Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC)

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Safety, Operational, and Energy Impacts of In-vehicle Adaptive Stop Displays Using Connected Vehicle Technology
Noble, Alexandria M. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2015-07-30)
Un-signalized intersections create multiple opportunities for missed or misunderstood information. Stop sign-controlled intersections have also been shown to be a source of delay and emissions due to their frequent, often inappropriate use. By using connected vehicle technology, it is possible to place electronic stop signs at more conspicuous locations that can communicate with the in-vehicle systems. Then, if a conflict is imminent at an intersection, the vehicle’s system alerts the driver, thus reducing the probability of missed information, as well as decreasing the amount of unnecessary delay, fuel consumption, and emissions by only prompting a stop when a conflict is present. Before implementing any new technology, it is important to assess it from both a transportation engineering and human factors standpoint to determine the value of such a system. The objective of this study was to assess perceived benefits of an adaptive in-vehicle stop display and to determine if there were any negative safety implications with the use of this system. This was accomplished through a test track experiment with 49 participants. These drivers were presented with a standard R1-1 stop sign on the in-vehicle display, as well as an experimental sign, which informed them to proceed through the intersection with caution. Results indicate the implementation of this technology reduces delay, decreases fuel consumption, and does not instigate any safety decrements.
Infrastructure Pavement Assessment & Management Applications Enabled by the Connected Vehicles Environment – Proof-of-Concept
Flintsch, Gerardo W.; Smith, Brian L. (Research and Innovative Technology Administration, 2015-09-30)
The objective of this project was to develop prototypes and conduct a field test of system level applications of a connected vehicle pavement condition measurement system. This allowed the research team to: (1) investigate different approaches to a connected vehicle pavement measurement system; and (2) determine the optimum procedures for collecting, processing, aggregating, and storing the data to support engineering and management decisions. The study found that roughness measures obtained from probe vehicles are comparable to roughness measures obtained from the profile, when the appropriate parameters that affect roughness were taken into account. A sensitivity analysis suggested that data sampling and quarter-car parameters were the most critical parameters. Finally, the results of the network-level simulations showed that the probe vehicle vertical acceleration measurements (collected from a mobile smart phone application) have the potential to be used for network-level prescreening of deficient pavement sections.
An Innovative Intelligent Awareness System for Roadway Workers Using Dedicated Short-Range Communications
Bowman, Darrell Scott; Martin, Tom L. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2015-10-15)
Roadside workers and emergency responders, such as police and emergency medical technicians, are at significant risk of being struck by vehicular traffic while performing their duties. While recent work has examined active and passive systems to reduce pedestrian collisions, current approaches require line of sight using either laser-, infrared-, or vision-based systems. We addressed this problem by developing a Global Positioning System (GPS)-based solution that equips roadside workers and vehicles with GPS units to estimate the trajectory of oncoming traffic, and to estimate whether worker strike is imminent. The results of our study show that our approach is 91% accurate in alerting the worker and vehicle of collisions and near misses. Furthermore, accurate warnings can be provided 5 to 6 seconds before any potential collision, allowing time for mitigating solutions.
Infrastructure Safety Assessment in a Connected Vehicle Environment
Smith, Brian L.; Kluger, Robert; Park, Hyungjun (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2015-12-15)
The goal of the Infrastructure Safety Assessment in a Connected Vehicle (CV) Environment project was to develop a method to identify infrastructure safety “hot spots” using CV data. Using these basic safety messages to detect hot spots may allow for quicker discovery than traditional methods, such as police-reported crashes. The basic safety message may be able to detect events that police normally cannot obtain, including unreported crashes and near-crashes. The project successfully explored some models and algorithms to detect crashes and near-crashes and also designed a methodology to apply to hot spot identification. With the data available, conclusive results were not achieved; however, the models showed some potential. Three techniques were tested to predict crashes using vehicles’ kinematic data. To predict where a crash was occurring, multivariate adaptive regression splines, classification and regression trees, and a novel pattern matching approach were all tested. The models were able to identify the majority of 13 known crashes with different amounts of false positives. The pattern matching approach outperformed a simple acceleration threshold by identifying nearly 70% of crashes in a crash- only test set and 74% of near-crashes in a near-crash only test set. On the training set, it was able to identify more crashes than the thresholds without increasing the number of false positives observed. Based on the work described in this report, the CVI-UTC is fully prepared to apply the methodology to data collected on the field test bed.
Prototyping and Evaluating a Smartphone Dynamic Message Sign (DMS) Application
Smith, Brian L.; Ma, Jiaqi; Park, Hyungjun (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2015-12-15)
Traveler Information Systems are designed and operated by transportation agencies to provide travelers with real-time traffic information, enabling them to make better travel decisions. One of the most commonly used ways to provide real-time, en route traveler information to motorists is through Dynamic Message Signs (DMSs). Despite their effectiveness, they are costly and limited in terms of the amount of information they can deliver. The wide availability of smart mobile devices can provide traveler information through in-vehicle devices (without incurring huge infrastructure costs) and (in a more flexible manner) to selected individuals and locations without geographical constraints. Research was conducted to comprehensively develop and evaluate this concept and a summary of tasks and findings is presented below. First, this research proposed the concept of a Virtual Dynamic Message Sign (VDMS) system utilizing a smartphone-based application to demonstrate and summarize user experience for future deployment. The user survey revealed a positive attitude among participants toward a VDMS system in terms of both usefulness and satisfaction; the average ratings were −0.90 and −0.81 respectively on a −2 to 2 (Totally agree to Totally disagree) five-point Likert scale. The survey also indicated that most drivers (81.0%) perceived VDMS as a safer way to receive information. Many drivers (66.7%) also felt more comfortable receiving an audible message from a VDMS system rather than a text message on a DMS. The results indicate great user acceptability and the potential for such systems to be deployed by public agencies in the future. This research also aimed to address the question of whether a VDMS conveys information at least as effectively as existing DMSs. A mixed, repeated-measure experiment was designed using a driver simulator to examine (1) the impacts of driver age, (2) information transmission mode, (3) amount of information, and (4) driving complexity on message comprehension, distraction, and perceived difficulty. Forty-two people were recruited and each of them participated in a test under different combinations. Participant performance was measured in terms of message comprehension, distraction, and self-reported message difficulty level. Results revealed that VDMS generally performs better than DMS across different amounts of information, under different driving conditions, and regardless of driver age. VDMS proved significantly better than DMS in message comprehension under relatively complex conditions. It reduced reaction time to unexpected stimuli (as measured with a reduced time-to-brake of 0.39 seconds), and made the same messages easier to process and retain for drivers than DMS. Based on these results, it is recommended that transportation agencies give careful consideration to VDMS as a future strategy for delivering public traffic information in a connected vehicle environment.
Connected Vehicle Enabled Freeway Merge Management – Field Test
Smith, Brian L.; Park, Hyungjun; Hayat, Md Tanveer (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-01-01)
Freeway congestion is a major problem of the transportation system, resulting in major economic loss in terms of traffic delays and fuel costs. With connected vehicle (CV) technologies, more proactive traffic management strategies are possible. The Freeway Merge Assistance System (FMAS) can implement innovative ramp management strategies by providing personalized advisories to individual drivers to ensure smoother merging. The benefits anticipated from these strategies will completely depend on the advisory compliance of the drivers; this, in turn, will be influenced by situational as well as individual behavioral factors. The purpose of this research was to investigate drivers’ responses to this new generation of personalized in-vehicle advisory messages. A field test was conducted with naïve human subjects to collect driver behavior data about different types of advisory messages under different traffic scenarios in a controlled environment. The data gathered from the field test indicated that the compliance rate was higher when a large- or medium-size gap was available for a lane change. The lowest compliance rate was observed for a small-gap scenario. In addition, it was discovered that more drivers would follow a direct advisory message that advised a lane change rather than an indirect message which was meant to stimulate a lane change through speed control.
Connected Motorcycle Crash Warning Interfaces
Song, Miao; McLaughlin, Shane B.; Doerzaph, Zachary R. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-01-15)
Crash warning systems have been deployed in the high-end vehicle market segment for some time and are trickling down to additional motor vehicle industry segments each year. The motorcycle segment, however, has no deployed crash warning system to date. With the active development of next generation crash warning systems based on connected vehicle technologies, this study explored possible interface designs for motorcycle crash warning systems and evaluated their rider acceptance and effectiveness in a connected vehicle context. Four prototype warning interface displays covering three warning mode alternatives (auditory, visual, and haptic) were designed and developed for motorcycles. They were tested on-road with three connected vehicle safety applications - intersection movement assist, forward collision warning, and lane departure warning - which were selected according to the most impactful crash types identified for motorcycles. It showed that a combination of warning modalities was preferred to a single display by 87.2% of participants and combined auditory and haptic displays showed considerable promise for implementation. Auditory display is easily implemented given the adoption rate of in-helmet auditory systems. Its weakness of presenting directional information in this study may be remedied by using simple speech or with the help of haptic design, which performed well at providing such information and was also found to be attractive to riders. The findings revealed both opportunities and challenges of visual displays for motorcycle crash warning systems. More importantly, differences among riders of three major motorcycle types (cruiser, sport, and touring) in terms of riders’ acceptance of a crash warning interface were revealed. Based on the results, recommendations were provided for an appropriate crash warning interface design for motorcycles and riders in a connected vehicle environment.
Connected Motorcycle System Performance
Viray, Reginald; Noble, Alexandria M.; Doerzaph, Zachary R.; McLaughlin, Shane B. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-01-15)
This project characterized the performance of Connected Vehicle Systems (CVS) on motorcycles based on two key components: global positioning and wireless communication systems. Considering that Global Positioning System (GPS) and 5.9 GHz Dedicated Short-Range Communications (DSRC) may be affected by motorcycle rider occlusion, antenna mounting configurations were investigated. In order to assess the performance of these systems, the Virginia Tech Transportation Institute’s (VTTI) Data Acquisition System (DAS) was utilized to record key GPS and DSRC variables from the vehicle’s CVS Vehicle Awareness Device (VAD). In this project, a total of four vehicles were used where one motorcycle had a forward mounted antenna, another motorcycle had a rear mounted antenna, and two automobiles had centermounted antennas. These instrumented vehicles were then subject to several static and dynamic test scenarios on closed test track and public roadways to characterize performance against each other. Further, these test scenarios took into account motorcycle rider occlusion, relative ranges, and diverse topographical roadway environments. From the results, both rider occlusion and approach ranges were shown to have an impact on communications performance. In situations where the antenna on the motorcycle had direct lineof-sight with another vehicle’s antenna, a noticeable increase in performance can be seen in comparison to situations where the line of sight is occluded. Further, the forward-mounted antenna configuration provided a wider span of communication ranges in open-sky. In comparison, the rear-mounted antenna configuration experienced a narrower communication range. In terms of position performance, environments where objects occluded the sky, such as deep urban and mountain regions, relatively degraded performance when compared to open sky environments were observed.
Next Generation Transit Signal Priority with Connected Vehicle Technology
Hu, Jia; Lee, Young-Jae; Park, Byungkyu Brian; Dadvar, Seyedehsan (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-01-30)
This project utilized connected vehicle (CV) technology allowing two-way communication among vehicles and infrastructure to develop a next-generation Transit Signal Priority (TSP) system that does not have to rely on conventional TSP sensors. The research team extended a previously proposed TSP system based on CV technology (TSPCV) to handle conflicting requests and to coordinate passage between intersections in a travel corridor. The proposed TSP mechanisms minimize installation and maintenance costs by eliminating the need for local agencies to perform a level of service (LOS) study and/or volume/capacity (v/c) ratio for potential TSP intersections before installation. Simulation-based evaluation results showed that, compared to conventional TSP mechanisms, the proposed TSP logic reduces bus delays between 5% and 48% (TSPCVM) and decreases the delay of a bus progressing along a corridor between 35% and 68% (TSPCV-C). The range of improvement corresponds to the four different v/c ratios tested, which were 0.5, 0.7, 0.9 and 1.0. In most cases, the proposed TSP logic caused no negative effects. A field experiment conducted on the Connected Vehicle test bed on the Virginia Smart Road, located at the Virginia Tech Transportation Institute (VTTI) in Blacksburg, Virginia, validated the performance of the proposed TSPCV system. The TSPCV algorithm provided green traffic signal timing to buses with different arrival times with a 100% success rate. It also reduced delays for a bus with a speed of 45 mph and a traffic signal with a 90-second cycle length and 30 seconds of green time by as much as between 32% and 75%. Moreover, the field experiment showed that two Global Positioning System (GPS) devices (regular and differential) performed almost identically and, in an aggregate sense, the difference in their performance was not statistically significant. This finding facilitates the large-scale implementation of TSP, since regular GPS devices are much cheaper than differential GPS devices and operated just as well for TSPCV.
Human Factors Evaluation of an In-Vehicle Active Traffic and Demand Management (ATDM) System
Sykes, Kayla (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-02-15)
This research study focused on the development and subsequent evaluation of an in-vehicle Active Traffic and Demand Management (ATDM) system deployed on Interstate 66 in Northern Virginia. The ATDM elements inside the vehicle allowed drivers to remain consistently aware of traffic conditions and roadway requirements even if external signage was inaccessible. Forty participants were accompanied by a member of the research team and experienced the following in-vehicle device (IVD) features: 1) dynamic speed limits, 2) dynamic lane use/shoulder control, 3) High Occupancy Vehicle (HOV) restrictions, and 4) variable message signs (VMS). This ATDM system was equipped with auditory and visual alerts to notify the driver when relevant information was updated. The research questions addressed distraction, desirability, and driver behavior associated with the system. Participant data was collected from the instrumented vehicle, various surveys, and researcher observation. Several key findings were uncovered related to each research category: 1) the IVD would not be classified as a distraction according to the National Highway Traffic Safety Association (NHTSA) distraction guidelines, 2) 73% of participants would want the in-vehicle technology in their next vehicle, and 3) the speed limit alert motivated participants to alter their speed (based on both survey results and actual participant speed data).
Connected Vehicle Freeway Speed Harmonization Systems
Rakha, Hesham A.; Yang, Hao (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-03-15)
The capacity drop phenomenon, which reduces the maximum bottleneck discharge rate following the onset of congestion, is a critical restriction in transportation networks that causes additional traffic congestion. Consequently, preventing or reducing the occurrence of the capacity drop not only mitigates traffic congestion, but can also produce environmental and traffic safety benefits. To address this issue, this project developed and evaluated a speed harmonization (SH) algorithm based on a bi-level feedback control system with the assistance of vehicle-to-infrastructure (V2I) communications. The algorithm computes advisory speed limits for individual vehicles to prevent the breakdown of downstream bottleneck discharge by regulating traffic flow approaching the bottleneck, which in turn reduces traffic stream delay, emissions and fuel consumption levels. To assess the benefits of the algorithm, a section of Interstate 66 in Northern Virginia was simulated with the INTEGRATION microscopic traffic simulation model, and five trailers were installed on the road to collect real-time traffic data for each vehicle equipped with V2I communications to implement the SH algorithm. The simulations demonstrated that the algorithm significantly mitigated road congestion when a capacity drop occurred at a bottleneck. Also, the study results showed that higher market penetration rates (MPRs) of vehicles equipped with the SH algorithm led to higher SH algorithm benefits. In particular, at 100% MPR, the bottleneck discharge flow rate increased by up to 1.5%, and the vehicular delay decreased by about 22%. Moreover, with the SH algorithm, CO2 and fuel consumption levels were reduced by up to 3.5%. A 100% MPR is the best-case scenario. However, the results also demonstrated that an MPR of even 10% is sufficient to produce overall emission and fuel consumption savings.
A Connected Vehicle–Enabled Virtual Dynamic Message Sign System Demonstration and Evaluation on the Virginia Connected Vehicle Test Bed
Park, Hyungjun; Babiceanu, Simona; Kluger, Robert; Smith, Brian L.; Recht, David (Connected Vehicle/Infrastructure University Transportation Center, 2016-03-15)
Dynamic message signs (DMSs) are widely used to deliver traveler information. While these have proven to be effective, key limitations exist: (1) the locations of DMSs are fixed, (2) reading a DMS message is distracting to drivers, and (3) installation and maintenance of DMSs is expensive. To address these limitations, a smartphone-based virtual DMS (VDMS) application was developed in the first round of Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC) projects. This application used smartphones to provide audible “reading” of DMS messages to drivers. This project built upon previous work to develop a more advanced, second generation of the VDMS system, that is fully integrated in the Dedicated Short Range Communications (DSRC) environment of the Virginia Connected Vehicle Test Bed. The highlights of the enhanced VDMS system include (1) use of four of 40+ DSRC-based roadside equipment units (RSEs) on the Virginia Connected Vehicle Test Bed, and (2) software (VDMS Manager) that has the capability to virtually “build” new DMSs and to create modified and new messages for those DMSs. To evaluate the VDMS system as an information dissemination tool to support advanced traffic management, operational testing (including three surveys, entrance, post-incident, and exit) was carried out with actual operators at the McConnell Public Safety and Traffic Operations Center. It was observed that operators preferred the VDMS system due to its capability of providing more detailed and customized messages at more appropriate locations for motorists.
Field Implementation Feasibility Study of Cumulative Travel-Time Responsive Intersection Control Algorithm under Connected Vehicle Technology
Choi, Saerona; Park, Byungkyu Brian; Lee, Joyoung (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-03-31)
This project utilized the Connected Vehicle (CV) environment, which provides two-way wireless communications between vehicles and infrastructure, to (1) improve the Cumulative Travel-time Responsive (CTR) Intersection Control Algorithm under low CV market penetration by utilizing Bluetooth technology, and (2) assess potential benefits of the CTR algorithm by examining mobility, energy, and greenhouse emissions measures. The project team developed and evaluated a hardware-in-the-loop simulation to ensure that the developed CTR algorithm will work with an existing traffic controller on the Northern Virginia Connected Vehicle Test Bed. The team enhanced the CTR algorithm and evaluated its impact to verify the feasibility of field implementation. Two prediction techniques, a standard Kalman filter (SKF) and an adaptive Kalman filter (AKF), were applied to estimate cumulative travel time for each phase in the CTR algorithm. In addition, traffic demand, the market penetration rate (MPR), and the types of available data were also considered in evaluating CTR algorithm performance. The Lee Highway and Nutley Street intersection on the Northern Virginia Connected Vehicle Test Bed was selected for a case study and simulated within VISSIM. The results showed that the CTR algorithm’s performance depends on the MPR, as the information collected from CVs is a key CTR algorithm-enabling factor. However, this study found that the MPR could be relaxed (1) when the data were collected from both CV and infrastructure sensors, and (2) when an AKF was adopted in the CTR algorithm. The minimum MPRs required to outperform the current actuated traffic signal control were empirically found for each prediction technique and types of available data—data from both Connected Vehicle and infrastructure sensors, or Connected Vehicle’s data only. Even without the infrastructure sensors, the CTR algorithm could be considered for implementation at an intersection with high traffic demand and a 50% to 60% MPR. As the MPR for this field evaluation was around 14%, much lower than the minimum 20% required with an AKF incorporated, the project team could not implement the proposed algorithm. Instead, the team developed an implementation plan that can be easily adopted by traffic engineers once the MPR reaches 20% or higher.
Field Testing of Eco-Speed Control Using V2I Communication
Rakha, Hesham A.; Chen, Hao; Almannaa, Mohammed Hamad; Kamalanathsharma, Raj Kishore; El-Shawarby, Ihab; Loulizi, Amara (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-04-15)
This research focused on the development of an Eco-Cooperative Adaptive Cruise Control (Eco-CACC) System and addressed the implementation issues associated with applying it in the field. The Eco-CACC system computes and recommends a fuel-efficient speed based on Signal Phasing and Timing (SPaT) data received from the traffic signal controller via vehicle-to-infrastructure (V2I) communication. The computed speed profile can either be broadcast as an audio alert to the driver to manually control the vehicle, or, implemented in an automated vehicle (AV) to automatically control the vehicle. The proposed system addresses all possible scenarios, algorithmically, that a driver may encounter when approaching a signalized intersection. Additionally, from an implementation standpoint, the research addresses the challenges associated with communication latency, data errors, real-time computation, and ride smoothness. The system was tested on the Virginia Smart Road Connected Vehicle Test Bed in Blacksburg, VA. Four scenarios were tested for each participant: a base driving scenario, where no speed profile data was communicated; a scenario in which the driver was provided with a “time to red light” countdown; a manual Eco-CACC scenario where the driver was instructed to follow a recommended speed profile given via audio alert; and finally, an automated Eco-CACC scenario where the AV system controlled the vehicle’s longitudinal motion. The field test included 32 participants, and each participant completed 64 trips to pass through a signalized intersection for different combinations of signal timing and road grades. The analyzed results demonstrate the benefits of the Eco-CACC system in assisting vehicles to drive smoothly in the vicinity of intersections, thereby reducing fuel consumption levels and travel times. Compared to an uninformed baseline drive, the longitudinally automated Eco-CACC system controlled vehicle drive resulted in savings in fuel consumption levels and travel times of approximately 37.8% and 9.3%, respectively.
Virginia Connected Vehicle Test Bed System Performance (V2I System Performance)
Viray, Reginald; Sarkar, Abhijit; Doerzaph, Zachary R. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-05-01)
This project identified vehicle-to-infrastructure (V2I) communication system limitations on the Northern Virginia Connected Vehicle Test Bed. Real-world historical data were analyzed to determine wireless Dedicated Short Range Communication (DSRC) coverage gaps and overlaps. In addition, a simulated scalability test was run to determine the effects of network congestion on the system. The results from the real-world historical data showed that significant loss of signal occurred due to obstructions commonly found in complex highway systems, including overpasses and underpasses, elevated concrete roadways, and foliage. Consequently, care must be taken to minimize loss of signal when selecting an installation site for roadside equipment (RSEs). The deployment of multiple RSEs or repeaters may be necessary to maximize coverage in localized dead zones. The results from the scalability test showed that the current network architecture is not able to handle a large deployment of connected vehicles (CV). If a large scale of CV were to be deployed, an assessment of the current network design needs to be investigated to account for the number of vehicles and subsequent flow of data expected in the operational area.
Bicycle Naturalistic Data Collection
Elhenawy, Mohammed; Jahangiri, Arash; Rakha, Hesham A. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-06-15)
Recently, bicycling has drawn more attention as a sustainable and eco-friendly mode of transportation. Between 2000 and 2011, bicycle commuting rates in the United States rose by 80% in large bicycle friendly cities (BFCs), by 32% in non-BFCs, and overall by 47%. On the other hand, about 700 cyclists are killed and nearly 50,000 are injured annually in bicycle–motor vehicle crashes in recent years in the United States. More than 30% of cyclist fatalities in the United States from 2008 to 2012 occurred at intersections, and up to 16% of bicycle-related crashes were due to cyclists’ violations at intersections. In light of these statistics, this project focused on investigating factors that affect cyclist behavior and predicting cyclist violations at intersections. Naturalistic cycling data were used to assess the feasibility of developing cyclist violation prediction models. Mixed-effects generalized regression model is used to analyze the data and identify the significant factor affecting the probability of violations by cyclists. At signalized intersections, right turn, side traffic and opposing traffic are statistically significant factors affecting the probability of red light violation. At stop-controlled intersections, the presence of other road users, left turn, right turn and warm weather are statistically significant factors affecting the probability of violations. Violation prediction models were developed for stop-controlled intersections based on kinetic data measured as cyclists approached the intersection. Prediction error rates were 0% to 10%, depending on how far from the intersection the prediction task was conducted. An error rate of 6% was obtained when the violating cyclist was at a time-to-intersection of about 2 seconds, which is sufficient for most motor vehicle drivers to respond.
Connected Vehicle Applications for Adaptive Overhead Lighting (On-demand Lighting)
Gibbons, Ronald B.; Palmer, Matthew; Jahangiri, Arash (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-07-01)
The Virginia Tech Transportation Institute (VTTI) has developed an on-demand roadway lighting system and has tested the system’s effect on driver visual performance. On-demand roadway lighting can dramatically reduce energy usage while maintaining or increasing vehicle and pedestrian safety. The system developed by VTTI uses connected vehicle technology (CVT), wireless lighting controls, LED luminaires, and a stand-alone processor on the Virginia Smart Road to sense vehicles and turn on roadway lighting only when needed. During this research project, the use of on-demand, or just-in-time, lighting was investigated with respect to assessing driver distraction, and to human factors, including a driver’s ability to visually detect and recognize on-road objects and pedestrians. The developed on-demand lighting system described above utilized dedicated short range communication (DSRC), connected vehicle infrastructure (CVI), and centralized wireless lighting controls, and was used with VTTI-developed in-vehicle instrumentation and custom software. The software allowed the study of forward preview time in terms of forward lighting distance needed for drivers to detect roadside pedestrians and hazards. Visual performance testing revealed a relationship between speed and the amount of forward lighting needed to detect pedestrians and hazards on the side of the roadway, and a small, but statistically insignificant, practical difference in visual performance between on-demand lighting and continuously-on lighting conditions. A survey of participant reactions indicated that the public generally accepts on-demand lighting and does not find it distracting as long as a minimum lighting condition is met. The survey also found that participants felt the system provided a safe driving environment. The main application for an on-demand lighting system would be on roadways with little traffic at night and higher accident rates, or higher conflict areas such as intersections, pedestrian crossings, and merge areas.
Emergency Vehicle-to-Vehicle Communication
Murray-Tuite, Pamela; Phoowarawutthipanich, Aphisit; Islam, Rauful; Hdieb, Naser (Connected Vehicle/Infrastructure University Transportation Center, 2016-08-15)
Emergency response vehicles (ERVs) frequently navigate congested traffic conditions to reach their destinations as quickly as possible. In this report, several efforts performed by the research group are described, including micro-simulation, field-testing, and optimization, to determine mechanisms for facilitating safe and efficient ERV travel. Micro-simulation of a network based on the Northern Virginia Connected Vehicle Test Bed examined the effect of a variety of factors on ERV travel time, including the presence of vehicle-to-vehicle (V2V) communication, traffic volumes, cycle length, ERV speed distributions, non-ERV speed distributions, and traffic signal preemption. The results indicated that V2V communication could reduce travel time for an ERV in congested traffic conditions. The research group developed a V2V communication prototype to alert non-ERVs of an approaching ERV by triggering a flash of the infotainment system, followed by audible instructions to move to the left, move to the right, or stay put. Twelve drivers, aged 25 to 50, tested the V2V prototype on the Northern Virginia Connected Vehicle Test Bed during off-peak periods. Data from this field test and associated questionnaires were used to investigate reaction time to the instructions. The estimated reaction times using the developed model varied from 1.4 to 5.8 seconds. A mixed-integer nonlinear program (MINLP) optimization model was formulated to maximize the forward progress of ERVs by sending information to ERVs and non-ERVs within a given road segment. A single set of instructions was sent to each non-ERV, assigning them to a location out of the ERVs path. Numerical case analysis for a small, uniform section of roadway with a limited number of non-ERVs revealed the model is capable of optimizing the behavior of non-ERVs to maximize the speed of the ERV.
Reducing School Bus/Light-Vehicle Conflicts Through Connected Vehicle Communications
Palframan, Kelly Donoghue; Alden, Andrew S. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-08-15)
This project aimed to develop and test a concept for improving the safety of school bus transportation using connected vehicle technology. The project consisted of three key steps that led to a final road study: 1) conducting focus groups with light vehicle drivers and school bus drivers to determine what type of in-vehicle school-bus related information they would like to receive/send; 2) developing a concept of operations to accommodate driver desires; and 3) evaluating the effect of an in-vehicle message that warns of a stopped school bus ahead. In the road study, researchers evaluated each driver’s response through analysis of vehicle kinematics (speed, longitudinal acceleration, and jerk) when a bus was staged either beyond a “School Bus Stop Ahead” roadside sign or beyond the point at which a similar in-vehicle message was presented. Driver responses for each condition were compared to a baseline condition that described their driving behavior when no bus was present on the roadway. The results showed a nearly immediate response to in-vehicle messages, whereas the corresponding roadside sign messages provided little evidence of modifying driver behavior prior to visually observing a stopped school bus in the roadway.
Intersection Management Using In-Vehicle Speed Advisory/Adaptation
Rakha, Hesham A.; Bichiou, Youssef; Hassan, Abdallah A.; Zohdy, Ismail H. (Connected Vehicle/Infrastructure University Transportation Center, 2016-08-30)
In recent years, connected vehicles (CVs) and automated vehicles (AVs) have emerged as a realistic and viable transportation option. Research centers and companies have dedicated substantial efforts to the technology, motivated largely by the potential safety benefits that can be realized through the elimination of human error, the enhancement of mobility via reduction of congestion and optimization of trips, and the associated positive environmental impacts. Both sensors and control mechanisms are needed for this technology to succeed. The goal of this study is to make use of vehicle connectivity via vehicle-to-vehicle (V2V) (i.e., exchanging information between vehicles) and vehicle-to-infrastructure (V2I) (i.e., exchanging information with the infrastructure, including intersection controllers) features, leveraging both connected and automated capabilities, to develop control algorithms/systems that deliver solutions/recommendations for connected automated vehicles (CAVs) [1] as they proceed through intersections. The algorithms developed in this report deliver optimal and/or near-optimal solutions, which required extensive simulations and field experiments for validation. In the work described in this report, the research group combined mathematical modeling, optimal control theory, and optimization into a simulation framework that allows vehicles to cross an intersection safely, while incurring the least amount of delay. These models feature kinematic, dynamic and static constraints. Different versions of the model were developed, ranging from exact solutions that cannot be implemented in real-time to heuristic solutions that are computationally efficient. The results of the final proposed model were compared to other control techniques already implemented in the field, and demonstrated that a reduction of at least 50% in delay was achievable. An interesting byproduct of this model was the reduction in fuel consumption, and thus emissions, by more than 10%.

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