When Adjacent Lane Dependencies Dominate the Uncongested Regime of the Fundamental Relationship: Abridged

Abstract This paper presents an empirical study of the fundamental relationship between speed, v, and flow, q, (denoted vqFR) under low flow in the uncongested regime. Using new analytical techniques to extract more information from loop detector data, the vqFR from a time of day HOV lane exhibits high v that slowly drops as q increases. This curve arises after binning several million vehicles by q and only considering those bins with q  Taking a broader view, four different factors appear to limit the speed a driver takes: (i) the roadway geometry, (ii) the posted speed limit, (iii) the vehicle ahead (car following), and (iv) traffic conditions in the adjacent lane. Whichever constraint is most binding determines the driver's speed. While the first three constraints are found in the literature, this work contributes the fourth, as per above. When the speed limit is the most binding constraint the uncongested regime of the vqFR is roughly flat with a near constant speed over a wide range of q. When the roadway geometry is the binding constraint, e.g., due to the lack of speed limits, drivers are able to travel fast enough to be sensitive to the vehicle ahead and exhibit lower v as q increases. Car following is by definition in the congested regime and thus, beyond the scope of this paper. Finally, the present work shows that as the adjacent lane moves slower, the uncongested drivers choose speeds below the speed limit and once more exhibit lower v as q increases. Although the chosen v is below the speed limit, the drivers continue to exhibit behavior consistent with the uncongested regime.

[1]  John Sullivan,et al.  Another Look at , 1979 .

[2]  J. Banks,et al.  EFFECTS OF LOCATION ON CONGESTED-REGIME FLOW-CONCENTRATION RELATIONSHIPS FOR FREEWAYS , 1993 .

[3]  Fred L. Mannering,et al.  MODELING THE ENDOGENEITY OF LANE-MEAN SPEEDS AND LANE-SPEED DEVIATIONS: A STRUCTURAL EQUATIONS APPROACH , 1998 .

[4]  B D Greenshields,et al.  A study of traffic capacity , 1935 .

[5]  Hesham Rakha,et al.  Variability of traffic-flow measures across freeway lanes , 1999 .

[6]  David Mahalel.  Appraisal of traffic stream friction , 1984 .

[7]  Yinhai Wang,et al.  Modeling Traffic Flow Dynamics on Managed Lane Facility , 2012 .

[8]  Balaji Ponnu,et al.  Speed-spacing dependency on relative speed from the adjacent lane: New insights for car following models , 2015 .

[9]  Robert L. Bertini,et al.  Comparison of Key Freeway Capacity Parameters on North American Freeways with German Autobahns Equipped with a Variable Speed Limit System , 2006 .

[10]  Geddes P. Mahabir.  Speed, Flow and Capacity Relations on Multilane Highways , 1981 .

[11]  Amal Ibrahim,et al.  EFFECT OF ADVERSE WEATHER CONDITIONS ON SPEED-FLOW-OCCUPANCY RELATIONSHIPS , 1994 .

[12]  Yong Shi,et al.  SOME OBSERVATIONS ON SPEED-FLOW AND FLOW-OCCUPANCY RELATIONSHIPS UNDER CONGESTED CONDITIONS , 1993 .

[13]  Benjamin Coifman,et al.  Revisiting the empirical fundamental relationship , 2014 .

[14]  D. Gazis,et al.  Density Oscillations Between Lanes of a Multilane Highway , 1962 .

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

[16]  Randall Guensler,et al.  Analysis of Reduction in Effective Capacities of High-Occupancy Vehicle Lanes Related to Traffic Behavior , 2008 .

[17]  Brian L Allen,et al.  ANOTHER LOOK AT IDENTIFYING SPEED-FLOW RELATIONSHIPS ON FREEWAYS , 1985 .

[18]  Keith Redmill,et al.  Mining vehicle classifications from the Columbus Metropolitan Freeway Management System , 2015 .

[19]  Benjamin Coifman,et al.  The Berkeley Highway Laboratory-building on the I-880 field experiment , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[20]  Benjamin Coifman,et al.  An Overview of Empirical Flow-Density and Speed-Spacing Relationships: Evidence of Vehicle Length Dependency , 2015 .

[21]  Yinhai Wang,et al.  Analysis of Operational Interactions between Freeway Managed Lanes and Parallel, General Purpose Lanes , 2011 .

[22]  Doug Robertson,et al.  Study of Speed-Flow Relationships on Individual Freeway Lanes , 1997 .

[23]  Eric T. Donnell,et al.  Speed Prediction Models for Multilane Highways: Simultaneous Equations Approach , 2010 .

[24]  J. Wardrop.  ROAD PAPER. SOME THEORETICAL ASPECTS OF ROAD TRAFFIC RESEARCH. , 1952 .

[25]  F. Heider,et al.  Principles of topological psychology , 1936 .

[26]  Werner Brilon,et al.  COMPARISON OF UNCONGESTED SPEED-FLOW RELATIONSHIPS USING DATA FROM GERMAN AUTOBAHNS AND NORTH AMERICAN FREEWAYS , 1994 .

[27]  Robert L. Bertini,et al.  Dynamics of Variable Speed Limit System Surrounding Bottleneck on German Autobahn , 2006 .

[28]  P. I. Richards.  Shock Waves on the Highway , 1956 .

[29]  Yinhai Wang,et al.  Operational Performance and Speed–Flow Relationships for Basic Managed Lane Segments , 2012 .

[30]  John Collura,et al.  Towards a Social Psychology-based Microscopic Model of Driver Behavior and Decision-making: Modifying Lewin's Field Theory , 2014, ANT/SEIT.

[31]  Kitae Jang,et al.  Traffic Characteristics of High-Occupancy Vehicle Facilities , 2012 .

[32]  Benjamin Coifman.  Jam Occupancy and Other Lingering Problems with Empirical Fundamental Relationships , 2014 .

[33]  M J Lighthill,et al.  On kinematic waves II. A theory of traffic flow on long crowded roads , 1955, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[34]  Thomas Urbanik,et al.  STUDY OF FREEWAY BOTTLENECKS IN TEXAS , 1993 .