The projected growth of persons ages 65 and older in the U.S. over the next few decades will usher in an era of unprecedented numbers of seniors licensed to drive. For some members of this group, there will come a time where driving will have to cease due to a variety of factors. At that juncture in their lives, these seniors may have to consider transportation alternatives other than the personally operated vehicle. The objective of this study is to evaluate potential changes in transit market share arising from travel behavior changes of seniors who lose their driving privileges. This includes determining seniors interest in, ability to, and subsequent use of public transit. First, a literature review of developments that have impacted senior travel behavior is presented. Developments such as the changing demographics of seniors, senior socio-economic status, the process of driving retirement, and factors influencing transit use by seniors are presented. Estimates of the numbers of licensed and former drivers are derived for the year 2030 using several methodological approaches. Trip rates are applied to the predicted non-driving population to derive estimates of the potential demand for transit and subsequent market share. Discussion of the estimated market share results also incorporates a descriptive overview of senior travel behavior as derived from analyses of publicly available datasets followed by focus group results illustrating the experiences of seniors and their transportation choices.Recommendations range from transit agencies engaging in direct "generational" marketing to seniors in order to understand their transportation needs as well as perceptions about transit, promoting the use of transit, and demonstrating the viability of transit for specific trip purposes and partner with rideshare providers. Despite the predicted increase in transit market shares attributable to the senior population, transit providers have extensive work to do to change the perceptions of transit service provision and subsequently encourage the use of such services by senior populations in forthcoming generations if transit is to become a viable transportation alternative for those seniors ceasing to drive.

Over the past few years automotive and technology companies have made significant advances in what has been traditionally a completely human function: driving. Crash avoidance features such as lane departure warning and forward collision warning are becoming increasingly more common and cheaper to obtain, even on non-luxury vehicles. Technology companies and auto manufacturers have announced plans to have self-driving vehicles ready for public use as early as 2020. The mass adoption of automated vehicles (AVs) could significantly change surface transportation as we know it today. This thesis is intended to provide a technical analysis of the potential impacts of AVs on current light-duty vehicle miles traveled (VMT) and parking decisions, the economic desirability of widespread deployment of partially automated technologies, and methods for existing roadways to transition to connected and automated vehicle (CAV) transportation, so that policymakers can make more informed decisions during the transition to CAVs. This work takes a look at AVs from a point in time where vehicles are equipped with driver assistance systems (Level 1) to a point in time where AVs are driverless (Level 5) and can self-park. The results of this work indicate that the fleet-wide adoption of partially automated crash avoidance technologies could provide net-benefit of about $4 billion at current system effectiveness and could provide an annual net-benefit up to $202 billion if all relevant crashes could be prevented. About 25% of all crashes could be addressed by the crash avoidance technologies examined in this dissertation. Over time, as technologies become more effective and cheaper due to economies of scale, greater benefits than the $4 billion could be realized. As automated technologies become more advanced and widespread, existing roadways will need to be able to accommodate these vehicles. This work investigates the effects of a dedicated truck platoon lane on congestion on the Pennsylvania Turnpike and provides a method for existing roadways and highways to determine viable platoon demonstration sites. The initial results suggest that there are several sections of turnpike that could serve as commercial truck platoon demonstration site while still providing a high LOS to all other vehicles. Once AVs can safely and legally drive unoccupied, vehicles will no longer be limited to their driver’s destination and can search for cheaper parking in more distant parking locations. This work simulates a fleet of privately owned vehicles (POVs) in search of cheaper parking in Seattle, using a rectangular grid throughout the study area. Model results indicate that we are not likely to see significant increase in vehicle miles traveled (VMT) and energy use from cars moving from downtown parking lots to cheaper parking in distance locations but at higher penetration rates, parking lot revenues could likely decline to the point where operating a lot is unsustainable economically, if no parking demand management policies are implemented. Driverless vehicles also promise to increase mobility for those in underserved populations. This work estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. Three demand wedges were established in order to conduct a first-order bounding analysis. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. AV technology holds much promise in providing a more accessible and safe transportation system. This thesis can help policymakers and stakeholders maximize the benefits and minimize the challenges.