Context-aware multi-modal route selection service for urban computing scenarios

IF 4.4 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Matheus Brito , Camilo Santos , Bruno S. Martins , Iago Medeiros , Marcos Seruffo , Eduardo Cerqueira , Denis Rosário
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引用次数: 0

Abstract

The rapid urban population growth introduces novel challenges to urban mobility scenarios, requiring innovative and connected solutions to relieve traffic congestion and enhance transportation efficiency, using unusual roads and public transportation modals. For instance, multi-modal routes allow more flexible modal combinations to offer smart multi-modal mobility. In this context, the route selection service must rely on different context information, such as criminality, accidents, air quality, and others, where Internet of Things technologies introduce active and ubiquitous sensing of many contexts along the urban scenario, providing data for statistical analysis to offer a safer and healthier urban reality. However, designing an efficient multi-modal route selection service that considers different context information to offer personalized routes is important. In this article, we describe a context-aware route selection service that considers adequate contextual information to provide routes according to the user’s preference. The multi-modal route selection service applies a multi-criteria method to give different degrees of importance to each criterion based on the user profile (i.e., Worker, Green, Safe, and Tourist). We present extensive evaluation results from applying our multi-modal route selection approach to a London dataset. The approach successfully enables user-preferred transportation choices using four balanced selection profiles and ten route features. The proposed multi-modal route selection service demonstrates better performance in terms of economic, ecological, and time-saving metrics for each user profile compared to a greedy selection manner.

面向城市计算场景的情境感知多模式路线选择服务
城市人口的快速增长给城市交通方案带来了新的挑战,需要创新的互联解决方案,利用非同寻常的道路和公共交通模式来缓解交通拥堵,提高交通效率。例如,多模式路线允许更灵活的模式组合,以提供智能多模式交通。在这种情况下,路线选择服务必须依靠不同的环境信息,如犯罪、事故、空气质量等,物联网技术引入了对城市场景中许多环境的主动和无处不在的感知,为统计分析提供数据,以提供更安全、更健康的城市现实。然而,设计一种高效的多模式路线选择服务非常重要,这种服务应考虑不同的环境信息,以提供个性化路线。在本文中,我们介绍了一种情境感知路线选择服务,它能考虑充分的情境信息,根据用户的偏好提供路线。这种多模式路线选择服务采用多标准方法,根据用户特征(即工人、绿色、安全和游客)对每个标准赋予不同的重要程度。我们在伦敦的一个数据集上应用了我们的多模式路线选择方法,并展示了广泛的评估结果。该方法利用四种平衡选择配置文件和十种路线特征,成功实现了用户首选的交通选择。与贪婪选择方式相比,所提出的多模式路线选择服务在每个用户配置文件的经济、生态和省时指标方面都表现出了更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ad Hoc Networks
Ad Hoc Networks 工程技术-电信学
CiteScore
10.20
自引率
4.20%
发文量
131
审稿时长
4.8 months
期刊介绍: The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to: Mobile and Wireless Ad Hoc Networks Sensor Networks Wireless Local and Personal Area Networks Home Networks Ad Hoc Networks of Autonomous Intelligent Systems Novel Architectures for Ad Hoc and Sensor Networks Self-organizing Network Architectures and Protocols Transport Layer Protocols Routing protocols (unicast, multicast, geocast, etc.) Media Access Control Techniques Error Control Schemes Power-Aware, Low-Power and Energy-Efficient Designs Synchronization and Scheduling Issues Mobility Management Mobility-Tolerant Communication Protocols Location Tracking and Location-based Services Resource and Information Management Security and Fault-Tolerance Issues Hardware and Software Platforms, Systems, and Testbeds Experimental and Prototype Results Quality-of-Service Issues Cross-Layer Interactions Scalability Issues Performance Analysis and Simulation of Protocols.
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