The Federal Highway Administration (FHWA) reported between 2016 and 2017, fatal crashes in work zones increased by 3%, while fatal crashes outside of work zones decreased by 1.5%. The FHWA also reported that work zones account for approximately 10% of the nation’s overall congestion and 24% of unexpected interstate delays. This paper reports on a study of 23 construction work zones that covered approximately 150 centerline miles of Indiana interstate roadway in the summer of 2019. Approximately 50% of all interstate crashes for the period of May to September 2019 occurred within or in an approach upstream or downstream of one of these work zones. Commercially available vehicle hard-braking event data is used for the study and geofenced to the work zone approaches and limits. This research examined 196,215 hard-braking events over a 2-month period in the summer of 2019 and 3132 crashes over the same 2-month period in 2018 and 2019 for the 23 interstate work zones. The study found there were approximately 1 crash/mile for every 147 hard-braking events in and around a construction site. The R2 was approximately 0.85. The paper concludes by recommending that hard-braking event data be used by agencies to quickly identify emerging work zone locations that show relatively large number of hard-braking events for further evaluation.
Typical safety improvements at signalized intersections are identified and prioritized using crash data over 3–5 years. Enhanced probe data that provides date, time, heading, and location of hard-braking events has recently become available to agencies. In a typical month, over six million hard-braking events are logged in the state of Indiana. This study compared rear-end crash data over a period of 4.5 years at 8 signalized intersections with weekday hard-braking data from July 2019. Using Spearman’s rank-order correlation, results indicated a strong correlation between hard-braking events and rear-end crashes occurring more than 400 ft upstream of an intersection. The paper concludes that using a month or two of hard-braking events occurring upstream from the stop bar may be a useful tool to screen potential locations with elevated rear-end crashes. Using these techniques described in this paper, new commercially available hard-braking data sources will provide an opportunity for agencies to follow up with mitigation measures addressing emerging problems much quicker than typical practices that rely on 3–5 years of crash data.
High-resolution connected vehicle (CV) trajectory and event data has recently become commercially available. With over 500 billion vehicle position records generated each month in the United States, these data sets provide unique opportunities to build on and expand previous advances on traffic signal performance measures and safety evaluation. This report is a synthesis of research focused on the development of CV-based performance measures. A discussion is provided on data requirements, such as acquisition, storage, and access. Subsequently, techniques to reference vehicle trajectories to relevant roadways and movements are presented. This allows for performance analyses that can range from the movement- to the system-level. A comprehensive suite of methodologies to evaluate signal performance using vehicle trajectories is then provided. Finally, uses of CV hard-braking and hard-acceleration event data to assess safety and driver behavior are discussed. To evaluate scalability and test the proposed techniques, performance measures for over 4,700 traffic signals were estimated using more than 910 million vehicle trajectories and 14 billion GPS points in all 50 states and Washington, D.C. The contents of this report will help the industry transition towards a hybrid blend of detector- and CV-based signal performance measures with rigorously defined performance measures that have been peer-reviewed by both academics and industry leaders.
Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist's assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue trucks present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.
The National Work Zone Safety Information Clearinghouse estimated there were approximately 115,000 work zone crashes with 842 fatalities in 2019. There is broad consensus that it is important for agencies to develop near real-time risk assessment of work zone traffic operations to proactively identify improvement opportunities. Due to the huge spatial distribution and relatively low frequency of crashes, legacy techniques of monitoring crash locations do not scale well for identifying all but the most severe construction zone operational problems. Past research identified hard braking and congestion as strong predictors for crashes in and around work zones. This paper presents scalable methodologies that can be used to systematically analyze hard-braking and speed data obtained from connected vehicles. These techniques have been applied to over 205 billion records in Indiana since 2019. These statewide data analytics are fused into concise graphics to identify work zones with emerging anomalies in congestion and/or hard braking. Weekly screening reports, institutionalized in Indiana for the past two years, provide information for agile agency monitoring and response. Case studies show quantitative changes in work zone performance measures, and corresponding surveillance video images illustrate the significance of these changes. During this period of near real-time monitoring and agile agency response, Indiana interstate crash rates have been reduced by 31% from 2019 to 2021, even though most 2021 interstate traffic volumes have rebounded to pre-pandemic 2019 volumes.
Many public safety agencies in the US have initiated a UAS-based procedure to document and map crash scenes. In addition to significantly reducing the time taken to document evidence as well as ensuring first responder safety, UAS-based mapping reduces incident clearance time and thus the likelihood of a secondary crash occurrence. There is a wide range of cameras used on these missions, but they are predominantly captured by mid-priced drones that cost in the range of $2000 to $4000. Indiana has developed a centralized processing center at Purdue University that has processed 252 crash scenes, mapped using 29 unique cameras, from 35 public agencies over the past three years. This paper includes a detailed case study that compares measurements obtained from a traditional ground-based real-time kinematic positioning base station and UAS-based photogrammetric mapping. The case study showed that UAS derived scale errors were within 0.1 ft (3 cm) of field measurements, a generally accepted threshold for public safety use cases. Further assessment was done on the 252 scenes using ground control scale error as the evaluation metric. To date, over 85% of the measurement errors were found to be within 0.1 ft (3 cm). When substantial errors are identified by the Purdue processing center, they are flagged for further dialog with the agency. In most of the cases with larger errors, the ground control distance was incorrectly measured, which is easily correctable by returning to the scene and performing new distance control measurements.
With an influx of public and private sector investment in the electric vehicle (EV) domain, public agencies and stakeholders need objective, equitable and systematic processes for identifying candidate sites for siting charging stations. This paper reports on a case study examining the Indiana Interstate network using connected vehicle data (CV). The Indiana Interstate network analyzed by this study is composed of 1247 centerline miles along nine routes. Each month, approximately 13 billion CV records representing more than 44 million unique trips are generated along all roads in Indiana. For this study 3.02 billion records comprising 4.78 million trips on and around Indiana Interstates and Exits were analyzed for usage patterns. The CV data was predominantly from internal combustion engine vehicle (ICEV) passenger cars, but provides insight into exit utilization and dwell times at 544 exits on 9 interstate roadways to evaluate how their current usage would align with building out Indiana’s Alternative Fuel Corridors. A pareto sorted graphic for the top 50 busiest exits in the state shows that all but two are not well served by fast charging infrastructure. The paper suggests this pareto sorted list as a good starting point for further analysis and identified 15 exits on Indiana interstates, if chosen for deploying charging infrastructure, would ensure full compliance. The results provide a systemwide look at present dwell patterns among ICEVs and help identify locations of interest that would most benefit from addition of charging infrastructure as the current fleet of ICEVs gradually transitions to EVs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.