Activity space estimation with longitudinal observations of social media data

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term dataset to address the problems caused by basing activity space studies off short-term data. In total, we use 63,114 geo-tagged tweets from 116 unique users to create individuals’ activity spaces based on minimum bounding geometry (convex hull). By using polygon density maps of activity space, we found clear differences between weekday and weekend activity spaces, and were able to observe the growth trajectory of activity space over 17 weeks. In order to reflect the heterogeneous nature of spatial behavior and tweeting habits, we used Latent Class Analysis twice. First, to identify five unique patterns of location-based activity spaces that are different in shape and anchoring. Second, we identify three unique growth trajectories. The comparison among these latent growth trajectories shows that in order to capture the extent of activity spaces we need long time periods for some individuals and shorter periods of observation for others. We also show that past studies using a single digit number of weeks may not be sufficient to capture individuals’ activity space. The major activity locations identified using a multilevel latent class model, do not appear to be statistically related to the growth patterns of Twitter users activity spaces. The evidence here shows Twitter data can be a valuable complementary source of information for heterogeneity analysis in activity-based modeling and simulation.     

Laboratory alignment procedure for improving reproducibility of tyre wet grip measurement

Since 2012, the Korean and EU governments have been running a tyre labelling system. All tyres sold in Korea have to carry a label that displays information of two performance criteria: rolling resistance and wet grip. The rolling resistance of the tyres determines their fuel efficiency grading, and the wet grip of the tyres determines their braking safety grading. The rolling resistance and wet grip measurements must be reproducible, so the same tests on the same tyres in different laboratories must produce the same results to ensure a fair comparison between tyres from different suppliers. In addition, a good reproducibility of testing results prevents market surveillance authorities from obtaining results different from those provided by suppliers when testing the same tyres. The laboratory alignment procedure for the rolling resistance measurements was developed and published as the EU Commission Regulation No. 1235 in 2011. However, the laboratory alignment procedure for the wet grip measurements has not yet been developed. Therefore, there are many differences in the wet grip test results among test laboratories throughout the world. The new procedure that is proposed for the wet grip measurement alignment for tyre testing laboratories can improve the reproducibility of the wet grip testing results, and five laboratory alignment tests were carried out between KATECH and five other test laboratories in the world to evaluate the results of the proposed procedure.     

Real-Time Longitudinal Location Estimation of Vehicle Center of Gravity

The longitudinal location of a vehicle’s center of gravity (CG) is used as an important parameter for vehicle safety control systems, and can change considerably according to various driving conditions. Accordingly, for the better performance of vehicle safety control systems, it is essential to obtain the accurate CG location. However, it is generally difficult to acquire the value of this parameter directly through sensors due to cost reasons. In this study, a practical algorithm for estimating vehicle’s longitudinal CG location in real time is proposed. This algorithm is derived based only on longitudinal motion of the vehicle, excluding excessive lateral, yaw and roll movements of the vehicle. Moreover, the proposed algorithm has main differences from previous studies in that it does not require information such as vehicle mass, vehicle moments of inertia, road grade or tire-road surface friction, which are difficult to acquire. In the proposed algorithm, the relationship between the ratio of rear-to-front tire longitudinal force and the corresponding wheel slips are used to determine the CG location. To demonstrate a practical use of the proposed algorithm, the ideal brake force distribution is tested. The proposed CG estimation algorithm and its practical use are verified via simulations and experiments using a test vehicle equipped with electro-mechanical brakes in the rear wheels. It is shown that the estimated CG locations are close to the actual ones, and that the deceleration can be maximized by the ideal brake force distribution.     

Model-Based Integrated Control of Engine and CVT to Minimize Fuel Use

In this study, a model-based integrated control method for engines and continuous variable transmissions (CVTs) is developed. CVT refers to a type of transmission which allows an engine to be operated independently with respect to the vehicle speed, with the engine torque and CVT gear ratio controlled in an integrated manner. In the proposed integrated control scheme, engine operating points which minimize the rate of instantaneous fuel consumption are calculated, and the engine target torque and target gear ratio are determined in an integrated manner based on the results of the calculations. Unlike the previous map-based control method, the method introduced in this study does not require an engine torque map or a CVT ratio map for tuning, and the engine torque and CVT ratio are controlled to minimize the amount of fuel used while satisfying the level of acceleration demand from the driver. The control scheme is based on the powertrain model, and the CVT response lag and transmission loss are also considered in the integrated control processes. The algorithm is simulated with various driving cycles, with the simulation results showing that the fuel economy performance of the vehicle system is improved with the newly suggested engine-CVT integrated control algorithm.     

Residential mobility and location choice: a nested logit model with sampling of alternatives

Residential mobility and relocation choice are essential parts of integrated transportation and land use models. These decision processes have been examined and modeled individually to a great extent but there remain gaps in the literature on the underlying behaviors that connect them. Households may partly base their decision to move from or stay at a current location on the price and quality of the available alternatives. Conversely, households that are on the market for a new location may evaluate housing choices relative to their previous residence. How and the degree to which these decisions relate to each other are, however, not completely understood. This research is intended to contribute to the body of empirical evidence that will help answer these questions. It is hypothesized that residential mobility and location choice are related household decisions that can be modeled together using a two-tier hierarchical structure. This paper presents a novel nested logit (NL) model with sampling of alternatives and a proposed procedure for sampling bias correction. The model was estimated using full-information maximum likelihood estimation methods. The results confirm the applicability of this NL model and support similar findings from other empirical studies in the residential mobility and location choice literature.