Traffic Operations and Management

Predictability of Time-Dependent Traffic Backups and Other Reproducible Traits in Experimental Highway Data

Smilowitz, Karen
Daganzo, Carlos
1999

Traffic data from a 4-mile long congested rural road in Orinda, California, are used to show that traffic delays and vehicle accumulations between any two generic observers located inside a road section can be predicted from the traffic counts measured at the extremes of the section. The traffic model does not require "recalibration" on the day of the experiment, and works well despite what appears to be location-specific driver behavior.

Multi-Sensor Traffic Data Fusion

Kim, ZuWhan
Skabardonis, A.
2003

This report describes unique surveillance system on a section of I-80 freeway in the city of Emeryville. The system, called the Berkeley Highway Laboratory (BHL), consists of eight dual loop detector stations along the freeway section, and 12 video cameras. Advanced machine vision algorithms were developed to process the video data to generate vehicle trajectories. Efforts are underway to fuse the loop and video detector data to obtain detailed and accurate information on traffic operating conditions

The Spatial Evolution of Traffic Under the Two Wave Speed Assumption: A Shortcut Procedure and Some Observations

Daganzo, Carlos F.
1993

This paper describes the behavior of traffic in a homogeneous highway according to the hydrodynamic theory, in the special casewhere the flow-density relationship is triangular; i.e. when only two wave velocities exist. It presents an exact formula thatpredicts the vehicle that would be found at position x at time t, given the locations of all the vehicles at time zero. The formula, which does not require identification of the vehicle positions at intermediate times, automatically accounts for the creation and dissipation of any shocks. It can be used to calculate system performance...

DYN-OPT Users Manual

Caliskan, C.
Hall, R.W.
1997

This document is a users manual for DYN-OPT, a linear program that optimally and dynamically assigns traffic to lanes on an automated highway. The program maximizes the total flow across the highway over a pre-specified length of time. DYN-OPT solves a path-based formulation in which the highway is represented by discrete segments, time is divided into periods and traffic between origins and destinations follows a user- specified distribution.

Event-based ATIS: Practical Implementation and Evaluation of Optimized Strategies (Part I)

Jayakrishnan, R.
Tsai, Wei K.
Oh, Jun-Seok
Adler, Jeffrey
1999

This project will further adapt and enhance the previous research of relevance to event-based Advanced Traveler Information Systems (ATIS) and implement the algorithms for traffic management in Anaheim. The implementation involves the Caltrans-UCI ATMS research testbed framework at the UCI Institute of Transportation Studies, as well as the physical hardware available for communication to the city of Anaheim. The analytical algorithms proposed for use here include those for static and dynamic traffic assignment. and the modeling schemes used are the result of previous PATH and Testbed...

Not So Fast: A Study of Traffic Delays, Access, and Economic Activity in the San Francisco Bay Area

Taylor, Brian
Osman, Taner
Thomas, Trevor
Mondschein, Andrew
2016

The San Francisco Bay Area regularly experiences some of the most severe traffic congestion in the U.S. This past year both Inrix and the Texas Transportation Institute (TTI) ranked the Bay Area third only to Washington D.C. and Los Angeles in the time drivers spend stuck in traffic. The TTI estimated that traffic congestion cost the Bay Area economy a staggering $3.1 billion in 2014 (Lomax et al., 2015). Such estimates are based on the premise that moving more slowly than free-flow speeds wastes time and fuel, and that these time and fuel costs multiplied over millions of travelers in...

Experimental Studies for Traffic Incident Management

Brownstone, David
McBride, Michael
Kong, Si-Yuan
Mahmassani, Amine
2017

This report documents the second year of a project using economics experimental techniques to investigate novel approaches for mitigating congestion caused by non-recurring traffic incidents. The first year demonstrated the feasibility of this approach and carried out a number of experiments using University of California, Irvine (UCI) undergraduates as experimental subjects. The experimental platform is described in Section 3 of this report. Most of the experiments conducted during the first year examined different variable message sign (VMS) wording, and later experiments examined...

Sustainable Operation of Arterial Networks

Kalathil, Dileep
Kurzhanskiy, Alex A.
Varaiya, Pravin
2017

This report describes operational data analysis and modeling of arterial networks with signalized intersections as follows: The setup for data collection, analysis and simulation is presented in Section 2.1. Detailed analysis of collected signal phasing and traffic data is provided in section 2.2. Arterial traffic and platoon modeling is described in Section 2.3. Simulation results of the Rollins Park network is discussed in Section 2.4. Research conducted under this task is an important stepping stone for building a three-level information and control system for urban networks with high-...

Control Strategies for Corridor Management

Amiri, Zahra
Lo, Yu-Chieh
Skabardonis, Alexander
Varaiya, Pravin
2016

Integrated management of travel corridors comprising of freeways and adjacent arterial streets can potentially improve the performance of the highway facilities. However, several research gaps exist in data collection and performance measurement, analysis tools and control strategies. In this project first we analyzed high resolution data consisting of time-stamped records of every event involving vehicles, together with the signal phase at real-world signalized intersections and developed procedures for estimating performance measures. Next, we assessed the performance of a new...

Traffic Predictive Control: Case Study and Evaluation

Coogan, Samuel
Dutreix, Maxence
2017

This project developed a quantile regression method for predicting future traffic flow at a signalized intersection by combining both historical and real-time data. The algorithm exploits nonlinear correlations in historical measurements and efficiently solves a quantile loss optimization problem using the Alternating Direction Method of Multipliers (ADMM). The resulting parameter vectors allow determining a probability distribution of upcoming traffic flow. These predictions establish an efficient, delay-minimizing control policy for the intersection. The approach is demonstrated on a...