Truck drivers’ views on the road safety benefits of advanced driver assistance systems and Intelligent Transport Systems in Tanzania

IF 2.2 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal on Multimodal User Interfaces Pub Date : 2024-08-03 DOI:10.1007/s12193-024-00437-w
Marwa Chacha, Prosper Nyaki, Ariane Cuenen, Ansar Yasar, Geert Wets
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Abstract

The transportation of goods by road is crucial in Tanzania’s Central and North-South Corridors. However, challenges such as truck congestion and road accidents are affecting the efficiency of these routes. Road crashes are prevalent in low- and middle-income countries, with Africa experiencing an exceptionally high rate. This study examines the opinions of Tanzanian truck drivers on the effectiveness of Advanced Driver Assistance Systems in reducing road safety risks. A discriminant analysis was conducted to assess the awareness and use of these systems among different driver experienced groups. The results highlight the importance of improving infrastructure, ensuring vehicle safety standards, providing comprehensive driver training, and integrating innovative Intelligent Transport Systems to address road safety issues. In conclusion, the study provides valuable insights for policymakers and stakeholders to strengthen road safety measures in Tanzania, facilitating smoother road freight transport operations and promoting economic growth.

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坦桑尼亚卡车司机对先进驾驶辅助系统和智能交通系统的道路安全效益的看法
公路货物运输对坦桑尼亚的中部和南北走廊至关重要。然而,卡车拥堵和道路事故等挑战正在影响这些路线的效率。道路交通事故在中低收入国家非常普遍,而非洲的交通事故发生率尤其高。本研究探讨了坦桑尼亚卡车司机对高级驾驶辅助系统在降低道路安全风险方面的有效性的看法。通过判别分析,评估了不同驾驶经验群体对这些系统的认识和使用情况。研究结果凸显了改善基础设施、确保车辆安全标准、提供全面的驾驶员培训以及整合创新型智能交通系统对于解决道路安全问题的重要性。总之,这项研究为政策制定者和利益相关者提供了宝贵的见解,有助于加强坦桑尼亚的道路安全措施,促进道路货物运输更加顺畅,并促进经济增长。
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来源期刊
Journal on Multimodal User Interfaces
Journal on Multimodal User Interfaces COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
6.90
自引率
3.40%
发文量
12
审稿时长
>12 weeks
期刊介绍: The Journal of Multimodal User Interfaces publishes work in the design, implementation and evaluation of multimodal interfaces. Research in the domain of multimodal interaction is by its very essence a multidisciplinary area involving several fields including signal processing, human-machine interaction, computer science, cognitive science and ergonomics. This journal focuses on multimodal interfaces involving advanced modalities, several modalities and their fusion, user-centric design, usability and architectural considerations. Use cases and descriptions of specific application areas are welcome including for example e-learning, assistance, serious games, affective and social computing, interaction with avatars and robots.
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