Protected intersections are used to facilitate safe crossings for non-motorized users. As a relatively new treatment in North America, it is essential to understand how their design elements, such as bicycle intersection-crossing pavement markings and corner refuge island size, enhance bicyclist safety. A driving simulation experiment was developed to test the effectiveness of different design elements of protected intersections on driver speeds. Participants were exposed to different protected intersection designs that varied with respect to the corner refuge island width and bicycle intersection-crossing pavement marking levels. Their speed at two parts of the right turn, that is, approach and curve speed, was analyzed. A combination of design elements, participant demographics, or bicyclist presence at the intersection affects driver behavior at a protected intersection. The results indicate that the presence of a bicyclist crossing a protected intersection significantly reduces speeds for drivers performing a right turn. Corner refuge islands with larger width were found to reduce speed at the curve as they were accompanied by larger curb extensions which essentially reduce the space for the automobiles. Bicycle intersection-crossing pavement markings influenced only approach speeds prior to the actual turn since that is the location where they were the most visible. Age, gender, and bicycling frequency were observed to affect turning speeds, indicating that design elements alone cannot determine the safety effectiveness of a protected intersection. The findings of this study can guide the implementation of protected intersections.
The transportation sector is considered one of the major contributors to greenhouse gas (GHG) emissions in metropolitan areas. Any efforts to reduce these emissions require strategic management of multiple transportation modes. This paper presents a method to identify opportunities to reduce GHG emissions by expanding commuter bus services and providing incentives to shift commuters from private cars to transit. The approach uses a nested multinomial logit model for mode choice in a region where modes include driving alone, carpooling, walking, cycling, and using four possible transit modes (ferry, commuter rail, rapid transit, and bus) by walk-access or drive-access. A model of existing conditions was calibrated with data from the Boston metropolitan area. Using an emission factor model based on average speeds from the California Air Resources Board, the net effect of a new commuter bus service on GHG emissions from transportation is estimated. Potential GHG reductions are weighed against the capital and operating costs of new transit services to quantify the cost-effectiveness of new commuter bus services for isolated origin-destination pairs. This modeling framework is used to optimize fares and bus frequency to identify the corridors with the most cost-effective potential for GHG reduction. Results are presented for the Boston region, demonstrating the feasibility of implementation and the potential magnitude of benefits for cost-effectively reducing GHG emissions associated with transportation. The method is general and can be applied in other cities around the world.
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