150+ Research Topics on Driverless Cars

Driverless or autonomous cars are transforming future mobility. They present fascinating research problems involving sensing, localization, controls, machine learning and system integration. This article provides a compilation of 150+ research topic ideas around autonomous vehicles to help students, engineers and researchers identify interesting problems to pursue.

The list covers various aspects like perception systems, planning and control algorithms, vehicular communications, HMI, V2X systems, security, validation testing, and societal impacts. Peruse this list to gain inspiration for your autonomous vehicle research projects, papers and products.

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Perception Systems

• Multi-modal sensor fusion for robust environment perception under varying conditions
• Deep learning for complex driving scene understanding using camera and LiDAR data
• Adversarial attacks on AV perception systems and countermeasures
• Synthetic data generation for sensor simulation and DNN training
• GNN-based moving object segmentation using point cloud sequences
• Real-time context-aware semantic segmentation using surround view cameras
• AR navigation HUDs overlaying sensor detected objects and trajectories
• Dimensionality reduction techniques for processing resource-heavy sensor data
• Free space detection using sparse 3D vision and deep learning
• Onboard real-time cameras, LiDAR calibration and synchronization

Localization and Mapping

• Robust localization using multi-sensor fusion even in GNSS denied environments
• Efficient representations for scalable high definition maps and change detection
• Distributed crowdsourced HD maps creation using fleets as roving sensors
• Coherent 6D localization fusing observations from LiDARS, radars and cameras
• Robust data association and tracking in presence of occlusions and missing detections
• Semantic maps enrichment with object properties like dynamics and interactivity
• Autonomous map updates and corrections using sequential Bayesian inference
• Lifelong map learning and adapting existing maps to new domains
• Distributed localization and collaborative pose graph SLAM for vehicle swarms
• Localization resilience under adversarial attacks on map data or GNSS spoofing

Planning, Control and Actuation

• Distributed motion planning for AV fleets accounting for connectedness constraints
• Safe trajectory planning under uncertain agent behaviors using game theory
• Model predictive control for comfortable ride experience and actuation
• Reinforcement learning for end-to-end vehicle control from cameras and map inputs
• Closed loop dynamic scene-level planning and control
• Minimal risk maneuver planning and control under system failures
• Agile maneuvers planning for racing or off-road driving
• Active suspension and adaptive cruise control for passenger comfort
• Lightweight verification of neural network based autonomous vehicle controllers
• Redundant by-wire actuation architectures for fault tolerance

Vehicle Communications and V2X

• Millimeter wave spectrum usage for high bandwidth V2V communications
• Blockchain and distributed ledger mechanisms for secure V2X data exchange
• Collaborative environment perception using vehicle fleets as a swarm sensor
• Edge/fog computing architectures for low latency V2X message processing
• Congestion control mechanisms tailored for dense C-V2X deployments
• Analysis of LTE-V2X and 5G NR C-V2X tradeoffs in performance metrics
• Incentivization mechanisms for data sharing among autonomous vehicles
• Cooperative driving using vehicle platoon orchestration over V2V
• Smart traffic signal control using vehicular data and reinforcement learning
• Vehicular social networks for transparent in-transit content sharing

Autonomous Driving Policies

• Analysis of regulatory implications on autonomous vehicle validation, certification and audit
• Quantified assurance case argumentation for AV safety
• Standards around controllability, explainability and transparency of autonomous systems
• Review of existing AD testing regulations – adequacy and limitations
• Policy requirements for minimal risk condition and fallback readiness
• Role of simulation vs road testing in AV evaluation regulations
• Cybersecurity standards for design, development and operation of AVs
• Guidelines for capturing edge case encounters and failures during AV testing
• Policy insights from AV trial deployments in guided operational domains
• Regulation of ADAS to AV feature escalation in production vehicles

Human-Machine Interaction

• Augmented reality dashboards for informing passengers about AV state and intent
• Interior and exterior HMI for communicating right of way intent with human stakeholders
• Speech interaction systems for naturalistic conversations with AV passengers
• Simulation engines for generating VR datasets for physically realistic AV user studies
• Personalized comfort and experience profiling in autonomous mobility services
• Inclusive solutions for accessibility of self-driving services
• Mitigation of motion sickness in AVs through HMI and cabin experience design
• Trajectory visualization interfaces for intuitive monitoring of AV status
• Naturalistic studies on remote monitoring and teleoperation UX for AVs
• Biometric sensors and personalization algorithms for comfort-optimized autonomy

Validation, Testing and Simulations

• Photorealistic simulations for validating autonomous driving systems
• Efficient search techniques like MCTS for scenario space coverage
• Test matrix optimization methods combining driving scenarios
• Metrics and criteria for measurable AV testing in simulation environments
• Automated test case generation using scene and traffic modeling
• Adaptive stress testing using co-evolutionary algorithms
• Falsification methods using temporal logic specifications
• Statistical approaches for safety validation based on required failure rates
• Hybrid testbeds integrating physical and simulated aspects
• Mining interesting test scenarios from existing driving datasets

Impacts of Autonomous Vehicles

• Traffic flow modeling and dynamics with mixed vehicle autonomy
• Benefits analysis of autonomous mobility for elderly and people with disabilities
• Agent-based simulations for assessing shared AV fleet adoption
• Impact of electrification and automation on automotive industry landscape
• Autonomous fleet operations for ride hailing and goods transport
• Business models and economic viability of various MaaS offerings using AVs
• Traffic safety outcomes from AV introduction accounting for risk compensation
• Urban planning implications of automated mobility - curb use, parking etc.
• Greenhouse gas emission trajectory predictions under AV adoption scenarios
• Second order effects like induced demand, land use change from AVs

Miscellaneous Topics

• Fail safe architectures for autonomous driving systems
• Anomaly detection in AV controllers using LSTM networks
• Digital twin models for testing and validation of AD systems
• Autonomous racing algorithms optimized for agility and traction
• Autonomous construction vehicles for hazardous environment operations
• Secure over-the-air software updates in AVs using blockchain
• Driver persona and behavior modeling for enhanced HMI and controls
• Audio-based perception for AV using microphones and sound sensing
• Application of meta learning methods like MAML for AV adaptation
• Explainable planning and control for transparent autonomous driving

Conclusion

This compilation summarizes over 150 research topic ideas spanning the breadth of autonomous vehicle technologies, systems and impacts. The growing complexity of fully autonomous systems requires sustained research. Aspiring researchers can utilize these topics to identify potential problems aligned with their interests. The future promises exciting innovation in intelligent vehicles that can transform transportation.

FAQs

Q1. How do I select a good research topic on autonomous vehicles?

Tips for choosing a good research topic:

• Select an area of personal interest within AV technologies
• Topic should have practical applications and solve real problems
• Identify gaps in existing literature and scope for tangible contributions
• Ensure access to required data, tools and infrastructure for research
• Align with advisor expertise to receive good guidance
• Explore leading conferences and journals for state-of-the-art insights
• Avoid reinventing the wheel, expand on prior work
• Pick focused problems, avoid scope creep
• Discuss ideas with professors and domain experts

Q2. What are good sources to find AV research topics?

Some fruitful sources for AV research topic ideas:

• Recent advances and trends in autonomous driving
• Technical papers in AV conferences like IV, IROS, ITSC, ICRA
• Government and industry R&D priority areas in AV technologies
• Competitions like DARPA Grand Challenge
• Automotive magazines and industry events
• Company initiatives and product roadmaps
• Research topics from top universities and labs
• Industry expert talks and technical forums
• User needs and pain points around autonomous mobility

Q3. How should an AV research proposal be structured?

A good AV research proposal should include:

• Motivation and importance of the problem
• Background - foundational concepts and literature review
• Objective and specific questions to address
• Proposed methods and techniques
• Expected outcomes and contributions
• Preliminary work done
• Quantitative results achieved
• Resources required for project execution
• Timelines for milestones
• Future work for further investigation
• References

Follow advisor guidance on specifics of formatting and presentation.