Personalized Route Planning System Based on Driver Preference

Wang, Ren; Zhou, MengChu; Gao, Kaizhou; Alabdulwahab, Ahmed; Rawa, Muhyaddin

doi:10.3390/s22010011

Cited by 20 publications

(13 citation statements)

References 47 publications

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“…Wang et al (2021) [45] used a two-part algorithm to solve the driver preference-based route planning (DPRP) problem, which consists of a first phase to eliminate those nodes and edges from the network that, if included in the chosen route, would exceed a threshold distance. The second phase of the algorithm is based on the concept of depth-first search traversal.…”

Section: Computation and Resultsmentioning

confidence: 99%

Designing Ecotourism Routes with Time-Dependent Benefits along Arcs and Waiting Times at Nodes

Piedra-de-la-Cuadra,

Ortega

2024

Mathematics

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Ecotourism routes serve as powerful tools for fostering environmental awareness. To achieve this, it is crucial to design itineraries within natural parks that strike a balance between visitor experience and ecological preservation. Limiting the duration of visits prevents undue strain on both visitors and ecosystems. Effective routes should showcase high biodiversity, traversing diverse sites to enhance knowledge acquisition. Considering natural factors such as light conditions and climate, it is prudent to tailor visiting times to optimize the experience. Therefore, it makes sense to incorporate time-dependent benefits at arcs and the possibility of introducing waiting times at nodes in the design models. These two characteristics have enriched the optimization models developed to solve the tourist trip design problem based on maximizing benefit only when points of interest are visited. However, the specific application of these aforementioned characteristics and enriched optimization models to the arc orientation problem remains yet to be reported on and published in the literature. Our contribution addresses this gap, proposing a route design model with scenic value in the arches of the graph where the benefits perceived by travelers are maximized, taking into account a diversity of evaluations depending on the time of starting the trip through each arc.

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Section: Computation and Resultsmentioning

confidence: 99%

Designing Ecotourism Routes with Time-Dependent Benefits along Arcs and Waiting Times at Nodes

Piedra-de-la-Cuadra,

Ortega

2024

Mathematics

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“…As relevant technologies continue to evolve, traffic situation information can now be sensed and acquired more promptly and precisely. This enables the integration of the real-time traffic condition status into route planning [5]. Besides static data (e.g., planned timetables), dynamic and realtime data (e.g., timetable deviations, current locations) and dynamic estimation models have been considered in traffic-aware route planning (TA), to find the optimal route [5,14].…”

Section: Literature Reviewmentioning

confidence: 99%

“…This enables the integration of the real-time traffic condition status into route planning [5]. Besides static data (e.g., planned timetables), dynamic and realtime data (e.g., timetable deviations, current locations) and dynamic estimation models have been considered in traffic-aware route planning (TA), to find the optimal route [5,14]. Furthermore, studies have also proposed self-aware route planning (SA), which considers planned routes with future traffic conditions [3].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Modern planning and navigation systems usually offer the shortest or fastest route. However, as people have diverse requirements for services, they may not be satisfied with these limited route planning options [5]. Therefore, there is potential for developing next-generation route planning services, which take into account multiple attributes and user preferences.…”

Section: Introductionmentioning

confidence: 99%

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A Federated Personal Mobility Service in Autonomous Transportation Systems

Jian,

Chen,

et al. 2023

Mathematics

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A personal mobility service (PMS) is developed to support personalized travel options for users in autonomous transportation systems (ATS), based on a macro-system state and micro-user behavior. However, this functionality necessitates processing and transmitting vast amounts of data, raising concerns about user privacy protection during data processing and transmission within the PMS. Furthermore, the PMS must be maintained and perform well, while preserving privacy. Therefore, we propose a novel federated PMS, denoted as a FPMS. Specifically, the FPMS can serve users’ personal mobility needs by facilitating the collaboration between the physical and information domains. Then, a common framework for FPMS architectures, which captures the features of ATSs, is proposed and discussed from both physical and logical perspectives, which include both the logical architecture and physical architecture; and we present the key algorithms for the FPMS, in conjunction with a artificial neural network (ANN). Additionally, in static estimation scenarios, the FPMS demonstrated a similar accuracy for three different models compared to the traditional PMS, while reducing the computing time by approximately 60% and communication resource consumption by approximately 85%.

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“…Indeed, preferences vary from driver to driver. In this regard, different routes will be proposed, benefiting both the driver (who will receive a route recommendation in line with their needs) and urban environments, as such an approach is considered beneficial in reducing traffic congestion in urban areas [24].…”

Section: Introductionmentioning

confidence: 99%

Driver-Centric Urban Route Planning: Smart Search for Parking

Ćelić,

Mandžuka,

Tomas

et al. 2024

Sustainability

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With urbanization, there is a growing need for mobility. Challenges for urban drivers include finding available parking spaces. Searching for a parking spot can be a frustrating experience, often time consuming and costly. Also, the increasing number of vehicles on the roads leads to an additional strain on traffic flow, while the search for parking spaces lowers the level of service. In inner cities, vehicles circulate in search of an available parking space, leading to an increase in travel time, fuel consumption, pollutant emissions, and a decrease in traffic safety. The search for a free parking space generates a significant increase in traffic in urban areas. To solve the parking search problem, it is necessary to develop certain strategies and measures that minimize circling in search of a parking space. The implementation of intelligent transportation systems stands out. By applying intelligent transport systems, drivers are provided with information about free parking spaces, which reduces the circulation of vehicles in search of free parking. Although initially ITS systems mainly provided services for closed parking lots and garages, with the further development of the system, the service was extended to street parking lots or open-type parking lots. These measures not only solve traffic challenges but also promote sustainability in urban areas. This article analyzes the effect of a cooperative approach of guiding vehicles to available parking spaces compared to a standard model of searching for an available parking space. Within the framework of the advanced model for searching for available space, four parking demand scenarios were defined and simulated. Based on the created traffic simulation, a comparative analysis was made between the classic and cooperative approach, while the primary differences are manifested in the load of the traffic flow A simulation model was developed using the road network from the urban center of Zagreb.

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Personalized Route Planning System Based on Driver Preference

Cited by 20 publications

References 47 publications

Designing Ecotourism Routes with Time-Dependent Benefits along Arcs and Waiting Times at Nodes

Designing Ecotourism Routes with Time-Dependent Benefits along Arcs and Waiting Times at Nodes

A Federated Personal Mobility Service in Autonomous Transportation Systems

Driver-Centric Urban Route Planning: Smart Search for Parking

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