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on Transport Economics |
| By: | Dion, Francois PhD; Patire, Anthony PhD; Chew, Jared; Mauch, Michael |
| Abstract: | Recent changes in California transportation policy have increased the importance of evaluating the impacts of highway capacity expansion on travel demand by shifting environmental review practices away from level-of-service toward assessing impacts on vehicle miles traveled (VMT) and travel demand. While established analytical tools exist for evaluating induced travel in urban regions, limited research and modeling resources have made it difficult to apply similar methods in rural areas. This research investigates whether capacity-enhancing projects on rural elements of the California State Highway System (SHS) are associated with measurable increases in VMT. The study evaluates county-level statistical relationships using historical data from 1990 to 2024, describing roadway supply, travel demand, and socioeconomic conditions across California counties. Regression analyses were conducted using Highway Performance Monitoring System (HPMS) data, populationestimates, employment statistics, and other supporting variables to examine relationships between VMT, SHS roadway capacity, population, and employment. Analyses included comparisons across counties, changes over 5-year, 10-year, and 20-year intervals, and separate evaluations of rural, partly rural, and urban county groupings. The findings indicate that relationships between roadway capacity and VMT in rural areas can be substantially variable and less consistent than expected. While some statistical relationships between SHS capacity and VMT were identified, the analyses did not consistently support strong or stable induced travel effects across rural counties. Population and employment changes were generally found to be important explanatory variables. However, data limitations associated with roadway supply measures and traffic estimation methods have affected analytical reliability. The results suggest caution in directly applying urban-based induced travel elasticity assumptions and tools to rural areas and point to the need for additional research with improved rural datasets to better understand the long-term impacts of rural capacity-enhancing projects. |
| Keywords: | Engineering, vehicle miles traveled, road capacity expansion, Induced travel demand, rural transportation, State Highway System |
| Date: | 2026–06–30 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt9604r0r7 |
| By: | Réka Juhász; Dávid Krisztián Nagy; Claudia Steinwender; Woan Foong Wong |
| Abstract: | Maritime transport remains the backbone of global trade, yet the port and shipping network that carries it has been transformed by containerization and related technological advances. Drawing on newly available granular data---digitized historical shipping records, georeferenced ship movements, and shipment-level routing information---we present five stylized facts on the structure and evolution of the maritime network. Global shipping activity is highly concentrated among a changing lineup of dominant top ports even as lower-ranked ports disperse, while state-owned Chinese port terminal operators increasingly account for these global volumes, boosting overall port operations while delivering efficiency gains mostly to Chinese vessels. We use these facts to organize a synthesis of a fast-growing literature: containerization reshaped which port cities could expand, reinforced hub-and-spoke concentration that yields large but localized welfare gains, embedded ports in multimodal networks that amplify the returns to infrastructure, and generated market power, congestion, and environmental costs. Together, this evidence shows how evolving maritime technologies simultaneously deepen global integration and heighten the economic and geopolitical importance of critical nodes in the transport network---and of who controls them. |
| JEL: | F13 F14 R41 R42 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35449 |
| By: | Lieberman, Joey; Hardman, Scott; Nordhoff, Sina |
| Abstract: | This research brief explores factors influencing consumers decision to buy an electric vehicle (EV). The brief also explores what areas of the EV ecosystem EV owners think need improvement. Results come from interviews conducted with EV owners across the US. Following the interviews transcripts were thematically coded to extract common themes. Overall, we find consumers decisions to purchase an EV are influenced by functional or economic factors, such as refueling cost or purchase price. Emotional factors in the form of environmentalism played a role, but less so than previous studies. Desired improvements to EVs were mostly related to charging infrastructure, including improvements to infrastructure availability, charging speed, reliability, and other issues. Improvements to driving range were also desired. |
| Keywords: | Social and Behavioral Sciences |
| Date: | 2026–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt5c67w666 |
| By: | Yang Gao; David Levinson (TransportLab, School of Civil Engineering, University of Sydney) |
| Abstract: | This paper constructs a theoretical model connecting day-to-day travel time reliability (TTR) and vehicle density, testing it on freeway stretches in Minneapolis - St. Paul and San Diego. We establish the presence of a counter-clockwise hysteresis loop between average vehicle density and experienced travel time standard deviation. We also observe that vehicle density heterogeneity exerts a more profound effect on TTR during moderate congestion. We find that a time-homogeneous Poisson process accurately characterizes the vehicle arrival process on segments of freeway stretches, both with and without on-ramps, during the morning peak period. The travel times for these segments align well with an exponential distribution. Through an analysis of the travel time correlations among different segments of the freeway stretch, we find that this correlation is higher during congestion offset periods, resulting in more severe travel time fluctuations due to increased density heterogeneity. Using the M/M/1 queueing model, we derive a model encapsulating the variance of experienced travel time, average vehicle density, and density heterogeneity for freeway stretches consisting of multiple segments. We use the birth-death process to model the relationship between average vehicle density and density heterogeneity. By integrating these two models, we derive a novel model that accurately approximates freeway stretch TTR based on average vehicle density and traffic flow. We apply our models to TTR changes on the two selected freeway stretches to validate across different time periods and select two subnetworks, each containing three additional freeway stretches, to validate across spatial dimensions. The results from these experiments corroborate the robustness and generality of our model across both temporal and spatial contexts. |
| Keywords: | Travel time reliability, Density heterogeneity, Queueing theory |
| JEL: | R40 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:nex:wpaper:paper-2026-19 |
| By: | Mohammad Amin Ashena; Adam Weiss; Jason Hawkins; Lina Kattan |
| 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. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.29756 |
| By: | Cherbonnier, Frédéric; Ivaldi, Marc; Muller-Vibes, Catherine; Van Der Straeten, Karine |
| Abstract: | This study estimates the impact of a carbon tax on welfare, considering modal shifts to less carbon-intensive transport, as well as its effects on environmental and fiscal externalities. We calibrate a modal competition model using logit demand functions for a specific long-distance connection in France and simulate the introduction of a Pigouvian tax. Our key findings are: First, a €190/tCO2 carbon tax is nearly welfare-neutral but significantly detrimental to consumer surplus; Second, rail price regulation has the side effect of reducing greenhouse gas emissions by subsidizing the cleanest transport mode; Third, the widespread adoption of electric vehicles enhances overall welfare without significantly harming consumer surplus. |
| JEL: | D43 L91 R40 Q51 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20515 |
| By: | Griffin, Greg Phillip (Oregon Dept. of Transportation); Roll, Josh F. |
| Abstract: | To address the rising increase in fatal and serious traffic injuries, the ODOT Traffic Safety Research Roadmap establishes a structured, five-year research agenda listing research concepts for funding through ODOT Research Unit’s annual funding cycle as well as other funding opportunities. The study identifies 51 priority traffic safety research needs, spanning the Safe Systems topics of safe people, safe vehicles, safe speeds, safe roads, and post-crash care. An implementation playbook suggests pathways of achieving the desired research needs to support transportation safety practice. |
| Date: | 2026–05–31 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:3wjd7_v1 |
| By: | Jason Hawkins; Omid Armantalab |
| Abstract: | Travel behavior and demand modeling seeks to understand the factors that motivate transportation decisions. At the same time, the field is increasingly adopting algorithmic and artificial intelligence (AI) tools that improve predictive accuracy, often at the cost of a grounding in hypothesis-based theory validation and behavioural explanation. In this discussion paper, we use goal pursuit theory (GPT) to illustrate why behavioral theory is a necessary complement to prediction in travel behavior research. Unlike random utility maximization (RUM) or close alternatives (e.g., random regret minimization (RRM)), GPT explicitly models how travelers (1) activate context-dependent goals (hedonic, gain, normative), (2) resolve conflicts between competing objectives, and (3) make sequential decisions across temporal scales. We demonstrate GPT's merits through three transport applications: activity scheduling (handling hierarchical goal structures), vehicle ownership (disentangling bundled mobility goals), and location choice (capturing latent goal interactions via matrix factorization). We provide actionable guidance for implementation, including: (a) hybrid choice model specifications linking goals to observable behaviors, (b) parallels to complementary behavioral theories from the transportation field, and (c) data requirements and comparative benchmarks against RUM/RRM models. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.29145 |
| By: | Mahdinia, Iman PhD; Griswold, Julia PhD; Erz, Tristan |
| Abstract: | The safe deployment of autonomous vehicles (AVs) depends on the ability of automated driving systems (ADS) to handle rare, complex, and safety-critical “edge cases.” This study develops a novel framework for identifying and analyzing such scenarios using the National Highway Traffic Safety Administration (NHTSA) ADS crash dataset. Two complementary approaches are applied. First, large language models (LLMs) are used to directly analyze crash narratives, identifying edge cases through high-risk keyword and phrase detection and anomaly-based rarity analysis. Second, LLMs are employed to extract structured variables from narrative fields, which are then analyzed using hierarchical clustering to systematically isolate unusual crash groups. Edge cases are characterized by a higher prevalence of unusual crash partner behaviors, non-motorist involvement, roadway anomalies, and disengagement of AV systems, highlighting their distinct and atypical nature. The findings underscore the importance of focusing AV evaluation on rare, high-risk scenarios that challenge ADS performance. The study advances AV safety research and can provide a foundation for refining testing protocols, safety standards, and regulatory frameworks to better capture the operational limits of AVs. |
| Keywords: | Engineering, Autonomous Vehicles, Advanced Vehicle Control Systems, Crash Data, Data Mining, Artificial Intelligence, Large Language Models, Crash Risk Forecasting |
| Date: | 2026–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsrrp:qt5fv1r72b |
| By: | Alireza Soltani; David M. Levinson; Mohsen Ramezani (TransportLab, School of Civil Engineering, University of Sydney) |
| Abstract: | This study presents a stochastic delay model that treats signal-free intersections as systems of servers where the probability of conflict between vehicles determines delay. Rather than relying on predetermined major-minor hierarchies, the model builds on interaction between any two approaching vehicles attempting to occupy the same conflict zone simultaneously. This conflict-probability framework applies across many traffic scenarios, from traditional unsignalized multi-modal intersections, merging sections, and roundabouts to signal-free intersections for autonomous vehicles (AVs). The model employs queuing theory formulations where service time depends on conflict probability and clearance time for conflict zones. The model extends to multi-movement intersections through dependent and independent conflict zone networks and accommodates time-varying demand through dynamic parameter adaptation. Theoretical analysis reveals that equal inflows maximize delays due to peak conflict probabilities. Validation using real-world trajectory datasets demonstrates improvements over Highway Capacity Manual and Austroads methods across diverse scenarios. Furthermore, the proposed delay model achieves mean absolute errors of 4.6 to 10.9 s using simulation of signal-free intersections for AVs under first-come first-served and communication-free distributed control algorithm protocols. |
| Keywords: | Signal-free junction, stochastic modeling, probability of conflict, autonomous vehicles, conflict networks, queue theory |
| JEL: | R40 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:nex:wpaper:paper-2026-18 |
| By: | Prema-chandra Athukorala; Archanun Kohpaiboon |
| Abstract: | This paper explores the growth trajectory and current state of Thailand’s automotive hub—often dubbed the "Detroit of the East"—and the adjustment challenges it faces in transitioning from the combustion engine era to the electric vehicle era. The findings suggest that Thailand’s success has been driven by a combination of structural changes in the global automotive industry, which opened opportunities for peripheral countries to join production networks, and the pragmatic, market-oriented policy approach of Thai authorities, which made the country an attractive location for international production. Despite this impressive performance during the combustion engine era, Thailand's automotive sector is now undergoing significant structural adjustments due to the rise of electric vehicles. Whether Thailand can continue to function as a global automobile hub under the emerging dominance of Chinese BEV manufacturers remains uncertain. Even under the optimistic scenario of vehicle assembly continues to expand in Thailand under Chinese dominance, the parts and components segment—which accounts for the bulk of employment in the industry—is likely to face a substantial contraction in the BEV era. This gloomy prospect underscores the need for a reorientation of industrial and labour market policies, including targeted support for supplier upgrading, workforce reskilling, and the development of complementary manufacturing and services capabilities to mitigate employment losses. |
| Keywords: | Thailand, automobiles, battery electrical vehicles (BEVs), combustion engine vehicles (ICEs), industrialisation, globalisation |
| JEL: | F13 F14 F23 L16 O19 O25 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:pas:papers:2026-03 |
| By: | David Schönholzer; Gregory Lane; Erin M. Kelley |
| Abstract: | Road traffic injuries are the leading cause of death among people aged 5–29. Where traffic laws are weakly enforced, it is unclear whether road safety interventions can change behavior. We run a randomized controlled trial among 203 Kenyan minibuses, testing whether an incentive scheme improves safety overall or merely shifts unsafe driving to unmonitored times. Drivers reduce speeding by 29 percent and harsh braking by 13 percent, improving a safety index by 0.096 standard deviations. Labor-supply and earnings effects are modest, with little displacement across times or places. Improvements fade quickly, suggesting lasting change requires sustained enforcement or stronger incentives. |
| JEL: | K42 O12 O18 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35394 |
| By: | Yu (Jasmine); Hao; Jinge Li |
| Abstract: | China's electric-vehicle (EV) sales share rose from about 1% in 2015 to roughly 45% in 2024. We evaluate this technology transition with an equilibrium differentiated-products model of the Chinese auto market, and quantify both its attribution and its welfare and reallocation consequences. Every yuan of 2024 EV subsidy delivered about 3.38 yuan of private surplus, but this surplus accrued asymmetrically. Per-capita consumer-surplus loss from subsidy removal is about five times larger in Tier 1 than in the Rest tier; about half of the aggregate welfare loss operates through indirect Wright's-law learning rather than the direct cash transfer; and EV-native firms (BYD, Tesla, New Forces) retain 16-27% of their 2024 EV business under subsidy removal while traditional state-owned manufacturers retain only 11%. A Shapley decomposition into six channels -- Quality, Variety, Battery, Subsidy, Residual, and Market -- attributes the historical 2015-2024 rise primarily to product-quality gains (+45.49%), choice-set expansion (+14.81%), and battery-cost decline (+8.20%). The Subsidy block is negative (-13.63%) because direct purchase subsidies were phased down, not because subsidies reduce demand: a separate counterfactual that removes the 2024 subsidy entirely lowers EV share by 23-33%. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2606.27924 |
| By: | Changle Song; David Levinson; Emily Moylan (TransportLab, School of Civil Engineering, University of Sydney) |
| Abstract: | Efficient dispatch policies are critical for ensuring equitable and effective emergency medical services (EMS). While vehicle specialisation offers tangible clinical benefits, integrating vehicle types into dispatch policy presents significant challenges. This study employs an agent-based simulation framework to evaluate the effects of alternative dispatch policies under varying proportions of specialised ambulances. Results indicate that allowing specialised vehicles to respond to a broader range of high-priority incidents enhances overall survival rates. However, the benefits of specialisation depend on how these vehicles are deployed within the system. When the supply of specialised vehicles exceeds demand, restrictive policies lead to longer response times and worsened outcomes for non-prioritised cases. In particular, restricting specialised vehicles to a narrow set of incidents can reduce overall system efficiency by limiting dispatch flexibility and increasing waiting times for other patients. Moderately flexible dispatch policies provide balance between outcome efficiency and response equity. These findings suggest that both the proportion of specialised vehicles and their dispatch eligibility should reflect the underlying mix of incidents in order to avoid over-constraining the system. Spatial analysis shows that survival and response disparities are more pronounced in peripheral areas. These findings underscore the need to align dispatch policy and fleet composition with incident typology and spatial demand, offering actionable insights for EMS policy and resource planning. |
| Keywords: | Dispatching policy, Emergency medical services, Agent-based simulation, Vehicle classes, Incident types, Priority |
| JEL: | R40 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:nex:wpaper:paper-2026-20 |
| By: | Jason Hawkins; Khandker Nurul Habib |
| Abstract: | Integrated urban models (IUM) typically rely on a measure of accessibility or travel time to form the link between the transportation and land use systems. Such integration does not fully capture the trade-offs made by households in how they spend their limited temporal and monetary budgets. We propose a microeconomic foundation for transportation and land use choice model integration based on the theory of home production. A utility function is developed that considers both household monetary expenditure and individual time use. We address several limitations in previous home production functions. First, the introduction of a parallel constrained multiple discrete-continuous extreme value (MDCEV) structure that allows for the inclusion of multi-person households in the model. Second, travel time is defined as the minimum time required to conduct an activity and deducted from the temporal budget. This assumption has several appealing features. It defines the minimum time to complete an activity as a measure of accessibility. An empirical application is provided for the Greater Toronto Area using a validated synthetic dataset. Empirical results demonstrate an economy of scale in time devoted to home production, analogous to scaling exhibit in market production. It was found that the mix of dwelling types (detached, apartment, etc.) has a significant influence on both time use and consumption. Finally, we provide several directions for future research to advance the practice of urban modelling and better capture the complex dynamics of household decision-making. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.05862 |
| By: | Santaro Sakata; Roberto Astolfi; Bram Edens; Suyeon Hwang |
| Abstract: | This working paper updates the existing OECD methodology for estimating Air Emission Accounts (AEAs) to enhance their comprehensiveness and international comparability. The new methodology draws primarily on data from national greenhouse gas emission inventories, a range of auxiliary data sources including Physical Energy Flow Accounts, as well as OECD experimental estimates of emissions from air and maritime transport. It improves the quality and granularity of estimates by economic activity (A*64 industry breakdown), expands the geographical coverage to all OECD countries, and extends the temporal scope of the estimates (1990 to year t-2). It also widens the emission coverage to include international air and maritime transport in line with emission boundaries of the System of Environmental Economic Accounting (SEEA), and incorporates the territory–residence adjustments to comply with the SEEA Central Framework (SEEA-CF). These improvements complement ongoing international methodological efforts to refine AEA estimates, such as those developed by the IMF and Eurostat, by drawing more extensively on country-specific data and achieving closer alignment with the SEEA-CF. |
| JEL: | C82 Q53 Q54 Q56 E01 |
| Date: | 2026–07–29 |
| URL: | https://d.repec.org/n?u=RePEc:oec:stdaaa:2026/03-en |
| By: | Davide Del Prete; Aminur Rahman; Edoardo Tolva |
| Abstract: | This paper examines how transport mode shapes the geography of exchange rate pass-through (ERPT) within Global Value Chains. Using transaction-level customs data from the Bangladeshi garment sector (2018–2024), we exploit the sharp depreciation of the Bangladeshi Taka in 2022 to compare maritime and air-based trade corridors through Chittagong seaport and Dhaka airport. We show that ERPT to exporter prices is incomplete on average and systematically lower in buyer–seller relationships that rely more intensively on air transport. This differential is concentrated in destinations and products where delivery speed is especially valuable, notably European fast-fashion markets. |
| Keywords: | global value chains, exchange rate pass-through, transport mode, Bangladesh |
| JEL: | D22 D43 E31 L14 L22 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12834 |
| By: | Nicolás Forteza (BANCO DE ESPAÑA); José M. Labeaga (UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA, SPAIN) |
| Abstract: | Low emission zones (LEZs) have emerged as a primary policy instrument to combat urban air pollution in Europe, yet rigorous evidence on their effectiveness and spatial spillovers remains limited. Using a high-resolution geospatial panel dataset covering 1km grid cells across 33 European countries from 2007 to 2022, we estimate that LEZ adoption reduces PM2.5 exposure by approximately 4% within designated zones. We find robust evidence of positive spillovers: pollution also declines in areas adjacent to LEZ boundaries. These average effects mask substantial heterogeneity: reductions are concentrated in larger, denser cities and in cities with medium-sized zones relative to total urban area, while the smallest cities and zones show no detectable effect. These findings suggest LEZs generate city-wide environmental benefits extending beyond formal boundaries, consistent with network effects and technology spillovers dominating displacement mechanisms. To contextualize these results, we estimate the pollution-density elasticity for European cities using instrumental variables based on historical settlement patterns, finding that a 1% increase in population density raises PM2.5 exposure by 6% (approximately half the magnitude documented for US cities). We interpret our findings through a spatial equilibrium model that formalizes how LEZs alter the pollution production function in monocentric cities. Our results indicate that moderate-stringency LEZs, as typically implemented across Europe, deliver meaningful aggregate pollution reductions of approximately 1.8% city-wide, with modal shift complementarities and fleet renewal mechanisms dominating traffic displacement effects. |
| Keywords: | low emission zones, air pollution, PM2.5, urban density |
| JEL: | I10 Q53 Q58 R11 R12 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2621 |