Ziqi Song

Link-Based Stochastic Loading Methods for Weibit Route Choice Model

The multinomial logit route choice model is known to have some drawbacks in traffic loading because of the independently and identically distributed assumption with the Gumbel distributed random error term. This assumption results in the models inability to handle the route overlapping and heterogeneous perception variance problems. This study proposed a new traffic loading technique for handling both route overlapping and heterogeneous perception variance problems. Specifically, a modified Dials STOCH algorithm and a link-based commonality factor were combined with the weibit route choice model to create the link-based C-weibit stochastic loading method. Numerical examples show the features of this stochastic loading method. The Chicago, Illinois, sketch network was used to demonstrate the applicability of the C-weibit stochastic loading method in a real transportation network.

Exit Choice Behavior of Pedestrians Involving Individuals with Disabilities During Building Evacuations

Pedestrian evacuation studies are critical in obtaining information about evacuation scenarios and in preparing to face the challenges of actual evacuations. Studies have examined evacuation policies, exit choice modeling, and evacuation curve analysis. Some studies have addressed the evacuation behavior of individuals with disabilities (IWDs), although this important aspect of evacuation seems to be missing from modeling of the exit choice in many studies. In modeling of the exit choice for evacuation, many studies have been found to be based on the stated preference survey method, where evacuees are asked to choose an exit based on descriptions, without an actual experiment taking place. This study focuses on the discrete choice model of the exit choice in the room for both IWDs and individuals without disabilities (IWODs). The results demonstrate that the presence of IWDs in the group plays a crucial role in the exit choice for all evacuees. The results demonstrate that there are significant differences in exit choice between IWDs and IWODs. Current evacuation policies have been found to be more focused on visual signs, while this study demonstrates that these visual signs are of little importance to individuals with visual disabilities.

Planning of Fast-Charging Stations for a Battery Electric Bus System under Energy Consumption Uncertainty

Battery-powered electric buses are gaining popularity as an energy-efficient and emission-free alternative for bus fleets. However, battery electric buses continue to struggle with concerns related to their limited driving range and time-consuming recharging processes. Fast-charging technology, which utilizes dwelling time at bus stops or terminals to recharge buses in operation employing high power, can raise battery electric buses to the same level of capability as their diesel counterparts in terms of driving range and operating time. To develop an economical and effective battery electric bus system using fast-charging technology, fast-charging stations must be strategically deployed. Moreover, due to the instability of traffic conditions and travel demands, the energy consumption uncertainty of buses should also be considered. This study addresses the planning problem of fast-charging stations that is inherent in a battery electric bus system in light of the energy consumption uncertainty of buses. A robust optimization model that represents a mixed integer linear program is developed with the objective of minimizing the total implementation cost. The model is then demonstrated using a real-world bus system. The performances of deterministic solutions and robust solutions are compared under a worst-case scenario. The results demonstrate that the proposed robust model can provide an optimal plan for a fast-charging battery electric bus system that is robust against the energy consumption uncertainty of buses. The trade-off between system cost and system robustness is also addressed.