Ex-Ante Evaluation of Optimal Mixed Transit Fleet Management Plans
Christina Iliopoulou, National Technical University of Athens (NTUA)Show Abstract
Ilias Laios, National Technical University of Athens (NTUA)
Konstantinos Kepaptsoglou, National Technical University of Athens (NTUA)
George Yannis, National Technical University of Athens (NTUA)
Transit operators are gradually incorporating hybrid and electric vehicles in existing conventional-drive and natural gas fleets, in an effort to improve carbon-footprint of transit services. Naturally, there are significant trade-offs in terms of purchase, operation and management costs between the various propulsion systems, which complicate fleet replacement and vehicle purchase decisions for agencies. To that end, the objective of this study is to provide an ex-ante evaluation of bus fleet management plans in cases of fleets with mixed propulsion technologies. An integer programming model is exploited for that purpose, seeking to minimize the total cost of purchasing, operating and selling buses, under various fiscal and operational constraints. A realistic data set from various sources is collected and a thorough scenario analysis is performed to assess the various trade-offs between different propulsion technologies. Results show that the largest reduction in the fleet management cost stems from favorable conditions for the purchase of more fuel-efficient types of buses, such as electric and natural gas buses.
A Transportation Asset Inventory and Transition Planning Tool for Americans with Disabilities Act Compliance in Washington, D.C.
Cesar Barreto, District Department of TransportationShow Abstract
Jianwei Wang, Precision Systems, Inc.
Steven Houh, Precision Systems, Inc.
Joseph Hood, Precision Systems, Inc.
The Americans with Disabilities Act places responsibility on transportation infrastructure providers to ensure equal access for persons with disabilities. The proportion of the population with disabilities has increased in recent decades and should continue to increase. Transportation infrastructures are large and multifaceted, such that sporadic improvements will not suffice to reach compliance. Brute force overhaul of these systems is also an unrealistic solution due to budget and time constraints. This paper summarizes the development of a method in Washington, DC to transition to ADA compliance efficiently using targeted plans based on comprehensive physical data. Key improvements are faster data collection and analysis through automation and in-office image analysis in place of some in-field measurements, a multifactor prioritization scheme, and the use of business intelligence platforms to monitor improvement efforts. The method is used as the basis of the ADA compliance transition in Washington, DC, but it is generalizable to any jurisdiction and is flexible to different priorities.
Exploring the Effects of Vehicular and Operational Characteristics on Bus Roadworthiness: An Application of the Multi-Level Modeling Approach
Jianrong Qiu, Monash UniversityShow Abstract
David B Logan, Monash University
Jennifer Oxley, Monash University
Christopher Lowe, Bus Association Victoria Inc.
This paper examines the effects of vehicular and operational characteristics on bus roadworthiness. The analysis was based on annual bus inspection data in Victoria, Australia between 2014 and 2017, consisting of 17,630 inspections of 6,447 vehicles run by 252 operators. A multilevel modeling approach was employed to account for the hierarchical data structure where inspections are nested within vehicles and vehicles within operators. The results offered insights into the effects on bus roadworthiness of characteristics attributable to inspections, vehicles, and operators. The probability of failing an inspection was found to be positively associated with vehicle age and odometer reading. Vehicle make played an important role in roadworthiness outcome, with the performance of different makes varying significantly. Small operators carried the highest risk of failure and large operators the lowest, irrespective of the location of operation. The multilevel analysis revealed that 28.9% of the variation in inspection outcomes occurred across operators and 5.2% across vehicles, which verified the presence of the hierarchical structure. The findings from this study provide safety regulators with solid research evidence to formulate policies aimed at enhancing bus roadworthiness.
GLC3: An Open Source Tool for Aiding the Minimization of Carbon Footprint of Transit Agencies
Adrita Islam, Fehr and PeersShow Abstract
Nicholas Lownes, University of Connecticut
Qiansheng Hu, The Hartford Financial Service
The United States in 2017 emitted about 14.36% of the total global Greenhouse Gas (GHG), 27% of which is from the transportation sector alone. In order to address some of these emission sources, alternative fuel technology vehicles are becoming more progressive and market ready. Transit agencies around the globe are making an effort to reduce their carbon footprint by adopting alternative fuel technology buses. The overarching objective of this paper is to introduce an open source tool that can aid transit agencies to analyze alternative technology buses adoption strategies. This paper introduces a Python-based web tool titled GHG emission and Life-Cycle Cost Calculator (GLC3). This tool lets the users control for the input values, run multiple scenario analysis, and compare results for different scenarios of adopting alternative fuel buses. It also takes into account the effect of replacing an existing fleet with newer technology buses. Data collected for the Connecticut Department of Transportation was used as a case study for this paper. Various Scenario analysis was performed by using the tool where different combinations of inputs were tested. Results from this tool help quantify the importance of adopting appropriate alternative fuel technologies by comparing cost per unit of Carbon dioxide (CO2) equivalent reduction which is significantly lower for Battery Electric Buses. GLC3 can help any transit and government agencies determine the best solution for emission reduction under a set of assumptions and achieve emission reduction goals.