CallCab: A unified recommendation system for carpooling and regular taxicab services

Stankovic, John A.; He, Tian; Liu, Yunhuai

doi:10.1109/bigdata.2013.6691605

Cited by 30 publications

(12 citation statements)

References 9 publications

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“…Fastprk was shown to reduce travel time and fuel consumption, by reducing the time and distance driven to find a parking space. In addition to these applications, other solutions are being investigated by the research community such as sophisticated carpooling [136], [137] and public transportation systems that may stimulate the citizens to use these alternative transportation modes, instead of driving their own cars.…”

Section: Parking Management Systemsmentioning

confidence: 99%

A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches

Djahel

Doolan

Muntean

et al. 2015

IEEE Commun. Surv. Tutorials

341

156

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The growing size of cities and increasing population mobility have determined a rapid increase in the number of vehicles on the roads, which has resulted in many challenges for road traffic management authorities in relation to traffic congestion, accidents and air pollution. Over the recent years, researchers from both industry and academia were focusing their efforts on exploiting the advances in sensing, communication and dynamic adaptive technologies to make the existing road Traffic Management Systems (TMS) more efficient to cope with the above issues in future smart cities. However, these efforts are still insufficient to build a reliable and secure TMS that can handle the foreseeable rise of population and vehicles in smart cities. In this survey, we present an up to date review of the different technologies used in the different phases involved in a TMS, and discuss the potential use of smart cars and social media to enable fast and more accurate traffic congestion detection and mitigation. We also provide a thorough study of the security threats that may jeopardize the efficiency of the TMS and endanger drivers' lives. Furthermore, the most significant and recent European and worldwide projects dealing with traffic congestion issues are briefly discussed to highlight their contribution to the advancement of smart transportation. Finally, we discuss some open challenges and present our own vision to develop robust TMSs for future smart cities.

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Section: Parking Management Systemsmentioning

confidence: 99%

A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches

Djahel

Doolan

Muntean

et al. 2015

IEEE Commun. Surv. Tutorials

341

156

View full text Add to dashboard Cite

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“…It leverages cachecoherent shortest path index and parallelism to achieve the efficient taix ride-sharing analysis. CallCab [28] deploys a generic Map-Reduce measure to tackle the raw dataset of 14,000 taxis efficiently. They deploy the incremental search approach, while in real world scenarios, this approach does not find all suitable taxis.…”

Section: Dynamic Ridesharingmentioning

confidence: 99%

A User-Oriented Taxi Ridesharing System with Large-Scale Urban GPS Sensor Data

Zhang

Shemshadi²,

Sheng

et al. 2021

IEEE Trans. Big Data

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Ridesharing is a challenging topic in the urban computing paradigm, which utilizes urban sensors to generate a wealth of benefits and thus is an important branch in ubiquitous computing. Traditionally, ridesharing is achieved by mainly considering the received user ridesharing requests and then returns solutions to users. However, there lack research efforts of examining user acceptance to the proposed solutions. To our knowledge, user decisions in accepting/rejecting a rideshare is one of the crucial, yet not well studied, factors in the context of dynamic ridesharing. Moreover, existing research attention is mainly paid to find the nearest taxi, whilst in reality the nearest taxi may not be the optimal answer. In this paper, we tackle the above un-addressed issues while preserving the scalability of the system. We present a scalable framework, namely TRIPS, which supports the probability of accepting each request by the companion passengers and minimizes users' efforts. In TRIPS, we propose three search techniques to increase the efficiency of the proposed ridesharing service. We also reformulate the criteria for searching and ranking ridesharing alternatives and propose indexing techniques to optimize the process. Our approach is validated using a real, large-scale dataset of 10,357 GPS-equipped taxis in the city of Beijing, China and showcases its effectiveness on the ridesharing task.

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“…Route recommendation for taxi drivers has drawn much attention from researchers [6,16,11,8,14,15,17,4,18,19,9]. Most existing recommender systems are designed based on real world GPS trajectories which were collected through a large number of probing taxis.…”

Section: Related Workmentioning

confidence: 99%

Scram

Qian

Cao

Mouël

et al. 2015

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

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Recommending routes for a group of competing taxi drivers is almost untouched in most route recommender systems. For this kind of problem, recommendation fairness and driving efficiency are two fundamental aspects. In the paper, we propose SCRAM, a sharing considered route assignment mechanism for fair taxi route recommendations. SCRAM aims to provide recommendation fairness for a group of competing taxi drivers, without sacrificing driving efficiency. By designing a concise route assignment mechanism, SCRAM achieves better recommendation fairness for competing taxis. By considering the sharing of road sections to avoid unnecessary competition, SCRAM is more efficient in terms of driving cost per customer (DCC). We test SCRAM based on a large number of historical taxi trajectories and validate the recommendation fairness and driving efficiency of SCRAM with extensive evaluations. Experimental results show that SCRAM achieves better recommendation fairness and higher driving efficiency than three compared approaches.

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CallCab: A unified recommendation system for carpooling and regular taxicab services

Cited by 30 publications

References 9 publications

A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches

A Communications-Oriented Perspective on Traffic Management Systems for Smart Cities: Challenges and Innovative Approaches

A User-Oriented Taxi Ridesharing System with Large-Scale Urban GPS Sensor Data

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