Assessing social equity in distance based transit fares using a model of travel behavior

The goal of this study is to develop and apply a new method for assessing social equity impacts of distance-based public transit fares. Shifting to a distance-based fare structure can disproportionately favor or penalize different subgroups of a population based on variations in settlement patterns, travel needs, and most importantly, transit use. According to federal law, such disparities must be evaluated by the transit agency, but the area-based techniques identified by the Federal Transit Authority for assessing discrimination fail to account for disparities in distances travelled by transit users. This means that transit agencies currently lack guidelines for assessing the social equity impacts of replacing flat fare with distance-based fare structures. Our solution is to incorporate a joint ordinal/continuous model of trip generation and distance travelled into a GIS Decision Support System. The system enables a transit planner to visualize and compare distance travelled and transit-cost maps for different population profiles and fare structures. We apply the method to a case study in the Wasatch Front, Utah, where the Utah Transit Authority is exploring a switch to a distance-based fare structure. The analysis reveals that overall distance-based fares benefit low-income, elderly, and non-white populations. However, the effect is geographically uneven, and may be negative for members of these groups living on the urban fringe.     

Application of social force model to pedestrian behavior analysis at signalized crosswalk

Limited pedestrian behavior models shed light on the case at signalized crosswalk, where pedestrian behavior is characterized by group or individual evasion with surrounding pedestrians, collision avoidance with conflicting vehicles, and response to signal control and crosswalk boundary. This study fills this gap by developing a microscopic simulation model for pedestrian behavior analysis at signalized intersection. The social force theory has been employed and adjusted for this purpose. The parameters, including measurable and non-measurable ones, are either directly estimated based on observed dataset or indirectly derived by maximum likelihood estimation. Last, the model performance was confirmed in light of individual trajectory comparison between estimation and observation, passing position distribution at several cross-sections, collision avoidance behavior with conflicting vehicles, and lane-formation phenomenon. The simulation results also concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.     

SCUBA Diver Specialization and Behavior Norms at Coral Reefs

SCUBA diving is an increasingly popular activity that provides a number of benefits to coastal communities. However, the sustainability of recreational diving on coral reefs is largely dependent on the health of reef ecosystems. Divers can minimize their impacts to coral reefs through responsible diving behaviors, which are in part guided by social norms. The behavioral obligation and sanction components of twelve diving behaviors were determined for Florida Keys divers throughout the course of a year. Recognizing that recreationists are not homogenous, these norms were compared according to diver specialization level. Specialized divers felt a stronger obligation not to touch corals and to pick up garbage from the sea floor than did less specialized divers. Specialized divers also reported they would feel greater embarrassment for losing buoyancy control, touching corals, taking pieces of dead corals, or touching marine mammals. The findings point to a connection between specialization level and social norms, and a relationship to ensuring continued reef health.     

Leveraging social networks for efficient hurricane evacuation

One of the important factors affecting evacuation performance is the departure time choices made by evacuees. Simultaneous departures of evacuees can lead to overloading of road networks causing congestion. We are especially interested in cases when evacuees subject to little or no risk of exposure evacuate along with evacuees subject to higher risk of threat (also known as shadow evacuation). One of the reasons for correlated evacuee departures is higher perceived risk of threat spread through social contacts. In this work, we study an evacuation scenario consisting of a high risk region and a surrounding low risk area. We propose a probabilistic evacuee departure time model incorporating both evacuee individual characteristics and the underlying evacuee social network. We find that the performance of an evacuation process can be improved by forcing a small subset of evacuees (inhibitors) in the low risk area to delay their departure. The performance of an evacuation is measured by both average travel time of the population and total evacuation time of the high risk evacuees. We derive closed form expressions for average travel time for ER random network. A detailed experimental analysis of various inhibitor selection strategies and their effectiveness on different social network topologies and risk distribution is performed. Results indicate that significant improvement in evacuation performance can be achieved in scenarios where evacuee social networks have short average path lengths and topologically influential evacuees do not belong to the high risk regions. Additionally, communities with stronger ties improve evacuation performance.     

Planning transport for social inclusion: An accessibility-activity participation approach

Social equity is increasingly becoming an important objective in transport planning and project evaluation. This paper provides a framework and an empirical investigation in the Greater Toronto and Hamilton Area (GTHA) examining the links between public transit accessibility and the risks of social exclusion, simply understood as the suppressed ability to conduct daily activities at normal levels. Specifically, we use a large-sample travel survey to present a new transport-geography concept termed participation deserts, neighbourhood-level clusters of lower than expected activity participation. We then use multivariate models to estimate where, and for whom, improvements in transit accessibility will effectively increase activity participation and reduce risks of transport-related social exclusion. Our results show that neighbourhoods with high concentrations of low-income and zero-car households located outside of major transit corridors are the most sensitive to having improvements in accessibility increase daily activity participation rates. We contend that transit investments providing better connections to these neighbourhoods would have the greatest benefit in terms of alleviating existing inequalities and reducing the risks of social exclusion. The ability for transport investments to liberate suppressed activity participation is not currently being predicted or valued in existing transport evaluation methodologies, but there is great potential in doing so in order to capture the social equity benefits associated with increasing transit accessibility.     

An equilibrium analysis of commuter parking in the era of autonomous vehicles

This study is the first in the literature to model the joint equilibrium of departure time and parking location choices when commuters travel with autonomous vehicles (AVs). With AVs, walking from parking spaces to the work location is not needed. Instead, AVs will drop off the commuters at the workplace and then drive themselves to the parking spaces. In this context, the equilibrium departure/arrival profile is different from the literature with non-autonomous vehicles (non-AVs). Besides modeling the commuting equilibrium, this study further develops the first-best time-dependent congestion tolling scheme to achieve the system optimum. Also, a location-dependent parking pricing scheme is developed to replace the tolling scheme. Furthermore, this study discusses the optimal parking supply to minimize the total system cost (including both the travel cost and the social cost of parking supply) under either user equilibrium or system optimum traffic flow pattern. It is found that the optimal planning of parking can be different from the non-AV situation, since the vehicles can drive themselves to parking spaces that are further away from the city center and walking of commuters is avoided. This paper sheds light on future parking supply planning and traffic management.     

Do social norms regarding carbon offsetting affect individual preferences towards this policy? Results from a stated choice experiment

This study investigates the idea that people’s willingness to offset flight-related carbon emissions is a function of the collective participation rate, which can be regarded as a social norm, towards carbon offsetting. Additionally, we reveal people’s preferences toward two other environmental policies; a baggage allowance and airline eco-efficiency index. A discrete choice experiment is designed and administrated among a sample of air travelers. The results indicate that carbon offsetting generates utility, with people gaining more utility when the collective participation rate is high. Additionally, it was found that the baggage allowance and the eco-efficiency index strongly influenced respondents’ airline choices. People also became more sensitivity towards a baggage allowance and the eco-efficiency label, when the collective offsetting rate was high.     

Correcting for endogeneity in behavioral choice models with social influence variables

While psychologists and behavioral economists emphasize the importance of social influences, an outstanding issue is how to capture such influences in behavioral models used to inform urban planning and policy. In this paper we focus on operational models that do not require explicit knowledge of the individual networks of decision makers. We employ a field effect variable to capture social influences, which is calculated as the percent of population in the peer group that has chosen the specific alternative. We define the peer group based on socio-economic status and spatial proximity of residential location. As in behavioral economics and psychology, the concept is that one is influenced by the choices made by one’s peers. However, using such a social influence variable in a behavioral model causes complications because it is likely endogenous; unobserved factors that impact the peer group also influence the decision maker, yielding correlation between the field effect variable and the error. The contribution of this paper is the use of the Berry, Levinsohn, and Pakes (BLP) method to correct the endogeneity in a choice model. The two-stage BLP introduces constants for each peer group to remove the endogeneity from the choice model (where it is difficult to deal with) and insert it into a linear regression model (where endogeneity is relatively easier to deal with). We test the method using a mode choice data set from the Netherlands and readily available software and find there is an upward bias of the field effect parameter when endogeneity is not corrected. The procedure outlined presents a practical and tractable method for incorporating social influences in choice models.     

Social networks as a source of private-vehicle transportation: The practice of getting rides and borrowing vehicles among Mexican immigrants in California

We examine the role of social networks in enabling access to private-vehicle transportation, through getting rides and borrowing cars. Based on qualitative findings from ten focus group discussions with recent Mexican immigrants to California, half of whom have no car, we describe the extent to which participants depend on rides and borrowed cars for transportation. We highlight the unique aspects of informal access to cars, drawing on social exchange theory and related research to characterize the procurement process and likely levels of exchange. We discuss the implications of these findings for transportation services that might serve this and other community groups.