Pavithra Parthasarathi

Network structure and travel time perception.

The purpose of this research is to test the systematic variation in the perception of travel time among travelers and relate the variation to the underlying street network structure. Travel survey data from the Twin Cities metropolitan area (which includes the cities of Minneapolis and St. Paul) is used for the analysis. Travelers are classified into two groups based on the ratio of perceived and estimated commute travel time. The measures of network structure are estimated using the street network along the identified commute route. T-test comparisons are conducted to identify statistically significant differences in estimated network measures between the two traveler groups. The combined effect of these estimated network measures on travel time is then analyzed using regression models. The results from the t-test and regression analyses confirm the influence of the underlying network structure on the perception of travel time.

Induced Demand: A Microscopic Perspective

This paper analyses the induced demand hypothesis using a disaggregate approach at the link level. A panel data-set of Minneapolis-Saint Paul highway network for the years 1980-98 is constructed. A model that predicts the traffic flow on the link in terms of vehicle kilometres travelled (VKT) based on the flow and capacity conditions existing on the link in the previous years is specified and estimated. The flow and capacity conditions existing on the identified neighbouring parallel links are also taken into account. Socio-demographic characteristics like population of the Minor Civil Division (MCD) to which the link belongs and the surrounding MCDs are also considered. The results indicate that capacity enhancements in the previous years, given by lane additions, have a positive and significant effect on the VKT of the link, confirming the induced demand hypothesis. The elasticities are lower than reported in previous research, indicating the importance of separating new construction from the expansion of existing links.

Network Structure and Spatial Separation

This research aims to identify the role of network architecture in influencing individual travel behavior using travel survey data from Minneapolis-Saint Paul and Florida (Fort Lauderdale and Miami). Various measures of network structure, compiled from existing sources, are used to quantify roadway networks, and to capture the arrangement and connectivity of nodes and links in the networks and the spatial variations that exist among and within networks. The regression models show that travel behavior is correlated with network design.

Street network structure and household activity spaces

This research analyses the influence of street network structure on household travel patterns, as measured by activity spaces. The analysis uses street network and travel survey data from the Minneapolis – St. Paul (Twin Cities) and Miami – Ft. Lauderdale (South Florida) metropolitan areas. Various measures of street network structure are used to quantify street network structure. The activity space polygon for each household in the travel survey data set is identified by combining the destinations reached by all household members on the given travel day including the household location. Statistical regression models are then estimated for each study area to test the relationship between street network structure and household activity space. The results show that network structure has a significant influence on household travel patterns, after controlling for other non-network variables such as accessibility to jobs and shops, and car ownership.

Network Structure and Activity Spaces

This research analyzes the influence of network structure on household spatial patterns, as measured by activity spaces. The analysis uses street network and travel survey data from the Twin Cities and South Florida to compile measures of network structure. Statistical regression models test the relationship between network structure and travel. The results show that network design does influence travel, after controlling for other non-network based measures. Results from this analysis can be used to understand how changes in network can be used to bring about desired changes in travel behavior.

The Influence of Network Structure on Travel Distance

The objective of this research is to identify the role of network architecture in influencing individual travel behavior using travel survey data from two urban areas in Florida: Fort Lauderdale and Miami. Various measures of network structure, compiled from existing sources, are used to quantify roadway networks, capture the arrangement and connectivity of nodes and links in the networks and the temporal and spatial variations that exist among and within networks. The results from the regression models estimated show that network design influences how people travel and make decisions. Results from this analysis can be used to understand how changes in network can be used to bring about desired changes in travel behavior.

Freeway Service Patrols

Highway assistance services, also called the freeway service patrols (FSPs), are one of the main approaches used by incident management programs. The objective of this study was to investigate the factors that contribute to people choosing to rely on the highway assistance services (FSP) in comparison to private assistance services such as the Automobile Association of America (AAA). Further the effectiveness of the Freeway Service Patrol was studied by carrying out a Benefit-Cost Analysis using Los Angeles as a test case. The results indicate that the probability that an individual would choose to depend on the highway assistance services depends on the key attributes like the annual fee of the program, the fee at the time of assistance, the time of waiting for assistance and cost of breakdown. The B/ C ratio for the Los Angeles FSP was calculated to be 5.91.

An economic evaluation of freeway service patrols

Highway assistance services, also called the freeway service patrols (FSPs), are one of the main approaches used by incident management programs. The objective of this study was to investigate the factors that contribute to people choosing to rely on the highway assistance services (FSP) in comparison to private assistance services such as the Automobile Association of America (AAA). Further the effectiveness of the Freeway Service Patrol was studied by carrying out a benefit-cost analysis using Los Angeles as a test case. The results indicate that the probability that an individual would choose to depend on the highway assistance services depends on the key attributes like the annual fee of the program, the fee at the time of assistance, the time of waiting for assistance and cost of breakdown. The B/C ratio for the Los Angeles FSP was calculated to be 5.91.

Accessibility Futures: Accessibility Futures

This study uses accessibility as a performance measure to evaluate a matrix of future land use and network scenarios for planning purposes. The concept of accessibility dates to the 1950s, but this type of application to transportation planning is new. Previous research has established the coevolution of transportation and land use, demonstrated the dependence of accessibility on both, and made the case for the use of accessibility measures as a planning tool. This study builds off of these findings by demonstrating the use of accessibility-based performance measures in the Twin Cities Metropolitan Area. This choice of performance measure also allows for transit and highway networks to be compared side-by-side. For roadway modeling, zone-to-zone travel time matrix was computed using stochastic user equilibrium (SUE) assignment with travel time feedback to trip distribution. A database of schedules was used on the transit networks to assign transit routes. This travel time data was joined with the land use data from each scenario to obtain the employment, population, and labor accessibility from each traffic analysis zone (TAZ) within specified time ranges. Tables of person-weighted accessibility were computed for 20 minutes with zone population as the weight for employment accessibility and zone employment as the weight for population and labor accessibility. Maps of accessibility by zone were produced to show the spatial distribution of accessibility across the region. The results show that a scenario where population and employment growth are concentrated in the center of the metropolitan area would produce the highest accessibility no matter which transportation network changes are made. However, another scenario which concentrates population growth in the center of the metropolitan area and shifts employment growth to the periphery consistently outperforms the scenario representing the projected 2030 land use without any growth management strategy.