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For more information regarding this award, please see: /https://www.eng.ufl.edu/newengineer/news/uf-researchers-to-augment-human-cognition-to-aid-in-extreme-work-environments/
For more information regarding this award, please see: https://www.nsf.gov/
(Mar. 2021.) Dr. Zahabi has been awarded the NSF CAREER award to study Adaptive Driver Assistance Systems and Personalized Training for Law Enforcement Officers. For more information regarding this award, please see https://www.nsf.gov/awardsearch/showAward?AWD_ID=2041889&HistoricalAwards=false
Award Abstract #1951864
SCC-IRG Track 2: CityGuide: Seamless and Inclusive Location-Based Services for Communities
| NSF Org: | CNS Division Of Computer and Network Systems |
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| Initial Amendment Date: | July 10, 2020 |
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| Latest Amendment Date: | July 10, 2020 |
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| Award Number: | 1951864 |
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| Award Instrument: | Standard Grant |
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| Program Manager: | Linda Bushnell CNS Division Of Computer and Network Systems CSE Direct For Computer & Info Scie & Enginr |
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| Start Date: | October 1, 2020 |
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| End Date: | September 30, 2023 (Estimated) |
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| Awarded Amount to Date: | $1,122,749.00 |
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| Investigator(s): | Vinod Namboodiri vinod.namboodiri@wichita.edu (Principal Investigator) Nils Hakansson (Co-Principal Investigator) Siny Joseph (Co-Principal Investigator) Maryam Zahabi (Co-Principal Investigator) Guler Arsal (Co-Principal Investigator) |
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| Sponsor: | Wichita State University 1845 Fairmount Wichita, KS 67260-0007 (316)978-3285 |
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| NSF Program(s): | S&CC: Smart & Connected Commun |
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| Program Reference Code(s): | 042Z, 9150 |
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| Program Element Code(s): | 033Y |
ABSTRACT
Persons with disabilities in our communities often find it difficult to achieve and maintain an independent and high quality of life. A significant cause of this issue is the challenge in independently accessing locations and services within the community. In spite of advances in global positioning system (GPS)-enabled applications, there are many daily-life scenarios where the lack of adequate location-based services presents mobility and access challenges to persons with disabilities. The long-term vision for this project is to design, deploy, evaluate, and refine an inclusive community-wide system (accessed through a smartphone app) called CityGuide that provides various auxiliary location-based services (ALBSs) for people with disabilities (and the general population), complementing satellite-based GPS systems. CityGuide will provide a core wayfinding application as a service with the twin capabilities of exploration and navigation. Building upon this core wayfinding service, numerous other applications can be built; some specific applications of interest within the scope of the project are: emergency evacuation, remote assistance, and transit.
This project attempts to use a common technology infrastructure to simultaneously serve the auxiliary wayfinding needs of people with a broad range of disabilities. The top-level goal of using technology to improve accessibility in communities naturally requires integrative socio-technical research contributions that advances knowledge on multiple fronts. From a technology design perspective, the project advances knowledge about providing seamless and scalable indoor and outdoor location-based services. From an information design perspective, the project advances knowledge about contextually appropriate cues and content for a variety of location-based applications. From a human-computer interaction perspective, the project advances knowledge in applying universal design principles towards accessing location-based services. From an economic analysis perspective, the project advances knowledge about the impact of economies of scope and scale in the feasibility and sustainability of accessibility technologies in small to medium-sized communities. Expected societal impacts from the project include the development of wayfinding technologies (and associated tech transfer) that provides people with disabilities and also the general population a useful tool to increase their independence, and thus, quality of life; and creation of a model for other similar future efforts (beyond wayfinding) to address the need for greater inclusivity in how various community-based services are accessed.
This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951864&HistoricalAwards=false
ANALYSIS OF ADVANCED DRIVER-ASSISTANCE SYSTEMS IN POLICE VEHICLES
Motor vehicle crashes are the leading cause of deaths for police officers. These crashes have been mainly attributed to the use of in-vehicle technologies while driving. Advanced driver-assistance systems (ADAS) have the potential to improve officer safety by removing some of driver vehicle control responsibilities. Although current ADAS in police vehicles can adapt to emergencies and provide multi-modal alerts, there has been little research on how ADAS can reduce driving task demands in situations that officers are also engaged in secondary-tasks while driving. The objective of this project is to evaluate ADAS in police vehicles. This project will investigate how ADAS features should adapt in situations of multi-tasking and what types of ADAS are most effective for improving driver safety. This project includes two phases including (1) ADAS needs and implementation analysis in police vehicles; and (2) evaluation of police ADAS in a driving simulation study. The first phase includes ride-along observations and focus group meetings with officers to understand their ADAS needs and current systems in police vehicles. The second phase will evaluate ADAS in high-demand situations using a high-fidelity driving simulator. Fifty (50) police officers will be recruited through our collaboration with Texas A&M Engineering Extension Services (TEEX). The outcomes will provide practical guidelines to automotive companies supplying police vehicles regarding effective ADAS features/types and can improve officer safety in police operations. This project addresses safety in the primary area of automated vehicles and secondary application areas of vehicle technology, planning for safety, and driver factors and interfaces.
Maryam Zahabi (TTI/TAMU)*
Farzaneh Shahini (TTI/TAMU-Graduate Student)
David Wonzniak (TTI/TAMU-Student)
Vanessa Nasr (TTI/TAMU-Student)
Start Date: 2020-05-01
End Date: 2022-03-31
Status: Active
Grant Number: 69A3551747115
Total Funding: $199,970
Source Organization: Safe-D National UTC
Project Number: TTI-05-02
Driver Factors and Interfaces
RiP URL
UTC Project Information Form
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Texas A&M University
Texas A&M Transportation Institute
3135 TAMU
College Station, Texas 77843-3135
USA
Analysis of Advanced Driver-Assistance Systems in Police Vehicles
