CTS Events
November 14, 2012

Dr. Nebiyou Tilahun, UPP, presents a seminar entitled "An agent based model of origin destination estimation (ADOBE)" Wednesday, November 14th at 4:00 pm in Rm 1127 SEO


November 7, 2012

Mr. Thomas Murtha, CMAP, will address the CTS-IGERT community at 4:00 p.m. in Room 1127 SEO.


October 24, 2012

Please join us in welcoming Dr. Bo Zou, CME, on Wednesday, October 24th, Room 1127 SEO, 4:00 p.m.


CTS Happenings
September 25, 2012

Award Received by Joshua Auld, CTS-IGERT alumnus.


April 20, 2012

Congratulations to James Biagioni, CTS Fellow and CS PhD candidate, winner of the Dean's Scholar award.


January 2, 2012

James Biagioni, CTS Fellow, receives "Best Presentation Award" at SenSys2011


July 30, 2010

Dr. Ouri Wolfson, Dr. Phillip Yu, and Leon Stenneth, CS student and CTS Associate, recently had a paper accepted to the 6th IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2010).


October 10, 2008

Dr. Marco Nie, "Arriving on time: routing in a stochastic network"

Download: "Arriving on Time: Routing in a Stochastic Network"

Dr. Marco Nie
Assistant Professor
Department of Civil and Environmental Engineering
Northwestern University

Time: 2:00 pm
Location: 1000 SEO

Routing in a stochastic network provides a general framework to deal with decision-making under uncertainty. In transportation, stochastic routing is used to provide predetermined optimal paths or adaptive en-route guidance. Often a routing strategy is considered optimal if it incurs the least expected travel time (LET). However, a LET path (or policy) may subject to high risks and therefore is not desirable to a risk averse traveler. For example, people tend to budget a large chunk of time for travel when they plan for important events (e.g., catch a flight). The key objective of routing in such a circumstance is to reduce the risk of running late rather than to minimize the expected travel time. In many cases, however, such risk averse behavior leads to excessively conservative time budgets. It is therefore necessary to find a way to both guarantee reliable on-time arrival and to avoid excessive waiting at the destination. This research addresses such risk averse behavior in routing under uncertainty. Specifically, we are concerned with the following instance of the stochastic routing:
Determine the latest possible departure time and the associated path (or a routing policy) which ensures on-time arrival (i.e., arrive on time or earlier) at a given reliability.
We provide a continuous, dynamic-programming-based formulation and a discrete solution algorithm which runs in polynomial time. We also present a multi-criteria shortest path algorithm to find predetermined optimal paths that guarantee a given probability of on-time arrival.

Dr Marco Nie is Assistant Professor of Civil and Environmental Engineering at Northwestern University, where he has held the position of Louis Berger Junior Chair since 2006. He received his B. E. in Structural Engineering from Tsinghua University (Beijing) in 1999, and his Ph.D. in Transportation Engineering from the University of California, Davis in 2006. He also received a Master of Engineering from National University of Singapore in 2001.

Dr. Nie's research covers a variety of topics in the areas of transportation network analysis, traffic simulation and traffic flow theory. He has published on high-performance traffic assignment algorithms, dynamic traffic assignment models, estimation of travel demands, and reliability-based routing models. Dr. Nie also has extensive experience in developing software tools for various transportation applications. He was the chief developer of Toolkit of Network Modeling (TNM), a programmer's toolbox for transportation network applications, which implements, among other functions, a variety of traffic assignment algorithms, O-D estimation methods, and mesoscopic/microscopic traffic simulators.

Dr. Nie's current research projects include providing reliable routing guidance in the Chicago area and validating novel traffic assignment algorithms that determine unique route flows. Both are funded by Federal Highway Administration (FHWA).