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On-demand ridesplitting is a form of ridesourcing where riders with similar origins and destinations are matched to the same driver and vehicle in real time, and the ride and costs are split among users. With the convenience of all kinds of ridesourcing services, the number of ridesplitting passengers increases, which may have a great impact on the urban mobility. In this paper, we analyze ridesplitting behavior and its impact on multimodal mobility, e.g., vehicle kilometers traveled (VKT) and transportation modal shift, using real-world ridesourcing data extracted from an on-demand ride service platform in Hangzhou, China, and questionnaires filled by on-demand ridesplitting passengers. With the consideration of the VKT shifted from non-passenger/private vehicles, this paper uses the saved VKT of two ridesplitting types, e.g., DiDi Hitch and DiDi Express ridesplitting, to quantify the ridesplitting impact. For the whole ridesourcing ecosystem, ridesplitting is estimated to decrease 58,124 VKT per day in Hangzhou, of which Hitch and Express ridesplitting contribute 2175 km and 55,949 km per day, respectively. The saved VKT of Hitch is much smaller than Express ridesplitting for the following two reasons: (1) Hitch orders are fewer than Express ridesplitting; (2) more than half of the Hitch passengers shift modes from bus/metro transit or other non-passenger/private cars. This paper shines some lights on understanding the emerging on-demand ridesplitting behavior and quantifying its impact on multimodal urban mobility.

This paper explores the respective roles of local and regional characteristics of urban form on vehicle travel. We hypothesize that the effects of urban form on vehicle use at the local and regional levels are complementary, and we introduce the concept of local and regional action spaces, which are defined based on the accessibility of alternative means of transport within an acceptable travel time, to test this hypothesis. Multilevel and ordered logit models are developed for the San Francisco Bay Area to estimate the effects of urban form and socioeconomic characteristics on vehicle kilometers traveled (VKT) and vehicle trip frequency (for work, shopping, and social/recreational purposes). We find that the two urban scale characteristics exert complementary effects on VKT. However, because people in the San Francisco Bay Area display significantly lower VKT in the local than in the regional action space, we conclude that regional-scale interventions would contribute more to the policy objective of VKT reduction, although local-scale design policies might also help reach this policy goal. Intersection density (for the local action space models) and regional jobs accessibility (for the regional action space models) demonstrated the strongest and most significant relationships with VKT. The built environment did not appear to significantly affect vehicle trip frequency, which is likely due to the uniformly high levels of vehicle use in both the local and regional action spaces in the area.

Carsharing is a vehicle sharing service for those with occasional need of private transportation. Transportation planners are beginning to see great potential for carsharing in helping to create a more diversified and sustainable transport system. While it has grown quickly in the US in recent years, it is still far from the level where it can deliver significant aggregate benefits. A key element to the potential growth of carsharing is its ability to provide cost savings to those who adopt it in favor of vehicle ownership. This research seeks to quantify these potential cost savings. The costs of carsharing and vehicle ownership are compared based on actual vehicle usage patterns from a large survey of San Francisco Bay Area residents. The results of this analysis show that a significant minority of Bay Area households own a vehicle with a usage pattern that carsharing could accommodate at a lower cost. Further research is required to indentify how these cost savings translate to the adoption of carsharing.

Objectives: To investigate the rate of helmet use among motorcycle drivers in Hai Duong province of Vietnam during winter/spring 2005, and to compare the rates of helmet use by road types. Method: Population-based observational surveys. Results: 16 560 motorcyclists were observed across 37 road sites (incorporating 5 road categories). The overall weighted average of helmet use for motorcyclists was 29.94%, with male drivers more likely to wear helmets than female drivers (odds ratio (OR) 1.64, 95% confidence interval (CI) 1.53 to 1.76). Male pillion passengers were less likely to wear helmets than female pillion passengers (OR 0.78, 95% CI 0.72 to 0.85). The number of adult drivers using helmets is larger as compared with that of young drivers (OR 8.56, 95% CI 5.93 to 12.19). The rates of helmet use were significantly higher (p<0.001) on compulsory roads and were 59.01%, 39.97%, 24.22%, 12.7% and 9.54% for national, provincial, district, commune and Hai Duong inner-city roads, respectively. Conclusion: Helmet legislation has increased the rate of helmet use by motorcycle drivers on compulsory roads. Elsewhere, rate of helmet use is very low, indicating that in the absence of legislation and enforcement, motorcyclists in Vietnam will not wear a helmet.

The preponderance of evidence suggests that communities with denser and more connected street networks and a higher degree of mixed land uses results in fewer vehicle kilometers traveled (VKT). However, there is less agreement on the size of the effect. Also, there is no clear understanding of the specific aspects of community design—such as street networks and land use mix—that are most important in contributing to lower VKT. One reason why there is some confusion on this point is that past studies have not always made a clear distinction between different street network design characteristics such as density, connectivity, and configuration. In this research, care was taken to control for land use mix while fully characterizing the different features of the street network, including a street pattern classification system that works at the neighborhood level but also focuses on the citywide street network as a separate entity. We employ a spatial kriging analysis of National Household Travel Survey (NHTS) data in combination with a generalized linear regression model in order to examine the extent to which community design, particularly in terms of street network design while controlling land use mix, influences VKT in 24 California cities of populations from 30,000 to just over 100,000. Our results suggest that residents of more compact street network designs tend to drive less. Street connectivity, however, played an adverse role in performance.