Cross-cutting Issues

The primary objective of this paper is to study and analyze the temporal characteristics of

traffic congestions and the associated speed distributions for congested expressways based on

the Floating Car Data (FCD) in Beijing. First, the temporal distributions of congestions with

different intensities are analyzed using the FCD of 5 workdays for a particular expressway

Link N26376. Results show that the longer the continuous congestion lasts, the lower the

speed distribution interval is. Then, the distribution curve is fitted, which finds that the

Log-Logistic model can well describe the survival function distribution of the severe

congestion durations for morning peak-hours of Tuesday. By comparison, it is found that the

duration distribution value of severe congestions at the aggregation interval of 2-minute is

lower than that at the 5-minute interval, and the duration distribution value of severe

congestions on Link N26376 is higher than that on its downstream Links N24162 and N23971.

Finally, the speed distributions in two proposed categories of congestion periods are analyzed

and compared. Results show that if the speed in the present time period falls in a higher

distribution interval, then the probability that the severe congestion will dissipate in the next

time period will be higher.

School of Traffic and Transportation, Beijing Jiaotong University

Texas Southern University

Beijing Transportation Research Center

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

Wireless communication between vehicles and the transportation infrastructure will provide

significantly more timely and comprehensive information about arterials and their performance.

However, most measures-of-effectiveness were developed based on data available from

traditional “point” sensors. The information made available in a connected vehicle environment

requires new metrics that can fully utilize the data. This paper identifies several new arterial

performance metrics made available in a connected vehicle environment, as well as several

existing metrics that can be evaluated more accurately and frequently than before. The new

metrics are person-delay, sudden deceleration, change in lateral acceleration, and aggregate

regulation compliance. Person-delay measures a vehicle’s lost time multiplied by the number of

passengers, and allows for more efficient movement of high-occupancy vehicles and

sophisticated transit signal priority. Sudden deceleration and change in lateral acceleration

measure activities such as unexpected braking and swerving, which may be leading indicators of

unsafe conditions. Aggregate regulation compliance detects unsafe driving behavior that is

difficult to collect in the field, such as speeding and illegal U-turns. Engineers can address

problem areas through signal timing changes traffic calming, and other measures. The proposed

metrics all require high-resolution detection, and are difficult or impossible to measure with

existing point detection. For each new metric, its compatibility with connected vehicles is

discussed, and required SAE J2735 DSRC Message Set Dictionary data elements are identified.

Virginia Center for Transportation Innovation and Research, Virginia DOT

University of Virginia

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

Weigh-in-motion (WIM) systems have been in use for several years, and the technology and accuracy have steadily improved. This paper describes the design, testing, and implementation of the first five Illinois State Toll Highway Authority (Tollway) WIM stations. Tollway applications employ a special configuration for enforcement by the Illinois State Police (ISP) in a way not typically implemented elsewhere, instantaneously identifying the type of apparent violation and displaying that to an ISP vehicle. WIM has proved to be valuable as an enforcement and engineering tool, since detailed vehicle statistics are automatically generated. The technology is important in helping limit damage that overweight trucks do to core infrastructure. The first few WIM stations have payback periods of one to two years, hence the agency expects to deploy about another seven WIM stations in the next few years. The paper addresses performance, adjustments needed, typical reports, and “lessons learned.” The need for proactive maintenance to assure a high level of performance in particular is highlighted.

Authors: John Benda, Jim Powell, Bill Hereth

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

The I-95 Vehicle Probe project (VPP) has been in production since July 2008 providing estimates of speed and travel time on network of roadways that has expanded to over 5,000 freeway miles. Each estimate of speed is accompanied by two metrics that provide an indication of the level of confidence and/or quality of the traffic data: Score and C-value. This paper statistically characterizes the distribution of Score and C-Value in the VPP data archive in order to better understand the quality of the VPP and reveal any improvements over the life of the project.  Both Score and C-Value are tested to determine their effectiveness as a data filter to improve real-time traffic data quality.

Authors: Stanley E. Young, P.E., Ph.D., Nayel Urena Serulle

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

The Vehicle Probe Project (VPP) is an outsourced traffic monitoring system established by the I-95 Corridor Coalition and has been active since July 2008. By contractual agreement with the vendor, INRIX Corporation, travel time and speed data are provided to minimum quality specifications whenever traffic flow exceeds 500 vehicles per hour (vph). The monthly validation program has confirmed the quality of the data by comparing VPP data against travel times collected using BluetoothTM traffic monitoring equipment, but typically during high volume periods when congestion is likely. Validation has not been confirmed for minimum flow conditions (less than 500 vph) due in part to lack of accurate volume data as well as the low probability of observing traffic congestion at low volumes. The VPP provides an indication of real-time data by the score attribute. When score is equal to 30, the traffic data is based on real-time information. A score less than 30 indicates reliance on historical data. Studies have shown that traffic data based primarily on historical data do not meet minimum quality specifications during moderate and severe congestion. By using volume data from the Maryland State Highway Administration and the Delaware Department of Transportation from permanent count locations, the likelihood of acquiring real-time data (as evidenced by score equal 30) as a function of hourly volume is established.

Authors: Hadi Sadrasadat, Ph.D., Stanley Ernest Young Ph.D.

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida