arXiv subjects

Megh Bahadur KC

Publications and source records attributed to Megh Bahadur KC.

3 recordsLinked to original sources

arXiv2025

School Transport Electrification -- Adoption, Strategies, Methods and Policy: A Comprehensive Review

The move towards electric school buses (ESBs) marks a critical step in creating a healthier and more sustainable future for students. To meet the ambitious goal of zero-emission school buses by 2035,this review focuses on the need assessment, practices, gaps, challenges, and way forward. We conducted a comprehensive assessment of more than 100 relevant sources, resulting in a final investigation. In-depth, systematic, and qualitative content analysis with SWOT analysis produced critical insights into school transport electrification. The results showed that 1.8% of the total buses in the US have already been converted to electric, where California alone owning 29% of the buses. Subsidies from various agencies and programs have contributed to the rapid growth of electrification. However, challenges in cost, technology, and policies must be mitigated through innovation and stakeholder partnerships. Policy support is boosting subsidies, industry investment and market readiness. Equitable policy is important to support underserved and disadvantaged populations, which can be addressed through four key dimensions of equity: procedural, recognition, distributive, and reparative equity. Furthermore, the traditional bus deployment model is still the most common, whereas Transportation-as-a-Service (TaaS) is an innovative ESB deployment model with the potential to accelerate ESB adoption by integrating vehicle-to-grid. SWOT analysis indicated that the achievement of the zero-emission goal, autonomous driving, and repowered vehicle technology are the greatest opportunities. Dynamic electrification strategies, V2G technology and system resiliency are yet to be discovered, which could be crucial for mass electrification.

physics.soc-ph↗

arXiv2025

Understanding Mode Choice Behavior of People with Disabilities: A Case Study in Utah

Despite the growing recognition of the importance of inclusive transportation policies nationwide, there is still a gap, as the existing transportation models often fail to capture the unique travel behavior of people with disabilities. This research study focuses on understanding the mode choice behavior of individuals with travel-limited disabilities and comparing the group with no such disability. The study identified key factors influencing mode preferences for both groups by utilizing Utah's household travel survey, simulation algorithm and Multinomial Logit model. Explanatory variables include household and socio-demographic attributes, personal, trip characteristics, and built environment variables. The analysis revealed intriguing trends, including a shift towards carpooling among disabled individuals. People with disabilities placed less emphasis on travel time saving. A lower value of travel time for people with disabilities is potentially due to factors like part-time work, reduced transit fare, and no or shared cost for carpooling. Despite a 50% fare reduction for the disabled group, transit accessibility remains a significant barrier in their choice of Transit mode. In downtown areas, people with no disability were found to choose transit compared to driving, whereas disabled people preferred carpooling. Travelers with no driving licenses and disabled people who use transit daily showed complex travel patterns among multiple modes. The study emphasizes the need for accessible and inclusive transportation options, such as improved public transit services, shorter first and last miles in transit, and better connectivity for non-motorized modes, to cater to the unique needs of disabled travelers. The findings of this study have significant policy implications such as an inclusive mode choice modeling framework for creating a more sustainable and inclusive transportation system.

physics.soc-ph↗

arXiv2025

Evolving School Transport Electrification: Integrated Dynamic Route Optimization and Partial Charging for Mixed Fleets

School bus transportation, the largest fleet size for public transportation in the US, plays a significant role in sustainability through transport decarbonization. Thus, effective planning of electric school bus routes and recharge schedules is vital. This study proposes a novel approach that simultaneously addresses electric school bus dynamic routing and partial charge scheduling, considering practical scenarios such as varying student demands, bus capacities, maximum ride time, stop time window, and fleet mixes. The model incorporates constraints like bell time tolerance and battery capacity and charging infrastructure candidate location, making it robust for school bus electrification. A linearized Mixed Integer Programming (MIP) model for homogeneous and heterogeneous fleets with full and partial recharging strategies is formulated. The proposed objective function for nonlinear and linear models is executed and compared for computational effectiveness. The model is tested on various sizes of school networks using modified benchmark instances, and a real-world case study demonstrates the benefits of electrified school transportation. The results show that employing heterogeneous fleets can lead to cost savings, reduced routing distance, and travel time for both the tested networks and the case study. Sensitivity analyses highlight the trade-offs between battery size and total cost. Furthermore, the benefits of partial charging and optimum riding time for school bus routes are suggested. The proposed optimization approach can achieve significant reductions in travel distance, up to 56.4% compared to the current situation and fleet size, supporting the case for school transport electrification. Potential additional investment subsidies from federal and state governments are added benefits for accelerated school bus electrification.

math.OC↗