Infrared thermal camera-based system for tram drivers warning about hazardous situations

Konieczka, Adam; Michalowicz, Ewelina; Piniarski, Karol

doi:10.23919/spa.2018.8563417

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Hence, one way to overcome this detection accuracy's deterioration is to use thermal sensors, which are more robust to adverse conditions with respect to canonical imaging sensors. In detail, thermal or Long Wavelength Infrared (LWIR) cameras [113] have the following characteristics: (i) can detect and classify objects in several particular conditions (e.g., darkness, rain, and through most fog conditions); (ii) offer increased robustness against reflections, shadows, and car headlights [114]; and (iii) are unaffected by sun glare, improving situational awareness [115]. Typically, the resolution of modern thermal cameras is lower than the resolution of color cameras, but recent on-market high-end thermal cameras are capable of producing full HD video streams.…”

Section: Camera Sensorsmentioning

confidence: 99%

On Driver Behavior Recognition for Increased Safety: A Roadmap

Davoli

Martalò

Cilfone

et al. 2020

Safety

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Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.

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Section: Camera Sensorsmentioning

confidence: 99%

On Driver Behavior Recognition for Increased Safety: A Roadmap

Davoli

Martalò

Cilfone

et al. 2020

Safety

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“…In paper [15], on the other hand, the authors demonstrated a system to detect and track obstacles using a multilayer laser scanner. Konieczka et al, in [16], presented a thermal camera-based system for tram drivers to increase the safety of tram traffic at night. In contrast, article [17] presents a monitoring system to reduce the risk of the unconsciousness of the driver (commonly referred to as a "dead-man device").…”

Section: Introductionmentioning

confidence: 99%

Embedded System for Learning Smooth and Energy-Efficient Tram Driving Techniques

Konieczka,

Stachowiak,

Feliński

et al. 2023

Energies

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Driving a tram in city traffic is a challenging task. It is especially difficult to drive smoothly (without unnecessary jerks) when the route runs through streets with many other vehicles, pedestrians, and traffic lights. A smooth driving style of the tram driver not only has a significant impact on the comfort of passengers being transported, but also affects the energy consumption of the tram. The paper focuses on the analysis of the tram driver’s way of driving and the resulting energy savings. The energy consumption of the tram was measured depending on the driver’s driving technique. For the analysis of the driving technique, an innovative electronic device was proposed to be installed on the tram. It detects jerks in the lateral and longitudinal directions. Based on vibration analysis, it evaluates the driver’s driving technique on an ongoing basis and displays the result of this assessment. The device is cheap and uses a popular minicomputer, a GPS system receiver, an IMU accelerometer, and a screen. It is independent of the electronic systems of the tram. Due to this, it is possible to increase passenger comfort and reduce electricity consumption. It can be useful when learning to drive a tram. Preliminary tests of this device were carried out on a real tram during rides with passengers in city traffic. Tests have confirmed its effectiveness.

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