The goal of this experiment was to determine what if any effect two different types of warnings have the brake reaction time of distracted commercial motor vehicle operators. The warning conditions were: No Warning, Auditory Tire Skid Warning, and One Second Brake Pulse Warning. Each participant was distracted via a distracter task during the experiment. As the participants were distracted, an obstacle was launched out into their forward path. Each participant received his/her appropriate warning, according to what condition they were placed, when the obstacle entered their headway. It was determined that the Auditory Tire Skid Warning aided in decreasing the movement times, while the One Second Brake Pulse Warning aided in decreasing the number of collisions with the barrels and speed at contact with the barrels. / Master of Science

This study is performed to identify the customer braking behaviors of Articulated haulers. The data files from the different customer sites are used to analyses the data. The braking definition for the braking event was created to identify the braking events by using of output braking pressure. Also the statistical features related to the vehicle were calculated for  identified braking events. Furthermore the braking events were classified according to the classification rules which were created based on calculated statistical features.The final results ( classification)  motivates and satisfies with the  aim of the project.

More than 900 bicyclists died in motor vehicle crashes in the United States in 2020, which represents a 50% increase from 2010 and the highest number of bicyclist deaths in nearly 35 years [1]. Reversing this trend will require efforts on multiple fronts, including reducing vehicle speeds and improving roadways and vehicles to be more hospitable to cyclists. Automatic emergency braking (ABB) with cyclist detection is a vehicle countermeasure with potential to prevent bicycle-motor vehicle crashes. AEB systems, which typically warn drivers of an impending collision and brake if drivers do not respond, have been shown to reduce vehicle-to-vehicle rear-end crash rates by 50% [2] and pedestrian crash rates by 27% [3]. Little is known about the real-world effects of ABB with cyclist detection on bicycle crashes. Subaru's EyeSight system, which includes ABB, has been capable of detecting cyclists in parallel configurations beginning in model year (MY) 2013 in the United States. The ability to detect cyclists in perpendicular configurations was added to some models beginning in MY 2022. The goal of this study is to evaluate the effects of the early version of EyeSight on U.S. bicycle crashes. [from Introduction]

This master’s thesis deals with driving maneuvers at low coefficient of adhesion, especially in winter season. It includes a list of adhesion coefficients on many surfaces, published by various authors. Figures were through the use of statistical methods divided into normal and exceeding. There are described terms having impact on adhesion. For determination of adhesion was used tests like emergency braking, circle test and slalom. The major part contains specification of used vehicles, surfaces, weather conditions, measuring devices and realized tests. In addition to using accelerometer, there was a successful attempt to use timekeeping facilities to determine deceleration of vehicle. Acquired data were processed and compared to another publications.

In this thesis project, brake performance of heavy vehicles is improved by the development of new wheel-based functions for a longitudinal slip control braking system using novel Fast Acting Braking Valves (FABVs). To achieve this goal, Volvo Trucks' vehicle dynamics model has been extended to incorporate the FABV system. After validating the updated model with experimental data, a slip-slope based recursive least squares friction estimation algorithm has been implemented. Using information about the tire-road friction coefifcient, the sliding mode slip controller has been made adaptive to different road surfaces by implementing a friction dependent reference slip signal and switching gain for the sliding mode controller. This switching gain is further optimized by means of a novel on-line optimization algorithm. Simulations show that the on-line friction estimation converges close to the reference friction level within one second for hard braking. Furthermore, using this information for the optimized controller has resulted in reduction of braking distance on most road surfaces of up to 20 percent, as well as in most cases a reduction in air usage.

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today’s advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems. This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS). Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data. Results: Three categories among today’s accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots. Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS. Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control. Identification of green spots evaluates safety benefits of state-of-the-art level 0–2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero.

With the advent of autonomous driving, concepts like road trains or platoons are becoming more popular. In these arrangements, vehicles travel at separations of only 5 to 10m between them. These short inter-vehicle distances allow compacting vehicle flows resulting in increased throughput on highways. In addition, there are also fuel/energy savings as the magnitude of aerodynamic resistance acting on vehicles is reduced. These benefits increase when reducing inter-vehicle separations to below 5m. However, it becomes extremely difficult to guarantee safety, especially, when braking in an emergency. The longitudinal and lateral control systems developed so far aim to achieve string stability in the cruise scenario, i.e., to prevent that small variations at the lead magnify towards the trail. Unfortunately, this has no relevance during emergency braking, since control systems incur saturation, i.e., the condition where computed output brake forces exceed those that can be applied by actuators. This is because all vehicles have to apply their maximum brake forces in order to minimize the stopping distance of the platoon and reach a complete standstill. As a result, emergency braking requires special attention and needs to be designed and verified independent of the cruise scenario. Braking in an emergency is mainly characterized by the problem of heterogeneous deceleration capabilities of vehicles, e.g., due to their type and/or loading conditions. As a result, a deceleration rate possible by one vehicle may not be achievable by its immediately leading or following vehicles. Not addressing this heterogeneity leads to inter-vehicle collisions. Moreover, transitions in the road profile increase the complexity of such brake maneuvers. Particularly, when there is a transition from a flat road to a steep downhill, an already saturated brake controller cannot counteract the effect of the downhill slope. Hence, its deceleration magnitude will be reduced, potentially leading to intra-platoon crashes that would otherwise not occur on a flat road. In this work, we first analyze the problem of emergency braking in platoons operating at inter-vehicle separations below 5m and under idealized conditions (i.e., flat road, instantaneous deceleration, etc.). For this case, we propose a cyber-physical approach based on exploiting space buffers that are present in the separations between vehicles, and compare it with straightforward schemes (such as Least Platoon Length and Least Stopping Distance) in terms of achieved aerodynamic benefits, overall platoon length, and stopping distance. We then consider realistic conditions (in particular, changing road profiles as mentioned before) and investigate how to design a brake-by-wire controller present at each vehicle that accounts for this. We further extend our proposed cyber-physical approach by adding cooperative behavior. In particular, if an individual vehicle is unable to track its assigned deceleration, it coordinates with all others to avoid inter-vehicle collisions, for which we propose a vehicle-to-vehicle (V2V) communication strategy. Finally, we present a detailed evaluation of the proposed cyber-physical approach based on high-fidelity vehicle models in Matlab/Simulink. Even though more work is needed towards a real-life implementation, our simulation results demonstrate benefits by the proposed approach and, especially, its feasibility.

New cooperative intelligent transportation system (C-ITS) applications become enabled thanks to advances in communication technologies between vehicles(V2V) and with the infrastructure (V2I). Communicating vehicles share information with each other and cooperate, which results in improved safety, fuel economy, and traffic efficiency. An example of a C-ITS application is platooning, which comprises a string of vehicles that travel together with short inter-vehicle distances (IVDs). Any solution related to C-ITS must comply with high safety requirements in order to pass standardization and be commercially deployed. Furthermore, trusted safety levels should be assured even for critical scenarios. This thesis studies the conditions that guarantee safety in emergency braking scenarios for heterogeneous platooning, or string-like, formations of vehicles. In such scenarios, the vehicle at the head of the string emergency brakes and all following vehicles have to automatically react in time to avoid rear-end collisions. The reaction time can be significantly decreased with vehicle-to-vehicle (V2V) communication usage since the leader can explicitly inform other platooning members about the critical braking. The safety analysis conducted in the thesis yields computationally efficient methods and algorithms for calculating minimum inter-vehicle distances that allow avoiding rear-end collisions with a predefined high guarantee. These IVDs are theoretically obtained for an open-loop and a closed-loop configurations. The former implies that follower drives with a constant velocity until braking starts, whereas in the latter, an adaptive cruise control (ACC) with a constant-distance policy serves as a controller. In addition, further optimization of inter-vehicle distances in the platoon is carried out under an assumption of centralized control. Such an approach allows achieving better fuel consumption and road utilization. The performed analytical comparison suggests that our proposed V2V communication based solution is superior to classical automated systems, such as automatic emergency braking system (AEBS), which utilizes only onboard sensors and no communication. Wireless communication, enabling to know the intentions of other vehicles almost immediately, allows for smaller IVDs whilst guaranteeing the same level of safety. Overall, the presented thesis highlights the importance of C-ITS and, specifically, V2V in the prevention of rear-end collisions in emergency scenarios. Future work directions include an extension of the obtained results by considering more advanced models of vehicles, environment, and communication settings; and applying the proposed algorithms of safety guaranteeing to other controllers, such as ACC with a constant time headway policy.

Indiana University-Purdue University Indianapolis (IUPUI) / Autonomous Emergency Braking (AEB) system uses vehicle’s on-board sensors such as radar, LIDAR, camera, infrared, etc. to detect the potential collisions, alert the driver and make safety braking decision to avoid a potential collision. Its limitation is that it requires clear line-of-sight to detect what is in front of the vehicle. Whereas, in current V2V (vehicle-to-vehicle communication) systems, vehicles communicate with each other over a wireless network and share information about their states. Thus the safety of a V2V system is limited to the vehicles with communication capabilities. Our idea is to integrate the complementary capabilities of V2V and AEB systems together to overcome the limitations of V2V and AEB systems. In a V2V-AEB system, vehicles exchange data about the objects information detected by their onboard sensors along with their locations, speeds, and movements. The object information detected by a vehicle and the information received through the V2V network is processed by the AEB system of the subject vehicle. If there is an imminent crash, the AEB system alerts the driver or applies the brake automatically in critical conditions to prevent the collision. To make V2V-AEB system advance, we have developed an intelligent heart Monitoring system and integrated it with the V2V-AEB system of the vehicle. The advancement of wearable and implantable sensors enables them to communicate driver’s health conditions with PC’s and handheld devices. Part of this thesis work concentrates on monitoring the driver’s heart status in real time by using fitness tracker. In the case of a critical health condition such as the cardiac arrest of a driver, the system informs the vehicle to take an appropriate operation decision and broadcast emergency messages over the V2V network. Thus making other vehicles and emergency services aware of the emergency condition, which can help a driver to get immediate medical attention and prevent accident casualties. To ensure that the effectiveness of the V2V-AEB system is not reduced by a time delay, it is necessary to study the effect of delay thoroughly and to handle them properly. One common practice to control the delayed vehicle trajectory information is to extrapolate trajectory to the current time. We have put forward a dynamic system that can help to reduce the effect of delay in different environments without extrapolating trajectory of the pedestrian. This method dynamically controls the AEB start braking time according to the estimated delay time in the scenario. This thesis also addresses the problem of communication overload caused by V2V-AEB system. If there are n vehicles in a V2V network and each vehicle detects m objects, the message density in the V2V network will be n*m. Processing these many messages by the receiving vehicle will take considerable computation power and cause a delay in making the braking decision. To prevent flooding of messages in V2V-AEB system, some approaches are suggested to reduce the number of messages in the V2V network that include not sending information of objects that do not cause a potential collision and grouping the object information in messages.

One central challenge for Autonomous Driving (AD) systems is ensuring functional safety. This is affected by all parts of vehicle automation systems: environment perception, decision making, and actuation. The AD system manages its activity towards achieving its goals to maintain in the safety domain, upon an environment using observation through sensors and consequent actuators. Therefore, this research investigates the operational safety for the AD system. In this research, a simulation for the Autonomous Emergency Braking (AEB) system and a simple scenario are constructed on CARLA, an open-source simulator for autonomous driving systems, to investigate the factors that impact the performance of the AEB system. The time-series data that influence the AEB are collected and fed into three time-series analysis algorithms, Autoregressive Integrated Moving Average model (ARIMA), regression tree and Long short-term memory (LSTM), to select a suitable time-series algorithm to be used for the AEB system. The results show that weather, the measurement range of the sensors, and noise can affect the results of the AEB system. After comparing the performance of these three time-series algorithms through contrasting the recall and precision of these three algorithms to detect noise in the data, the results can be obtained that LSTM has the better performance for long-term analysis. And ARIMA is more suitable for short-term time-series analysis. LSTM is chosen to analyze the time-series data, since the long-term time-series analysis is necessary for the AEB system and it can detect the noise in the variables of the AEB system with better performance. / En central utmaning för AD system är att säkerställa funktionell säkerhet. Detta påverkas av alla delar av fordonsautomatiseringssystem: miljöuppfattning, beslutsfattande och aktivering. AD -systemet hanterar sin aktivitet för att uppnå sina mål att upprätthålla inom säkerhetsområdet, i en miljö som använder observation genom sensorer och därav följande ställdon. Därför undersöker denna forskning den operativa säkerheten för AD systemet. I denna forskning konstrueras en simulering för AEB -systemet och ett enkelt scenario på CARLA, en simulator med öppen källkod för autonoma körsystem, för att undersöka de faktorer som påverkar prestandan för AEB systemet. Tidsseriedata som påverkar AEB samlas in och matas in i tre tidsserieanalysalgoritmer, ARIMA, regressionsträd och LSTM, för att välja en lämplig tidsserie-algoritm som ska används för AEB systemet. Resultaten visar att väder, mätområdet för sensorerna och brus kan påverka resultaten av AEB systemet. Efter att ha jämfört prestandan för dessa tre tidsserie-algoritmer genom att kontrastera återkallelsen och precisionen för dessa tre algoritmer för att detektera brus i data kan resultaten erhållas att LSTM har bättre prestanda för långsiktig analys. Och ARIMA är mer lämpad för korttidsanalyser i tidsserier. LSTM väljs för att analysera tidsseriedata, eftersom långsiktig tidsserieanalys är nödvändig för AEB systemet och det kan detektera bruset i variablerna i AEB system med bättre prestanda.