How shared autonomous vehicle services affect commuters’ value of travel time in Shanghai, China

Shared autonomous vehicles (SAVs), a combination of shared mobility service and autonomous vehicle technology, are widely regarded as a promising pathway toward more sustainable, efficient, and equitable urban transportation systems. The impact of SAVs on commuters' value of travel time (VOTT) is critical for transportation planning authorities but remains insufficiently understood. Since the high uncertainty in the VOTT often arises from substantial preference heterogeneity across individuals, this paper developed a mixed multinomial Probit model with correlated error terms to analyze the impact of SAV service on commuters’ mode choice and the VOTT in Shanghai, China. The results show that, relative to the VOTT derived from revealed preference data, the VOTT for private cars based on stated preference data after the introduction of SAV services shows a slight increase, while the VOTTs for taxis and public transit remain largely unchanged. The results further indicate a reduction of nearly one-half in the VOTT for SAV relative to private cars. Policy implications are also discussed to promote the development and sustainability of urban mobilities.