Traffic Operations and Management

Expediting Vehicle Infrastructure Integration (EVII): Where the Rubber Meets (and Talks to) the Road

Varaiya, Pravin P
2006

This research demonstrated two potential VII (vehicle-infrastructure integration) services, one in traffic data probes and the other with safety. A real private vehicle, operating on California roadways, “talked” to the roadside, with the roadside backhaul interfacing into an existing California Department of Transportation (Caltrans) database and archival application. Demonstration of a probe application showed great promise for supplementing Caltrans’ database with VII- or DSRC-based probe data. Similar promise was shown with a road condition monitoring system, which demonstrated the...

Unintended Environmental Impacts of Nighttime Freight Logistics Activities

Sathaye, Nakul
Harley, Robert
Madanat, Samer
2009

In recent years, the reduction of freight vehicle trips during peak hours has been a common policy goal. To this end, policies have been implemented to shift logistics operations to nighttime hours. The purpose of such policies has generally been to mitigate congestion and environmental impacts. However, the atmospheric boundary layer is generally more stable during the night than the day. Consequently, shifting logistics operations to the night may increase 24‐hour average concentrations of diesel exhaust pollutants in many locations. This paper presents realistic scenarios for two...

Traffic Management Systems Performance Measurement: Final Report

Banks, James H.
Kelly, Gregory
1997

This report documents a study of performance measurement for Transportation Management Centers (TMCs). Performance measurement requirements were analyzed, data collection and management techniques were investigated, and case study traffic data system improvement plans were prepared for two Caltrans districts.

Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams. FINAL REPORT

Liu, Hao
Xiao, Lin
Kan, Xingan (David)
Shladover, Steven E.
Lu, Xiao-Yun
Wang, Meng
Schakel, Wouter
van Arem, Bart
2018

Freeway capacity and throughput can be significantly improved via CACC vehicle string operations. This research aims to provide authoritative predictions regarding impacts of CACC on traffic flow and quantitative estimations of the influences of CACC operation strategies that might create the capacity and throughput improvement in the freeway traffic stream. To this end, the PATH and Delft team have independently developed micro simulation platforms that represent the behaviors of CACC vehicles and their interactions with human drivers. The models have been calibrated using archived data...

Deep Learning Framework for Vessel Trajectory Prediction using Auxiliary Tasks and Convolutional Networks

Shin, Yuyol
Kim, Namwoo
Lee, Hyeyeong
In, Soh Young
Hansen, Mark
Yoon, Yoonjin
2024

With the exponential growth in vessel traffic and the increasing complexity of maritime operations, there is a pressing need for reliable and efficient methods to forecast vessel movements. The accurate prediction of vessel trajectories plays a pivotal role in various maritime applications, including route planning, collision avoidance, and maritime traffic management. Traditional statistical and machine learning approaches have shown limitations in capturing the complex spatial–temporal patterns of vessel movements. Deep learning techniques have emerged as a promising solution due to...

Regional Ground Delay Program (R-GDP): Extending GDP to Regional Airport Systems

Zhang, Yu
Hansen, Mark
2009

Following the authors’ previous research on real-time intermodalism, this study proposes a Regional Ground Delay Program (Regional GDP) concept into the Collaborative Decision Making (CDM) system when a hub airport located in a regional airport system encounters a severe airside capacity reduction. It suggests air traffic flow managers evaluating not only the imbalance of traffic demand and terminal capacity at this hub airport but also excess capacities at other airports in the same region assuming that airlines could incorporate ground modes into their disruption management and use...

Causal Analysis of Flight en Route Inefficiency

Liu, Yulin
Hansen, Mark
Ball, Michael O.
Lovell, David J.
2021

En route inefficiency is measured in terms of extra distance flown by an aircraft, above a benchmark distance that relates to the theoretical shortest distance route (great circle route). In this paper, we have explored causal relations among en route inefficiency with multiple identified sources: convective weather, wind, miles-in-trail (MIT) restrictions, airspace flow programs (AFPs) and special activity airspace (SAA). We propose two mechanisms – strategic route choice and tactical reroute – to ascribe flight en route inefficiency to these factors. In our framework, we first propose an...

Improvements to Airport Ground Access and Behavior of Multiple Airport System: BART Extension to San Francisco International Airport

Monteiro, Ana Beatriz Figueiredo
Hansen, Mark
1996

Metropolitan regions with more than one major airport—multiple airport systems (MASs)—are important to the U.S. air transport system because of the large number of passengers they serve. Airport ground access factors strongly influence the allocation of traffic in MASs. The effects of improvements to airport ground access (by nonautomobile modes) on airport use in a MAS are analyzed. A case study of an extension of a Bay Area Rapid Transit rail link into the San Francisco International Airport (SFO) is presented. Two airport choice models were developed. One is a nested logit model in...

Scenario-Free Sequential Decision Model for the Single Airport Ground Holding Problem

Liu, Pei-Chen Barry
Hansen, Mark
2007

This paper aims to advance the support of decision-making in air traffic flow management under uncertainty with a focus on the single airport ground holding problem (SAGHP). Learning from the shortcomings of the scenario-based models for SAGHP, which address uncertainty using probabilistic capacity scenarios, the paper develops a sequential decision model that is not limited by a small set of scenarios. The paper presents computational strategies and demonstrates the computational feasibility of the model.

A Comparative Evaluation of Greenhouse Gas Emission Reduction Strategies for the Maritime Shipping and Aviation Sectors

Hansen, Mark
Smirti, Megan
Zou, Bo
2008

The transportation sector is one of the largest sectors contributing to Greenhouse Gas (GHG) emissions, the gases which cause anthropogenic climate change. The aviation and maritime shipping sectors are growing segments of transportation GHG emissions, yet mitigation strategies have largely avoided these sectors. There is a need for clearly defined strategies which can reduce GHG emissions of maritime and aviation operations and for an understanding of the potential magnitude and barriers to reduction. This research presents a framework for GHG emission reduction strategies and evaluates...