The advent of transportation network companies (TNCs), also known as commercial ridesharing providers, has disrupted transportation systems leading to new facility designs. Dedicated pickup/dropoff areas can facilitate the future shift to autonomous vehicles. In this study, angled stalls and parallel curbside parking, along with signage and education, were investigated using pedestrian and wheelchair simulators. Human behavior was examined with regard to safety, efficiency, and accessibility. Microsimulation and Surrogate Safety Assessment Model were used to examine the effect of increased demand on design capacity and number of conflicts. In simulations, both stall and curbside designs performed comparably in crosswalk usage, but the stall design was safer when passengers waited longer for vehicle arrival. It is preferable to wait to approach the loading area until the TNC vehicle arrives. Stall design was more accessible but curbside design had greater efficiency because of shorter vehicle waiting time (−7.31 s [ p < 0.01]). Signage and education were found to be effective in increasing sidewalk usage, decreasing deviations from the crosswalk, and reducing vehicle waiting time. Post-simulator surveys showed similar ratings for safety (80.65%), with stall design scoring higher in accessibility (90% versus 52%) and curbside design slightly higher in efficiency (77% versus 68%). Participants reported almost equal preference for stall or curbside designs (48% versus 52%), and over 90% found the signage and education effective. Microsimulation indicated that stall design had higher capacity (500 vehicles per hour) than curbside design (350 vehicles per hour) within 180 linear feet, and fewer overall conflicts at 300 loadings.


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    Title :

    Simulator and Microsimulation Study of Transportation Network Company Pickup/Dropoff Area Designs


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Kaltenbronn, Jacob (author) / Jin, Peng (author) / Shu, Xiaofan (author) / Sun, Carlos (author) / Zhang, Siyang (author)


    Publication date :

    2023-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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