February 26, 2010

Modeling Multimodal Morning Commute in a One-to-one Corridor Network

Speaker(s)

Zhen (Sean) Qian, ITS-Davis Graduate Researcher, UC Davis

Abstract

The problem of eliminating congestion in the morning commute, also known as “morning commute problem”, dates back to Vickrey (1969). Following Vickrey’s pioneering work, we consider travelers’ commuting pattern on a single route with a single bottleneck. In a typical morning commute problem, there exists an equilibrium departure time pattern if commuters all attempt to minimize their own travel costs, which include the travel time cost and an early/late arrival penalty, and in this equilibrium pattern all commuters incur the same travel cost no matter when he starts his trip. This research extends the morning commute problem in two aspects: multimodal and parking.

In the first part, we address the morning commute problem with three modes: transit, diving alone and carpool. The transit mode uses its own separate guideway, but the auto modes can access two parallel routes to reach the destination — a freeway and an arterial road (AR). Moreover, carpoolers are assumed to share their fuel costs and road tolls, if there is any, in addition to their advantage of using specially provided lanes (HOV lanes). However, there is an added cost of carpool: the cost of “gathering together”. We studied the interactions among the three modes and how different factors affect their mode share and network performances.

In the second part, we investigate parking choices in morning commute where parking capacity, parking fee and its walking time to the office are three variables. Dependent on the fees and walking time of parking lots, there are five parking patterns. Assuming parking lots are public owned and the network planner has full control of all three variables, we perform the sensitivity analysis to investigate how each factor influences the network performance and the travel profiles. More importantly, from the perspective of system optimum, we show how all three variables should be set jointly to obtain the optimal travel pattern.

Biographical Sketch

  • Sep 2006 ~ present: PhD candidate, University of California at Davis, U.S.A
  • Sep 2004 ~ July 2006: Tsinghua University, Beijing, P. R. China, M.S. of Transportation Planning and Management, July 2006
  • Sep 2000 ~July 2004: Tsinghua University, Beijing, P. R. China, B.S. of Civil Engineering, July 2004