Reduce Collision Risk Research Articles

Behavioral responses to offshore windfarms during migration of a declining shorebird species revealed by GPS-telemetry

EU member countries and the UK are currently installing numerous offshore windfarms (OWFs) in the Baltic and North Seas to achieve decarbonization of their energy systems. OWFs may have adverse effects on birds; however, estimates of collision risks and barrier effects for migratory species are notably lacking, but are essential to inform marine spatial planning. We therefore compiled an international dataset consisting of 259 migration tracks for 143 Global Positioning System-tagged Eurasian curlews (Numenius arquata arquata) from seven European countries recorded over 6 years, to assess individual response behaviors when approaching OWFs in the North and Baltic Seas at two different spatial scales (i.e. up to 3.5 km and up to 30 km distance). Generalized additive mixed models revealed a significant small-scale increase in flight altitudes, which was strongest at 0–500 m from the OWF and which was more pronounced during autumn than during spring, due to higher proportions of time spent migrating at rotor level. Furthermore, four different small-scale integrated step selection models consistently detected horizontal avoidance responses in about 70% of approaching curlews, which was strongest at approximately 450 m from the OWFs. No distinct, large-scale avoidance effects were observed on the horizontal plane, although they could possibly have been confounded by changes in flight altitudes close to land. Overall, 28.8% of the flight tracks crossed OWFs at least once during migration. Flight altitudes within the OWFs overlapped with the rotor level to a high degree in autumn (50%) but to a significantly lesser extent in spring (18.5%). Approximately 15.8% and 5.8% of the entire curlew population were estimated to be at increased risk during autumn and spring migration, respectively. Our data clearly show strong small-scale avoidance responses, which are likely to reduce collision risk, but simultaneously highlight the substantial barrier effect of OWFs for migrating species. Although alterations in flight paths of curlews due to OWFs seem to be moderate with respect to the overall migration route, there is an urgent need to quantify the respective energetic costs, given the massive ongoing construction of OWFs in both sea areas.

Analysis of speed reductions and crash risk of aggressive drivers during emergent pre-crash scenarios at unsignalized intersections

Aggressive driver behavior (ADB) is often linked with road crashes, especially during crash imminent situations. Previous studies demonstrated that ADB was positively correlated with collision risk; however, this relationship has not quantified evidently. This study aimed to analyze drivers’ collision risk and speed reduction behavior during an emergent pre-crash scenario (such as a conflict encroaching into an unsignalized intersection at different critical time gaps) using a driving simulator. The effect of ADB on crash risk is investigated using the time to collision (TTC). Further, drivers’ collision evasive behavior is analyzed using speed reduction time (SRT) survival probabilities. Fifty-eight Indian drivers are identified as aggressive, moderately aggressive, and, non-aggressive based on aggressive indicators such as vehicle kinematics (percentage of the time spent in speeding and rapid accelerations, maximum brake pressure, etc.). Two separate models are built to analyze ADB effects on TTC and SRT using a Generalized Linear Mixed Model (GLMM) and a Weibull Accelerated Failure Time (AFT) model, respectively. From the results, it can be observed that aggressive drivers’ TTC and SRT are reduced by 82% and 38%, respectively. Compared to a 7 sec conflict approaching time gap, TTC is reduced by 18%, 39%, 51%, and 58% for 6 sec, 5 sec, 4 sec, and 3 sec conflict approaching time gaps, respectively. The estimated SRT survival probabilities for aggressive, moderately aggressive and non-aggressive drivers are 0%, 3% and 68% at 3 sec of conflict approaching time gap, respectively. SRT survival probability increased by 25% for matured drivers and decreased by 48% for drivers who tend to engage in frequent speeding. Important implications of the study findings are discussed.

Safety Spacing Policy and Cruise Control Strategy for Heterogeneous Platoon to Enhance Safety and Efficiency

Automated platooning is gaining increasing attention because it is regarded as a highly efficient transportation mode to solve traffic congestion problem. Although different intraplatoon spacing strategies have been proposed, little research has focused on quantitative optimization of spacing policy from a safety perspective considering differences between automated and human-driven platooning. In addition, there still is a lack of comprehensive research into string stability and delay robustness of cooperative adaptive cruise control (CACC) for heterogeneous platoons. This paper proposes a quantitative spacing policy in quadratic form based on safety index optimization under hard braking scenarios. The expected value of collision severity is taken as the main index for spacing optimization. The CACC strategy then tracks the proposed spacing considering fluctuation of multitime delays and uncertainty of vehicle dynamics. Based on sliding model control theory and frequency stability criteria, the sufficient conditions satisfying CACC stability and string stability were given. The robustness of the CACC system considering communication latency fluctuation was shown using simulation results. Compared with the existing control strategy, the proposed control strategy is more robust to communication latency, and string stability can be guaranteed. The proposed spacing strategy effectively can reduce collision risk, and the proposed CACC strategy improves latency robustness on the premise of ensuring string stability.

Bi-level ramp merging coordination for dense mixed traffic conditions

Connected and Autonomous Vehicles (CAVs) hold great potential to improve traffic efficiency, emissions and safety in freeway on-ramp bottlenecks through coordination between mainstream and on-ramp vehicles. This study proposes a bi-level coordination strategy for freeway on-ramp merging of mixed traffic consisting of CAVs and human-driven vehicles (HDVs) to optimize the overall traffic efficiency and safety in congested traffic scenarios at the traffic flow level instead of platoon levels. The macro level employs an optimization model based on fundamental diagrams and shock wave theories to make optimal coordination decisions, including optimal minimum merging platoon size to trigger merging coordination and optimal coordination speed, based on macroscopic traffic state in mainline and ramp (i.e., traffic volume and penetration rates of CAVs). Furthermore, the micro level determines the real platoon size in each merging cycle as per random arrival patterns and designs the coordinated trajectories of the mainline facilitating vehicle and ramp platoon. A receding horizon scheme is implemented to accommodate human drivers’ stochastics as well. The developed bi-level strategy is tested in terms of improving efficiency and safety in a simulation-based case study under various traffic volumes and CAV penetration rates. The results show the proposed coordination addresses the uncertainties in mixed traffic as expected and substantially improves ramp merging operation in terms of merging efficiency and traffic robustness, and reducing collision risk and emissions, especially under high traffic volume conditions.

Reduction of Collision Risk in Multi-ligament Knee Injury KD-III-M and KD-IV Surgery—Superficial Medial Collateral Ligament Reconstruction with Suture Anchors

Surgical reconstruction of the medial collateral ligament (MCL) can be challenging during multi-ligament knee injury surgery due to the limited working space. There is risk of collision between the guide pin, pulling sutures, reamer, tunnel, implant, and graft of the different ligament reconstructions. In this Technical Note, we detail our senior author’s technique for superficial MCL reconstruction using suture anchors and cruciate ligament reconstruction with all-inside techniques. The technique mitigates the risk of collision by confining the reconstruction process and implants for MCL fixation on the medial femoral condyle and medial proximal tibia.

Wind energy production in forests conflicts with tree-roosting bats

Many countries are investing heavily in wind power generation,1 triggering a high demand for suitable land. As a result, wind energy facilities are increasingly being installed in forests,2,3 despite the fact that forests are crucial for the protection of terrestrial biodiversity.4 This green-green dilemma is particularly evident for bats, as most species at risk of colliding with wind turbines roost in trees.2 With some of these species reported to be declining,5,6,7,8 we see an urgent need to understand how bats respond to wind turbines in forested areas, especially in Europe where all bat species are legally protected. We used miniaturized global positioning system (GPS) units to study how European common noctule bats (Nyctalus noctula), a species that is highly vulnerable at turbines,9 respond to wind turbines in forests. Data from 60 tagged common noctules yielded a total of 8,129 positions, of which 2.3% were recorded at distances <100m from the nearest turbine. Bats were particularly active at turbines <500m near roosts, which may require such turbines to be shut down more frequently at times of high bat activity to reduce collision risk. Beyond roosts, bats avoided turbines over several kilometers, supporting earlier findings on habitat loss for forest-associated bats.10 This habitat loss should be compensated by developing parts of the forest as refugia for bats. Our study highlights that it can be particularly challenging to generate wind energy in forested areas in an ecologically sustainable manner with minimal impact on forests and the wildlife that inhabit them.

A data-driven approach for ship-bridge collision candidate detection in bridge waterway

The consequences caused by bridge failures owing to the ship-bridge collision are always severe in terms of loss of life, economy, and environmental consequences to individuals and societies. The previous studies focused on the ship-bridge collision mainly concentrated on passive anti-collision, such as strengthening the bridge structure or setting anti-collision facilities. Compared with the previous research, the contribution of this work is to facilitate the reduction of collision risk of ship-bridge collision from the perspective of active anti-collision. A data-driven approach for ship-bridge collision candidate detection method in inland bridge waterways is proposed in this research. The approach is mainly divided into two steps: 1) The features (channel boundary, pier domain, and ship domain) of bridge waterways are identified using Kernel Density Estimation (KDE) method based on the historical AIS data; 2) Collision candidate detection with Velocity Obstacle (VO) method considering the identified features. This work can provide beneficial support for the ship-bridge active collision avoidance system.

Enabling non-isocentric dynamic trajectory radiotherapy by integration of dynamic table translations

Objective. The purpose of this study is to develop a treatment planning process (TPP) for non-isocentric dynamic trajectory radiotherapy (DTRT) using dynamic gantry rotation, collimator rotation, table rotation, longitudinal, vertical and lateral table translations and intensity modulation and to validate the dosimetric accuracy. Approach. The TPP consists of two steps. First, a path describing the dynamic gantry rotation, collimator rotation and dynamic table rotation and translations is determined. Second, an optimization of the intensity modulation along the path is performed. We demonstrate the TPP for three use cases. First, a non-isocentric DTRT plan for a brain case is compared to an isocentric DTRT plan in terms of dosimetric plan quality and delivery time. Second, a non-isocentric DTRT plan for a craniospinal irradiation (CSI) case is compared to a multi-isocentric intensity modulated radiotherapy (IMRT) plan. Third, a non-isocentric DTRT plan for a bilateral breast case is compared to a multi-isocentric volumetric modulated arc therapy (VMAT) plan. The non-isocentric DTRT plans are delivered on a TrueBeam in developer mode and their dosimetric accuracy is validated using radiochromic films. Main results. The non-isocentric DTRT plan for the brain case is similar in dosimetric plan quality and delivery time to the isocentric DTRT plan but is expected to reduce the risk of collisions. The DTRT plan for the CSI case shows similar dosimetric plan quality while reducing the delivery time by 45% in comparison with the IMRT plan. The DTRT plan for the breast case showed better treatment plan quality in comparison with the VMAT plan. The gamma passing rates between the measured and calculated dose distributions are higher than 95% for all three plans. Significance. The versatile benefits of non-isocentric DTRT are demonstrated with three use cases, namely reduction of collision risk, reduced setup and delivery time and improved dosimetric plan quality.

Developing dynamic speed limit strategies for mixed traffic flow to reduce collision risks at freeway bottlenecks

Connected and automated vehicles (CAVs) have the great potential to improve traffic flow because of their particular characteristics of connectivity and automation. This study aims to develop CAV control strategies based on car-following speed balance, which are defined as dynamic speed limit (DSL) strategies, and examine their performances on reducing freeway collision risks via microscopic simulations. The core idea of DSL strategy is to command the CAVs to slow down actively before reaching the bottlenecks, and form moving barriers to guide the following human driven vehicles to passively decelerate. Three DSL strategies are first developed for CAVs based on vehicle dynamics principles, and the influences of various position distribution patterns of CAVs on three strategies are compared in the one-lane scenario. Then, the DSL strategy with the best performance is selected based on simulation experiments, and a conventional variable speed limit control is used to compare the performance of our proposed methods. Finally, the DSL strategy based on Min control is tested in the two-lane, three-lane and four-lane scenarios to verify the effectiveness. Simulation results indicate that: (1) three DSL strategies based on CAVs can significantlyreduce collision risks when CAVs reach a certain proportion; (2) the uniform distribution of CAVs can maximize the effect of the moving barriers; (3) DSL strategy based on Min control is negatively affected by lane-changing behaviors, but still works well in the multi-lane scenario.

In-vehicle warnings for work zone and related rear-end collisions: A driving simulator experiment

Work zone area on roads is a critical component of road networks which concerns the safety of workers and passing by drivers. However, the passive speed reduction and lane changes caused by lane closure have led to frequent rear-end collisions in work zone areas. To help drivers better anticipate work zone situation and reduce collision risks, this paper proposes two types of in-vehicle warnings for work zone areas: Leading Vehicle Brake Warning (LVBW), and Lane-Closed Warning & Leading Vehicle Brake Warning (LCW & LVBW). The LVBW delivers a danger warning message to drivers upon the brake of the leading vehicle, while the LCW & LVBW provides an additional work-zone position message to remind drivers to decelerate in advance. A driving simulator experiment was conducted with 44 participants (24 males and 20 females) to test drivers’ performance in work zone area under different conditions, comprising two warning types (LVBW vs. LCW & LVBW), four warning times (3 s, 5 s, 7 s and 9 s) and two visibility conditions (clear and foggy weather). The results showed significant safety benefits of the lane-closed warning message under the LCW & LVBW condition. In contrast, the warning of leading vehicle’s brake in both LVBW and LCW & LVBW conditions had limited efficacy, which indicates that earlier warning about lane-closure is important to assist drivers in anticipating the complex situations in work zones. Drivers’ speed control and collision avoidance performances were impaired in fog, but the impairment was compensated by the warning messages. Compared with male drivers, female drivers tend to be more cautious when approaching the work zone areas. Overall, this study plays a pioneering role in developing effective safety countermeasures for work zone areas and providing strong support for implementing in-vehicle warning technologies.

An integrated lane change prediction model incorporating traffic context based on trajectory data

Predicting lane change maneuvers is critical for autonomous vehicles and traffic management as lane change may cause conflict in traffic flow. Most existing studies do not consider the effect of traffic context (i.e., traffic level and vehicle type) on lane change maneuvers. Therefore, these models cannot adapt to different traffic environments. This study aims to address this problem and establish an integrated lane change prediction model incorporating traffic context using machine learning algorithms. In addition, lane change decisions and lane change trajectories are both predicted to capture the whole process, which have been less studied. The framework of the proposed model contains two parts: the traffic context classification model, which is used to predict traffic level and vehicle type, and the integrated lane change prediction model, which is used to predict lane change decision with XGBoost and lane change trajectories with LSTM incorporating context information. Instead of considering lane change, we establish trajectory prediction models for left lane change and right lane change, further improving the prediction accuracy. The naturalistic trajectories of the highD dataset are used to train and validate the model. The results show that the proposed model improves the accuracy from 97.02% to 98.20% when predicting lane change decision that incorporate traffic context. In addition, the MSE decreases from 11.21 to 6.62 when predicting trajectories. The proposed models are also validated on NGSIM dataset, proving the adaptability of the model. The proposed model can be applied to different environments to reduce collision risks caused by lane change maneuvers and improve traffic management and driving safety.

A Novel Dynamic Lane-Changing Trajectory Planning Model for Automated Vehicles Based on Reinforcement Learning

Lane changing behavior has a significant impact on traffic efficiency and may lead to traffic delays or even accidents. It is important to plan a safe and efficient lane-changing trajectory that coordinates with the surrounding environment. Most conventional lane-changing models need to establish and solve constrained optimization models during the whole process, while reinforcement learning can just take the current state as input and directly output actions to vehicles. This study develops a lane-changing model using the deep deterministic policy gradient method, which can simultaneously control the lateral and longitudinal motions of the vehicle. To optimize its performance, a reward function is properly designed by combining safety, efficiency, gap, headway, and comfort features. To avoid collisions, a safety modification model is developed to check and correct acceleration at every time step. The driving trajectory data of 1169 lane-changing scenarios extracted from the Next Generation Simulation (NGSIM) dataset are used to train and test the model. The proposed model can quickly converge in training phase. Testing results show it can complete safe and efficient lane changing in different lane-changing scenarios with both shorter time headway and lane-changing duration than human drivers. Compared with the conventional dynamic lane-changing trajectory planning model, our model can reduce collision risk. It is also evaluated in automated and nonautomated mixed traffic in SUMO. Simulation results show that the proposed model also has a positive effect on the average speed of overall traffic flow.

Hotspots in the grid: Avian sensitivity and vulnerability to collision risk from energy infrastructure interactions in Europe and North Africa

Abstract Wind turbines and power lines can cause bird mortality due to collision or electrocution. The biodiversity impacts of energy infrastructure (EI) can be minimised through effective landscape‐scale planning and mitigation. The identification of high‐vulnerability areas is urgently needed to assess potential cumulative impacts of EI while supporting the transition to zero carbon energy. We collected GPS location data from 1,454 birds from 27 species susceptible to collision within Europe and North Africa and identified areas where tracked birds are most at risk of colliding with existing EI. Sensitivity to EI development was estimated for wind turbines and power lines by calculating the proportion of GPS flight locations at heights where birds were at risk of collision and accounting for species' specific susceptibility to collision. We mapped the maximum collision sensitivity value obtained across all species, in each 5 × 5 km grid cell, across Europe and North Africa. Vulnerability to collision was obtained by overlaying the sensitivity surfaces with density of wind turbines and transmission power lines. Results: Exposure to risk varied across the 27 species, with some species flying consistently at heights where they risk collision. For areas with sufficient tracking data within Europe and North Africa, 13.6% of the area was classified as high sensitivity to wind turbines and 9.4% was classified as high sensitivity to transmission power lines. Sensitive areas were concentrated within important migratory corridors and along coastlines. Hotspots of vulnerability to collision with wind turbines and transmission power lines (2018 data) were scattered across the study region with highest concentrations occurring in central Europe, near the strait of Gibraltar and the Bosporus in Turkey. Synthesis and applications. We identify the areas of Europe and North Africa that are most sensitive for the specific populations of birds for which sufficient GPS tracking data at high spatial resolution were available. We also map vulnerability hotspots where mitigation at existing EI should be prioritised to reduce collision risks. As tracking data availability improves our method could be applied to more species and areas to help reduce bird‐EI conflicts.

Bird protection treatments reduce bird-window collision risk at low-rise buildings within a Pacific coastal protected area.

BackgroundIn North America, up to one billion birds are estimated to die annually due to collisions with glass. The transparent and reflective properties of glass present the illusion of a clear flight passage or continuous habitat. Approaches to reducing collision risk involve installing visual cues on glass that enable birds to perceive glass as a solid hazard at a sufficient distance to avoid it.MethodsWe monitored for bird-window collisions between 2013 and 2018 to measure response to bird protection window treatments at two low-rise buildings at the Alaksen National Wildlife Area in Delta, British Columbia, Canada. After 2 years of collision monitoring in an untreated state, we retrofitted one building with Feather Friendly® circular adhesive markers applied in a grid pattern across all windows, enabling a field-based assessment of the relative reduction in collisions in the 2 years of monitoring following treatment. An adjacent building that had been constructed with a bird protective UV-treated glass called ORNILUX® Mikado, was monitored throughout the two study periods. Carcass persistence trials were conducted to evaluate the likelihood that carcasses were missed due to carcass removal between scheduled searches.Results and ConclusionsAfter accounting for differences in area of glass between the two buildings, year, and observer effects, our best-fit model for explaining collision risk included the building’s treatment group, when compared to models that included building and season only. We found that the Feather Friendly® markers reduced collision risk at the retrofitted building by 95%. Collision incidence was also lower at the two monitored façades of the building with ORNILUX® glass compared to the building with untreated glass. Although more research is needed on the effectiveness of bird-protection products across a range of conditions, our results highlight the benefit of these products for reducing avian mortality due to collisions with glass.

An IoT-Aware Smart System Exploiting the Electromagnetic Behavior of UHF-RFID Tags to Improve Worker Safety in Outdoor Environments

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety.

Dynamic control allocation between onboard and delayed remote control for unmanned aircraft system detect-and-avoid

This paper develops and evaluates the performance of an allocation agent to be potentially integrated into the onboard Detect and Avoid (DAA) computer of an Unmanned Aircraft System (UAS). We consider a UAS that can be fully controlled by the onboard DAA system and by a remote human pilot. With a communication channel prone to latency, we consider a mixed initiative interaction environment, where the control authority of the UAS is dynamically allocated by the allocation agent. In an encounter with a dynamic intruder, the probability of collision may increase in the absence of pilot commands in the presence of latency. Moreover, a delayed pilot command may not result in safe resolution of the current scenario and need to be improvised. We design an optimization algorithm to reduce collision risk and refine delayed pilot commands. Towards this end, a Markov Decision Process (MDP) and its solution are employed to create a wait time map. The map consists of estimated times that the UAS can wait for the remote pilot commands at each state. A command blending algorithm is designed to select an avoidance maneuver that prioritizes the pilot intention extracted from the pilot commands. The wait time map and the command blending algorithm are implemented and integrated into a closed-loop simulator. We conduct ten thousands fast-time Monte Carlo simulations and compare the performance of the integrated setup with a standalone DAA setup. The simulation results show that the allocation agent enables the UAS to wait without inducing any near mid air collision (NMAC) and severe loss of well clear (LoWC) while positively improve pilot involvement in the encounter resolution.

Risk evaluation of onshore wind farms in relation to wild duck (Anatidae) movements in the Yangtze River Mouth, China

Although wind power is a promising source of renewable energy, previous studies have focused on uncovering species and abundance decreases caused by wind farms. However, very few studies focus on collision risk of onshore wind farms in relation to birds’ movements which are the important indicators for balancing wind energy development and biodiversity conservation. Here, birds’ movement were recorded by combining 15 ducks’ satellite tracking and six field surveys to assess collision risks in Yangtze River Mouth, the wintering site for migratory waterbirds along the East Asian–Australasian Flyway. It is found that distances between ducks’ locations and nearest wind turbines in middle and later wintering periods were significantly higher than during early period. Besides, ducks inside wind farm tended to fly outside turbine rotor height range (45–135 m: between lowest and highest points the rotor tips) within 300 m from the dyke where the turbines were located, thus decreasing their collision risk. Ducks also tended to fly below the minimum rotor tip height (< 45 m) when the turbines were rotating. These results suggest that ducks adopt behavioural avoidance strategies in response to wind farms, and turning off turbines to reduce collision risks may be unnecessary.

Optimization of lane-changing advisory of connected and autonomous vehicles at a multi-lane work zone

The work zone with lane closure will be an active bottleneck due to vehicles’ mandatory lane-changing conflicts. The emerging Connected Autonomous Vehicle (CAV) technology provides opportunities for vehicle motion planning to improve traffic performance. However, the literature using CAV technology mainly focuses on single-lane lane-changing control in the merging area. The algorithm dealing with multi-lane lane-changing control is absent. In this paper, a simulation system with a lane-changing optimal strategy embedded for the multi-lane work zone is presented under the heterogeneous traffic flow. First, the road upstream of the work zone is divided into several segments, and an optimal multi-lane lane-changing algorithm is designed. It is recommended that CAVs, on the closure lane and the merged lane, change lanes on each segment to balance traffic distribution and minimize traffic delay. Second, to validate the algorithm proposed, a typical three-lane freeway with one-lane closed for the work zone is researched, and the simulation platform based on cellular automata is developed. Third, the advantages of multi-lane control strategies are studied and discussed in traffic efficiency improvement and collision risk reduction by comparing previous lane-changing control algorithms.

Ship-to-ship dialogues and agreements for collision risk reduction

AbstractNon-compliance with or misinterpretation of the International Regulations for Preventing Collisions at Sea (COLREGs) when assessing vessel encounters, and the lack of good communication between the vessels involved in a critical situation, are primary contributing factors in collisions. Vessels engaged in an encounter should be aware that they are part of the same scenario and situation, which can become critical. Sharing and contrasting their information about the encounter would help those responsible to take manoeuvring decisions in a consistent way. There are situations whose evaluation by the respective officers in charge of the navigational watch may diverge and lead to disagreements on the actions to be taken. If there is no proper inter-ship communication, a collision may result. This paper presents a proposal for safety communication implemented in a programmable system using common equipment (automatic identification system), and applies it to a case study of one such special situation, showing how it could help to reduce the risk of collision.

Field testing an "acoustic lighthouse": Combined acoustic and visual cues provide a multimodal solution that reduces avian collision risk with tall human-made structures.

Billions of birds fatally collide with human-made structures each year. These mortalities have consequences for population viability and conservation of endangered species. This source of human-wildlife conflict also places constraints on various industries. Furthermore, with continued increases in urbanization, the incidence of collisions continues to increase. Efforts to reduce collisions have largely focused on making structures more visible to birds through visual stimuli but have shown limited success. We investigated the efficacy of a multimodal combination of acoustic signals with visual cues to reduce avian collisions with tall structures in open airspace. Previous work has demonstrated that a combination of acoustic and visual cues can decrease collision risk of birds in captive flight trials. Extending to field tests, we predicted that novel acoustic signals would combine with the visual cues of tall communication towers to reduce collision risk for birds. We broadcast two audible frequency ranges (4 to 6 and 6 to 8 kHz) in front of tall communication towers at locations in the Atlantic migratory flyway of Virginia during annual migration and observed birds' flight trajectories around the towers. We recorded an overall 12-16% lower rate of general bird activity surrounding towers during sound treatment conditions, compared with control (no broadcast sound) conditions. Furthermore, in 145 tracked "at-risk" flights, birds reduced flight velocity and deflected flight trajectories to a greater extent when exposed to the acoustic stimuli near the towers. In particular, the 4 to 6 kHz stimulus produced the greater effect sizes, with birds altering flight direction earlier in their trajectories and at larger distances from the towers, perhaps indicating that frequency range is more clearly audible to flying birds. This "acoustic lighthouse" concept reduces the risk of collision for birds in the field and could be applied to reduce collision risk associated with many human-made structures, such as wind turbines and tall buildings.