Transport Companies, Truck Drivers, and the Notion of Semi-Autonomous Trucks

Trösterer, Sandra; Meneweger, Thomas; Meschtscherjakov, Alexander; Tscheligi, Manfred

doi:10.1145/3131726.3131748

Cited by 12 publications

(4 citation statements)

References 7 publications

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“…Finally, although our manuscript focuses on the application of the SBB to autonomous cars, the SBB pipeline can be adapted for intelligent data recording in other domains as well. Autonomous and semi-autonomous systems are being developed for truck, sea, and air transport to accommodate increased volume [41][42][43] and to improve safety [44]. As the onboard sensor suites of these mediums continue to increase in complexity and data bandwidth, intelligent event data recorders must be developed to store and manage valuable sensor data.…”

Section: Discussionmentioning

confidence: 99%

Smart Black Box 2.0: Efficient High-Bandwidth Driving Data Collection Based on Video Anomalies

2021

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Autonomous vehicles require fleet-wide data collection for continuous algorithm development and validation. The smart black box (SBB) intelligent event data recorder has been proposed as a system for prioritized high-bandwidth data capture. This paper extends the SBB by applying anomaly detection and action detection methods for generalized event-of-interest (EOI) detection. An updated SBB pipeline is proposed for the real-time capture of driving video data. A video dataset is constructed to evaluate the SBB on real-world data for the first time. SBB performance is assessed by comparing the compression of normal and anomalous data and by comparing our prioritized data recording with an FIFO strategy. The results show that SBB data compression can increase the anomalous-to-normal memory ratio by ∼25%, while the prioritized recording strategy increases the anomalous-to-normal count ratio when compared to an FIFO strategy. We compare the real-world dataset SBB results to a baseline SBB given ground-truth anomaly labels and conclude that improved general EOI detection methods will greatly improve SBB performance.

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Section: Discussionmentioning

confidence: 99%

Smart Black Box 2.0: Efficient High-Bandwidth Driving Data Collection Based on Video Anomalies

2021

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“…This demonstrates the significant ambiguity that businesses have when deciding whether or not to employ such technologies owing to their lack of present proof. Trösterer et al (2017) provide the results of a contextual inquiry investigation conducted at six different transportation enterprises. It focuses on understanding how truck drivers are incorporated into the business, current procedures, and the potential advantages and downsides of semi-autonomous driving from the transportation industry's perspective.…”

Section: Literature Reviewmentioning

confidence: 99%

Life Cycle Employment and Carbon Footprint Assessment of Automation and Electrification in the US Trucking Sector

M. Mandouri,

C. Onat,

Kucukvar

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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This study investigates the relationship of emissions reduction, technological transition, and employment dynamics within introducing autonomy to the trucking industry. Results highlight the urgency of adopting cleaner technologies and integrating autonomy to curtail greenhouse gas emissions. Despite additional emissions originating from manufacturing autonomous system components and additional maintenance operations, autonomous trucks offer fuel efficiency improvements and emission reductions compared to non-autonomous trucks. Employment implications reveal potential job losses due to automation overwhelming opportunities arising in autonomous system components manufacturing and maintenance, resulting in net losses of jobs within the industry. Transitioning from non-autonomous diesel trucks to autonomous battery electric trucks showcases a 50% reduction in emissions, highlighting the significance of combining autonomy and electrification in reducing emissions. The Green Employment Index is utilized to measure how green employment within the trucking industry is, unveiling a sustainable framework for job creation in tandem with emissions reduction. Based on this, for low penetration levels of less than 50%, transitioning from non-autonomous battery electric trucks to autonomous battery electric trucks offers the "greenest" employment opportunities.

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“…Apart from these "bottom-up" or "worker-driven" uses of automation features, vehicle automation is also seen as a valuable feature by companies. For example, L4 highly automated trucks, have been considered by logistics companies as a means for performing non-driving related tasks (NDRT) during longer periods of times such as during long-haul highway trips (e.g., [5,16]). In restricted intralogistics hubs and production sites, fully autonomous L5 trucks are already in operation and are expected to be widespread in the near future and integrated into automated workspaces for loading and warehouse management [17].…”

Section: Introductionmentioning

confidence: 99%

AutoWork 2021: Workshop on the Future of Work and Well-Being with Automated Vehicles

Fröhlich

Schartmüller

Wintersberger

et al. 2021

13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

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The emergence of automated driving systems will influence roles and practices in many parts of work life. Human factors and user interface design will play an important role in shaping the transition towards more productivity and well-being. The AutoWork 2021 workshop builds on its predecessor workshops by refining a research agenda and drafting concrete research studies and projects towards achieving this goal. This year's version will especially tackle the challenge of designing both for bottom-up "workerdriven" empowerment and engagement in individual, partly automated transport, as well as for supporting affected users and stakeholders in the systemic economically-driven introduction of fully autonomous vehicles in closed intralogistics areas. In a twosession schedule tailored to fit the requirements of an online event, participants will evaluate gathered requirements from previous workshops and projects on these topics and define relevant user stories and elaborate experimental designs with measurable outcomes to contribute to the research roadmap. CCS CONCEPTS• Human-centered computing → Human computer interaction (HCI); • Applied computing → Computers in other domains.

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Transport Companies, Truck Drivers, and the Notion of Semi-Autonomous Trucks

Cited by 12 publications

References 7 publications

Smart Black Box 2.0: Efficient High-Bandwidth Driving Data Collection Based on Video Anomalies

Smart Black Box 2.0: Efficient High-Bandwidth Driving Data Collection Based on Video Anomalies

Life Cycle Employment and Carbon Footprint Assessment of Automation and Electrification in the US Trucking Sector

AutoWork 2021: Workshop on the Future of Work and Well-Being with Automated Vehicles

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