Integrating Origin-Destination Survey and Stochastic User Equilibrium: A Case Study for Route Relocation

The paper analyses integrating origin-destination (O-D) survey results with stochastic user equilibrium (SUE) in traffic assignment. The two methods are widely used in transportation planning but their applications have not yet fully integrated. While O-D gives a generalized trip patterns, purpose and characteristics, SUE provides optimal trip distributions using the characteristics found in O-D survey. The paper utilized O-D and SUE in route relocation study for the town of Coamo in Puerto Rico. The O-D survey was used initially in studying possible trip distribution and assignment for the new route. Initial distribution and assignment of traffic to the existing roadway networks and the proposed route were allocated utilizing the O-D survey findings. The SUE was then used to optimize the assignments considering roadway characteristics such as number of lanes, capacity limits, free flow speed, signal spacing density, travel time and gasoline cost. The travel time was optimized through the Bureau of Public Roads (BPR) equation found in 2000 HCM. The optimal trips found from the SUE were then used to propose the final alignment of the new route. Traffic assignment from the SUE was slightly different from those initially assigned using O-D, indicating there was optimization. The assignment on new route was increased by 13.8% from the one assigned using O-D while assignment on the existing link was reduced by 22%.

[1]  Benjamin Heydecker,et al.  Dynamic departure time and stochastic user equilibrium assignment , 2005 .

[2]  Hani S. Mahmassani,et al.  Two-Stage Stochastic Model for Sensor Location Problem in a Large-Scale Network , 2008 .

[3]  Kurt Jörnsten,et al.  Overcoming the (Apparent) Problem of Inconsistency in Origin-Destination Matrix Estimations , 1993, Transp. Sci..

[4]  Rasmus Dyhr Frederiksen,et al.  Stochastic user equilibrium traffic assignment with turn-delays in intersections , 1998 .

[5]  H. Spiess.  A MAXIMUM LIKELIHOOD MODEL FOR ESTIMATING ORIGIN-DESTINATION MATRICES , 1987 .

[6]  Hironori Kato,et al.  EMPIRICAL ANALYSIS ON RELATIONSHIP BETWEEN TYPES OF TRAVEL DEMAND TECHNIQUES AND ESTIMATED USER'S BENEFIT STEMMING FROM TRANSPORTATION INVESTMENT , 2005 .

[7]  Lingjiang Kong,et al.  Urban Mixed Traffic Flow Considering the Influence by Origin-destination of Public Transportation , 2011 .

[8]  Stephen D. Clark,et al.  Sensitivity analysis of the probit-based stochastic user equilibrium assignment model , 2002 .

[9]  Martin L. Hazelton.  Some Remarks on Stochastic User Equilibrium , 1998 .

[10]  William H. K. Lam,et al.  Estimation of an origin-destination matrix with random link choice proportions : a statistical approach , 1996 .

[11]  Hai Yang,et al.  Optimal traffic counting locations for origin–destination matrix estimation , 1998 .

[12]  Sangjin Han,et al.  Dynamic traffic modelling and dynamic stochastic user equilibrium assignment for general road networks , 2003 .

[13]  Martin L. Hazelton,et al.  SOME COMMENTS ON ORIGIN-DESTINATION MATRIX ESTIMATION , 2003 .

[14]  William H. K. Lam,et al.  EVALUATION OF COUNT LOCATION SELECTION METHODS FOR ESTIMATION OF O-D MATRICES , 1998 .

[15]  M G H Bell.  STOCHASTIC USER EQUILIBRIUM ASSIGNMENT AND ITERATIVE BALANCING. , 1993 .

[16]  SooCheong Jang,et al.  Understanding travel expenditure patterns: a study of Japanese pleasure travelers to the United States by income level , 2004 .

[17]  Martin L. Hazelton,et al.  Estimation of origin-destination matrices from link flows on uncongested networks , 2000 .

[18]  Hani S. Mahmassani,et al.  Dynamic Origin-Destination Demand Estimation Using Turning Movement Counts , 2008 .