Connected Vehicle Infrastructure University Transportation Center

Awarded Projects

Connected Vehicle/Infrastructure University Transportation Center
Project Highlights

V2I (Vehicle to Infrastructure)

Connecting vehicles and infrastructure introduces endless possibilities. When cars and roads can communicate with one another we may no longer need signage along roadways and signalized intersections can alert us to how long before the light changes. Scroll down to learn more about how we are connecting our infrastructure.

Safety and Human Factors of Adaptive Stop/Yield Signs Using Connected Vehicle Infrastructure

Researchers examined how participants responded when stop and yield signs where brought inside vehicle.

Selected Highlights:

  • Participants were generally able to learn how to use the display quickly.
  • A stop made in compliance with the adaptive stop display had a compliance level of 62.11 percent compared to a stop made at a traditional stop sign (12.44 percent compliance).
  • A stop made in compliance with the adaptive stop display had a compliance level of 62.11 percent compared to a stop made at a traditional stop sign (12.44 percent compliance).

Field Testing of Eco-Speed Control Using V2I Communication

Investigators implemented Eco-Cooperative Adaptive Cruise Control (ECACC) which uses SPaT information to assess fuel consumption and eco-friendly driving behaviors.

Selected Highlights:

  • Fuel consumption of vehicles increased as the demand in the network grew with a more drastic increase beyond the peak volume.
  • Savings in fuel consumption were highest at 25 percent and 150 percent of the peak volume, with savings in the 13 to 30 percent range.
  • Analysis of total delay incurred by an average vehicle showed a significant decrease for penetration rates beyond 75 percent.

Infrastructure Safety Assessment Using Connected Vehicle Data

This project analyzed data archived from the connected vehicle test beds to extract “near miss” maneuvers and identify hot spots for further analysis.

Selected Highlights:

  • Utilized naturalistic driving data to classify crash and near-crash events with elements of the Basic Safety Message (BSM).
  • Successfully developed a model to detect crashes and near-crashes and also designed a methodology to apply hot spot identification.
  • Project findings outline an approach to identify crash hotspots utilizing connected vehicle data, once testbed data is widely available.

Infrastructure Pavement Assessment and Management Applications Enabled by the Connected Vehicles Environment Research Program – Phase I: Proof-of-Concept

VT and UVA collaborated to investigate feasibility of using connected vehicles as sensors to assess pavement conditions.

Selected Highlights:

  • Proposed method can correctly identify between 80 and 93 percent of deficient pavement sections.
  • Transportation agencies should consider using this low-cost application for pavement condition network screening to identify locations where repairs are needed.
  • Application can serve as a surrogate pavement roughness assessment method for local transportation agencies.

Develop and Test Connected Vehicle Freeway Speed Harmonization Systems

Researchers developed a speed harmonization application (SPD-HARM) that makes use of the frequently collected and rapidly disseminated multi-source data drawn from connected travelers, roadside sensors, and infrastructure.

Selected Highlights:

  • When the algorithm was applied, the speed of the equipped vehicles decreased gradually to restrict the arrival rates at the downstream bottleneck and mitigate traffic congestion.
  • With increased market penetration rates of the equipped vehicles, the discharge flow rate of the bottleneck was greater, the traffic stream delay was reduced, and vehicle emissions and fuel consumption levels were reduced.

Connected Vehicle Applications for Adaptive Lighting

This project investigated the use of connected vehicles to communicate with the lighting infrastructure to tailor lighting systems to the needs of the environment.

Selected Highlights:

  • Survey results indicate acceptance of the on-demand lighting concept with participants often rating the system to be safe for the speeds they were driving (35 and 55mph).
  • Participants were able to detect pedestrians on the side of the road under the on-demand conditions nearly as well as under the continuous lighting conditions, but the differences were not statistically significant.

Field Demonstration of Cumulative Travel-time Responsive Intersection Control Algorithm under Connected Vehicle Technology

This research project will assess the impacts of the Connected Vehicle technology-enabled traffic signal control with the support of Bluetooth device that collects cumulative travel time data.

Selected Highlights:

  • The cumulative travel-time responsive (CTR) algorithm was enhanced by adopting adaptive Kalman filter (AFK) algorithm that works much better under low market penetration rates of connected vehicles. The AKF seems outperform existing actuated signal control at a lower market penetration rate of 15%.
  • Developed hardware in the loop simulation environment featuring actual controller used in the Northern Virginia, CID, and VISSIM microscopic traffic simulator.
  • A field testing of the Bluetooth readers indicated that the market penetration rate of the Bluetooth devices was much lower than expected — approximately 10% (compared to some literature indicating about 20%). This might lead to significant disadvantage in the field deployment.

Human Factors Evaluation of an In-Vehicle Active Traffic and Demand Management (ATDM) System

This project seeks to determine if in-vehicle signage coupled with ATDM can successfully manage traffic while maintaining a balance between salience and annoyance.

Selected Highlights:

  • None of the in-vehicle alerts were distracting or annoying based on in-vehicle and post-drive survey responses.
  • A vast majority of the participants found the in-vehicle VMS to be clear and concise based on post-drive survey responses (95%).
  • Of the twenty-seven participants who provided price ranges, 48% were willing to pay $100 – $500 for the in-vehicle system.

Connected Vehicle Virginia Test Bed System Performance

This project seeks to verify the functionality of the Connected Vehicle Virginia Test Bed.

Selected Highlights:

  • Evaluated the performance by assessing three standard communication parameters: Packet Error Rate, Latency and Inter-Packet Gap.
  • Associated with several intrinsic and extrinsic factors including heading, speed, ahead, across, range, roundabouts.
  • Initial results indicate that physical obstacles in the roadway may be impacting communication performance between vehicles and RSEs. Such obstacles include overpasses, underpasses, highway barrier walls, and/or tree foliage.

Next Generation Transit Signal Priority with Connected Vehicle Technology

This research will utilize the connected vehicle technology to allow two-way communications among the vehicles, including buses, and infrastructure to develop a next generation Transit Signal Priority (TSP) that does not have to rely on conventional TSP sensors.

Selected Highlights:

  • Field evaluation test confirmed that the transit signal priority (TSP) under connected vehicle technology work as expected.
  • A simulation-based study shows that the TSP under Connected Vehicle significantly improves both bus travel time as well as network delay when compared to Conventional TSP and No TSP cases.
  • TSP under connected vehicle developed in this study can handle multiple buses as well as coordination with adjacent intersections.

V2V (Vehicle to Vehicle)

Connecting vehicles to one another has the potential to alert you of vehicles in blind spots, assist merging onto freeways, or alerting drivers which shoulder to use when an emergency vehicle is approaching. Scroll down to learn more about how we are testing these capabilities.

Connected Vehicle Enabled Freeway Merge Management – Field Test

Researchers tested UVA CTS-developed algorithms on the connected vehicle test bed and refined CTS connected vehicle simulation environment.

Selected Highlights:

  • Based on the compliance data, it is evident that the highest compliance rates are achieved for large and medium gap size scenarios, with no significant difference of compliance rates between these gap sizes.
  • Based on the compliance data, it is evident that the highest compliance rates are achieved for large and medium gap size scenarios, with no significant difference of compliance rates between these gap sizes.
  • Based on the compliance data, it is evident that the highest compliance rates are achieved for large and medium gap size scenarios, with no significant difference of compliance rates between these gap sizes.

Connected Motorcycle Crash Warning Interfaces

Displays that may be be safe for four wheel vehicles may not be the safest option for motorcyclists. This study investigates ernate ways to communicate safety information or warnings to riders.

Selected Highlights:

  • Auditory display using in-helmet headset system was successful in presenting warnings.
  • Riders could easily distinguish between the haptic warnings and handlebar vibration.
  • Visor-mounted LED light strips were level with eyes which make them hard to be ignored.

Measuring User Acceptance of and Willingness to Pay for CVI Technology

This project seeks to identify the relative importance of product attributes, but also the most preferred bundles of attributes, as well as policy suggestions for increasing potential benefits of CVI based on understanding drivers’ preference structures.

Selected Highlights:

  • Results to date indicate that price will be the main factor in deciding to purchase a connected-vehicle technology, and safety benefits are most appealing to drivers.
  • Comparisons of willingness-to-pay with several socioeconomic variables found that drivers between the ages of 40 and 49, African-Americans, those with less than a bachelor’s degree, and a higher budget for vehicle purchase are positively related to willingness-to-pay.
  • Early adopters or innovators of connected-vehicle technologies are willing to pay more for such systems.

Emergency Vehicle-to-Vehicle Communication

Researchers are investigating a V2V application which can help alert vehicles to the presence of an emergency vehicle and with information about the emergency vehicle’s desired maneuvers.

Selected Highlights:

  • Increasing the desired speed of the EV had only small effects on its travel time in a congested network, where the EV’s speed was limited by other vehicles on the road.
  • Based on a field test of a prototype, reaction times to messages were not equal to 2.7 seconds.
  • Numerical case analysis for a small, uniform section of roadway with a limited number of non-EVs revealed our mixed integer non-linear program is capable of optimizing the behavior of non-EVs to maximize the speed of the EV.

Connected Motorcycle System Performance

This proposed research project focuses on characterizing the target classification, positioning, and communications performance of connected vehicle systems on motorcycles.

Selected Highlights:

  • Across the various tests, it was apparent that rider occlusion and ranges impacts communication performance. In situations where the motorcycle has direct line of sight with the vehicle, a noticeable increase in performance is seen.
  • For the dynamic range tests, it was observed that the forward mounted antenna had an overall wider communication range of -300m to +300m in the open sky environment. For the rear mounted antenna, a -300m to +100m in the open sky environment.
  • Having a wider overall communication range allows for effective detection of motorcycles in crash avoidance applications.

Reducing School Bus/Light-Vehicle Conflicts Through Connected Vehicle Communications

This project will develop a ConOps for the connected school bus and prototype in-vehicle display for following vehicles to alert them of a stopped school bus.

Selected Highlights:

  • Initial analysis of results indicate that the “school bus ahead” alert provided by the on-board HMI was effective at providing an enhanced awareness of school bus loading ahead.

V2X (Vehicle to anything else)

Connecting vehicles to external entities can allow drivers to integrate variable message signs into vehicles with their smart phones or warn drivers of a near collision with a construction worker. Scroll down to learn more about how we are testing these capabilities.

Prototyping and Evaluating a Smart Phone Dynamic Message Sign Application in the CVI-UTC Testbed

Researchers investigated the ability to integrate roadway variable message sign information into a smart phone app that read the message to the driver.

Selected Highlights:

  • The developed VDMS application has satisfying technical performance in terms of battery life, latency, and location accuracy.
  • Positive attitude among participants (21 total) towards VDMS in terms of both usefulness and satisfaction.
  • Most participants (80.95 percent) perceived that VDMS is a safer way to receive information; most (66.67 percent) felt more comfortable receiving information from the VDMS compared to a DMS.

Innovative “Intelligent” Awareness System for Roadway Workers Using Dedicated Short-Range Communications

Researchers developed and tested an “intelligent” system of awareness device, InZoneAlert, to be deployed on both vehicles and workers on foot, and evaluated functional effectiveness.

Selected Highlights:

  • Approach enables detection of roadside workers in situations where existing solutions may fail due to visual occlusions or environmental conditions.
  • Experimental results show that the warning system can distinguish between a near miss, complete miss, and collision with a worker with 91% accuracy.
  • Accurate warnings can be provided 5 to 6 seconds before any potential collision, allowing time for mitigating solutions.

Bicycle Naturalistic Data Collection

Researchers designed and implemented a naturalistic experiment to collect and study bicyclist behavior when approaching and crossing intersections in order to utilize CVI technology to mitigate danger factors.

Selected Highlights:

  • A naturalistic cycling data collection system was conducted that can be used to develop bicycle violation prediction models.
  • The system architecture that embodied cyclist violation prediction models was demonstrated. It was shown how connected vehicle technology can be adopted for different parts to communicate amongst themselves.
  • Violation prediction models at stop-controlled intersections were developed. The model accuracy of about 94 percent was obtained when the time to intersection for the cyclist was about 2 seconds.

Applications of Connected Vehicle Infrastructure Technologies to Enhance Transit Service Efficiency and Safety

This project developed an architectural framework for two CVI applications: 1) an application for dynamic demand-response transit (DRT) services and 2) an enhanced traveler safety application that allows individuals to notify a transit vehicle that they are within a specified distance of the vehicle’s current stop location.

Selected Highlights:

  • This project developed a rudimentary architectural framework for two CVI applications which is conceptual and designed to generically map communications and linkages between components that make up the applications.
  • A handheld mobile app for users, a mobile app for transit drivers, and a management server program are being developed, and they are in the final debugging process.
  • An annotated bibliography of resources used for this study was developed.

Vehicle Based BSM Generator for Accelerating Deployment

This research project focuses on development of a BSM generating algorithm implemented to expedite the benefits of connected vehicle systems.

Selected Highlights:

  • The team has developed an algorithm that estimates the velocity and GPS position of radar targets from the perspective of a moving host vehicle.
  • This algorithm was improved upon through iterations of validation with Model Deployment naturalistic driving data.
  • The system can transmit BSMs on behalf of up to 4 non-connected vehicles at one time.

A Connected Vehicle-Enabled Virtual Dynamic Message Sign System Demonstration and Evaluation on the Virginia Connected Vehicle Testbed

This project developed a second-generation VDMS system suitable for demonstration and evaluation on the Northern Virginia Connected Vehicle Test Bed.

Selected Highlights:

  • The VDMS system is intended to be used by TOC operators; therefore, the operational testing of the VDMS system was conducted with actual operators at PSTOC and the results are being analyzed.
  • The goal of this operational testing is to evaluate the VDMS system as a tool to support TOC’s efforts to manage traffic. More specifically, it is to gain feedback from TOC operators on the usability, and the effectiveness of the VDMS system as an information dissemination tool to support advanced traffic management.

Mobile User Interface Development for the Virginia Connected Corridors

This project represents the development effort required to build an initial mobile application featuring driver messaging concepts based on several CVI-UTC research projects as well as applications provided by VDOT that fit within their strategic interests and transportation technology implementation plans.

Selected Highlights:

  • The mobile app interfaces with the cloud computing environment to access a variety of messages that are constantly updated from VDOT Operations computing systems and the 511 Virginia driver information system. Categories of information include:
    • Traffic congestion messages
    • Traffic incident events
    • Special weather events
    • Work Zone information
    • Dynamic message sign content
    • Future additions to be added soon include:
      • ATM information
      • EMS information