Modeling Mode and Departure Time Responses to Congestion Pricing: A Spatial and Behavioral Analysis Using Cross-Nested Logit Model

2026-06-29

AI Summary

This study investigates commuters’ joint choice behavior regarding travel mode and departure time under congestion pricing policies, with a focus on spatial heterogeneity. Using stated preference data from Calgary commuters, the authors estimate and compare multinomial logit, nested logit, and cross-nested logit models. The cross-nested logit model proves superior in capturing cross-substitution effects between mode and time dimensions, significantly improving behavioral fit. Findings reveal higher price elasticity among travelers in central urban areas and during peak periods. The results suggest that dynamic, differentiated pricing schemes—such as zone- and time-based tolling (e.g., cordon pricing combined with time-of-day rates)—can effectively alleviate congestion. The study further underscores the critical importance of complementary public transit enhancements and equity-oriented measures for the successful implementation of congestion pricing policies.

Abstract

Effective congestion management strategies require a detailed understanding of how travellers respond to different pricing interventions. This paper presents an in-depth analysis of traveller behaviour under congestion pricing scenarios, focusing specifically on mode and departure time decisions. Utilizing stated preference survey data from commuters in Calgary, Canada, three discrete choice models including Multinomial Logit, Nested Logit, and Cross-Nested Logit are developed and compared. Results indicate that the Cross-Nested Logit model provides superior behavioural realism and flexibility by capturing simultaneous substitutions across modes and departure times. Spatial analysis and elasticity assessments reveal substantial geographic variation in traveller sensitivity to pricing, particularly highlighting stronger responses among commuters travelling to high-demand central locations and during peak travel periods. Further elasticity analyses clarify behavioural patterns, identifying traveller groups with varying degrees of flexibility. Policy analyses underscore the effectiveness of targeted, dynamic tolling, particularly cordon-based pricing combined with time-specific toll adjustments, in reducing congestion levels. Additionally, the findings highlight the necessity of complementary measures, including improved transit services and targeted discounts, to ensure equitable outcomes. The findings offer targeted insights into how specific pricing strategies such as cordon, distance, and travel time-based tolls can be used to influence travel behaviour, reduce peak-period congestion, and guide equitable policy design in urban transportation planning.

Problem

• congestion pricing
• travel behavior
• mode choice
• departure time
• spatial variation

Innovation

• Cross-Nested Logit
• congestion pricing
• departure time choice
• mode choice
• spatial elasticity