Klaas Fiete Krutein, Ph.D.

Klaas Fiete Krutein, Ph.D.

Operations Research Scientist

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publications

Systematic approach for the design of flight simulator studies

Published in Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2019

The examination of commercial pilot workload often requires the use of controlled simulated studies to identify causal effects. The specific scenarios to consider within a simulator study require an extensive understanding of the safety situations that can occur in flight while also considering the specific training that pilots are provided within a simulated environment. The purpose of this paper is to provide a more systematic approach to scenario identification based on historical data, feasibility of capturing behavioral changes, simulator constraints, and training curricula.

Recommended citation: Krutein, K. F. & Boyle, L. N. (2019). "Systematic approach for the design of flight simulator studies." Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 63(1). https://doi.org/10.1177/1071181319631524

Commercial Vehicle Driver Behaviors and Decision Making: Lessons Learned from Urban Ridealongs

Published in Transportation Research Record: Journal of the Transportation Research Board, 2021

As e-commerce and urban deliveries spike, cities grapple with managing urban freight more actively. To manage urban deliv- eries effectively, city planners and policy makers need to better understand driver behaviors and the challenges they experi- ence in making deliveries. In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also track- ing vehicles with global positioning system devices. The results showed that, on average, urban CVs spent 80% of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehi- cles) parked in authorized parking locations, with only less than 5% of stops occurring in the travel lane. Dwell times associ- ated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times. We also identified three main criteria CV drivers used for choosing a park- ing location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and competition with other com- mercial drivers. The results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

Recommended citation: Dalla Chiara, G., Krutein, K. F., Ranjbari, A. & Goodchild, A. (2021). "Commercial Vehicle Driver Behaviors and Decision Making: Lessons Learned from Urban Ridealongs." Transportation Research Record: Journal of the Transportation Research Board. 2675(9). https://doi.org/10.1177/03611981211003575

Evacuating isolated islands with marine resources: A Bowen Island case study

Published in International Journal of Disaster Risk Reduction, 2022

Inhabited islands are susceptible to natural hazards, such as wildfires. To avoid disasters, preventative measures and guidelines need to be in place to strengthen community resilience. If these fail, evacuation is often the only choice. However, island evacuation is a vastly understudied problem in both research and practice, particularly for islands without permanent road connections to the mainland that require marine evacuation. Multiple vessel trips are necessary to evacuate the population from suitable access points, which previous studies did not entertain. Furthermore, most existing studies either focus on evacuations from an academic, or from a government perspective. Instead, this paper presents a collaborative approach. It applies a recently developed evacuation routing model that optimizes the evacuation plan for Bowen Island in Canada through minimizing the expected evacuation time across disaster scenarios. These were designed with the participation of a broad range of stakeholders, from local residents and volunteer groups to agencies from all levels of government and companies, which integrates both academic and practical perspectives to maximize solution quality. Different options for fleet sizes, staging locations and scenarios were considered. The results show that the optimized evacuation time for Bowen Island varies between 1 and 8 h, as it strongly depends on the disaster scenario, the evacuation fleet, and can be accelerated by temporary staging areas. The suitability of the approach for evacuation studies can be confirmed through the identification of key improvements for increased community resilience and the inclusion of the results in the official Bowen Island evacuation plan.

Recommended citation: Krutein, K. F., McGowan, J. & Goodchild, A. (2022). "Evacuating isolated islands with marine resources: A Bowen Island case study." International Journal of Disaster Risk Reduction. 72(102865). https://doi.org/10.1016/j.ijdrr.2022.102865

The isolated community evacuation problem with mixed integer programming

Published in Transportation Research Part E: Logistics & Transportation Review, 2022

As awareness of the vulnerability of isolated regions to natural disasters grows, the demand for efficient evacuation plans is increasing. However, isolated areas, such as islands, often have characteristics that make conventional methods, such as evacuation by private vehicle, impractical to infeasible. Mathematical models are conventional tools for evacuation planning. Most previous models have focused on densely populated areas, and are inapplicable to isolated communities that are dependent on marine vessels or aircraft to evacuate. This paper introduces the Isolated Community Evacuation Problem (ICEP) and a corresponding mixed integer programming formulation that aims to minimize the evacuation time of an isolated community through optimally routing a coordinated fleet of heterogeneous recovery resources. ICEP differs from previous models on resource-based evacuation in that it is highly asymmetric and incorporates compatibility issues between resources and access points. The formulation is expanded to a two-stage stochastic problem that allows scenario-based optimal resource planning while also ensuring minimal evacuation time. In addition, objective functions with a varying degree of risk are provided, and the sensitivity of the model to different objective functions and problem sizes is presented through numerical experiments. To increase efficiency, structure-based heuristics to solve the deterministic and stochastic problems are introduced and evaluated through computational experiments. The results give researchers and emergency planners in remote areas a tool to build optimal evacuation plans given the heterogeneous resource fleets available, which is something they have not been previously able to do and to take actions to improve the resilience of their communities accordingly.

Recommended citation: Krutein, K. F. & Goodchild, A. (2022). "The isolated community evacuation problem with mixed integer programming." Transportation Research Part E: Logistics & Transportation Review. 161(102710). https://doi.org/10.1016/j.tre.2022.102710

Robust and Rolling Horizon Optimization Approaches for Handling Uncertainty in the Isolated Community Evacuation Problem during Emergency Response

Published in Under Review, 2022

During responses to evacuation notices, emergency managers and coordinators need to make decisions on resource allocation quickly. Frequently, information about the location and exact numbers of evacuees is incomplete or uncertain. This is especially relevant for evacuations that require the coordination of evacuation resources that are specifically for isolated areas. While the recently introduced Isolated Community Evacuation Problem (ICEP) has provided a tool to plan the evacuation for isolated areas, it relies on accuracy of the demand numbers and distribution to provide a high quality solution. The models presented in this paper provide solutions to this problem through two alternative approaches to handle uncertainty during emergency response. The proposed robust optimization (R-ICEP) and rolling-horizon optimization (RH-ICEP) variants of the ICEP, provide methods that optimize evacuation routes considering uncertainty sets and evolving information on demand numbers respectively. Computational results demonstrate that the rolling-horizon method consistently outperforms the deterministic baseline model, while the robust method outperforms only for certain problem structures, and to a lesser degree than the rolling-horizon method. Taking advantage of evolving information through the RH-ICEP is therefore the most reliable method for emergency response involving uncertainty and can help emergency coordinators to respond more efficiently to isolated community evacuation.

Recommended citation: Krutein, K. F., Goodchild, A., & Boyle, L. N. (2022). "Robust and Rolling Horizon Optimization Approaches for Handling Uncertainty in the Isolated Community Evacuation Problem during Emergency Response." Under Review

How to Improve Urban Delivery Routes’ Efficiency Considering Cruising for Parking Delays

Published in SSRN: https://ssrn.com/abstract=4183322, 2022

This paper explores the value of information on parking availability in urban environments for commercial vehicle deliveries. The research investigates how historic cruising and parking delay data can be leveraged to improve the routes of carriers in urban environments to increase cost efficiency. To do so, the paper develops a methodology consisting of a travel time prediction model and a routing model, which account for parking delay estimates. The method is applied to both a real-world case study to show immediate application potential as well as a synthetic data set to identify environments and route characteristics which benefit the most from considering this information. Results on the real-world data set show a mean total drive time savings of 1.5 percent. The synthetic data set shows potential mean total drive time saving of 21 percent with routes with fewer stops, homogeneous spatial distribution, and high cruising time standard deviation showing the largest savings potential at up to 62.3 percent. The results demonstrate that higher visibility on curb activity for commercial vehicles can reduce time per vehicle spent in urban environments and with that decrease the impact on congestion and space use in cities.

Recommended citation: Krutein, K. F., Dalla Chiara, G., Dimitrov, T., & Goodchild, A.(2022). "How to Improve Urban Delivery Routes’ Efficiency Considering Cruising for Parking Delays." Available at SSRN https://ssrn.com/abstract=4183322

Providing curb availability information to delivery drivers reduces cruising for parking

Published in Scientific Reports, 2022

Delivery vehicle drivers are experiencing increasing challenges in finding available curb space to park in urban areas, which increases instances of cruising for parking and parking in unauthorized spaces. Policies traditionally used to reduce cruising for parking for passenger vehicles, such as parking fees and congestion pricing, are not effective at changing delivery drivers’ travel and parking behaviors. Intelligent parking systems that use real-time curb availability information to better route and park vehicles can reduce cruising for parking, but they have never been tested for delivery vehicle drivers. The current study tested whether providing real-time curb availability information to delivery drivers reduces the travel time and distance spent cruising for parking. A curb parking information system deployed in a study area in Seattle, Wash., displayed real-time curb availabilities on a mobile app called OpenPark. A controlled experiment assigned drivers’ deliveries in the study area with and without access to OpenPark. The data collected showed that when curb availability information was provided to drivers, their cruising for parking time significantly decreased by 27.9 percent, and their cruising distance decreased by 12.4 percent. These results demonstrate the potential for implementing intelligent parking systems to improve the efficiency of urban logistics systems.

Recommended citation: Dalla Chiara, G., Krutein, K. F., Ranjabri, A., & Goodchild, A. (2022). "Providing curb availability information to delivery drivers reduces cruising for parking." Sci Rep 12 (19355) https://doi.org/10.1038/s41598-022-23987-z

A Meta-Heuristic Solution Approach to Isolated Evacuation Problems

Published in Proceedings of the 2022 Winter Simulation Conference, 2022

This paper provides an approximation method for the optimization of isolated evacuation operations, modeled through the recently introduced Isolated Community Evacuation Problem (ICEP). This routing model optimizes the planning for evacuations of isolated areas, such as islands, mountain valleys, or locations cut off through hostile military action or other hazards that are not accessible by road and require evacuation by a coordinated set of special equipment. Due to its routing structure, the ICEP is NP-complete and does not scale well. The urgent need for decisions during emergencies requires evacuation models to be solved quickly. Therefore, this paper investigates solving this problem using a Biased Random-Key Genetic Algorithm. The paper presents a new decoder specific to the ICEP, that allows to translate in between an instance of the S-ICEP and the BRKGA. This method approximates the global optimum and is suitable for parallel processing. The method is validated through computational experiments.

Recommended citation: Krutein, K. F., Goodchild, A., & Boyle, L. N. (2023). "A Meta-Heuristic Solution Approach to Isolated Evacuation Problems." 2022 Winter Simulation Conference (WSC) 2002-2012. https://doi.org/10.1109/WSC57314.2022.10015470

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