Since the introduction of electric vehicles (EVs) in the US market, there have been no adjustments to evacuation planning to address their unique charging needs. EV drivers may face range anxiety, and long recharging times while navigating sparse public charging networks, which challenge both preemptive and short-notice evacuations. This research proposes a multi-criteria vulnerability assessment of coupled EV driver and charging station networks in various evacuation scenarios. We study flooding evacuations in Chicago, Illinois, and hurricane evacuations in the Southeast Florida road networks. Our findings show that vehicle and infrastructure characteristics (i.e., charging stations network, driving range, and vehicle type heterogeneity) and evacuation characteristics (i.e., network scale and topology, hazard type, and warning system type) impact evacuation feasibility and performance and increase drivers' vulnerability. Furthermore, the initial state of charge is critical in determining EV drivers’ capability to initiate an evacuation. Last, we discuss potential infrastructure and preparedness measures that can curb vulnerability and better accommodate EV evacuations.

Vehicle electrification is a key component of sustainable development goals yet the mass adoption of electric vehicles can lead to unintended consequences on community mobility during natural hazards. Electric vehicles pose a challenge to owners during natural hazards which lead to power outages, as a lack of home charging limits the mobility of EV owners. Due to the direct relation between driving distance to essential services and vehicle battery consumption, changes in mobility will be impacted by geographic and technological factors. Geography determines the driving distance to essential services which will be translated to electricity consumption devoted to transportation and technology determines the size of electric vehicle batteries and vehicle efficiency. The linkage between mobility, electric power availability and quality-of-life has broad implications for community resilience as equitable access to essential services has been identified as the most important aspect of community resilience. In this work we develop a computational modeling framework to quantify the impact of vehicle electrification on limited mobility and access to essential services in urban areas during prolonged blackouts. We define measures of access risk and evaluate how risk changes across large urban centers in the U.S. Our results indicate inequalities in access to essential services will be exacerbated by vehicle electrification during blackouts. We also find that urban areas with high population density are associated with lower levels of access risk whereas high car ownership rates correlate with higher access risk. Moreover, we test different electric vehicle technologies and find that increased battery size lowers access risk by increasing potential driving distance, however the impact of battery size is highly dependent on the geography of each city. Finally, we test how vehicle to grid (V2G) technology creates a trade-off between access to services and use of household amenities and find that V2G disproportionately benefits access-rich households.

Transportation Network Companies (TNCs) like Uber and Lyft have been rapidly growing. This growth could increase greenhouse gas (GHG) emissions and health risk by air pollutant emissions, as well as congestion, noise, and crashes. In this study, we identify 1 million trips from real-world travel data recorded by TNC services in Chicago. We then assess the social cost of these trips–including GHG emissions, health damages from other air pollution (PM2.5, NOx, SO2, VOC), congestion, and crashes. We repeat the analysis for two cases: one in which we assume that the trips are performed using gasoline vehicles, and other in which we assume that they are performed using electric vehicles. The data record how much the customer paid for the trip and its approximate duration. For each trip, we then use the Google Maps API to identify a method by which the trip could have occurred using only transit. For this transit alternative, we calculate monetary costs, travel time, as well as the same set of social costs we estimate for the TNC trips. We then compare the cost of performing the trip using a TNC ride and using transit. The analysis allows us to characterize the trade-offs between the different types of private and public costs incurred by each mode. By combining trip data with historical weather data, we are also able to quantitatively describe how this trade-off varies with weather conditions (e.g., if, in extreme cold, people use TNCs for trips where the time savings do not compensate for the extra cost). Preliminary results indicate that the total social cost of a TNC trip is $1.5 for electric vehicles and $1.7 for gasoline vehicles. These are significantly higher than the social costs of a transit trip, which range between $0.1 and $0.3. However, these dynamics shift when considering private costs, including both monetary fares and time value. The fare alone of a TNC trip is on average $20, six times that of a transit trip. But when factoring in the monetized value of additional time needed for transit, the private costs would be approximately equal between TNCs and transit. Further analysis revealed that 60% of the monetized additional time cost in transit trips was allocated to walking and transferring, and 40% to waiting time. These primary findings indicate that riders are acting rationally in choosing TNCs over transit, and given the relatively small magnitude of external vs private costs, would continue to make the same choice if external costs were internalized. A policy to improve transit frequency and location of stops could potentially enhance the appeal of transit and increase the social benefits. With more in-depth analysis of these cost trade-offs under different weather conditions and times of day, we discuss further potential policy interventions.