Scalable Methods for Monitoring Limited Access Roadways using Crowd-Sourced Probe Data

Commercial crowd-sourced probe vehicle data has been gaining traction in recent years as a ubiquitous and scalable resource for identifying traffic congestion on limited access roadways. It is routinely used in real-time by navigation software that displays color coded maps. However, outside of public agency traffic management centers, there are no factual “big picture” reports on traffic conditions. The media tries to fill this gap, but they either provide descriptions of construction locations, or highly subjective opinions. This paper proposes and illustrates a “big picture” characterization of regional and national traffic conditions using archived and real-time data. Average speeds of vehicles on segments of roadway can be retrieved in near real-time at one-minute intervals to produce performance metrics that measure cumulative miles of congestion per route, per entire Metropolitan Statistical Area (MSA), and on coast-to-coast Interstates using speed profile analysis. Moreover, both real-time and historic archival performance measures can be used for after-action analysis of major traffic events. In this study, the traffic congestion for four MSAs and two Interstates during the week of June 28 to July 6 was used as a case study to illustrate the concepts. The study found most congestion in the Chicago, Los Angeles, and New York City metropolitan areas occurred during the PM rush on July 2 before the holiday weekend, with at least 20% of all limited access roadways in each area falling below 40 mph between the hours of 4:30 PM and 5:45 PM local time. On a coast-to-coast level, Interstate 80 showed the heaviest congestion eastbound at 5:15 PM EDT with 140 combined miles of congestion across 11 states. Data reduction and aggregation methods using 15-minute medians outlined in this study allow future systems to implement regional congestion graphs, speed profile charts, and temporal congestion graphs for operational and practical uses. This information can be leveraged by local, regional, and state transportation agencies as well as for media dissemination and outreach to inform the public

Characterizing Interstate Crash Rates Based on Traffic Congestion Using Probe Vehicle Data

Crash reduction factors are widely used by engineers for prioritizing safety investments. Work zones are routinely analyzed by the length and duration of queues. Queue detection warning technology has been growing in availability and reliability in recent years. However, there is sparse literature on the impact of freeway queueing on crash rates. This paper analyzes three years of crash data and crowdsourced probe vehicle data to classify crashes as being associated with queueing conditions or free flow conditions. In 2014, only 1.2% of the distanced-weighted hours of operation of Indiana interstates operated at or under 45 MPH. A three-year study on Indiana interstates indicates that commercial vehicles were involved in over 87% of back-of-queue fatal crashes compared to 39% of all fatal crashes during free flow conditions. A new measure of crash rate was developed to account for the presence and duration of queues: crashes per mile-hour of congestion. The congested crash rate on all Indiana interstates in 2014 was found to be 24 times greater than the uncongested crash rate. These data were also separated into both rural and urban categories. In rural areas, the congested crash rate is 23 times the uncongested crash rate. In urban areas, the congested crash rate is 21 times the uncongested crash rate. Queues are found to be present for five minutes or longer prior to approximately 90% of congestion crashes in 2014. Longer term, this information shows the importance in the development of technology that can warn motorists of traffic queues

Roadway System Assessment Using Bluetooth-Based Automatic Vehicle Identification Travel Time Data

This monograph is an exposition of several practice-ready methodologies for automatic vehicle identification (AVI) data collection systems. This includes considerations in the physical setup of the collection system as well as the interpretation of the data. An extended discussion is provided, with examples, demonstrating data techniques for converting the raw data into more concise metrics and views. Examples of statistical before-after tests are also provided. A series of case studies were presented that focus on various real-world applications, including the impact of winter weather on freeway operations, the economic benefit of traffic signal retiming, and the estimation of origin-destination matrices from travel time data. The technology used in this report is Bluetooth MAC address matching, but the concepts are extendible to other AVI data sources

A hazard-based analysis of airport security transit times

AbstractAirport security screening, and the amount of time it costs travelers, has been a persistent concern to travelers, airport authorities, and airlines – particularly in recent years where changes in perceived threats have resulted in changes in security procedures that have caused great uncertainty relating to security transit times. To gain a better understanding of the factors influencing travelers' security transit times, determinants of security transit times are studied by using anonymous Bluetooth media access control address matching to determine the actual security travel times of individual passengers at the Cincinnati/Northern Kentucky International Airport. These transit-time data are then analyzed using a random-parameters hazard-based duration model to statistically explore the factors that affect airport security transit times. The estimation results reveal, as expected, that a wide variety of factors affect security transit times including the number of enplaning seats (reflecting flight schedules), weather conditions, day of week, as well as obvious variables such as traveler volume and the number of open security lanes. The detailed statistical findings show that current security procedures are reactive instead of proactive, and that substantial reductions in security transit times could be attained by optimizing security operations using a statistical model such as the one estimated in this paper

Characterizing Interstate Crash Rates Based on Traffic Congestion Using Probe Vehicle Data

Crash reduction factors are widely used by engineers for prioritizing safety investments. Work zones are routinely analyzed by the length and duration of queues. Queue detection warning technology has been growing in availability and reliability in recent years. However, there is sparse literature on the impact of freeway queueing on crash rates. This paper analyzes three years of crash data and crowd-sourced probe vehicle data to classify crashes as being associated with queueing conditions or free flow conditions. In 2014, only 1.2% of the distanced-weighted hours of operation of Indiana interstates operated at or under 45 MPH. A three-year study on Indiana interstates indicates that commercial vehicles were involved in over 87% of back-of-queue fatal crashes compared to 39% of all fatal crashes during free flow conditions. A new measure of crash rate was developed to account for the presence and duration of queues: crashes per mile-hour of congestion. The congested crash rate on all Indiana interstates in 2014 was found to be 24 times greater than the uncongested crash rate. These data were also separated into both rural and urban categories. In rural areas, the congested crash rate is 23 times the uncongested crash rate. In urban areas, the congested crash rate is 21 times the uncongested crash rate. Queues are found to be present for five minutes or longer prior to approximately 90% of congestion crashes in 2014. Longer term, this information shows the importance in the development of technology that can warn motorists of traffic queues

Real-Time Probe Data Dashboards for Interstate Performance Monitoring During Winter Weather and Incidents

The Indiana Department of Transportation (INDOT) manages over 1800 centerline miles of interstate that can be profoundly impacted by weather, crashes, and construction. Real-time performance measurement of interstate speeds is critical for successful traffic operations management. Agency managers and Traffic Management Center decision makers need situational awareness of the network and the ability to identify irregularities at a glance in order to manage resources and respond to media queries. One way to access this level of detail is crowdsourced probe vehicle data. Crowdsourced probe vehicle data can be obtained by collecting speed data from cell phones and global positioning system (GPS) devices. In Indiana, approximately 2673 predefined interstate segments are used to generate over 3.8 million speed records per day. These data can be overwhelming without efficient procedures to reduce and aggregate both spatially and temporally. This paper introduces a spatial and temporal aggregation model and an accompanying real-time dashboard to characterize the current and past congestion history of interstate roadways. The primary high level view of the aggregated data resembles a stock ticker and is called the “Congestion Ticker.” The data archive allows for after-action review of major events such as ice storms, major crashes, and construction work zones. The utility of this application is demonstrated with two case studies: a snowstorm that covered northern and central Indiana in February 2015 and an I-70 back of queue crash in April 2015

Variable Speed Limit Study Upstream of an Indiana Work Zone with Vehicle-Matching

Managing traffic in workzones presents significant mobility and safety challenges for agencies. The goals of a workzone traffic management plan are to safely slow vehicles ahead of the workzone, maintain speeds that provide for the safety of motorists and construction workers, and manage the growth of queues. Variable speed limits have historically been presented as a technology that can dynamically regulate speed in response to prevailing traffic conditions. However, techniques used to evaluate the impact of variable speed limits typically use aggregated statistics such as mean and standard deviation to determine the “typical” speed reduction. This paper presents a new methodology to evaluate the impact of variable speed limit signage based on individual vehicle-matching. The speeds and speed changes of these matched vehicles were used to analyze individual driver response to the variable speed limits. This allows agencies to understand the impact variable speed limit signage has on the distribution of vehicle speeds. It was concluded that vehicles need to observe multiple signs prior to any tangible reduction in speed limit. Placing signs on both shoulders and in multiple longitudinal locations have a greater impact on speeds than a single sign

2011 Indiana Interstate Mobility Report—Summary Version

The 2011 Mobility Report—Summary Version introduces the use of crowd sourced probe data collected from vehicles and mobile devices to quantify the location and duration of congestion on Indiana interstates. The report presents a detailed case study of the I-65 corridor, as well as examples of travel time reliability information for sections of Interstates 65, 70, and 94. Summary monthly mobility statistics for all 943 centerline miles of Indiana Interstates 64, 65, 69, 70, 74, 94, and 465 are tabulated in a graphical format to facilitate comparison of mobility along those corridors

Real-Time Probe Data Dashboard for Monitoring Detour Route during I-65 N Road Closure

On August 7, 2015, a 37 mile stretch of I-65 N from MM 141 to 178 was closed due to a structural evaluation of a bridge. Traffic was detoured onto US-52, SR-26, and US-231 before returning to the highway. In order to monitor delay and congestion on the detour route, a real-time dashboard was implemented in the style of the interstate Traffic Ticker. Throughout the detour, this website was used to monitor congestion in real time and measure the impact of mitigation actions. The improvement in travel can be seen from the addition of temporary signals, retiming of the US-231 corridor, and conversion of US-231 and SR-18 to a two-way stop