Kara Kockelman

University of Texas at Austin | UT · Department of Civil, Architectural & Environmental Engineering

This paper presents a microsimulation analysis of interdependent evacuation decisions concerning departure times and destination choices in the hurricane-vulnerable coastal area of Houston, TX. Utilizing cumulative prospect theory (CPT), two predominant behaviors were identified: those of risk-conscious- and time-cautious evacuees. Risk-conscious e...

The increasing demand for electricity from electric vehicles (EVs) will require new paradigms to guarantee reliable and low-cost electricity. This study evaluated an approach to coupling an agent-based travel demand simulator and an electricity grid model to assess the economic costs of supplying power to meet this additional demand in Chicago. The...

Power companies are developing plug-in electric vehicle (EV) smart charging programs to shift charging to off-peak hours, when demand is lower, and to align charging with renewable energy. An internet-based survey of over 1,000 Americans ascertains opinions on supplier-managed charging (SMC) programs and the expected benefits of program participati...

An increasing number of battery-electric vehicles (BEVs) have bidirectional charging technology that provides motorists, homeowners, and power grid operators with new benefits. The study investigates the willingness of over 300 Americans to pay for added bidirectional charging features, namely, Vehicle-to-Load (V2L), Vehicle-to-Home (V2H), and Vehi...

Power companies are developing plug-in electric vehicle smart charging programs to shift charging to off-peak hours when demand is lower and to align charging with renewable energy. Anticipating public acceptance and attitudes toward smart charging programs can ensure a sustainable transportation-clean energy transition. An internet-based survey of...

Parking spots are a premium commodity, especially in dense downtown settings, so this study examines the service impacts of shared autonomous vehicles (SAVs) parking in legal on- or off-street locations when idle across Travis County in Austin, Texas. Using an agent-based activity-based travel demand model with dynamic traffic simulation, two restr...

This paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand...

Vehicle automation and smartphone app-based ride-splitting are commonly discussed topics in the transportation literature. While these technologies have been examined for their role in transportation decarbonization through simulation study, the motivation for such work is rarely made explicit. In this commentary, we provide a motivation for resear...

Fleets of electric vehicles will likely shift electricity demand, and the effect of upstream charging emissions will come from generation sources that are dispatched in response. This study proposes a multi-stage charging and discharging problem to translate low-cost energy transactions into vehicle dispatch decisions. A day-ahead charging optimiza...

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and...

Fleets of electric vehicles will likely shift electricity demand, and the effect of upstream charging emissions will come from generation sources that are dispatched in response. This study proposes a multi-stage charging and discharging problem to translate low-cost energy transactions into vehicle dispatch decisions. A day-ahead charging optimiza...

This paper studies the frequency of traffic crashes at intersections across Texas by employing Zero-inflated Negative Binomial (ZINB) and Negative Binomial-Lindley (NB-L) generalized linear models, as well as various tree-based machine learning (ML) methods, namely Random Forests (RF), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Ma...

This paper explores the effects of day of week and season of year demand variations for shared rides, along with realistic travel party sizes, on shared autonomous vehicle (SAV) services across the Austin, Texas region. Using the agent-based POLARIS program, synthetic person-trips that reflect travel-party size (from one to four persons) and demand...

Understanding the preferences for new and future transportation technologies is important to ensure an efficient and equitable future transportation system. A survey was conducted of Americans’ preferences for several such technologies. Americans are concerned about vehicle range and charging station availability for electric vehicles (EVs) and hes...

Parking spots are a premium commodity, especially in dense downtown settings, so this study examines the service impacts of Shared Autonomous Vehicles (SAVs) parking in legal on-or off-street locations when idle across Travis County in Austin. Using an agent-based activity-based travel demand model with dynamic traffic simulation, two restricted-pa...

Using over a thousand Americans’ population-weighted responses to a long-distance travel survey, this paper examines reductions in trips over 75-miles (one-way) in 2020, during the pandemic, versus behaviors in 2019. Negative binomial models of trip counts suggest that people age 25 to 64 took 0.20 fewer annual long-distance business trips during t...

This study analyzes pedestrian crash counts at more than one million intersections and midblock segments using Texas police reports over ten years. Developing large-scale micro-level analyses is challenging due to the lack of geographic information and characterization at a statewide scale. Therefore, key contributions include methods for obtaining...

This research monetizes the access benefits of making shared autonomous vehicles (SAVs) available to residents of Texas’ Dallas-Fort Worth metroplex in the U.S. Residents’ willingness to pay for SAV access under different fares and modes was estimated and compared across the region’s 5,386 traffic zones, with emphasis on those housing the regions’...

Sharing vehicles and rides may become the norm with public use of fully-automated self-driving vehicles in the near future, assuming pandemic-related health concerns fade. Dynamic ride-sharing (DRS) or ride-pooling of trips can significantly improve system performance by lowering empty vehicle-miles traveled (eVMT) and increasing average vehicle oc...

The emergence of on-demand shared autonomous electric vehicle (SAEV) service requires careful charging station planning and a joint charging and repositioning strategy to mitigate empty travel. This study couples charging and repositioning events as a means of improving service quality (rider wait times), reducing empty travel due to repositioning...

Objective: This study investigates various risk factors associated with pedestrian crash occurrence and injury severity based on 78,497 reported pedestrian-involved crashes across Texas from 2010 through 2019. Methods: Crashes are mapped to over 708,738 road segments, along with road design, land use, transit, hospital, rainfall, and other locat...

This paper overviews emerging technology development by emphasizing Connected, Automated, Shared, and Electric (CASE) technologies. Existing literature on 15 CASE technologies is reviewed, and adds to the literature by consolidating important predictions of CASE-related technologies, services, and policies. Connected and automated technologies have...

Animal-vehicle collisions (AVCs) are common around the world and result in considerable loss of animal and human life, as well as significant property damage and regular insurance claims. Understanding their occurrence in relation to various contributing factors and being able to identify high-risk locations are valuable to AVC prevention, yielding...

Vehicle electrification delivers fast decarbonization benefits by significantly improving vehicle efficiency and relying on less carbon-intense feedstocks. As power grids transition away from carbon-intensive generation and battery energy density improves, the transportation sector’s greenhouse gas savings may deliver upwards of a 75% reduction in...

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM conne...

Autonomous vehicles are not a panacea for the issues that currently plague transportation systems. Smart policies — which are flexible enough to deal with emerging technologies — are required to help cities and states realize the benefits of these vehicles.

The increasing demand for shared mobility services has led to multiple Public-Private Partnerships (PPP), where public transit agencies and mobility providers work together to increase transit service coverage. However, several partnerships have failed due to budget constraints and lack of ridership. Furthermore, the limited data-sharing agreements...

Machine learning (ML) is being used regularly in many different fields. This paper compares traditional econometric methods that have better explanations of data analysis to ML methods, focusing on predicting, understanding and unpacking ML methods which have higher prediction accuracies of four key transport-planning variables: household vehicle-m...

Shared automated vehicles (SAVs) offering a fixed-route transit may compete well against privately operated vehicles. This paper analyzes the system costs of all travelers along a 6.4-kilometer (4-mile) corridor under different penetration rates for 10-seat SAVs. The work prices out walking, waiting, riding, and driving times for all travelers in t...

The market share of plug-in electric vehicles (PEVs) is growing, thanks to improvements in battery efficiency, declining production costs, and sustained policy support. Concurrently, concerns are growing over the supply of decommissioned PEV batteries. This has attracted a growing interest among scientists to determine the utility of repurposing PE...

With autonomous vehicles (AVs) still in the testing phase, researchers and planners must resort to simulation techniques to explore possible futures regarding shared and automated mobility. An agent-based discrete-event transport simulator, POLARIS, is used in this study to simulate travel in the 20-county Chicago region with a shared AV (SAV) mobi...

Introduction & research objectives Pedestrian crash rates and deaths have risen across the United States over the past decade, in contrast to motor vehicle traffic crash counts and rates. Analysis of pedestrian crash rates per vehicle-mile traveled and walk-mile traveled (VMT and WMT) illuminates the impacts of homelessness, land development densit...

With rising use of ridesourcing apps and, eventually, self-driving vehicles, demands for airport parking spaces, rental cars, and, ultimately, air travel is expected to fall everywhere, relative to background trends. This study uses publicly available ridesourcing demand data for the Austin, Texas area to pursue simulations of a fleet of shared aut...

A scheduling algorithm is developed for optimal planning of large-scale, complex evacuations to minimize total delay plus travel time across residents. The algorithm is applied to the eight-county Houston-Galveston region and land use setting under the 2017 Hurricane Harvey scenario with multiple destinations. Autonomous vehicle (AV) use under cent...

An increasing number of corporations and workplaces are providing flexible working hours or flextime for employees, which is expected to reduce congestion by redistributing the temporal pattern of commuters’ departure time. This study examines the impact of flextime on departure time choice using a Bayesian continuous-time hazard duration model. Th...

Long-distance (LD) travel accounts for over 30% of person-trip miles, with important energy and emissions impact. LD business travel can often be replaced by remote participation, so targeting such trips for cost, time, and emissions savings may be a wise strategy for protection of the climate, budgets, and human health. To appreciate Americans’ LD...

The emergence of on-demand shared autonomous electric vehicle (SAEV) service will provide local air quality, regional greenhouse gas reduction, and access benefits, while possibly increasing urban congestion. Charging trips will add to empty travel (eVMT) and could magnify the spatiotemporal fleet imbalance of vehicles depending on charging station...

Before shared automated vehicles (SAVs) can be widely adopted, they are anticipated to be implemented commercially in confined regions or fixed routes where the benefits of automation can be realized. SAVs have the potential to operate in a traditional transit corridor, replacing conventional transit vehicles, and have frequent interactions with ri...

Cost reductions and technological advancements are priming autonomous, electric, and shared vehicles for rapid growth, which may improve safety and mobility, but may also increase vehicle-miles traveled (VMT). This study seeks to improve upon existing fleet evolution work, by simulating the adoption of autonomous, electric, and shared vehicles in a...

The market share of plug-in electric vehicles (PEVs) is growing, thanks to improvements in battery efficiency, declining production costs, and sustained policy support. Concurrently, concerns are growing over the supply of decommissioned PEV batteries. Following their service life, PEV batteries can maintain close to 80% of their original capacity,...

Shared automated vehicles can provide different services in the future, including door-to-door (D2D) service, first-mile last-mile (FMLM) connections to transit stations, and as a low-cost transit vehicle. This paper leverages the agent-based simulator POLARIS to analyze the deployment of different SAV services in an integrated transit system for a...

Animal-vehicle collisions (AVCs) are common around the world and result in considerable loss of animal and human life, as well as significant property damage and regular insurance claims. Understanding their occurrence in relation to various contributing factors and being able to identify locations of high risk are valuable to AVC prevention, yield...

The transportation sector is a major greenhouse gas emitter. Concurrent electrification of vehicles and investment in renewable energy sources (RESs) is required to mitigate these emissions. The introduction of intermittent RESs such as solar and wind at a large scale presents challenges to utility operators. This study quantifies the opportunity a...

As ride-hailing becomes more common in cities, public agencies increasingly seek transportation network company (TNC) service data to understand (and potentially regulate) demand and service response. Despite the increase in ride-hailing or TNC demand and subsequent research into its determinants, there remains little research on shared TNC trips a...

Transportation greenhouse gas (GHG) reduction is often called a “three-legged stool” where vehicle efficiency, fuel carbon content, and vehicle miles traveled (VMT) each contribute to decreasing travel’s carbon footprint. Federal interventions such as revisions to Corporate Average Fuel Economy (CAFE) or fuel content standards address two legs of t...

Technological improvements and investments by vehicle manufacturers and technology companies suggest that self-driving or “autonomous” vehicles (AVs) will become publicly accessible in many locations within the next decade or two, although design, production, and licensing challenges remain. AVs will change several aspects of personal trip making a...

This study micro-simulates 2% and 5% of the region's 9.5 million daily person-trips and 20% of trips in the central Twin Cities with shared autonomous vehicles (SAVs) in the 7-county Minneapolis-Saint Paul region using MATSim to appreciate the effects of different trip-making densities and curb-use restrictions. Results suggest the average SAV in t...

The increasing demand for shared mobility services has led to multiple Public-Private Partnerships (PPPs), where public transit agencies and mobility providers work together to increase transit service coverage. However, several partnerships have failed due to the lack of demand and budget constraints. Furthermore, the limited data-sharing agreemen...

Shared autonomous vehicles (SAVs) will likely emerge in many urban settings over the coming decade and may significantly impact passenger travel. SAV fleet managers, the public, and policymakers may be attracted to all-electric drivetrains' lower operating costs and environmental benefits, but fleet managers will need to account for charging times...

This paper anticipates the impacts of self-driving or “autonomous” vehicles (AVs), shared AVs, and Atrucks on travel across the Texas Triangle megaregion using year 2040 land use (and network) forecasts. A statewide travel demand model forecasts changes in trip generation, mode and destination choices, and thus vehicle-miles traveled (VMT), congest...

Shared fleets of fully automated vehicles (SAVs) coupled with real-time ride-sharing to and from transit stations are of interest to cities and nations in delivering more sustainable transportation systems. By providing first-mile last-mile (FMLM) connections to key transit stations, SAVs can replace walk-to-transit, drive-to-transit, and drive-onl...

This study seeks smart credit-based congestion pricing (CBCP) solutions for maximally improving travelers’ welfare by varying toll levels and locations across the Austin, Texas network. Scenarios evaluated include selecting links with maximum delays by variably tolling bridges and by recognizing congestion externalities across all links. Travel dem...

This study anticipates changes in U.S. highway and rail trade patterns following widespread availability of self-driving or autonomous trucks (Atrucks). It uses a random-utility-based multiregional input–output model, driven by foreign export demands, to simulate changes in freight flows among 3109 U.S. counties and 117 export zones, via a nested-l...

Over 30 years have passed since activity-based travel demand models (ABMs) emerged to overcome the limitations of the preceding models which have dominated the field for over 50 years. Activity-based models are valuable tools for transportation planning and analysis, detailing the tour and mode-restricted nature of the household and individual trav...

Congestion pricing of high-demand roadways seeks to influence travelers’ route choices, trip timing, modes, and destination choices, to keep vehicles moving and avoid excessive congestion. This paper describes the use of various technologies to enable more advanced and cost-effective congestion pricing applications, and a credit-based policy to ens...

This paper used an implementation of the land-use model SILO in Austin, Texas, over a 27-year period with an aim to understand the impacts of the full adoption of self-driving vehicles on the region’s residential land use. SILO was integrated with MATSim for the Austin region. Land-use and travel results were generated for a business-as-usual case...

Sharing vehicles and rides may become the norm with public use of fully-automated self-driving vehicles in the near future, assuming pandemic-related health concerns fade away. Dynamic ride-sharing (DRS) or pooling of trips can significantly improve system performance by lowering empty vehicle-miles traveled (eVMT) and increasing average vehicle oc...

With autonomous vehicles (AVs) still in the testing phase, researchers and planners must resort to simulation techniques to explore possible futures regarding shared and automated mobility. An agent-based discrete-event transport simulator, POLARIS, is used in this study to simulate travel in the 20-county Chicago region with a shared AV (SAV) mobi...

Automated driving technology along with electric propulsion are widely expected to fundamentally change our transport systems. They may not only allow a more productive use of travel time, but will likely trigger completely new business models in the mobility market. A key determinant of the future prospects of both existing and new mobility servic...

High costs of owning fully-automated or autonomous vehicles (AVs) will fuel the demand for shared mobility, with zero driver costs. Although sharing sounds good for the transport system, congestion can easily rise without adequate policy measures. Many or all public transit lines will continue to exist, and carefully-designed policies can be implem...

Diesel-powered, human-driven buses currently dominate public transit options in most U.S. cities, yet they produce health, environmental, and cost concerns. Emerging technologies may improve fleet operations by cost-effectively reducing emissions. This study analyzes both battery-electric buses and self-driving (autonomous) buses from both cost and...

This paper develops a dynamic spatial general equilibrium model of urban environments to enable more land-use detail, population growth, and change dynamics and applies it to evaluate impacts of land-use externalities and zoning regulations on land-use markets. The new model specification tracks not just different parcel sizes and access attributes...

Many well-known enterprises are road-testing fully-automated vehicles (AVs), including General Motors, Uber, Tesla, and Apple. Most AVs are expected to be used in shared AV (SAV) fleets initially, for daily trip-by-trip use, as an autonomous ride-sourcing service. SAVs will allow savings on vehicle ownership and maintenance costs, parking search an...

High added costs of fully-automated-vehicles (AV) for ownership will fuel the demand for shared mobility, and this will especially be profitable from reduced operating costs. Although sharing ought to be good for the system, congestion is likely to increase without adequate policy measures. Public transit will continue to exist, with or without aut...

With rising use of ride-sourcing apps and, eventually, self-driving vehicles, ground transportation at airports are being impacted. Demands for airport parking spaces, rental cars, and, ultimately , airline service and availability are expected to fall everywhere, relative to background trends. This study uses publicly available ride-sourcing deman...

A central challenge facing Mobility as a Service (MaaS) is mispricing of its a core input: the use of scarce road space. A transparent real-time market for road use is essential for MaaS to reach its full potential. We focus on how network-wide, real-time markets for road use support MaaS, and how such markets can be developed. In our proposed net...

Increasing population and travel demand has prompted new efforts to model travel demand across the United States. One such model is rJourney that estimates travel demand among thousands of regions and models mode and destination choice. rJourney includes records representing 1.17 billion long-distance trips throughout the year 2010. Although inter-...

Rapid advances in technologies have accelerated the timeline for public use of fully-automated and communications-connected vehicles. Public opinion on self-driving vehicles or AVs is evolving rapidly, and many behavioral questions have not yet been addressed. This study emphasizes AV mode choices, including Americans’ willingness to pay (WTP) to r...

Shared fully-automated, or autonomous, mobility (SAVs) is anticipated to be the likely choice for future urban travel. SAVs boast many operational benefits but will add congestion in the form of unoccupied miles. The fleet’s success further depends on service measures like the wait times for pickup trips. Agent-based simulation tools have closely l...

Battery-only electric vehicles (BEVs) generally offer better air quality through lowered emissions, along with energy savings and security. The issue of long-duration battery charging makes charging-station placement and design key for BEV adoption rates. This work uses genetic algorithms to identify profit-maximizing station placement and design d...

Gasoline-powered motorcycles contribute disproportionately to traffic noise and emissions, so motorcycle electrification merits investigation. Recent advances in battery efficiency allow electric motorcycles (EMCs) to join electric cars and bicycles as a viable consumer option. This study quantifies noise and emissions using both simulations and ex...