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1. Assessing trauma center accessibility in the Southeastern region of the U.S. to improve healthcare efficacy using an anti-covering approach

   https://doi.org/10.1371/journal.pgph.0002230  

   Chea, Heewon; Kim, Hyun (August 2023, PLOS Global Public Health)

   Jhunjhunwala, Rashi (Ed.)

   Accessibility to trauma centers is vital for the patients of severe motor vehicle crashes. Many vehicle crash fatalities failed to reach the proper emergency medical services since the accident location was far away from trauma centers. The spatial discordance between the service coverage area of trauma centers and actual locations of motor vehicle accidents delays the definitive medical care and results in death or disability. Many fatalities would have been prevented if the patients had a chance to get proper treatment in time at Southeastern region of the U.S. Also, the accessibility to trauma centers from the actual locations of motor vehicle accidents is different in the Southeastern region. This research aimed to facilitate the accessibility to trauma centers for severe motor vehicle crash patients in the Southeastern region. The analyses are conducted to assess current trauma center accessibility and suggest the optimal locations of future trauma centers using the Anti-covering location model for trauma centers (TraCtmodel). This study found that existing trauma centers failed to serve many demands, and the actual coverages of the current locations of trauma centers over potential demands are highly different in each Southeastern state.TraCtmodel is applied to each Southeastern state, and its solutions provide better coverage for demand locations. However, theTraCtmodel for each state tends to choose too many facilities, with excessively supplied facilities across the Southeastern region. The excessive service supply issue is addressed by applying theTraCtModel to a broader spatial extent.TraCtmodel applied to the entire Southeastern region and most of the demand, over 98% covered by the service coverage of optimal facility locations with 15 additional facilities. This research proves that the GIS andTraCtmodel applied to the broader spatial extent works well with increasing trauma medical service beneficiaries while providing a minimum number of additional facilities. 

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2. Delineations for Police Patrolling on Street Network Segments with p-Median Location Models

   https://doi.org/10.3390/ijgi13110410  

   Lee, Changho; Kim, Hyun; Chun, Yongwan; Griffith, Daniel A (November 2024, ISPRS International Journal of Geo-Information)

   Police patrolling intends to enhance traffic safety by mitigating the risks associated with vehicle crashes and accidents. From a view of operations, patrolling requires an effective distribution of resources and often involves area delineations for this distribution purpose. Given constraints such as budget and human resources for traffic safety, delineating geographic areas optimally for police patrol areas is an important agenda item. This paper considers two p-median location models using segments on a street network as observational units on which traffic issues such as vehicle crashes occur. It also uses two weight sets to construct an enhanced delineation of police patrol areas in the City of Plano, Texas. The first model for the standard p-median formulation gives attention to the cumulative number of motor vehicle crashes from 2011 to 2021 on the major transportation networks in Plano. The second model, an extension of this first p-median one, uses balancing constraints to achieve balanced spatial coverage across patrol areas. These two models are also solved with network kernel density count estimates (NKDCE) instead of crash counts. These smoothed densities on a network enable consideration of uncertainty affiliated with this aggregation. The analysis results of this paper suggest that the p-median models provide effective specifications, including their capability to define patrol areas that encompass the entire study region while minimizing distance costs. The inclusion of balancing constraints ensures a more equitable distribution of workloads among patrol areas, improving overall efficiency. Additionally, the model with NKDCE results in an improved workload balance among delineated areas for police patrolling activities, thus supporting more informed spatial decision-making processes for public safety. 

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3. Participatory Design in the Classroom: Exploring the Design of an Autonomous Vehicle Human-Machine Interface with a Visually Impaired Co-Designer

   Huff, E.; Lucaites, K.; Roberts, A; Brinkley, J (January 2020, Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   Self-driving vehicles are the latest innovation in improving personal mobility and road safety by removing arguably error-prone humans from driving-related tasks. Such advances can prove especially beneficial for people who are blind or have low vision who cannot legally operate conventional motor vehicles. Missing from the related literature, we argue, are studies that describe strategies for vehicle design for these persons. We present a case study of the participatory design of a prototype for a self-driving vehicle human-machine interface (HMI) for a graduate-level course on inclusive design and accessible technology. We reflect on the process of working alongside a co-designer, a person with a visual disability, to identify user needs, define design ideas, and produce a low-fidelity prototype for the HMI. This paper may benefit researchers interested in using a similar approach for designing accessible autonomous vehicle technology. INTRODUCTION The rise of autonomous vehicles (AVs) may prove to be one of the most significant innovations in personal mobility of the past century. Advances in automated vehicle technology and advanced driver assistance systems (ADAS) specifically, may have a significant impact on road safety and a reduction in vehicle accidents (Brinkley et al., 2017; Dearen, 2018). According to the Department of Transportation (DoT), automated vehicles could help reduce road accidents caused by human error by as much as 94% (SAE International, n.d.). In addition to reducing traffic accidents and saving lives and property, autonomous vehicles may also prove to be of significant value to persons who cannot otherwise operate conventional motor vehicles. AVs may provide the necessary mobility, for instance, to help create new employment opportunities for nearly 40 million Americans with disabilities (Claypool et al., 2017; Guiding Eyes for the Blind, 2019), for instance. Advocates for the visually impaired specifically have expressed how “transformative” this technology can be for those who are blind or have significant low vision (Winter, 2015); persons who cannot otherwise legally operate a motor vehicle. While autonomous vehicles have the potential to break down transportation 

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4. Optimal trauma care network redesign with government subsidy: A bilevel integer programming approach

   https://doi.org/10.1016/j.omega.2023.102885  

   Liu, Shaonan; Kong, Nan; Parikh, Pratik; Wang, Mingzheng (September 2023, Omega)

   Trauma presents a prominent health problem worldwide. However, trauma centers are often clustered in urban areas and sparsely located in rural areas. The geographic maldistribution of trauma centers leads to system-related mistriage errors. While some local governments oer subsidy to incentivize the affiliated hospital group to redesign the trauma care network, the approach is ad hoc. To address this issue, we propose a bilevel integer programming model to investigate the subsidized trauma care network redesign problem, which considers the government as the leader and the hospital group as the follower. To solve the resultant problem efficiently, we propose a branching idea to exclude additional infeasible solutions and suboptimal solutions, in turn speeding up the branch-and-bound algorithm. In a case study, we redesign a trauma care network in the midwestern area of the U.S. based on closed-form approximate functions of system-related mistriage errors. The results show that the optimal network redesign redistributes the network by slightly reducing the number of trauma centers to relieve the crowded trauma care resource, and achieves an overall improvement of about 11% over the original network. 

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5. A family of models in support of realistic drug interdiction location decision‐making

   https://doi.org/10.1111/tgis.12921  

   Price, Ashleigh N.; Curtin, Kevin M.; Magliocca, Nicholas R.; Turner, Daniel; Mitchell, Penelope; McSweeney, Kendra; Summers, Diana L. (March 2022, Transactions in GIS)

   Abstract Long‐standing federal drug‐control policy aims to reduce the flow of narcotics into the USA, in part by intercepting cocaine shipments en route from South American production regions to North American consumer markets. Drug interdiction efforts operate over a large geographic area, containing complex drug trafficking networks in a dynamic environment. The extant interdiction models in the operations research and location science literature do not realistically model the objectives of and constraints on the interdiction forces, and therefore counterdrug organizations do not employ those models in their decision‐making processes. This article presents three new models built on the maximal covering location problem (MCLP): the maximal covering location problem for interdiction (MCLP‐I), multiple‐demand maximal covering location problem (MD‐MCLP), and multiple‐type maximal covering location problem (MT‐MCLP). These are novel formulations that permit multiple types of demands and facilities to be covered, and the utility of these formulations is demonstrated in the context of counterdrug operations. Optimal interdiction locations are determined within the geography of the Central American transit zone, using a coupled GIS and optimization framework. The results identify the optimal interdiction locations for known or estimated drug shipments and can constrain those optimal locations by differentiating among drug traffickers, the types of interdiction resources, and agency jurisdictions. This research both demonstrates the flexibility in designing alternative interdiction scenarios and presents novel covering models that may be extended to other application areas and operational contexts. 

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