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The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

The performance of structure-borne road NVH can be cascaded down to three major systems: 1) vehicle body structure, 2) chassis/suspension, 3) tire/wheel. The forces at the body attachment points are controlled by the isolation efficiency of the chassis/suspension system and the excitation at the spindle/knuckle due to the tire/road interaction. The chassis force transmissibility is a metric to quantify the isolation efficiency. This paper presents a new experimental methodology to estimate the chassis force transmissibility from a fully assembled vehicle. For the calculation of the transmissibility, the spindle force/moment estimation and the conventional Noise Path Analysis (NPA) methodologies are utilized. A merit of the methodology provides not only spindle force to body force transmissibility but also spindle moment to body force transmissibility. Hence it enables us to understand the effectiveness of the spindle moments on the body forces.

Past studies have shown that NVH CAE tire model quality is not adequate to correctly capture a mid-frequency range (100-300 Hz). A new methodology has been developed to estimate tire forces that are independent of dynamic characteristics of vehicle suspension and rig test fixture. The forces are called tire blocked forces and defined as a force generated by a tire/wheel system whose boundary condition is constrained. The tire blocked force is estimated by removing the dynamic effect of the tire force measurement fixture. The blocked forces can be applied to CAE models to predict vehicle road NVH responses. This new method can also be used as a target setting tool. Tire suppliers can check the blocked tire forces from the rig testing data against a force target before they submit tires to automotive manufacturers for evaluations on a prototype vehicle.

Explicit finite element simulations were conducted on an aluminum wheel model where a rotating bend moment was applied on its hub to simulate wheel cornering fatigue testing. A post-processor was developed to calculate equivalent von Mises alternating and mean stresses from stress tensor. The safety factors of fatigue design for each finite element were determined to assess the fatigue performance by utilizing the Goodman linear relationship. Elements with low safety factors were identified due to the prescribed boundary conditions and stress concentrations arising from wheel geometry.

The world urbanization is growing rapidly, bringing many challenges for people to move in dense metropolitan regions. Public transportation is not able to attend the whole demand, and individual transportation modes are struggling with traffic congestion and stringent regulations to reduce its attractiveness, such as the license plate restriction in São Paulo. On the other hand, enablers like smartphones mass penetration, GPS connected services and shared economy have opened space to a whole new range of possible solutions to improve people perception on urban mobility. This work aims to evaluate the modal choice behavior models and understand the success factor of current mobility solutions in the city of São Paulo. The data available through origin/destination researches will be used to validate the models used in this work.

Plug in hybrid electric vehicles (PHEVs) have gained interest over last decade due to their increased fuel economy and ability to displace some petroleum fuel with electricity from power grid. Given the complexity of this vehicle powertrain, the energy management plays a key role in providing higher fuel economy. The energy management algorithm on PHEVs performs the same task as a hybrid vehicle energy management but it has more freedom in utilizing the battery energy due to the larger battery capacity and ability to be recharged from the power grid. The state of charge (SOC) profile of the battery during the entire driving trip determines the electric energy usage, thus determining overall fuel consumption.

Current CAE modeling and simulation techniques in the time domain allow, by now, very accurate prediction of many ride-comfort performances of the cars. Nevertheless, the prediction of the steering wheel rotation vibration excited by, for instance, wheel unbalance or asymmetric obstacle impact, often runs into the difficulty of modeling the steering line with sufficient accuracy. For a classic rack and pinion, hydraulic assisted steering line, one of the challenges is to model the complex and non linear properties - stiffness, friction and damping - of the rack-rack case system. This paper proposes a rack model, thought for easy implementation in complex multi-body models, and an identification procedure of its parameters, based on measurements, in the operational range of the wheel unbalance excitation. The measurements have been gathered by specific tests on the components and the test set-up is also shown here.

Vehicle dynamics CAE capabilities has increased in the past few years, specially, for handling and steering attributes. However, secondary ride simulations are still highly depended on the tire model. Such tire model must be capable to simulate high order phenomenon such as impact and harshness transmissibility in three directions. In order to gather tire information sufficient to cope with these phenomena, one needs to perform a series of specific tests, and so be able to build the intended tire model. Still, there could be correlation issues. This whole process takes a lot of time and resources. This article presents a semi-analytical approach, using data gathered via wheel force transducers (WFTs) that are typically used for load cascading and durability purposes. The method main advantage is that since it relies on measured data at the wheel center, it is independent of a tire model, and, as such, it demands less time and resources.

The development of the Advanced Restraint System has lead to an innovative way in which we evaluate the systems effect on the occupant. This paper presents some initial investigation into the driver airbag system that consists of an inflator, cushion fold, tear seam pattern, and offset of the airbag cover to steering wheel rim plane. An initial DOE is reviewed to establish significant parameters and to identify equations for further investigation.

This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.

This paper proposes a method to make diagnostic/prognostic judgment about the health of a tire, in term of its wear, using existing on-board sensor signals. The approach focuses on using an estimate of the effective rolling radius (ERR) for individual tires as one of the main diagnostic/prognostic means and it determines if a tire has significant wear and how long it can be safely driven before tire rotation or tire replacement are required. The ERR is determined from the combination of wheel speed sensor (WSS), Global Positioning sensor (GPS), the other motion sensor signals, together with the radius kinematic model of a rolling tire. The ERR estimation fits the relevant signals to a linear model and utilizes the relationship revealed in the magic formula tire model. The ERR can then be related to multiple sources of uncertainties such as the tire inflation pressure, tire loading changes, and tire wear.

Autonomous vehicles are expected to change our lives with significant applications like on-demand, shared autonomous taxi operations. Considering that most vehicles in a fleet are parked and hence idle resources when they are not used, shared on-demand services can utilize them much more efficiently. While ride hailing of autonomous vehicles is still very costly due to the initial investment, a shared autonomous vehicle fleet can lower its long-term cost such that it becomes economically feasible. This requires the Shared Autonomous Vehicles (SAV) in the fleet to be in operation as much as possible. Motivated by these applications, this paper presents a simulation environment to model and simulate shared autonomous vehicles in a geo-fenced urban setting.

The interaction of Connect and Automated vehicles (CAV) with regular vehicles in the traffic stream has been extensively researched. Most studies, however, focus on calibrating driver behavior models for CAVs based on various levels of automation and driver aggressiveness. Other related studies largely focus on the coordination of CAVs and infrastructure like traffic signals to optimize traffic. However, the effects of different strategic flow management of CAVs in the traffic stream in the comparative scenario-based analysis is understudied. Thus, this study develops a framework and simulations for integrating CAVs in a corridor section. We developed a calibrated model with CAVs for a corridor section in Corktown, Michigan, and simulate how dedicated CAV lane operations can be implemented without significant change in existing infrastructure.

The unpleasant noise (creak) originated from latch-striker interaction, perceived mainly when the vehicle is submitted to uneven road conditions is generated by stick-slip phenomenon mainly due materials incompatibility of contact surfaces. Generally, eliminate this incompatibility is unfeasible due technical and/or economics constrains; this scenario makes it necessary to act in other fronts to neutralize the effects of that incompatibility. Reduce the coefficient of friction from one of contact surfaces is an alternative that can be easily applied at striker through a thin thickness coating with that property.

In this study, tests were performed with modified tires at the right rear location on a solid axle sport utility vehicle to compare vehicle inputs and responses from both: (1) staged tire tread belt detachments, and (2) stepped diameter (“lumpy”) tires. Lumpy tires consist of equal size sections of tread that are vulcanized at equidistant locations around the outer circumference of the tire casing. Some have used lumpy tires in attempt to model the force and displacement inputs created by a tire tread belt separation. Four configurations were evaluated for the lumpy tires: 1-Lump, 2-Lump (2 lengths), and 3-Lump.

Durability of automotive structures is a primary engineering consideration that is evaluated during a vehicle's design and development. In addition, it is a basic expectation of consumers, who demand ever-increasing levels of quality and dependability. Automakers have developed corporate requirements for vehicle system durability which must be met before a products is delivered to the customer. To provide early predictions of vehicle durability, prior to the construction and testing of prototypes, it is necessary to predict the forces generated in the vehicle structure due to road inputs. This paper describes an application of the “virtual proving ground” approach for vehicle durability load prediction for a vehicle on proving ground road surfaces. Correlation of the results of such a series of simulations will be described, and the modeling and simulation requirements to provide accurate simulations will be presented.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

Along with the development and marketability of vehicles without an internal combustion engine, electrically heated surfaces within these vehicles are getting more and more important. They tend to have a quicker response while using less energy than a conventional electric heater fan, providing a comfortable temperature feel within the cabin. Due to the big area of heated surface it is important to spread the heating power in a way that different heat conduction effects to underlying materials are considered. In case an accurate sensor feedback of the targeted homogeneous surface temperature cannot be guaranteed, a thermal energy model of the heated system can help to set and maintain a comfortable surface temperature. For a heated steering wheel development project, different models have been created to meet that aim using mechanistic approaches starting with a predominantly first-order dynamics model and ending with a distributed parameter multi-feedback system.

This paper presents the characterization of the random noise in driveline output shaft torque measurements that is commonly induced by road disturbances. To investigate the interaction between the shaft torque and road side excitation, torque signals are measured using a magnetoelastic torque sensor, as well as a conventional strain gauge sensor, under various types of road surfaces and conditions such as unevenness. A generalized de-trending method for producing a stationary random signal is first conducted. Statistical methods, in particular the probability density function and transform technique, are utilized to provide an evident signature for identifying the road excitation effect on the vehicle output shaft torque. Analysis results show how the road surface can act as a disturbance input to the vehicle shaft torque.

In the last years various advanced driver assistance systems (ADAS) have been introduced on the market. More highly advanced functions up to automated driving functions are currently under research. By means of these functions partly automated driving in specific situations is already or will be realized soon, e.g. traffic jam assist. Besides the technical challenges to develop such automated driving functions for complex situations, e.g. construction or intersection areas, new approaches for the evaluation of these functions under different driving conditions are necessary, in order to assess the benefits and identify potential weaknesses. Classical approaches for evaluation and market sign off will require an extensive testing, which results in high costs and time demands. Therefore the classical approaches are hardly feasible taking into account higher levels of support and automation. Today the final sign-off requires a high amount of real world tests.