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The purpose of this paper is to demonstrate the impact of low- floor bus seating configuration, passenger load factor (PLF) and passenger characteristics on individual boarding and disembarking (B-D) times -a key component of vehicle dwell time and overall transit system performance. A laboratory study was conducted using a static full-scale mock-up of a low-floor bus. Users of wheeled mobility devices (n=48) and walking aids (n=22), and visually impaired (n=17) and able-bodied (n=17) users evaluated three bus layout configurations at two PLF levels yielding information on B-D performance. Statistical regression models of B-D times helped quantify relative contributions of layout, PLF, and user characteristics viz., impairment type, power grip strength, and speed of ambulation or wheelchair propulsion. Wheeled mobility device users, and individuals with lower grip strength and slower speed were impacted greater by vehicle design resulting in increased dwell time.

Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.

The characterization of human drivers' performance is of great significance for highway design, driver state monitoring, and the development of automotive active safety systems. Many earlier studies are restricted by experimental scope, the number and diversity of human subjects, and the accuracy and extent of measured variables. In this work, driver lateral control performance on limited-access highways is quantified by utilizing a comprehensive naturalistic driving database, with the emphasis on measures of vehicle lateral position and time to lane crossing (TLC). Normative values at various speed ranges are reported. The results represent a statistical view of baseline on-road naturalistic driving performance, and can be used for quantitative studies such as driver impairment and alertness monitoring, the triggering of lane departure warning systems, and highway design.

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each other in close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces greenhouse gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel.

Strain gage instrumented transducers were used to measure the cord loads at a number of locations in several different automotive tires loaded against both flat and cylindrical road wheel surfaces. The two basic types of cord load fluctuation encountered in all automobile tires have been identified from these measurements, and the most severe location for cord load fluctuations has been closely bracketed. By these measurements, it has been possible to show that for each tire definite relations exist between the cord loads induced while running on a cylindrical drum and while running on a flat surface. The maximum cord load fluctuations in a tire are the same for the NBS roadwheel and flat surface when the tire is loaded against the roadwheel with a load of between 85 and 90% of that used on the flat surface.

Testing for vehicle emissions and fuel economy certification occurs primarily on chassis dynamometers in a laboratory setting and therefore the actual road conditions, such as forces due to tire rolling resistance and internal friction, must be simulated. Test track coastdown procedures measure vehicle road load forces and produce an equation which relates these forces to velocity. The recent inclusion of onboard anemometry has allowed the coastdown procedure to account for varying wind effects; however, the new anemometer based mechanical loss coefficients do not take into account ambient weather conditions. The two purposes of this study are (1) to determine the new tire rolling resistance temperature correction coefficient that should be used when test ambient temperature is different from the standard reference value of 68°F, and (2) to investigate the effects of auxiliary measurements, such as other ambient conditions and vehicle settings, on this correction coefficient.

Intelligent Vehicle-Highway Systems (IVHS) improve the operation of cars and trucks on public roads by combining information technology with road transportation technologies. The basic ideas about IVHS are by no means new but a number of converging forces have encouraged significant IVHS development in North America recently. Based on the results of a Delphi survey to project realistic future scenarios, both applied and fundamental research agenda are being formulated in a Michigan-based IVHS program to push the IVHS technologies for advanced motorist information systems and for backup vehicle controls under emergency conditions. The scope of the research agenda includes social/human elements as well as hardware and software technological systems. The Michigan research program is expected to contribute to the development of IVHS in North America, both technically and institutionally.

As intelligent automated vehicle technologies evolve, there is a greater need to understand and define the role of the human user, whether completely hands-off (L5) or partly hands-on. At all levels of automation, the human occupant may feel anxious or ill-at-ease. This may reflect as higher stress/workload. The study in this paper further refines how perceived workload may be determined based on occupant physiological measures. Because of great variation in individual personalities, age, driving experiences, gender, etc., a generic model applicable to all could not be developed. Rather, individual workload models that used physiological and vehicle measures were developed.

Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly. The next question usually is “How likely is it that the task will exceed some limit?”

As new technology is added to vehicles and traffic congestion increases, there is a concern that drivers will be overloaded. As a result, there has been considerable interest in measuring driver workload. This can be achieved using many methods, with subjective assessments such as the NASA Task Loading Index (TLX) being most popular. Unfortunately, the TLX is unanchored, so there is no way to compare TLX values between studies, thus limiting the value of those evaluations. In response, a method was created to anchor overall workload ratings. To develop this method, 24 subjects rated the workload of clips of forward scenes collected while driving on rural, urban, and limited-access roads in relation to 2 looped anchor clips. Those clips corresponded to Level of Service (LOS) A and E (light and heavy traffic) and were assigned values of 2 and 6 respectively.

Many highway accidents are caused by distracted drivers and those suffering from drowsy driver syndrome. A driver alert indicating a lane departure could thwart such accidents, saving lives and making our roads safer. Products called Lane Departure Warning Systems (LDWS) have been developed to alert drivers of a lane departure. However, due to their high cost, lane departure warning systems are available only on luxury vehicles, barring their benefits from the majority of drivers. With Field Programmable Gate Arrays (FPGA) becoming more powerful and more affordable, a LDWS implementation utilizing hardware rather than software to conduct image processing eliminates the need for a costly high-power microprocessor, and could bring LDWS to a broader user base. This paper will discuss an FPGA based approach to LDWS. The proof-of-concept system is based on a Xilinx FPGA, taking its image data from an off-the-shelf NTSC camera.

Many Intelligent Transportation System (ITS) technologies have been developed to improve the safety and efficiency of cars, trucks, public transport and infrastructure. However, very few ITS have been developed specifically for the motorcycle user protection. In this paper an analysis of dynamic and static communications tests between a vehicle and two motorcycles are provided. The system enables vehicles and motorcycles to exchange safety information such as speed, heading, location, and brake status through the use of 5.9 GHz Dedicated Short Range Communication (DSRC) protocol. The vehicles and motorcycles can then assess the potential threat level based on the incoming messages from the nearby traffic. Several high-impact motorcycle-to-vehicle collision scenarios are analyzed. Technical challenges, such as motorcycle wireless unit antenna direction performance, communication performance and target classification accuracy are further investigated.

At the forefront of intelligent vehicle technologies are vehicle-to-vehicle communication (V2V) and vehicle-infrastructure integration (VII). Their capabilities can be added to currently-available systems, such as adaptive cruise control (ACC), to drastically decrease the number and severity of collisions, to ease traffic flow, and to consequently improve fuel efficiency and environmental friendliness. There has been extensive government, industry, and academic involvement in developing these technologies. This paper explores the capabilities and challenges of vehicle-based technology and examines ways that policymakers can foster implementation at the federal, state, and local levels.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

Lean NOx Traps (LNTs) are one type of lean NOx reduction technology typically used in smaller diesel passenger cars where urea-based Selective Catalytic Reduction (SCR) systems may be difficult to package . However, the performance of lean NOx traps (LNT) at temperatures above 400 C needs to be improved. The use of Rapidly Pulsed Reductants (RPR) is a process in which hydrocarbons are injected in rapid pulses ahead of a LNT in order to expand its operating window to higher temperatures and space velocities. This approach has also been called Di-Air (diesel NOx aftertreatment by adsorbed intermediate reductants) by Toyota. There is a vast parameter space which could be explored to maximize RPR performance and reduce the fuel penalty associated with injecting hydrocarbons. In this study, the mixing uniformity of the injected pulses, the type of reductant, and the concentration of pulsed reductant in the main flow were investigated.

A method has been developed for calculating the internal temperature distribution in an aircraft tire while free rolling under load. The method uses an approximate stress analysis of each point in the tire as it rolls through the contact patch, and from this stress change the mechanical work done on each volume element may be obtained and converted into a heat release rate through a knowledge of material characteristics. The tire cross-section is then considered as a body with internal heat generation, and the diffusion equation is solved numerically with appropriate boundary conditions at the wheel and runway surface. Comparisons with buried thermocouples in actual aircraft tires shows good agreement.

This paper presents the theory and experimental performance of a system for detecting engine misfires in automobiles. The method is potentially suitable for meeting the California Air Resources Board (CARB) requirements under On Board Diagnostics II (OBDII) rules. The instrumentation for the present method measures (noncontacting) crankshaft instantaneous angular speed. Highly efficient signal processing algorithms permit detection of each individual misfire. The performance of the present method is expressed in terms of error rates made in detecting individual misfires. Normal operating conditions yield error rates under 10-4. Under worst case conditions consisting of light load, high RPM and rough roads with the torque converter in lockup are under 10-3.

Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.

This study was designed to investigate how the spectral power distribution (SPD) of LED headlamps (including correlated color temperature, CCT) affects both objective driving performance and subjective responses of drivers. The results of this study are not intended to be the only considerations used in choosing SPD, but rather to be used along with results on how SPD affects other considerations, including visibility and glare. Twenty-five subjects each drove 5 different headlamps on each of 5 experimental vehicles. Subjects included both males and females, in older (64 to 85) and younger (20 to 32) groups. The 5 headlamps included current tungsten-halogen (TH) and high-intensity discharge (HID) lamps, along with three experimental LED lamps, with CCTs of approximately 4500, 5500, and 6500 K. Driving was done at night on public roads, over a 21.5-km route that was selected to include a variety of road types.

Security is a huge concern in VANETs (Vehicular Ad hoc NETworks) since the information being conveyed may affect life-or-death decisions. One of the security concerns is the Sybil Attack. This attack attempts to create multiple identities to disrupt or control the network. A malicious node utilizing the Sybil Attack in VANETs can disrupt the network in various ways. It can create a large number of Sybil nodes to intervene in message forwarding, potentially causing a massive pileup and great loss of life. A malicious node can also use the Sybil Attack to create illusions of traffic congestions, getting other drivers to take alternate routes and leaving a clear path for the malicious node to its destination. In this paper, we discuss several defense strategies for the Sybil Attack in VANETs.