Evasive Maneuvers Research Articles

Application of simulated AIS data to study the collision risk system of ships

Abstract In previous research, several computational methods have been proposed to analyse the navigation, transportation safety and collision risks of maritime vessels. The objective of this study is to use Automatic Identification System (AIS) data to assess the collision risk between two vessels before an actual collision occurs. We introduce the concept of an angle interval in the model to enable real-time response to vessel collision risks. When predicting collision risks, we consider factors such as relative distance, relative velocity and phase between the vessels. Lastly, the collision risk is divided into different regions and represented by different colours. The green region represents a low-risk area, the yellow region serves as a cautionary zone and the red region indicates a high-alert zone. If a signal enters the red region, the vessel's control system will automatically intervene and initiate evasive manoeuvres. This reactive mechanism enhances the safety of vessel operations, ensuring the implementation of effective collision avoidance measures.

Evasion Maneuver and Timing Strategy for UAVs Under Direct Force Control

Given the capabilities of modern high-performance missiles, efficient evasion maneuver strategies are crucial for enhancing UAV survivability. This paper addresses the integration of evasion strategies and maneuver timing for targeted UAVs. First, a three-dimensional engagement scenario is modeled using the relative motion mechanism. Subsequently, a fundamental evasion strategy focusing on large roll maneuvers and two-phase acceleration is developed. With the initiation timing of direct force control designated as the control variable, the formulation of a constrained optimization problem to maximize miss distance is fully articulated. While preserving the high fidelity of the established switching model, the feasible timing intervals and the optimal timing are determined through numerical optimization. Finally, simulation experiments are conducted focusing on omnidirectional attacks from the upper hemisphere. The results demonstrate that by implementing specific evasion maneuvers at optimal timing, the target successfully escapes the effective range of the proximity fuse, thus confirming the feasibility of the proposed evasion maneuver and timing strategy.

Responses of Vehicular Occupants During Emergency Braking and Aggressive Lane-Change Maneuvers.

To validate active human body models for investigating occupant safety in autonomous cars, it is crucial to comprehend the responses of vehicle occupants during evasive maneuvers. This study sought to quantify the behavior of midsize male and small female passenger seat occupants in both upright and reclined postures during three types of vehicle maneuvers. Volunteer tests were conducted using a minivan, where vehicle kinematics were measured with a DGPS sensor and occupant kinematics were captured with a stereo-vision motion capture system. Seatbelt loads, belt pull-out, and footrest reaction forces were also documented. The interior of the vehicle was 3D-scanned for modeling purposes. Results indicated that seatback angles significantly affected occupant kinematics, with small female volunteers displaying reduced head and torso movements, except during emergency braking with a upright posture seatback. Lane-change maneuvers revealed that maximum lateral head excursions varied depending on the maneuver's direction. The study concluded that seatback angles were crucial in determining the extent of occupant movement, with notable variations in head and torso excursions observed. The collected data assist in understanding occupant behavior during evasive maneuvers and contribute to the validation of human body models, offering essential insights for enhancing safety systems in autonomous vehicles.

Anticipated buffer time – An evasive surrogate safety indicator for risk assessment of unsignalized intersections under heterogeneous traffic and aggressive driving conditions

Risk assessment of unsignalized intersections is particularly challenging when confronted with a combination of factors such as heavy traffic, diverse vehicle types, lane indiscipline, aggressive driving, and evasive manoeuvres. Understanding how people drive in these situations is crucial for accurately assessing the risks at unsignalized intersections. This study introduces a novel surrogate safety indicator, i.e. Anticipated Buffer Time (ABT), designed to account for these various factors. Additionally, three new indicators derived from ABT are introduced, namely ABT Negation Ratio, ABT Extremity Ratio, and ABT Progression Ratio. A risk assessment measure, denoted as UnSigRisk Score, is formulated using these three indicators for unsignalized intersections. Three intersections in Ahmedabad, India, were selected for the study due to their manifestation of these challenging conditions. Spearman Rank Correlation Coefficient was estimated to find out how well can UnSigRisk Score measure is able to quantify evasive behaviour. The results indicate that this score proficiently measures evasive behaviour, exhibiting coefficients exceeding 0.6 in all cases—significantly outperforming the current evasive indicators, Yaw Rate Ratio and Jerk. The proposed risk assessment score could serve as a practical tool for transportation authorities, enabling them to identify the most vulnerable intersections and allocate resources for targeted safety interventions wisely. The study unequivocally demonstrates that the use of ABT paves the way for a thorough examination of safety at unsignalized intersections, regardless of driving behaviour and traffic conditions.

Influence of the surrounding environment on the response of seated midsize male volunteers subjected to lateral sled accelerations

Predicting vehicle occupants’ posture during evasive manoeuvres is crucial for assessing their safety in the event of a collision. Volunteer experiments have been performed in the past under lateral accelerations, both within a vehicle cabin and on a seat mounted on a sled. However, discrepancies in the volunteer responses between both setups have been identified. This study hypothesizes that the response of the volunteers differs as a consequence of the proximity to the frame in the vehicle cabin, in comparison to the absence of such a structure on the sled.The present study conducted a novel sled experiment, on which five volunteers with anthropometry comparable to the 50th percentile male were subjected to 0.3 g lateral accelerations, with three different surrounding environments. In twelve pulses, an additional lateral structure was placed to the right or left side of the seated volunteers. The volunteers were asked to either brace or relax their muscles.The results show significant differences between the configurations with and without the structure placed on the right side. This effect was observed for both the lateral excursion of the upper body and the corresponding rotation when the volunteers were relaxed (p < 0.01). The average maximum lateral head rotation decreased from 27° to 14° with the structure on the right. No significant difference in head rotation was found for the braced muscle configuration.This study supports the hypothesis that the proximity to a surrounding environment influences human responses during dynamic loading. Nevertheless, there was no significant difference in maximum muscle activation between the configurations, but a faster reaction of the sternocleidomastoid muscle with the presence of the structure.

Springing into action: Comparing escape responses between bipedal and quadrupedal rodents.

Predation is a fundamental selective pressure on animal morphology, as morphology is directly linked with physical performance and evasion. Bipedal heteromyid rodents, which are characterized by unique morphological traits such as enlarged hindlimbs, appear to be more successful than sympatric quadrupedal rodents at escaping predators such as snakes and owls, but no studies have directly compared the escape performance of bipedal and quadrupedal rodents. We used simulated predator attacks to compare the evasive jumping ability of bipedal kangaroo rats (Dipodomys) to that of three quadrupedal rodent groups-pocket mice (Chaetodipus), woodrats (Neotoma), and ground squirrels (Otospermophilus). Jumping performance of pocket mice was remarkably similar to that of kangaroo rats, which may be driven by their shared anatomical features (such as enlarged hindlimb muscles) and facilitated by their relatively small body size. Woodrats and ground squirrels, in contrast, almost never jumped as a startle response, and they took longer to perform evasive escape maneuvers than the heteromyid species (kangaroo rats and pocket mice). Among the heteromyids, take-off velocity was the only jump performance metric that differed significantly between species. These results support the idea that bipedal body plans facilitate vertical leaping in larger-bodied rodents as a means of predator escape and that vertical leaping likely translates to better evasion success.

Influence of initial belt torso contact on the kinematics and kinetics of booster-seated ATDs in frontal-oblique impacts

Objective Varying initial belt torso contact (i.e., belt gap) on belt-positioning boosters may have implications for potential shoulder belt slip-off in low-speed evasive vehicle maneuvers and differences in dynamic outcomes in frontal sled tests. This study evaluated the influence of initial booster belt gap and belt fit conditions on the kinematic and kinetic outcomes during frontal oblique impacts. Methods Frontal oblique (+15° from frontal) sled tests (n = 18; 23.6 ± 0.1 g at 12.4 ± 0.1 ms) were conducted using the Q-Series 6-year-old (Q6) and 10-year-old (Q10) and the Large Omni Directional Child (LODC) anthropomorphic test devices (ATDs). Various initial belt fit and belt gap conditions were investigated by evaluating each ATD on 2 high-back (HB), 3 low-back (LB), and 1 low-profile (Low) booster. Initial belt fit and belt gap were quantified, and boosters were categorized as “smaller gap” or “larger gap” for comparison. Results Larger-gap boosters produced greater peak lumbar FY and MZ (HB: −23.2 ± 8.8 Nm, LB: −23.6 ± 9.7 Nm) compared to smaller-gap boosters (HB: −12.6 ± 4.4 Nm, LB/Low: −12.4 ± 7.2 Nm) for the LODC and Q10. Peak axial torso rotations were also observed for larger-gap LB (38.6°) compared to smaller-gap LB boosters (23.8°), and the LODC experienced greater peak thoracic rotations on larger-gap boosters compared to smaller-gap boosters. These results suggest that ATDs on larger-gap boosters experienced greater torso rotation and lumbar MZ due to lack of initial contact between the shoulder belt and inferior torso. No ATDs experienced complete shoulder belt slip-off; however, larger-gap boosters displayed more visual evidence of outboard shoulder belt positioning at the time of peak forward head excursion. Conclusion This study provides a novel investigation on the role of initial belt fit and belt gap metrics on the dynamic response of booster-seated ATDs in frontal oblique impacts. Larger-gap boosters allowed the torso to undergo greater axial rotation before restraint was provided by the shoulder belt to the lower torso. Increased shoulder rotations may indicate greater propensity for shoulder belt slip-off in more severe crashes, in oblique maneuvers, or with variations in initial occupant posture. These results suggest the importance of continued evaluation of the implications of initial belt gap provided by boosters and the importance of evaluating lumbar FY and MZ and useful metrics for discrimination of differences in ATD response across booster designs.

Fault Detection Methods for Electric Power Steering System Using Hardware in the Loop Simulation

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers.

Flying in the Strike Zone: Urban Air Mobility and Wildlife Strike Prevention

The number and rate of wildlife strikes continue to increase worldwide. More than 30 years of wildlife strike data indicate that approximately 92% of wildlife strikes for commercial aircraft occur at or below 3500 ft above ground level. Since urban air mobility (UAM) operations are envisioned to carry cargo and passengers up to an altitude of 4000 ft above ground level, UAM operations will face increased exposure to wildlife strike risks throughout their operations. Moreover, the comparatively small size of UAM aircraft, proposed cruising speeds of up to 170 kt, and quieter electric engines are expected to reduce opportunities for threat perception and evasive maneuvers by aircraft operators and wildlife. This paper presents how well-established wildlife strike prevention measures can be adapted to meet the needs of UAM operations and how, with new technology, original equipment manufacturers (OEMs), regulatory agencies, aircraft operators, communities, airspace managers, and vertiport operators can work together to enhance safety.

Analytical game strategies for active UAV defense considering response delays

In the realm of aerial warfare, the protection of Unmanned Aerial Vehicles (UAVs) against adversarial threats is crucial. In order to balance the impact of response delays and the demand for onboard applications, this paper derives three analytical game strategies for the active defense of UAVs from differential game theory, accommodating the first-order dynamic delays. The targeted UAV executes evasive maneuvers and launches a defending missile to intercept the attacking missile, which constitutes a UAV-Missile-Defender (UMD) three-body game problem. We explore two distinct operational paradigms: the first involves the UAV and the defender working collaboratively to intercept the incoming threat, while the second prioritizes UAV self-preservation, with independent maneuvering away from potentially sacrificial engagements. Starting with model linearization and order reduction, the Collaborative Interception Strategy (CIS) is first derived via a linear quadratic differential game formulation. Building upon CIS, we further explore two distinct strategies: the Informed Defender Interception Strategy (IDIS), which utilizes UAV maneuvering information, and the Unassisted Defender Interception Strategy (UDIS), which does not rely on UAV maneuvering information. Additionally, we investigate the conditions for the existence of saddle point solutions and their relationship with vehicle maneuverability and response agility. The simulations demonstrate the effectiveness and advantages of the proposed strategies.

Research on Time-Cooperative Guidance with Evasive Maneuver for Multiple Underwater Intelligent Vehicles

In order to achieve the precise attack of multiple underwater intelligent vehicles (UIVs) on the same target ship at a fixed impact time, and to improve the penetration capability of the UIVs themselves, this study investigated the guidance law for the time-cooperative guidance of UIVs with maneuvering evasion. The evasive maneuver of the UIV increases the line-of-sight angle between the UIV and the target, which decreases the guidance precision of the UIV. A segmented control strategy is proposed to solve the problem of decreasing guidance precision caused by evading maneuvers, which is also the main contribution of this paper. This control strategy is dividing the guidance trajectory into two segments. The first segment allows for intelligent underwater vehicles to make evasion maneuvers and penetrate the defense, while the second segment controls the terminal time and achieves precision strike. Different desired target-vehicle distances are designed for each segment, unifying the impact time control issue and evasion maneuver problem into the pursuit of desired target-vehicle distances. Finally, based on feedback linearization control theory, a time-cooperative guidance law with evasion maneuver capability is proposed. Simulation results validate the effectiveness of the proposed method in attacking-moving targets.

Holistic collision avoidance decision support system for watchkeeping deck officers

The paper presents a 3-stage synthesis-based Decision Support System for watchkeeping deck officers. Its functional scope covers conflict detection, maneuver selection, and maneuver execution, all phases supplemented by collision alerts. First, a customized elliptic ship domain is used for checking if both OS and TS will have enough free space. A survey-based navigators’ declarative OS arena is then used to determine the time at which OOW would like to take evasive action. Next, a safety level is assigned to the current situation based on the predicted violations of the ship domain and the declarative arena. The safety levels are also attributed to potential evasive maneuvers (single actions combining course alteration and rudder deflection). For a selected maneuver, Collision Avoidance Dynamic Critical Area (CADCA) is displayed, which informs OOW about the time window when the maneuver remains feasible. All of the above contribute to a holistic system of multi-level safety assessment utilizing: empirical ship domain, survey-based declarative arena, and ship dynamics-based CADCA. These, in turn, take into account navigators’ knowledge and preferences, ship maneuverability, and the impact of environmental conditions. The system is presented in three real-life scenarios located in the southern part of the Baltic Sea around the Danish straits.

A simulator-based approach for testing and assessing human supervised autonomous ship navigation

AbstractThis paper proposes and demonstrates a simulator-based approach for testing and assessing human operators’ ability and performance in supervising autonomous ships. In the autonomy concept studied here, it is assumed that the autonomous navigation system is capable of detecting and notifying the human operator prior to entering a challenging situation. The system will attempt to resolve the situation with a proposed evasive maneuver, but the system may occasionally make errors or select sub-optimal solutions. When the human operator is notified about a challenging situation, the operator should closely assess the situation, and intervene if (and only if) necessary. The proposed approach allows us to test and quantify the human operators’ abilities and performances in supervising an autonomously navigated ship. The approach is demonstrated on 56 simulator experiments, involving seven different navigators that perform eight different traffic scenarios. The scenarios are all based on real traffic data collected from a Norwegian ferry-crossing. The demonstration shows that the candidates are successful in supervising the autonomous ship in low-complexity traffic scenarios where it is easy for the operator to interpret the system’s decisions. The operators’ ability to intervene when and only when needed does, however, decline in more complex scenarios, and their performance is highly dependent on the traffic scenario and vary significantly between the candidates.

WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems

Supply Chain (SC) Optimization is a key activity in today’s industry with the goal of increasing operational efficiency, reducing costs, and improving customer satisfaction. Traditional optimization methods often struggle to effectively use resources while handling complex and dynamic Supply chain networks. This paper introduces a novel biomimetic metaheuristic algorithm called the Wombat Optimization Algorithm (WOA) for supply chain optimization. This algorithm replicates the natural behaviors observed in wombats living in the wild, particularly focusing on their foraging tactics and evasive maneuvers towards predators. The theory of WOA is described and then mathematically modeled in two phases: (i) exploration based on the simulation of wombat movements during foraging and trying to find food and (ii) exploitation based on simulating wombat movements when diving towards nearby tunnels to defend against its predators. The effectiveness of WOA in addressing optimization challenges is assessed by handling the CEC 2017 test suite across various problem dimensions, including 10, 30, 50, and 100. The findings of the optimization indicate that WOA demonstrates a strong ability to effectively manage exploration and exploitation, and maintains a balance between them throughout the search phase to deliver optimal solutions for optimization problems. A total of twelve well-known metaheuristic algorithms are called upon to test their performance against WOA in the optimization process. The outcomes of the simulations reveal that WOA outperforms the other algorithms, achieving superior results across most benchmark functions and securing the top ranking as the most efficient optimizer. Using a Wilcoxon rank sum test statistical analysis, it has been proven that WOA outperforms other algorithms significantly. WOA is put to the test with twenty-two constrained optimization problems from the CEC 2011 test suite and four engineering design problems to showcase its ability to solve real-world optimization problems. The results of the simulations demonstrate that WOA excels in real-world applications by delivering superior solutions and outperforming its competitors.

Analysis of a capacitance tomography system for object detection and localization

Abstract To ensure safe human-robot cooperation, it is necessary not only to measure the force exerted during contact, but also to monitor an approaching action. This would allow avoiding any unintentional contact through evasive maneuvers and thus prevent possible injuries. In our contribution we analyze a localization system based on capacitance tomography where an approaching object constitutes an electrode of a multi-electrode capacitance. The system processes measured voltages made on the surface of a conductive layer. From this, the location of the capacitive coupling between the object and the layer can be reconstructed, and the position of the object can be estimated. The system’s performance is further analyzed using the Neyman–Pearson detector. To define the performance of the system, for object detection only, the influence of object distance, object area, and number of measurements used on the probability of detection is examined.

Robust Decision-Making for the Reactive Collision Avoidance of Autonomous Ships against Various Perception Sensor Noise Levels

Autonomous ships are expected to extensively rely on perception sensors for situation awareness and safety during challenging operations, such as reactive collision avoidance. However, sensor noise is inevitable and its impact on end-to-end decision-making has not been addressed yet. This study aims to develop a methodology to enhance the robustness of decision-making for the reactive collision avoidance of autonomous ships against various perception sensor noise levels. A Gaussian-based noisy perception sensor is employed, where its noisy measurements and noise variance are incorporated into the decision-making as observations. A deep reinforcement learning agent is employed, which is trained in different noise variances. Robustness metrics that quantify the robustness of the agent’s decision-making are defined. A case study of a container ship using a LIDAR in a single static obstacle environment is investigated. Simulation results indicate sophisticated decision-making of the trained agent prioritising safety over efficiency when the noise variance is higher by conducting larger evasive manoeuvres. Sensitivity analysis indicates the criticality of the noise variance observation on the agent’s decision-making. Robustness is verified against noise variance up to 132% from its maximum trained value. Robustness is verified only up to 76% when the agent is trained without the noise variance observation with lack of its prior sophisticated decision-making. This study contributes towards the development of autonomous systems that can make safe and robust decisions under uncertainty.

Design of a tracking controller for autonomous articulated heavy vehicles using a nonlinear model predictive control technique

This article proposes a design of a tracking controller for autonomous articulated heavy vehicles (AAHVs) using a nonlinear model predictive control (NLMPC) technique. Despite economic and environmental benefits in freight transportation, articulated heavy vehicles (AHVs) exhibit poor directional performance due to their large sizes, multi-unit vehicle configurations, and high centers of gravity (CGs). AHVs represent a 7.5 times higher risk of traffic accidents than single-unit vehicles (e.g. rigid trucks, cars, etc.) in highway operations. Human driver errors cause about 94% of traffic collisions. However, little attention has been paid to autonomous driving control of AHVs. To increase the safety of AHVs, we design a novel NLMPC-based tracking controller for an AHV, that is, a tractor/semi-trailer combination, and this tracking controller is distinguished from others with the feature of controlling both the lateral and longitudinal motions for both the leading and trailing units. To design the tracking controller, a new prediction AHV model is developed, which represents both the lateral and longitudinal dynamics of the vehicle and captures its rearward amplification feature over high-speed evasive maneuvers. With the proposed tracking controller, the AAHV tracks the predefined reference path and follows a planned forward-speed scheme. Co-simulation demonstrates the effectiveness and robustness of the proposed NLMPC tracking controller.

White-tailed deer detection rates increase when coyotes are present.

Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator-prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator-prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.

Mosquitoes escape looming threats by actively flying with the bow wave induced by the attacker

To detect and escape looming threats, night-flying insects must rely on other senses than vision alone. Nocturnal mosquitoes can evade looming objects in the dark, but how they achieve this is still unknown. Here, we show how night-active female malaria mosquitoes escape from rapidly looming objects that simulate defensive actions of blood-hosts. First, we quantified the escape performance of flying mosquitoes from an event-triggered mechanical swatter, showing that mosquitoes use swatter-induced airflow to increase their escape success. Secondly, we used high-speed videography and deep-learning-based tracking to analyze escape flights in detail, showing that mosquitoes use banked turns to evade the threat. By combining escape kinematics data with numerical simulations of attacker-induced airflow and a mechanistic movement model, we unraveled how mosquitoes control these banked evasive maneuvers: they actively steer away from the danger, and then passively travel with the bow wave produced by the attacker. Our results demonstrate that night-flying mosquitoes can detect looming objects when visual cues are minimal, suggesting that they use attacker-induced airflow both to detect the danger and as a fluid medium to move with away from the threat. This shows that escape strategies of flying insects are more complex than previous visually induced escape flight studies suggest. As most insects are of similar or smaller sizes than mosquitoes, comparable escape strategies are expected among millions of flying insect species. The here-observed escape maneuvers are distinct from those of mosquitoes escaping from odor-baited traps, thus providing new insights for the development of novel trapping techniques for integrative vector management.

Emergency collision avoidance maneuvers of multi-trailer articulated heavy vehicles

A simulation investigation of emergency evasive maneuvers of the type experienced during obstacle avoidance is conducted for long combination vehicles at highway speeds. The dynamic model includes a commercial truck with a configuration that is typical of what is used in the U.S., with two 28-ft trailers connected to the tractor through a fifth wheel, and to each other by an A-dolly. The model is validated against test data and used for evaluating distance and time needed to safely perform a steering maneuver to avoid an obstacle on the road. The simulation results indicate a significant difference in both the required time and distance for safely exercising an emergency obstacle avoidance, ranging from approximately 151–276 ft in distance and 1.7–2.4 s from the start of the driver action. The reaction time of the driver will add to both measures by an amount corresponding to the lapse in time between the moment the driver recognises the obstacle and when a steering action is initiated. To the extent that the lighting and road condition add to the reaction time, a significantly larger distance and longer time are needed during nighttime driving as compared with daytime, under similar road and loading conditions.