial regression models for estimating the frequency of traffic accidents on expressway ramps.