Stretching resources: Sensitivity of optimal bus frequency allocation to stop-level demand elasticities, 2015
Bus transit route frequencies in practice are often set reactively, without consideration of ride... more Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where elasticities are used in frequency allocation, a single across the board value or two respective values for peak and off-peak are used for the entire set of routes and stops throughout the day. With growing availability of ridership data, estimation of spatially and temporally disaggregated elasticities is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of elasticities corresponding to varying levels of disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a transit network frequency setting framework: (1) temporal elasticities based on time of day, (2) spatial elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer. It is also important to capture longer-term effects—over a year or more—because seasonal activity patterns may bias elasticity estimates over shorter time horizons.
Transportation Research Part A: Policy and Practice, 2015
In practice, travel time is assigned a cost and treated as a disutility to be minimized. There is... more In practice, travel time is assigned a cost and treated as a disutility to be minimized. There is a growing body of research supporting the hypothesis that travel time has some value of its own, and the proliferation of information and communication technology (ICT) may be contributing to that value. Travelers' attitudes are confounded with their mode choice, and as telecommunications mediate travel behavior, analysts must recognize the interaction between time use and customer satisfaction for appropriate travel demand management. To that end, this paper presents results from jointly estimated models of travelers' latent satisfaction and on-board activity engagement using Chicago transit rider data gathered in April 2010. The simple questionnaire and small sample corroborate the findings of past research indicating travel attitudes and activity engagement have potential to influence travelers' value of time, and many transit riders consider transit a better use of time and/or money than driving. The findings affirm the need for a more holistic understanding of value of time for travel demand management and infrastructure valuation. As time use has an influence on users' valuation of the transit mode, offering opportunities to conduct certain leisure activities could improve the perceived value of travel time.
Travelers' choices are central to the performance of a transportation system, but little is known... more Travelers' choices are central to the performance of a transportation system, but little is known about what influences such choices or the impact they have on system performance. When selecting a transportation management strategy, a transportation management center operator must understand and anticipate how travelers will respond: Will they stay on the same routes or divert? Will they decide to walk, bike, or take a bus or train instead of driving? Will they leave earlier or later?
Meeting California's 2020 greenhouse gas emissions target will require an average CO2 emissions r... more Meeting California's 2020 greenhouse gas emissions target will require an average CO2 emissions reduction of approximately 380 lbs per month per person in the U.S. For the typical two-person household, 760 lbs per month can be saved by employing such near-term measures as reducing monthly miles traveled (by auto and aircraft) and altering behaviors related to appliance energy consumption (e.g., employing a smart thermostat, reducing water heater temperature settings, and eliminating phantom loads). Additional long-term savings can be obtained by purchasing more fuel efficient vehicles, reducing home floor area, moving into multi-family housing units with shared walls, and replacing old appliances with energy efficient products. To get a sense of where these strategies exist for individuals and households, this paper quantifies greenhouse gas reductions from these and other household decisions. Upstream and downstream emissions-reductions policies are discussed, including taxation, cap and trade among energy producers, and household-level carbon budgets. Given the variability in U.S. climate zones, the sizable contributions of both upstream and downstream carbon sources, and the variety of electricity generation processes, a combination of policy measures seems warranted, in order to achieve recommended targets in a rapid, equitable, and relatively pain-free manner.
Bus transit route frequencies in practice are often set reactively, without consideration of ride... more Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where elasticities are used in frequency allocation, a single across the board value or two respective values for peak and off-peak are used for the entire set of routes and stops throughout the day. With growing availability of ridership data, estimation of spatially and temporally disaggregated elasticities is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of elasticities corresponding to varying levels of disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a transit network frequency setting framework: (1) temporal elasticities based on time of day, (2) spatial elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer. It is also important to capture longer-term effects-over a year or more-because seasonal activity patterns may bias elasticity estimates over shorter time horizons.
Transportation Research Record: Journal of the Transportation Research Board, 2014
ABSTRACT The main goal of the study was to integrate demand models into weather-responsive networ... more ABSTRACT The main goal of the study was to integrate demand models into weather-responsive network traffic estimation and prediction system methodologies. The study examined the behavioral responses of travelers along several dimensions in response to weather-related transportation management strategies in conjunction with active travel demand management strategies before and during severe weather events. Specific management interventions included pretrip, information-based mode, and departure time choice adjustments, as well as policy-based rescheduling of school hours. The paper presents a case study of the Chicago, Illinois, area network under snow conditions to assess the effect of a combination of demand management strategies to maintain the same level of network performance as under clear weather conditions. A combination of earlier dissemination of information and school-opening policy resulted in a similar level of network performance maintained under a median snow day as compared with a clear weather day. The paper presents integrated supply and demand models for simulation and an assessment of demand management strategies in conjunction with weather-related congestion.
Stretching resources: Sensitivity of optimal bus frequency allocation to stop-level demand elasticities, 2015
Bus transit route frequencies in practice are often set reactively, without consideration of ride... more Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where elasticities are used in frequency allocation, a single across the board value or two respective values for peak and off-peak are used for the entire set of routes and stops throughout the day. With growing availability of ridership data, estimation of spatially and temporally disaggregated elasticities is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of elasticities corresponding to varying levels of disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a transit network frequency setting framework: (1) temporal elasticities based on time of day, (2) spatial elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer. It is also important to capture longer-term effects—over a year or more—because seasonal activity patterns may bias elasticity estimates over shorter time horizons.
Transportation Research Part A: Policy and Practice, 2015
In practice, travel time is assigned a cost and treated as a disutility to be minimized. There is... more In practice, travel time is assigned a cost and treated as a disutility to be minimized. There is a growing body of research supporting the hypothesis that travel time has some value of its own, and the proliferation of information and communication technology (ICT) may be contributing to that value. Travelers' attitudes are confounded with their mode choice, and as telecommunications mediate travel behavior, analysts must recognize the interaction between time use and customer satisfaction for appropriate travel demand management. To that end, this paper presents results from jointly estimated models of travelers' latent satisfaction and on-board activity engagement using Chicago transit rider data gathered in April 2010. The simple questionnaire and small sample corroborate the findings of past research indicating travel attitudes and activity engagement have potential to influence travelers' value of time, and many transit riders consider transit a better use of time and/or money than driving. The findings affirm the need for a more holistic understanding of value of time for travel demand management and infrastructure valuation. As time use has an influence on users' valuation of the transit mode, offering opportunities to conduct certain leisure activities could improve the perceived value of travel time.
Travelers' choices are central to the performance of a transportation system, but little is known... more Travelers' choices are central to the performance of a transportation system, but little is known about what influences such choices or the impact they have on system performance. When selecting a transportation management strategy, a transportation management center operator must understand and anticipate how travelers will respond: Will they stay on the same routes or divert? Will they decide to walk, bike, or take a bus or train instead of driving? Will they leave earlier or later?
Meeting California's 2020 greenhouse gas emissions target will require an average CO2 emissions r... more Meeting California's 2020 greenhouse gas emissions target will require an average CO2 emissions reduction of approximately 380 lbs per month per person in the U.S. For the typical two-person household, 760 lbs per month can be saved by employing such near-term measures as reducing monthly miles traveled (by auto and aircraft) and altering behaviors related to appliance energy consumption (e.g., employing a smart thermostat, reducing water heater temperature settings, and eliminating phantom loads). Additional long-term savings can be obtained by purchasing more fuel efficient vehicles, reducing home floor area, moving into multi-family housing units with shared walls, and replacing old appliances with energy efficient products. To get a sense of where these strategies exist for individuals and households, this paper quantifies greenhouse gas reductions from these and other household decisions. Upstream and downstream emissions-reductions policies are discussed, including taxation, cap and trade among energy producers, and household-level carbon budgets. Given the variability in U.S. climate zones, the sizable contributions of both upstream and downstream carbon sources, and the variety of electricity generation processes, a combination of policy measures seems warranted, in order to achieve recommended targets in a rapid, equitable, and relatively pain-free manner.
Bus transit route frequencies in practice are often set reactively, without consideration of ride... more Bus transit route frequencies in practice are often set reactively, without consideration of ridership elasticity to the service frequency provided. Where elasticities are used in frequency allocation, a single across the board value or two respective values for peak and off-peak are used for the entire set of routes and stops throughout the day. With growing availability of ridership data, estimation of spatially and temporally disaggregated elasticities is possible. But do these make a difference in the resulting solution to the frequency allocation problem? This study is intended to examine this question by comparing the quality of solutions obtained using an optimal frequency allocation model with different sets of elasticities corresponding to varying levels of disaggregation. Three main methodologies for estimating ridership elasticity with respect to headway are compared in the context of a transit network frequency setting framework: (1) temporal elasticities based on time of day, (2) spatial elasticities via grouping stops into demand, supply and land use classes and (3) spatio-temporal elasticities using a linear regression model. Elasticities based only on temporal aggregation result in an underestimation of the potential improvements as compared to elasticities which account for some spatial characteristics, such as land use and the opportunity to transfer. It is also important to capture longer-term effects-over a year or more-because seasonal activity patterns may bias elasticity estimates over shorter time horizons.
Transportation Research Record: Journal of the Transportation Research Board, 2014
ABSTRACT The main goal of the study was to integrate demand models into weather-responsive networ... more ABSTRACT The main goal of the study was to integrate demand models into weather-responsive network traffic estimation and prediction system methodologies. The study examined the behavioral responses of travelers along several dimensions in response to weather-related transportation management strategies in conjunction with active travel demand management strategies before and during severe weather events. Specific management interventions included pretrip, information-based mode, and departure time choice adjustments, as well as policy-based rescheduling of school hours. The paper presents a case study of the Chicago, Illinois, area network under snow conditions to assess the effect of a combination of demand management strategies to maintain the same level of network performance as under clear weather conditions. A combination of earlier dissemination of information and school-opening policy resulted in a similar level of network performance maintained under a median snow day as compared with a clear weather day. The paper presents integrated supply and demand models for simulation and an assessment of demand management strategies in conjunction with weather-related congestion.
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Papers by Charlotte Frei