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- Aggressive driving (1)
- Connected vehicle data (1)
- Continuous authentication (1)
- DC rail transit systems (1)
- Electric rail traction systems (1)
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- Electrical devices (1)
- Empirical forms (1)
- Ground inclination (1)
- Horizontal curves (1)
- Information technology (1)
- Keystroke dynamics (1)
- Random forest (1)
- Recuperated power (1)
- Regenerative braking energy (1)
- Regenerative power (1)
- Security (1)
- Traffic safety (1)
- Train scheduling (1)
- Typical DC-traction system (1)
- Vehicle dynamics (1)
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Articles 1 - 3 of 3
Full-Text Articles in Risk Analysis
Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Application Of Real Field Connected Vehicle Data For Aggressive Driving Identification On Horizontal Curves, Arash Jahangiri, Vincent Berardi, Sahar Ghanipoor Machiani
Psychology Faculty Articles and Research
The emerging technology of connected vehicles generates a vast amount of data that could be used to enhance roadway safety. In this paper, we focused on safety applications of a real field connected vehicle data on a horizontal curve. The database contains connected vehicle data that were collected on public roads in Ann Arbor, Michigan with instrumented vehicles. Horizontal curve negotiations are associated with a great number of accidents, which are mainly attributed to driving errors. Aggressive/risky driving is a contributing factor to the high rate of crashes on horizontal curves. Using basic safety message data in connected vehicle data …
Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed
Quantitative Analysis Of Regenerative Energy In Electric Rail Traction Systems, Mahmoud Saleh, Oindrilla Dutta, Yusef Esa, Ahmed Mohamed
Publications and Research
This paper aims at determining the influential factors affecting regenerative braking energy in DC rail transit systems. This has been achieved by quantitatively evaluating the dependence of regenerative energy on various parameters, such as vehicle dynamics, train scheduling, ground inclination and efficiency of the electrical devices. The recuperated power and energy have been presented by a mathematical model, comprising of a set of empirical forms, which allows for thorough analysis. A detailed simulation model of a typical DC-traction system has been developed to validate the developed empirical forms. The results verified the validity of the proposed mathematical model, and demonstrated …
Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung
Capturing Cognitive Fingerprints From Keystroke Dynamics, J. Morris Chang, Chi-Chen Fang, Kuan-Hsing Ho, Norene Kelly, Pei-Yuan Wu, Yixiao Ding, Chris Chu, Stephen B. Gilbert, Amed E. Kamal, Sun-Yuan Kung
Morris Chang
Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of computer users. Two machine techniques, SVM and KRR, have been developed for the system. The best results from experiments conducted with 1,977 users show a false-rejection rate of 0.7 percent and a false-acceptance rate of 5.5 percent. CTR therefore constitutes a cognitive fingerprint for continuous. Its effectiveness has been verified through a large-scale dataset. This article is part of …