Measurement of Freeway Traffic Flow Quality Using GPS-Equipped Vehicles

The evaluation of freeway service quality is crucial work, and thus, transportation professionals have developed numerous measures including traffic volume, speed, and density. However, recent research efforts have indicated that such traditional measures may not fully reflect the quality of roadway service from the perspective of individual drivers, necessitating the development of alternative approaches that complement or replace the current service quality measures. As an alternative approach, the speed variation of a vehicle has been suggested as a promising indicator of traffic flow quality perceived by individual drivers. In particular, acceleration noise, defined by the standard deviation of the acceleration of a vehicle, has been often studied as a measure of the degree of speed variation. However, previous studies have been limited to the experimental level due to the difficulty in collecting high-resolution vehicle speed profiles for computing acceleration noise. In this dissertation, the characteristics of speed variation, measured by acceleration noise, are investigated using the rich set of GPS data collected from the instrumented vehicles driven by the participants of the Commute Atlanta research program. The employment of the real-world vehicle activity data, composed of every second of vehicle operation, renders this research effort unique and provides an opportunity to investigate the various aspects of acceleration noise in the real-world context. The investigation is performed by relating acceleration noise to its three influential factors: traffic conditions, roadway, and driver/vehicles. In addition, a fuzzy inference system-based methodology, combining vehicle speed and acceleration noise from instrumented vehicles, is proposed as an approach to evaluating traffic flow quality.Ph.D.Committee Chair: Guensler, Randall; Committee Co-Chair: Hunter, Michael; Committee Member: Meyer, Michael; Committee Member: Ogle, Jennifer; Committee Member: Rodgers, Michae

Unraveling the impact of travel time, cost, and transit burdens on commute mode choice for different income and age groups

It is well known that faster and less-expensive transit systems with shorter walking distances, as well as less transfers, are associated with transit use. In this regard, recent studies have focused on estimating transit’s competitiveness and further suggested possible policy interventions. However, there were not much attention on measuring travel time and cost differences between transit and auto by considering the temporal variability. In addition, only a limited study have focused on the impact of either walking during transfers on mode choice or the stage of walking that most affects mode choice. This paper provides additional insights into the impact of travel time, cost, and transit burdens on commute mode choice based on the analysis in a transit-oriented mega city, Seoul, Korea. Together with the 2016 household travel survey data, we utilize the web-based route guide information to measure time, cost, and transit burdens for both chosen and non-chosen modes. The results reveal that commuters are significantly affected by the travel time and cost difference between modes. Additionally, the results indicate that the odds of driving increases by 4.7% and 24.3% when commuters have to transfer once or more than once, respectively. Also, commuters were mostly disinclined to walk longer distances during transfer and egress. The effect of time, cost, and transit burdens on mode choice also varied by income and age groups, further implying the group of people that should be focused when devising policies to encourage transit use. To conclude, this paper suggests potential levers for transportation policies to trigger modal shifts toward sustainable modes by using advanced data sources that better estimate the travel characteristics by departure time based on a point-to-point travel survey data

Exploring factors associated with commute mode choice: An application of city-level general social survey data

Developing sustainable transportation systems in a city can be substantially assisted by promoting environmentally friendly transportation modes such as walking, cycling, and public transit rather than private cars. Strategies for promoting these desirable transportation modes can be effectively identified based on a sound understanding of how citizens choose a travel mode. In this study, we sought to enhance this understanding by exploring factors associated with commute mode choice utilizing data from a general social survey in Seoul, South Korea. Based on the data, parametric and non-parametric statistical models based on classification tree and multilevel logistic regression approaches, respectively, were developed as a way to capture influential factors associated with the mode choice decision. The models illustrate that commuters\u27 socio-demographic characteristics such as income, occupation, gender, and residence duration tend to significantly influence mode choice. In addition, they showed that respondents\u27 attitudes and behaviors, including the amount of time spent on the internet and self-assessed social status, can be strongly associated with mode choice. This study is also meaningful in that it demonstrates the potential applicability of general social survey data for investigating travel behavior considering various factors that are rarely included in general transportation surveys

Investigating commuters’ satisfaction with public transit: A latent class modeling approach

This study explores the factors associated with commute satisfaction of public transit users in the Seoul Metropolitan Area, identifying the critical role of commuters’ attitudes in influencing their commute satisfaction. Using a latent class ordered probit model, the study identifies two latent segments—optimistic multitasker (Class 1) and dissatisfied commuter (Class 2)—assuming that the association between determinants and satisfaction with commute could depend highly on attitudes. A majority of transit commuters (71.8%) belong to Class 1, meaning that most Seoul commuters are satisfied with their commute and use their travel time productively. Moreover, in comparing the two-class profiles, Class 1 commuters tend to be more satisfied with their lifestyle, perceive themselves as healthier, have a positive personality, and are more satisfied with their commute. Such empirical evidence demonstrates the existence of taste heterogeneity in determining commute satisfaction and the role of attitudes in that mechanism

Transit Ridership Evaluation Using Aggregate-Level Causal Analyses of Subway Mode Shares in Seoul, South Korea

Adequate evaluations of transit system efficiency in direct connection with environmental concerns and the economic aspects of the city are critical for development of a better system. This paper presents an evaluation framework by comparing the subway mode shares of 25 districts in Seoul, South Korea. In this effort, causal relationships between the inherent conditions of the district and the resultant mode shares were identified on the basis of regression models with independent variables indicating the system supply level. The expected mode shares from the regression model and the actual shares were then compared as a way to identify districts displaying relatively higher or lower subway mode shares. These processes revealed key influential factors affecting subway mode share and suggest that the system supply level is strongly related to mode share and that ridership increases may be achieved by providing convenient access to stations. The implications of this study are expected to shed light on potential policy actions to improve transit ridership, particularly for those districts with relatively lower levels of ridership