1. Trajectory data map-matching
1.1 Introduction
1.2 Definitions and problem formulation
1.3 SD-Matching algorithm
1.4 Evaluations
1.5 Conclusions and discussions
2. Trajectory data compression
2.1 Introduction
2.2 Basic concepts and system overview
2.3 HCC algorithm
2.4 System implementation
2.5 Evaluations
2.6 Conclusions
3. Trajectory data protection
3.1 Introduction
3.2 Preliminary
3.3 Trajectory protection mechanism
3.4 Performance evaluations
3.5 Conclusions
Part II: Enabling Smart Urban Services: Travellers
4. TripPlanner: Personalized trip planning leveraging heterogeneous trajectory data
4.1 Introduction
4.2 TripPlanner System
4.3 Dynamic network modelling
4.4 The two-phase approach
4.5 System evaluations
4.6 Conclusions and future work
5. ScenicPlanner: Recommending the most beautiful driving routes
5.1 Introduction
5.2 Preliminary
5.3 The two-phase approach
5.4 Experimental evaluations
5.5 Conclusion and future work
Part III: Enabling Smart Urban Services: Drivers
6. GreenPlanner: Planning fuel-efficient driving routes
6.1 Introduction
6.2 Basic concepts and problem formulation
6.3 Personal fuel consumption model building
6.4 Fuel-efficient driving route planning
6.5 Evaluations
6.6 Conclusions and future work
7. Hunting or waiting: Earning more by understanding taxi service strategies
7.1 Introduction
7.2 Empirical study
7.3 Taxi strategy formulation
7.4 Understanding taxi service strategies
7.5 Conclusions
About the Author: Chao Chen is a Full Professor of Computer Science at Chongqing University. He received his Ph.D. in Computer Science from Pierre and Marie Curie University and Institut Mines-Télécom/Télécom SudParis, France in 2014. He has authored or co-authored more than 100 papers including 20 ACM/IEEE Transactions. His research interests include pervasive computing, mobile computing, urban logistics, data mining from large-scale taxi GPS trajectory data, and big data analytics for smart cities. Dr. Chen's work on taxi trajectory data mining was featured by IEEE SPECTRUM in 2011, 2016 and 2020, respectively. He was also the winner of the Best Paper Runner-Up Award at MobiQuitous 2011.
Daqing Zhang is a Chair Professor at Peking University, China. He received his Ph.D. from the University of Rome "La Sapienza" and University of L'Aquila in 1996. He has authored or co-authored more than 180 referred journal and conference papers, particularly on practical applications in digital cities, mobile social networks, and elderly care. His research interests include large-scale data mining, urban computing, context-aware computing, and ambient assistive living. He is a recipient of the 10 Years CoMoRea Impact Paper Award at IEEE PerCom 2013, the Best Paper Award at IEEE UIC 2015/2012, and the Best Paper Runner Up Award at MobiQuitous 2011.
Yasha Wang is a Full Professor and Associate Director of the National Research and Engineering Center of Software Engineering at Peking University, China. He received his Ph.D. from Northeastern University, Shenyang, China, in 2003. He also served as the head of the technical special group of the National Big Data Standards Committee of China, and as a standing committee member of the ubiquitous computing special interest group of CCF. He has long been engaged in research in the fields of data analysis, ubiquitous computing, and urban computing, and has published more than 100 papers in international high-level academic conference proceedings and journals such as IEEE TMC, ACM Ubicomp, IEEE ICDE, ACM CSCW, AAAI, and IJCAI. Cooperating with major smart-city solution providers, the results of his work have been adopted in more than 20 Chinese cities.
Hongyu Huang is an Associate Professor of Computer Science at Chongqing University. He received his B.S. degree from Chongqing Normal University in 2002, his M.S. from Chongqing University in 2005, and his Ph.D. from Shanghai Jiao Tong University in 2009. His research interests include mobile crowd-sensing, privacy preserving computing, and vehicular ad hoc networks.
