• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Korea journal of population studies
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• v.11 no.2
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• pp.54-66
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• 1988

I. Introduction Since the 1970's drug abuse among young people has increasingly become a social problem in Korea. In the 1980's, drug abuse, especially glue sniffing, has become the cause of many unfortunated incidents resulting in harm to others as well as the abusers themselves. Taking into consideration of the seriousness of this problem, the Republic of Korea National Red Cross initiated a nation-wide research programme, to understand the present situation and to raise the level of public awareness. The goal of this research was to begin a nation - wide campaign against drug abuse. The research team was composed of the Advisary Committee members and the staff of the Youth Department of the Republic of Korea National Red Cross. The data were collected in February 1988 with the collaboration of the staff and volunteers in the local Chapters. The respondents were allocated nation-wide by the quota sampling method. The questionnaires were distributed to the respondents in three groups :2, 700 to junior and senior high school students, 605 to working youths, and 916 to delinquent youths. A total of 4, 221 questionnaires were collected. II. Characteristics of the Respondents The respondents in each group were selected evenly from rural and urban areas. The general characteristics of the respondents can be described as follow: in case of students, the proportions between male and female respondents, and between senior high school and junior high school students were almost evenly distributed. In case of working youths, the proportion of females (80.5%) was higher than those of the students and the delinquents groups. Delinquent youths were defined as those currently being under custody of the centers for juvenile delinquents. Of this number, 38.8% and 68.2% were junior and senior high school drop-outs respectively. The majority of them (92.6%) were male. As for the family background of the respondents, the proportion of those residing in poverty - stricken areas, and the proportion of those from broken families were higher in case of working youths and delinquent youths than those in case of students. III. Present Patterns of Drug Abuse The following summarizes the presents of drug abuse, as tabulated from the results of the survey. 1. Smoking The percentage of youths who smoke was 36% in the student group, 32% m the working youths group, and 94.4% in the delinquent youths group. 2. Alcohol 50.3% of students, 71.6% of working youths, and 93.3% of delinquent youths has experienced drinking alcohol beverages. 3. Tonic: non - alcoholic, caffeinated beverages popular in Korea and Japan The percentage of those who have used tonic at least once was over 90% in all of the three groups. 4. Sedative About 70% of each group has used sedative with the proportion of working youths use higher than those in other groups. 5. Stimulants Those who have used stimulants comprised around 15% in each group. 6. Tranquilizers Somewhat less than 5% of students and working youths, and 28% of delinquent youths, have used tranquilizers. 7. Hypnotics The users of hypnotics amounted to 0.4% of students, 2.6% of working youths and 7.1% of delinquent youths. 8. Marihuana Those who have used marihuana indicated 0.7% of students, 0.8% of working youths, and 13% of delinquent youths. 9. Glue-sniffing The percentage of glue-sniffing was 3.7%, 5% in the students group and in the youths group respectively, but the proportion was unusually high, at 40.7% in the delinquent youths group. From the results of the survey the present situation of drug abuse in Korea can be summarized as follows: 1. A high percentage of Korean youths have experienced smoking cigarettes and drinking alcoholic beverages. 2. Tonics (non - alcoholic, caffeinated beverages), antipyretic analgesics and stimulants quite regularly used. 3. Tranquilizers, hypnotics, marihuana and glue-sniffing are more widely used among delinquent youths than the other youths. From this fact, there exists a correlation between drug abuse and juvenile delinquency. IV. Time-series Analysis of the First Experience of Drug Abuse and Deviant Behaviour The respoundents were asked when they were first exposed to drugs and when they committed deviant acts. By calculating the average age of each experience, the following pattern was found (See Figure 1). Youths are first exposed to drugs by abuse of tonic(non - alcoholic, caffeinated beverages). At the age of 13, they amoke cigarettes, the use of antipyretic analgesics begins at 14 year old, while at the age of 15, they use tranquilizers, and at 16 hynotics. The period of drug abuse which starts from drinking caffeinated beverages and smoking cigarettes and ends in the use of hypnotics takes about three years. During this period, other delinquent behaviours begin to surface, that is, at the age of 13 when smoking cigarettes begins, the delinquent behaviour pattern starts with truancy. Next, they start taking money from others by using physical force. Prior to the age of 15, they are suspended from school, become hostile to adults, begin running away from home, and start using stimulants and alcohol. Soon they become involved even in glue-sniffing and in the use of marihuana. At the age of 15, they begin to see adult videos and carry weapons. Sexual promiscuity and usage of tranquilizers follows the viewing of adult videos. Consequently, by the time they reach the age of 16, they visit drinking establishments, and are picked up by police for committing delinquent acts. And finally, they come to use hypnotic - type drugs. From the above descriptions, drug abuse can be assumed to have a close correlation with delinquent behaviour. V. Social Factors Related to Drug Abuse As for the Korean youths, glue-sniffing is found to he related to aggressive delinquency, in such cases as run - aways, being picked up by the police, and taking money by force. Smoking cigarettes and drinking alcohol is found to be related to seeing adult videos and visiting drinking establishments. Hypnotics and marihuana were found to be representive of drugs which are related to degenerational delinquency, irrespective of social delinquency. The social factors connected with these drug abuse are as follows: 1. Individual factors Male students were more heavily involved in the usage of drug than females. Youths who do not attend church were more likely to be involved in drugs than those who attend. 2. Family factors The youths who were displeased with their mothers smoking and those who thought their parents did not love each other, or those whose parents had used drugs without prescription, were more likely to he drug users. 3. School factors Those youths who found school life boring, were unsuccessful in their studies, spend most of their time with friends, feel their teachers smoke too much, those who had a positive perception of their teachers smoking were likely to he drug users. To sum up, drug abusers depend on the influence of their parents, teachers and peers. IV. Reasons for Drug Abuse Korean students have mainly used drugs to release stress (42.8%), to stay awake (19.7%), and because of the easy accessibility of drugs( 16.6%). Other reasons are due to their ignorance of the side effects of the drugs (3.6%), natural curiosity (4.2%), and to increase strength(3.O%). From the above facts, the major reasons for drug abuse among Korean youths are to release stress and to stay awake in order to prepare exams. Furthermore, since drugs are readily available, we can conclude that drug abuse is caused by the school system(such as entrance exams) in Korea. VII. Conclusion Drug usage among Korean youths are relatively less common than those of western youths. In some cases, such as, glue-sniffing and use of stimulants, the pattern of drug abuse is found. Moreover, early drug abuse is evident, and it has a close connection with deviant behaviour, resulting in juvenile delinquency. Drug abuse cannot be attributed to any one social factor. Specifically, drug abuse depends on parents, peers, teachers and other members of the community, and also is influenced by social institutions such as the entrance exam system. Every person and organization concerned with youth must participate collectively in restraining drug abuse. Finally, it is suggested that social agencial working for youth welfare should make every effort to tackle this serious problem confronted by the Korean youths today.