Region-based dynamic forecast routing for autonomous vehicles

In this paper, we aim to implement an urban network-level traffic routing scheme for autonomous vehicles to mitigate congestion in urban areas. We first present an implementation of a region-based dynamic traffic model. Subsequently, we present an innovative predictive routing approach for autonomous vehicles, dynamic forecast routing, and apply it on a set of homogeneous regions, making use of Urban-scale Macroscopic Fundamental Diagram to define the state of congestion in each region. This approach is compared with periodically adjusted routing, as well as logit routing, which is used to model self-interested human driver behavior. We also integrate a public transit diversion mechanism on all approaches. Results show that our approach surpasses all other approaches on all performance metrics by at least 40%.

[1]  Nikolaos Geroliminis,et al.  Properties of a well-defined Macroscopic Fundamental Diagram for urban traffic , 2011 .

[2]  Nikolaos Geroliminis,et al.  Estimating MFDs in Simple Networks with Route Choice. , 2013 .

[3]  Serge P. Hoogendoorn,et al.  Simulation Model for Traffic Using Network Fundamental Diagrams , 2015 .

[4]  Rong Su,et al.  Time-dependent partitioning of urban traffic network into homogeneous regions , 2014, 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV).

[5]  S. P. Hoogendoorn,et al.  Routing Strategies Based on Macroscopic Fundamental Diagram , 2012 .

[6]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[7]  Nikolas Geroliminis,et al.  Equilibrium analysis and route guidance in large-scale networks with MFD dynamics , 2015 .

[8]  Serge P. Hoogendoorn,et al.  The effect of signal settings on the macroscopic fundamental diagram and its applicability in traffic signal driven perimeter control strategies , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[9]  Markos Papageorgiou,et al.  Urban congestion gating control based on reduced operational network fundamental diagrams , 2013 .

[10]  Nikolas Geroliminis,et al.  Macroscopic modeling of traffic in cities , 2007 .

[11]  Nikolas Geroliminis,et al.  Model predictive perimeter-control for two-region urban cities. , 2012 .

[12]  Joseph L. Schofer,et al.  A STATISTICAL ANALYSIS OF SPEED-DENSITY HYPOTHESES , 1965 .

[13]  J. Y. Yen,et al.  Finding the K Shortest Loopless Paths in a Network , 2007 .

[14]  Markos Papageorgiou,et al.  Exploiting the fundamental diagram of urban networks for feedback-based gating , 2012 .

[15]  Dirk Helbing,et al.  The spatial variability of vehicle densities as determinant of urban network capacity , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[16]  M. Simoni.  Congestion pricing schemes controlled by the gMFD: A comprehensive design and appraisal to bridge the engineering and economic perspective , 2013 .

[17]  C. Daganzo,et al.  Macroscopic relations of urban traffic variables: Bifurcations, multivaluedness and instability , 2011 .

[18]  Nikolas Geroliminis,et al.  Optimal hybrid macroscopic traffic control for urban regions: Perimeter and switching signal plans controllers , 2013, 2013 European Control Conference (ECC).

[19]  Vikash V. Gayah,et al.  On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram , 2014 .

[20]  C. Daganzo.  THE CELL TRANSMISSION MODEL.. , 1994 .

[21]  H. M. Zhang,et al.  On the distribution schemes for determining flows through a merge , 2003 .

[22]  Nikolaos Geroliminis,et al.  Perimeter and boundary flow control in multi-reservoir heterogeneous networks , 2013 .

[23]  Bart De Schutter,et al.  Optimal dynamic route guidance: A model predictive approach using the macroscopic fundamental diagram , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[24]  Serge P. Hoogendoorn,et al.  Two-Variable Macroscopic Fundamental Diagrams for Traffic Networks , 2013 .

[25]  Nikolaos Geroliminis,et al.  On the spatial partitioning of urban transportation networks , 2012 .