Transportation Research Part C Submission Guide

Source: TR-C journal page, accessed May 27, 2026.

ScienceDirect's current Guide for Authors frames TR-C around emerging technologies because of their implications for transportation systems, not because the technology is novel in isolation. The journal's recent editorial direction emphasizes:

• Connected and autonomous vehicles (CAVs)

• AI/ML methods for traffic prediction, control, and optimization

• Shared mobility (ride-sharing, micromobility, MaaS)

• Electric and alternative-fuel vehicles

• IoT and sensor-based traffic systems

• Blockchain and decentralized transportation systems

• Vehicle-to-everything (V2X) technologies

Before submitting to Transportation Research Part C, a Transportation Research Part C manuscript fit check identifies whether the package meets the editorial bar before you commit to the submission.

This guide tells you what TR-C editors look for; the review tells you whether your paper passes the transportation-technology fit bar before upload. Paid Manusights reviews include a 60-day money-back guarantee; submitted manuscripts are not used for model training.

Three operational signals govern editorial assessment:

1. Technology-driven contribution. TR-C publishes work whose primary contribution is technology-applied or technology-driven. Pure mathematical methodology fits TR-B; pure policy fits TR-A.

2. Methodological rigor in emerging-tech methods. AI/ML methods, sensor-based systems, and CAV methods all require rigorous evaluation, baseline comparison, and reproducibility documentation.

3. Open-science and benchmarking credibility. Manuscripts using large-scale datasets, AI/ML, simulation, or sensor systems need a reproducibility and transferability story, not only a result table.

Recent issues span CAV trajectory optimization, deep-learning-based traffic prediction, ride-sharing platform optimization, electric-vehicle charging scheduling, blockchain in transportation, and IoT-based traffic monitoring. For specific recent papers and DOIs, see the TR-C journal page on ScienceDirect. The DOI prefix is 10.1016/j.trc.* with paper-specific identifiers.

For initial submission via Elsevier's Editorial Manager:

1. Manuscript following the current Guide for Authors

1. Title page, authors, affiliations

1. Abstract within standard length

1. Cover letter explaining technology-driven contribution and TR-C fit

1. Suggested reviewers as needed

1. Conflict-of-interest disclosure

1. Data and code availability statement

A Transportation Research Part C submission readiness check before upload can flag whether the contribution is technology-driven (vs methodological), whether word count is compliant, and whether scope fits TR-C vs sister TR-A through TR-F journals or IEEE T-ITS.

• Editorial review: 2-4 weeks

• First peer-review round: 8-12 weeks

• Total to first decision: 4-6 months

Across transportation-technology manuscripts targeting TR-C, three patterns generate the most consistent desk-screen risk.

Technology demo without transportation-system consequence

Across emerging-transportation manuscripts targeting Transportation Research Part C, the first recurring risk is a technically strong AI, control, sensing, CAV, V2X, shared-mobility, or optimization paper whose transportation-system consequence is too thin. ScienceDirect's current scope says TR-C is interested in technologies through their implications for planning, design, operation, control, maintenance, rehabilitation, monitoring, efficiency, safety, reliability, resource consumption, and the environment. That means the manuscript has to prove a transportation outcome, not only a technology capability.

The repair is to make the transportation system the object of the paper. The abstract should name the network, service, mode, demand setting, operational decision, and system metric changed by the method. The methods section should explain data provenance, simulator or field setting, benchmark baselines, calibration, transferability limits, and reproducibility.

Figures should show effects on travel time, reliability, safety surrogate, capacity, energy, emissions, equity, service quality, or operational resilience rather than only model loss or algorithm speed. The supplementary material should hold extended ablations, not the only evidence that the model works outside a toy case.

If the methods contribution can stand without the transportation setting, TR-B, Transportation Science, IEEE Transactions on Intelligent Transportation Systems, INFORMS Journal on Computing, or Expert Systems with Applications may be a more natural route.

Check whether your TR-C transportation-system consequence is visible enough →

TR family misrouting

For manuscripts targeting TR-C, the second recurring risk is choosing Part C because the work sounds modern, even when the paper's actual center belongs elsewhere in the Transportation Research family. A pure methodological paper with a strong proof, decomposition, equilibrium result, or optimization theory may be closer to TR-B. A logistics or freight-routing paper may belong at TR-E. A transport-emissions or environmental-impact paper may belong at TR-D.

A policy, practice, or planning paper may belong at TR-A. A behavior and safety-psychology paper may belong at TR-F. TR-C needs emerging technology plus transportation-system implications.

The repair is to write the routing case directly into the cover letter, introduction, and figures. The cover letter should explain why the contribution is not only a transportation method, not only an environmental analysis, and not only a logistics model. The introduction should name the technology class and the transportation-system decision it changes.

The methods should show why the technology setting matters to the model design or evaluation. The discussion should compare the paper against recent TR-C work and adjacent TR-B, TR-D, TR-E, IEEE T-ITS, Transportation Science, and Accident Analysis and Prevention papers.

If the same contribution would be equally convincing with a generic network, generic demand data, or generic simulation benchmark, editors may read the TR-C framing as retrofitted.

Check whether your TR-C cover letter makes the right family-routing case →

Open-science benchmarking gap

Across TR-C-targeted manuscripts, the third recurring risk is an impressive technology result without enough benchmark transparency. ScienceDirect's scope gives special emphasis to open-science initiatives, large-scale datasets, transferability, and benchmarking. That makes the data and code package part of the editorial argument, not a back-office compliance item. A manuscript can have strong neural-network, reinforcement-learning, control, or simulation results and still feel weak if the paper does not show how another transportation researcher could test the claim in a comparable setting.

The repair is to move benchmarking evidence into the main manuscript. The abstract should state the dataset, system context, and benchmark class. The methods should name the public or proprietary data source, cleaning rules, feature construction, simulation assumptions, calibration, hyperparameters, baseline models, and statistical comparison.

Figures should compare against simple operational baselines and recent TR-C or IEEE T-ITS benchmarks, not only against variants of the proposed model. The data availability statement should specify what can be shared through Mendeley Data, Zenodo, IEEE DataPort, institutional repositories, or a code repository, and what cannot be shared because of operator agreements or privacy.

If the paper's main contribution is a reusable algorithm with limited transport-system interpretation, Transportation Science, TR-B, IEEE T-ITS, or an AI venue may be stronger.

Check whether your TR-C data and benchmarking package is credible enough →

Check whether your TR-C manuscript is submission-ready →

TR-C manuscripts move through a four-stage editorial timeline. The editorial triage pattern at Elsevier transportation-emerging-technology journals favors submissions where the cover letter names a failure pattern in current transportation-technology practice that the manuscript addresses. Co-Editors-in-Chief routinely reject methodologically-novel-but-technology-agnostic submissions and consistently screen for cover letters that demonstrate awareness of the journal's recent editorial culture around emerging-technology-with-real-system-deployment integration.

Day 0 to 5: Editorial Manager intake and technical check

The platform performs automated checks (source-file format, single-column Word layout, highlights, declarations, AI-use disclosure). Editorial staff verify the cover letter and the TR-family-fit.

Day 5 to 28: Co-Editor-in-Chief or Subject Editor desk-screen

A Subject Editor (matched to connected and autonomous vehicles, AI/ML for transportation, smart mobility and shared mobility, traffic and demand management with new sensing, on-demand transport and ride-sharing, transportation IoT and V2X, or pedestrian/soft-mode emerging tech) reviews scope fit and the emerging-technology contribution. Pure mathematical optimization submissions are offered transfer to TR-B.

Week 4 to 12: External peer review

Manuscripts that pass desk-screen go to 2-3 reviewers selected for both the emerging-technology subfield and any computational methods used.

Week 12 to 24: Decision and revision rounds

First decisions arrive at the 8-12 week median, typically as major or minor revision. Revision cycles add 6-12 weeks each. Authors may file a formal appeal per Elsevier's Appeal Policy (one appeal per submission, decision final).

• Is Transportation Research Part C a good journal?

• Accident Analysis and Prevention Submission Guide for safety manuscripts where the core contribution is accident analysis, injury prevention, or countermeasure interpretation rather than emerging transportation technology.

• Transportation Research Part B Submission Guide

• Transportation Science Submission Guide

• IEEE T-ITS Submission Guide

• Analytic Methods in Accident Research Under Review status

Last verified: April 2026 against TR-C editorial pages.