Autonomous driving paper index
Will high-speed rail compete for long-distance travel in a car-dependent society? Insights from a Canadian high-speed rail survey
One-line summary
We develop a two-stage sequential weighted multinomial logit model capturing current travel behaviour and stated HSR adoption intentions.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充:本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
High-speed rail (HSR) represents a significant transport investment designed to drive economic growth and enhance long-distance regional connectivity. While HSR has demonstrated strong competitive performance against road and short-haul air travel in European and East Asian corridors, the behavioural parameters governing how HSR competes against the private vehicle in automobile-oriented North American markets, where car travel accounts for over 80% of intercity trips, remain comparatively underexamined. It is therefore less clear how travellers in such markets weigh travel time, cost, and service quality when a mature HSR alternative is introduced into a car-dominated mode share structure. The goal of this paper is to evaluate the potential for modal shift to HSR within the structural constraints of a car-dependent society. Unlike studies in transit-integrated European or Asian contexts, this study isolates the group travel penalty and car-habituation effects that characterize North American intercity travel. The study uses the Toronto-Québec City corridor in Canada, which was announced as an HSR project in 2025, to better understand if such investment can achieve its intended ridership and sustainability targets. The study analyzes data from an online bilingual long-distance travel behaviour survey (N = 6,813) conducted in October 2025. We develop a two-stage sequential weighted multinomial logit model capturing current travel behaviour and stated HSR adoption intentions. The analysis reveals that travellers are most sensitive to travel cost and travel time, with an implied value of travel time of approximately $31.5 per hour. Under a medium-adoption scenario, HSR is projected to capture 26% of corridor trips, with the largest substitution from private car and conventional rail. These findings provide an evidence-based demand projection that is essential for investment decisions while avoiding the common pitfall of ridership overestimation in large HSR projects. Practitioners can use these insights to prioritize fare-based incentives and target specific trip purposes such as business and student travel, to maximize the operational success of future HSR projects.
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