On Ride-Sharing: A Departure Time Choice Analysis with Latent Carpooling Preference

Abstract

This paper presents a departure time choice analysis, based on the notion of a latent carpooling preference. The study is based on combined revealed preference and stated preference survey data collected on the Maryland side of the Capital Beltway (I-495). A conditional logit model is first estimated to identify drivers' choice of departure time when tolls and congestion management strategies, including high-occupancy vehicle (HOV) lanes and high-occupancy toll (HOT) lanes, are implemented. Then a latent class model accounting for heterogeneity across categories of drivers is proposed to examine difference in behavioral preferences across classes. The latent class model result reveals significant heterogeneity in drivers' latent preference toward ride-sharing, which can potentially support ranges of transportation policy and incentive design related to congestion management strategies such as HOV/HOT lane usage.

An Empirical Study on the Segmentation of Potential Users of Shared Parking Spaces considering Individual Heterogeneity

“…Teichert et al [39] recognized the limitations of traditional segmentation techniques, adopted LCM to classify air passengers, and explored the importance of routes and flight segments to airlines' selection behavior; Crouch et al [40] collected data on people's past vacation experience choices, travel motives, and basic demographic characteristics, established LCM to divide tourists into 5 classes, and explored how tourists choose vacation experiences/activity types. Xiong et al [41] used the LCM to reveal the significant heterogeneity of Maryland drivers' potential preferences for carpooling, which supports traffic policies and incentive mechanisms related to congestion management strategies (such as HOV/ HOT channel use). In addition, LCM is also widely used in other studies, such as long-distance drivers' route selection behavior [42], bicycle users [43], driving behavior on combined road segments [44], the time spent by tourists at destinations [45], the acceptance of self-driving vehicles [15], and the satisfaction with public transportation [13].…”

Optimal Supplier Selection in a Supply Chain with Predetermined Loading/Unloading Time Windows and Logistics Truck Share

“…The time window constraint of suppliers is modeled in Constraint (11) declaring that the raw materials can be picked up after the specified earliest pickup time and before the specified latest pickup time. Constraint (12) imposes that a truck should reach the parking lot for unloading the raw material before the latest possible time.…”

“…Ride sharing is a solution used to prevent road congestion, as well as dynamic tolling and managed lanes [11]. Ride sharing can reduce traffic congestion's negative impacts, such as air pollution and wasting resources (i.e.…”