CARLA Cooperative V2X Intersection

A virtual intersection manager that replaces traffic lights with a V2X-inspired, reservation-based protocol for autonomous vehicles, built and benchmarked in the CARLA simulator.

PythonCARLA 0.9.16V2X
−51%
Avg. Crossing Time
+105%
Throughput
−51%
Queue Clearance Time
CARLA 0.9.16
Simulator

Architecture

Intersection Manager: the central decision-maker. It maintains a First-Come-First-Served queue, infers path conflicts from each vehicle's declared intent (straight/left/right), and grants PERMIT messages only when it's safe to proceed.

Vehicle Agent: built on CARLA's BasicAgent, overridden to report state continuously, obey PERMIT/stop decisions, and otherwise drive normally once cleared.

A lightweight mailbox communication layer stands in for real V2X hardware — vehicles publish REQUEST/INTENT/STATE messages, the manager responds with PERMIT/CROSSING/CLEARED — modeling the interaction pattern without needing a real DSRC/C-V2X stack.

Algorithms

Vehicle detection uses a simple geometric approach-radius check rather than lane-level reasoning, keeping registration O(n) and making the system map-agnostic.

Permission assignment is FCFS conflict-aware: vehicles are ordered by arrival time, and each is granted passage only if its declared intent doesn't conflict with currently active vehicles — an O(n log n) sort per tick, versus the much heavier fine-grained space-time reservation grid used by systems like AIM (UT Austin).

An axis-aligned conflict box around the intersection tracks each vehicle's active/cleared lifecycle — entering the box marks a vehicle active, exiting and clearing 75% of the approach radius marks it cleared and releases its reservation.

Results

Benchmarked head-to-head against a fixed-cycle traffic signal: 51% lower average crossing time (2.56s → 1.25s per vehicle), 105% higher throughput (23.4 → 48 cars/min), and 51% faster total clearance time for a 16-vehicle queue (41s → 20s).

Notably, even running vehicles at half speed, the V2X manager still cleared the queue faster than the signal-based baseline at full speed — coordination mattered more than raw vehicle speed.

Limitations

Single-intersection only, fully cooperative traffic assumed (no human drivers, pedestrians, or cyclists), and communication is modeled as instantaneous and lossless — none of the physical-layer realism of real V2X hardware.

Group project at USC with 3 teammates (Shahid Shaikh, Hitansh Surani, Harshal Dave).