Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.2.2911
T. Light
This paper explores how alternative pricing and operating policies influence revenue generation, level of service, and travel time costs for high occupancy toll (HOT) lane facilities. A framework for modeling HOT lanes is applied to a hypothetical facility. The analysis suggests that the way in which tolls are set can have a non-trivial influence on competing measures of HOT lane performance. Other operating characteristics, such as the number of lanes designated as free and priced and whether carpools are allowed to ride free or must pay a toll to access the HOT lanes, are shown to significantly influence performance as well.
{"title":"High Occupancy Toll lane Performance Under Alternative Pricing Policies","authors":"T. Light","doi":"10.5399/OSU/JTRF.51.2.2911","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.2.2911","url":null,"abstract":"This paper explores how alternative pricing and operating policies influence revenue generation, level of service, and travel time costs for high occupancy toll (HOT) lane facilities. A framework for modeling HOT lanes is applied to a hypothetical facility. The analysis suggests that the way in which tolls are set can have a non-trivial influence on competing measures of HOT lane performance. Other operating characteristics, such as the number of lanes designated as free and priced and whether carpools are allowed to ride free or must pay a toll to access the HOT lanes, are shown to significantly influence performance as well.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125144006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.2.2921
A. Sparger, M. Prater
There are several annual rail rate indices commonly used to depict changes in the prices paid for rail service. While accurate for general analyses, each of these indices falls short in capturing the three major components of total railroad grain rates – tariff rates, fuel surcharges, and secondary railcar market costs. Grain is a rail commodity whereby bids in the secondary railcar market can affect whether the actual rate paid by shippers is above or below the published tariff rate. The seasonality of rates inherent in grain transportation is captured through the secondary market but is neither contained in other grain rail rate indices nor apparent in annualized data. In addition, most grain rate indices do not include fuel surcharges, which have become a major component of the total rate paid for any rail commodity movement. In this paper, we develop new rail rate indices for unit trains and shuttle trains and compare them against a rail cost index. The new indices are an improvement upon past grain rail rate indices by including information from the secondary rail market, fuel surcharges, and tariff rates into a weekly index between the years 1997 and 2011. The improved indices show a higher level of detail when compared to other annualized indices, allowing for a more thorough analysis of grain rates. These indices show grain rail rates generally higher than do other indices with a notable departure from rail costs at the beginning of the economic recession in 2009. A comparison of the rail indices with rail costs calls into question whether earlier conclusions about rail market power still hold.
{"title":"A Comprehensive Rail Rate Index for Grain","authors":"A. Sparger, M. Prater","doi":"10.5399/OSU/JTRF.51.2.2921","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.2.2921","url":null,"abstract":"There are several annual rail rate indices commonly used to depict changes in the prices paid for rail service. While accurate for general analyses, each of these indices falls short in capturing the three major components of total railroad grain rates – tariff rates, fuel surcharges, and secondary railcar market costs. Grain is a rail commodity whereby bids in the secondary railcar market can affect whether the actual rate paid by shippers is above or below the published tariff rate. The seasonality of rates inherent in grain transportation is captured through the secondary market but is neither contained in other grain rail rate indices nor apparent in annualized data. In addition, most grain rate indices do not include fuel surcharges, which have become a major component of the total rate paid for any rail commodity movement. In this paper, we develop new rail rate indices for unit trains and shuttle trains and compare them against a rail cost index. The new indices are an improvement upon past grain rail rate indices by including information from the secondary rail market, fuel surcharges, and tariff rates into a weekly index between the years 1997 and 2011. The improved indices show a higher level of detail when compared to other annualized indices, allowing for a more thorough analysis of grain rates. These indices show grain rail rates generally higher than do other indices with a notable departure from rail costs at the beginning of the economic recession in 2009. A comparison of the rail indices with rail costs calls into question whether earlier conclusions about rail market power still hold.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130162805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.1.2836
B. Sloboda
You are given vehicle accident data from 337 rural interstate road sections in the state of Indiana for a 5-year period (1995 to 1999). The use of accidents per vehiclemiles traveled has an intuitive appeal in highway safety – providing a standardized measure of the relative safety of roadway segments that is more easily interpreted than the number of accidents per some time period. Because accident rates on specific highway segments are assessed over some finite time period, there is the likelihood that many highway segments will have no accidents reported during the analysis period. Thus, modeling accident rates by standard OLS would result in biased and inconsistent parameter estimates. The solution to this is to consider accident rates as a censored dependent variable (censored at zero) and apply a tobit model. For the accident-rate considered, the data will be left-censored with a clustering at zero (zero accidents per 100-million vehicle miles traveled) because accidents may not be observed on all roadway segments during the period of observation. For model estimation, the accident rate (number of accidents per 100-million VMT) was calculated as:
{"title":"Statistical and Econometric Methods for Transportation Data Analysis","authors":"B. Sloboda","doi":"10.5399/OSU/JTRF.51.1.2836","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.1.2836","url":null,"abstract":"You are given vehicle accident data from 337 rural interstate road sections in the state of Indiana for a 5-year period (1995 to 1999). The use of accidents per vehiclemiles traveled has an intuitive appeal in highway safety – providing a standardized measure of the relative safety of roadway segments that is more easily interpreted than the number of accidents per some time period. Because accident rates on specific highway segments are assessed over some finite time period, there is the likelihood that many highway segments will have no accidents reported during the analysis period. Thus, modeling accident rates by standard OLS would result in biased and inconsistent parameter estimates. The solution to this is to consider accident rates as a censored dependent variable (censored at zero) and apply a tobit model. For the accident-rate considered, the data will be left-censored with a clustering at zero (zero accidents per 100-million vehicle miles traveled) because accidents may not be observed on all roadway segments during the period of observation. For model estimation, the accident rate (number of accidents per 100-million VMT) was calculated as:","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"261 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126061293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.1.2796
G. Barone, Kevin E. Henrickson, Annie Voy
In response to increasing fuel costs, airlines began introducing baggage fees as a new source of revenue, fees which have since been increased. In this study, an event study methodology is used to examine the impact of these announcements on airline stock prices. The results indicate that the initial announcements led to negative abnormal returns for the announcing firm and other competing airlines, as they were interpreted as a sign of industry weakness. However, the results also show that subsequent increases in baggage fees, which had been shown to positively impact the airline’s financial performance, are associated with positive abnormal returns.
{"title":"Baggage Fees and Airline Stock Performance: A Case Study of Initial Investor Misperception","authors":"G. Barone, Kevin E. Henrickson, Annie Voy","doi":"10.5399/OSU/JTRF.51.1.2796","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.1.2796","url":null,"abstract":"In response to increasing fuel costs, airlines began introducing baggage fees as a new source of revenue, fees which have since been increased. In this study, an event study methodology is used to examine the impact of these announcements on airline stock prices. The results indicate that the initial announcements led to negative abnormal returns for the announcing firm and other competing airlines, as they were interpreted as a sign of industry weakness. However, the results also show that subsequent increases in baggage fees, which had been shown to positively impact the airline’s financial performance, are associated with positive abnormal returns.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128592259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.1.2826
M. Babcock, Abhinav Alakshendra
While rural roads are essential to state economies, increasing farm size and the corresponding increase in farm vehicle size coupled with declining rural population have stressed the rural road system. As county population declines the financial ability of counties to maintain and rebuild the road and bridge system isn’t keeping up with the rate of deterioration. If counties can’t maintain the rural road system as it currently exists, reducing the size of the system should be considered. The overall objective of the paper is to estimate the economic impact on selected county road systems from reducing the size of the system. The specific objectives include (a) for a sample of three Kansas counties, measure the benefits and costs of keeping the road system as it currently exists and (b) for the same sample of Kansas counties, measure the benefits and costs of several scenarios of county road closure. The main conclusion is that rural counties will be able to save money by closing some relatively low traffic volume roads and redirecting the savings toward increasing the quality of other county roads. Counties with relatively extensive road systems (miles of road per square mile) and relatively high population density are less likely to realize savings from road closure. In contrast, counties with less extensive road systems and relatively low population density are more likely to realize significant savings from closure of relatively low volume roads.
{"title":"Methodology to Measure the Benefits and Costs of Rural Road Closure: A Kansas Case Study","authors":"M. Babcock, Abhinav Alakshendra","doi":"10.5399/OSU/JTRF.51.1.2826","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.1.2826","url":null,"abstract":"While rural roads are essential to state economies, increasing farm size and the corresponding increase in farm vehicle size coupled with declining rural population have stressed the rural road system. As county population declines the financial ability of counties to maintain and rebuild the road and bridge system isn’t keeping up with the rate of deterioration. If counties can’t maintain the rural road system as it currently exists, reducing the size of the system should be considered.\u0000\u0000The overall objective of the paper is to estimate the economic impact on selected county road systems from reducing the size of the system. The specific objectives include (a) for a sample of three Kansas counties, measure the benefits and costs of keeping the road system as it currently exists and (b) for the same sample of Kansas counties, measure the benefits and costs of several scenarios of county road closure.\u0000\u0000The main conclusion is that rural counties will be able to save money by closing some relatively low traffic volume roads and redirecting the savings toward increasing the quality of other county roads. Counties with relatively extensive road systems (miles of road per square mile) and relatively high population density are less likely to realize savings from road closure. In contrast, counties with less extensive road systems and relatively low population density are more likely to realize significant savings from closure of relatively low volume roads.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131317428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.50.2.2731
Uttara Roy, S. Dissanayake
This study examines the trends, characteristics, as well as contributory causes associated with run-off-road (ROR) and non-run-off-road (NROR) crashes. Likelihood ratios of these causes for ROR crashes with respect to NROR crashes are assessed using the Bayesian Statistical Approach. Nighttime, weekends, adverse weather, rural area, gravel and curved roads, higher speed limits, wet and icy road surface, and utility vehicles are found to be the common characteristics of ROR crashes. Fell asleep, ill or medical condition, driving under the influence, too fast for conditions, tires and wheels, strong winds, freezing rain, shoulders, ruts, holes, and bumps are found to have the greatest likelihood ratios and as such have a greater role in contributing to ROR crashes than NROR crashes.
{"title":"Comparison of Factors Associated With Run-Off-Road and Non-Run-Off-Road Crashes in Kansas","authors":"Uttara Roy, S. Dissanayake","doi":"10.5399/OSU/JTRF.50.2.2731","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.50.2.2731","url":null,"abstract":"This study examines the trends, characteristics, as well as contributory causes associated with run-off-road (ROR) and non-run-off-road (NROR) crashes. Likelihood ratios of these causes for ROR crashes with respect to NROR crashes are assessed using the Bayesian Statistical Approach. Nighttime, weekends, adverse weather, rural area, gravel and curved roads, higher speed limits, wet and icy road surface, and utility vehicles are found to be the common characteristics of ROR crashes. Fell asleep, ill or medical condition, driving under the influence, too fast for conditions, tires and wheels, strong winds, freezing rain, shoulders, ruts, holes, and bumps are found to have the greatest likelihood ratios and as such have a greater role in contributing to ROR crashes than NROR crashes.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133916925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.50.2.2711
Steve Leon
A comprehensive review of airport choice modeling studies is presented in this paper, highlighting the key determinants of passenger preferences. Empirical research presented which models using binary logistic regression in the likelihood that airline travelers in the Fargo-Moorhead Metropolitan Statistical Area will not use the local airport, but instead use the competing major hub airport in Minneapolis-St. Paul, located 250 miles away as a viable origin airport. Moreover, this study investigates whether collecting empirical data from local travel agents may perhaps allow airport planners and airport managers to identify important passenger choice behaviors without incurring the added time and expense of administering formal passenger surveys. This study found that it is possible to obtain useful data from travel agents at significantly less time and effort. The significant factors obtained from the regression analysis were trip purpose, trip duration, number of connections, and airline.
{"title":"Airport Choice Modeling: Empirical Evidence from a Non‐Hub Airport","authors":"Steve Leon","doi":"10.5399/OSU/JTRF.50.2.2711","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.50.2.2711","url":null,"abstract":"A comprehensive review of airport choice modeling studies is presented in this paper, highlighting the key determinants of passenger preferences. Empirical research presented which models using binary logistic regression in the likelihood that airline travelers in the Fargo-Moorhead Metropolitan Statistical Area will not use the local airport, but instead use the competing major hub airport in Minneapolis-St. Paul, located 250 miles away as a viable origin airport. Moreover, this study investigates whether collecting empirical data from local travel agents may perhaps allow airport planners and airport managers to identify important passenger choice behaviors without incurring the added time and expense of administering formal passenger surveys. This study found that it is possible to obtain useful data from travel agents at significantly less time and effort. The significant factors obtained from the regression analysis were trip purpose, trip duration, number of connections, and airline.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132331031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.50.2.2721
Thuan V. Truong
Except in adverse weather conditions, congestion at large airport hubs appears to be predictable. This paper attempts to translate this predictability into a distribution of taxi-out times, a key component of airport congestion. When scheduled flights are chosen to define the dataset, taxi-out times follow a uniform distribution. This is not only the simplest distribution that inferences can be based on, but also a distribution that can be estimated by simple linear regression leading to very accurate forecasts. But above all, it is an invertible distribution function that can help solve a large class of stochastic optimization problems.
{"title":"The Distribution Function of Airport Taxi‐Out Times and Selected Applications","authors":"Thuan V. Truong","doi":"10.5399/OSU/JTRF.50.2.2721","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.50.2.2721","url":null,"abstract":"Except in adverse weather conditions, congestion at large airport hubs appears to be predictable. This paper attempts to translate this predictability into a distribution of taxi-out times, a key component of airport congestion. When scheduled flights are chosen to define the dataset, taxi-out times follow a uniform distribution. This is not only the simplest distribution that inferences can be based on, but also a distribution that can be estimated by simple linear regression leading to very accurate forecasts. But above all, it is an invertible distribution function that can help solve a large class of stochastic optimization problems.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130659065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.50.2.2746
Kevin Horn
{"title":"Intelligent Freight Transportation","authors":"Kevin Horn","doi":"10.5399/OSU/JTRF.50.2.2746","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.50.2.2746","url":null,"abstract":"","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132387542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-09-04DOI: 10.5399/OSU/JTRF.51.1.2801
C. Caldas, Zhanmin Zhang, Ragheb Al Halabi, Elizabeth Kincaid
When right-of-way is acquired for highway projects, state departments of transportation (DOTs) must ensure property owners receive a fair market value for their land by delivering high-quality appraisals. Despite recent technological advances, the highly complicated appraisal process often results in similar properties being assessed differently. Several DOTs sponsored a study to develop an electronic appraisal method to improve the appraisal process and to reduce the likelihood of inconsistent appraisal values by capturing, transmitting, storing, managing, and analyzing the appraisal data. The proposed method’s framework is discussed and a prototype of the system has been developed to demonstrate its features.
{"title":"Electronic Appraisal Methodology for Right-of-Way Acquisition in Highway Projects","authors":"C. Caldas, Zhanmin Zhang, Ragheb Al Halabi, Elizabeth Kincaid","doi":"10.5399/OSU/JTRF.51.1.2801","DOIUrl":"https://doi.org/10.5399/OSU/JTRF.51.1.2801","url":null,"abstract":"When right-of-way is acquired for highway projects, state departments of transportation (DOTs) must ensure property owners receive a fair market value for their land by delivering high-quality appraisals. Despite recent technological advances, the highly complicated appraisal process often results in similar properties being assessed differently. Several DOTs sponsored a study to develop an electronic appraisal method to improve the appraisal process and to reduce the likelihood of inconsistent appraisal values by capturing, transmitting, storing, managing, and analyzing the appraisal data. The proposed method’s framework is discussed and a prototype of the system has been developed to demonstrate its features.","PeriodicalId":405535,"journal":{"name":"Journal of the Transportation Research Forum","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132941546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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