Congestion-aware Traffic Routing System using sensor data

In this paper, we present a congestion-aware route planning system. First we learn the congestion model based on real data from a fleet of taxis and loop detectors. Using the learned street-level congestion model, we develop a congestion-aware traffic planning system that operates in one of two modes: (1) to achieve the social optimum with respect to travel time over all the drivers in the system or (2) to optimize individual travel times. We evaluate the performance of this system using 10,000+ taxis trips and show that on average our approach improves the total travel time by 15%.

[1]  Hari Balakrishnan,et al.  Stochastic motion planning and applications to traffic , 2011, Int. J. Robotics Res..

[2]  Matthew G. Karlaftis,et al.  A multivariate state space approach for urban traffic flow modeling and prediction , 2003 .

[3]  Yang Zhang,et al.  CarTel: a distributed mobile sensor computing system , 2006, SenSys '06.

[4]  Markos Papageorgiou,et al.  Parameter identification for a traffic flow model , 1979, Autom..

[5]  Panos G Michalopoulos,et al.  IMPROVED ESTIMATION OF TRAFFIC FLOW FOR REAL-TIME CONTROL (DISCUSSION AND CLOSURE) , 1981 .

[6]  John Krumm,et al.  Hidden Markov map matching through noise and sparseness , 2009, GIS.

[7]  H. Balakrishnan,et al.  Stochastic Motion Planning and Applications to Traffic Stochastic Motion Planning and Applications to Traffic , 2011 .

[8]  Daniela Rus,et al.  Stochastic motion planning with path constraints and application to optimal agent, resource, and route planning , 2012, 2012 IEEE International Conference on Robotics and Automation.

[9]  Martin A. Ferman,et al.  A simple analytical model of a probe-based traffic information system , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[10]  Martin A. Ferman,et al.  A simulation evaluation of a real-time traffic information system using probe vehicles , 2003, Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems.

[11]  Daniela Rus,et al.  Stochastic distributed multi-agent planning and applications to traffic , 2012, 2012 IEEE International Conference on Robotics and Automation.

[12]  Rolf H. Möhring,et al.  System-optimal Routing of Traffic Flows with User Constraints in Networks with Congestion System-optimal Routing of Traffic Flows with User Constraints in Networks with Congestion , 2022 .

[13]  Mingyan Liu,et al.  Surface street traffic estimation , 2007, MobiSys '07.

[14]  Fabián A. Chudak,et al.  Stattic Traffic Assignment Problem: A comparison between Beckmann (1956) and Nesterov & De Palma (1998) models , 2007 .

[15]  J. G. Wardrop,et al.  Some Theoretical Aspects of Road Traffic Research , 1952 .

[16]  Dinesh Manocha,et al.  Self-Aware Traffic Route Planning , 2011, AAAI.

[17]  Alexandre M. Bayen,et al.  Optimal decomposition of travel times measured by probe vehicles using a statistical traffic flow model , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[18]  Alexandre M. Bayen,et al.  An adaptive routing system for location-aware mobile devices on the road network , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[19]  Larry J. LeBlanc,et al.  A comparison of user-optimum versus system-optimum traffic assignment in transportation network design , 1984 .

[20]  Tim Roughgarden,et al.  How bad is selfish routing? , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[21]  José R. Correa,et al.  Sloan School of Management Working Paper 4319-03 June 2003 Selfish Routing in Capacitated Networks , 2022 .