Advances in pedestrian travel monitoring: Temporal patterns and spatial characteristics using pedestrian push-button data from Utah traffic signals

In this study, we advanced pedestrian travel monitoring using a novel data source: pedestrian push-button presses obtained from archived traffic signal controller logs at more than 1,500 signalized intersections in Utah over one year. The purposes of this study were to: (1) quantify pedestrian activity patterns; (2) create factor groups and expansion/adjustment factors from these temporal patterns; and (3) explore relationships between patterns and spatial characteristics. Using empirical clustering, we classified signals into five groups, based on normalized hourly/weekly counts (each hour’s proportion of weekly totals, or the inverse of the expansion factors), and three clusters with similar monthly adjustment factors. We also used multinomial logit models to identify spatial characteristics (land use, built environment, socio-economic characteristics, and climatic regions) associated with different temporal patterns. For example, we found that signals near schools were much more likely to have bimodal daily peak hours and lower pedestrian activity during out-of-school months. Despite these good results, our hourly/weekday patterns differed less than in past research, highlighting the limits of existing infrastructure for capturing all kinds of activity patterns. Nevertheless, we demonstrated that signals with push-button data are a useful supplement to existing permanent counters within a broader pedestrian traffic monitoring program.

Public transport strategy: Minimal service vs. competitor to the car

With regard to public policy for public transport services, two dominant approaches are found: the provision of minimal services to the car-less population, or the provision of a service that competes directly with the car (in terms of time, cost, convenience, etc.). Increased acknowledgement of the need to mitigate traffic growth and reduce greenhouse gas (GHG) emissions has led to a growing need to shift from the former to the latter, encouraging the use of public transport. This paper sets out to explore whether competitiveness with the car is a priority for the public transport planning of medium-sized European cities, as well as whether the change in European regulation (European Commission, 2007) has managed to contribute to the acceptance of this priority. In this study, we take a closer look at a country undergoing significant regulatory and procedural transformations. An exploratory analysis is conducted regarding plans, actions, and development projects in recent years in four Portuguese municipalities. Relevant planners and transport authorities are interviewed on matters such as how local policies and plans favor public transport; how the planning process was implemented; the actors involved; and the support tools used to achieve the established goals. The findings reveal that relative competitiveness of public transport is considered important by planning practitioners. Nevertheless, other concerns seem to be more timely, such as, providing minimal services, restructuring existing networks, and budget constraints. The results suggest that changes in the planning process have been overwhelming and are seen as restricting the steps required toward making public transport more competitive vis-à-vis the car. So far, local authorities recognize the potential of adding relative competitiveness concerns in the future, as well as the added value of planning support tools capable of revealing such relative competitiveness.

Mobility and accessibility paradigms in Dutch policies: An empirical analysis

To promote sustainable urban development, transport policies need to change from a car-oriented mobility planning paradigm to an accessibility-based paradigm, integrating land-use and transport policies. This paper uses the concept of planning paradigms to describe the current status of municipal transport planning and problem framing. The dominant transport planning paradigm of 172 Dutch municipalities is determined, based on a conceptual framework with 24 mobility and accessibility planning criteria. Statistical analysis is then conducted to find linkages between the planning paradigm and transport, land-use, and institutional characteristics of the municipalities. We show that the mobility planning paradigm still dominates Dutch municipal transport planning, and the accessibility planning paradigm is mostly found in large cities and highly urban municipalities. However, we do find indications of slow change in the transport planning paradigms in Dutch municipalities, as older policy documents are more (car) mobility focused than newer policy documents. Further research is necessary to examine the evolution of the paradigm shift in municipal transport planning over time and what factors promote the realization of such a paradigm shift.

Spatiotemporal effects of proximity to metro extension on housing price dynamics in Manhattan, New York City

Investment in public transportation such as a metro line extension is often capitalized partially into housing values due to the spatiotemporal effects. Using housing transaction data from 2014 to 2019, this paper studies the Second Avenue Subway or Q-line extension in New York’s City’s Manhattan borough. Multiple metro station catchment areas were investigated using spatial autocorrelation-corrected hedonic pricing models to capture the variation of housing price dynamics. The results indicate that properties in closer proximity to the Q-line extension received higher price discounts. The effect varied by occupancy type and building form: condominiums experienced the highest price discount, while walk-up and elevator co-ops experienced a price premium. After controlling for location variations, we observed price discounts on the westside and price premiums on the eastside of the Q-line. Residential properties within 150 m west to the Q-line extension received the highest price discount post operation, while on the eastside, properties in the same proximity received the highest price premium. The anticipation effect varies by distance to metro extension stations, both before and after the operation of metro line extension. We discuss the disruption of metro construction on the housing market depending on housing type, location variation, and changes over time.

The evolution of choice set formation in dwelling and location with rising prices: A decadal panel analysis in the Greater Toronto Area

Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting the types of dwelling and locations considered by households. A large sample of real estate listings from 2006 and 2016 from the Greater Toronto Area is used to develop the empirical models. Two recently developed discrete choice models are used in the study: a nested logit model with latent class feedback (LCF) and a semi-compensatory independent availability logit (SCIAL) model. A method of alternative aggregation is proposed to overcome the computational hurdle that often impedes the estimation of choice set models. We find a significant increase in the probability of larger households considering townhouses and apartments over detached single-family dwellings between 2006 and 2016.

Developing vehicular and non-vehicular trip generation models for mid-rise residential buildings in Kelowna, British Columbia: Assessing the impact of built environment, land use, and neighborhood characteristics

This study develops vehicular and non-vehicular trip generation models for mid-rise, multi-family residential developments. A comparative analysis of observed and Instiutue of Transportation Engineers (ITE) trip rates suggests that ITE rates consistently overestimate. A latent segmentation-based negative binomial (LSNB) model is developed to improve the methodology for estimating vehicular and non-vehicular trips. One of the key features of an LSNB model is to capture heterogeneity. Segment allocation results for the vehicular and non-vehicular models suggest that one segment includes suburban developments, whereas the other includes urban developments. Results reveal that a higher number of dwelling units is likely to be associated with increased vehicle trips. For non-vehicular trips, a higher number of dwelling units and increased recreational opportunities are more likely to increase trip generation. The LSNB model confirms the existence of significant heterogeneity. For instance, higher land-use mix has a higher probability to deter vehicular trips in urban areas, whereas trips in the suburban areas are likely to continue increasing. Higher density of bus routes and sidewalks are likely to be associated with increased non-vehicular trips in urban areas, yet such trips are likely to decrease in suburban areas. An interesting finding is that higher bikeability in suburban areas is more likely to increase non-vehicular trips. The findings of this study are expected to assist engineers and planners to predict vehicular and non-vehicular trips with higher accuracy.

The effects of pedestrian and bicycle exposure on crash risk in Minneapolis

Exposure to risk is a theoretically important correlate of crash risk, but many safety performance functions (SPFs) for pedestrian and bicycle traffic have yet to include the mode-specific measures of exposure. When SPFs are used in the systematic approach to assess network-wide crash risk, the omission of the exposure potentially could affect the identification of high-risk locations. Using crash data from Minneapolis, this study constructs and compares two sets of SPFs, one with pedestrian and bicycle exposure variables and the other without, for network-wide intersection and mid-block crash models. Inclusion of mode-specific exposure variables improves model validity and measures of goodness-of-fit and increases accuracy of predictions of pedestrian and bicycle crash risk. Including these exposure variables in the SPFs changes the distribution of high-risk locations, including the proportion of high-risk locations in low-income and racially concentrated areas. These results confirm the importance of incorporating exposure measures within SPFs and the need for pedestrian and bicycle monitoring programs to generate exposure data.

Place quality in high-speed rail station areas: Concept definition

High-speed railway (HSR) station areas are expected to benefit urban environments, not simply as transportation or economic hubs but also as urban places contributing to living quality. However, the relationship between HSR and place quality has not received systematic attention, despite the evolution of urban planning paradigms toward a clearer focus on quality of life. We have reviewed 44 academic articles written between 1996 and 2019 and analyzed concepts of place quality spanning the disciplines of urban design, urban planning, and urban economics. We identified three dimensions commonly associated with quality of place: a spatial dimension associated with aesthetic qualities of urban spaces; a socio-cultural dimension associated with experienced “sense of place”; and an economic dimension associated with the agglomeration of economic activities. Then we worked out these three dimensions in the context of HSR station areas and attributed features accordingly. We concluded that the economic dimension far outweighs the others in academic debates, with dominant theories being primarily concerned with land use, accessibility, and economic performance. Studies from the urban design field have tackled the spatial elements of place quality and showed a strong correlation with economic dimension. However, the literature remains insufficiently developed when it comes to addressing user experience and “sense of place.”

Exploring the interaction effect of poverty concentration and transit service on highway traffic during the COVID-19 lockdown

During COVID-19 lockdowns, transit agencies need to respond to the decline in travel but also maintain the essential mobility of transit-dependent people. However, there are a few lessons that scholars and practitioners can learn from. Using highway traffic data in the Twin Cities, this study applies a generalized additive model to explore the relationships among the share of low-income population, transit service, and highway traffic during the week that occurred right after the 2020 stay-at-home order. Our results substantiate that transportation impacts are spread unevenly across different income groups and low-income people are less able to reduce travel, leading to equity concerns. Moreover, transit supply influences highway traffic differently in areas with different shares of low-income people. Our study suggests that transportation agencies should provide more affordable travel options for areas with concentrated poverty during lockdowns. In addition, transit agencies should manage transit supply strategically depending on the share of low-income people to better meet people’s mobility needs.

Built environment correlates of walking for transportation: Differences between commuting and non-commuting trips

As a sustainable mode of travel, walking for transportation has multiple environmental, social, and health-related benefits. In existing studies, however, such walking has rarely been differentiated between commuting and non-commuting trips. Using multilevel zero-inflated negative binomial regression and multilevel Tobit regression models, this study empirically examines the frequency and duration of commuting and non-commuting walking and their correlates in Xiamen, China. It finds that (1) non-commuting walking, on average, has a higher frequency and longer duration than commuting walking; (2) most socio-demographic variables are significant predictors, and age, occupation, and family size have opposite-direction effects on commuting and non-commuting walking; and (3) different sets of built environment variables are correlated with commuting and non-commuting walking, and the built environment collectively influences the latter more significantly than the former. The findings provide useful references for customized interventions concerning promoting commuting and non-commuting walking.