Curve Speed Warning
CTCAV-043Curve Speed Warning uses Vehicle-to-Everything (V2X) communications to notify connected vehicles approaching a curve about the recommended speed for that curve. This enables the vehicle to take additional warning actions if its current speed exceeds the suggested limit. With timely alerts from the infrastructure, this application aims to improve the safety of the transportation system for both motorized and non-motorized users (e.g., reducing potential crashes and fatalities).
Caltrans Centers:
RSU
OBU
Deployment Specification
v1.0 DraftCurve Speed Warning uses V2X communications to notify connected vehicles approaching a curve about the recommended speed for that curve. This enables the vehicle to take additional warning actions if its current speed exceeds the suggested limit. With timely alerts from the infrastructure, this application aims to improve the safety of the transportation system for both motorized and non-motorized users (e.g., reducing potential crashes and fatalities).
This application aims to improve safety for both motorized and non-motorized road users. It also aims to enhance transportation system efficiency by reducing delays caused by crashes, as well as fuel consumption and emissions. Additionally, it supports effective system management and operations, thereby boosting the resilience and reliability of the transportation network.
Safety
- Number of crashes, injuries, and fatalities for a selected time period, such as a month or a year.
- Number of detected speed violations per day, week, or month.
Mobility
- Flow rates, speeds (e.g., average, 90th/95th percentile, and variance), delays, travel times (e.g., average, 90th/95th percentile, and variance), energy/fuel consumption
- Changes in the above measures
Caltrans Implementation Options
Curve Speed Warning is not a latency-critical application, since warning messages can be sent to vehicles as they approach a curve. For regular road curves, a lightweight implementation that leverages network communications (e.g., through cellular providers like AT&T) is recommended. For critical road curves at high risk of incidents or with poor or no cellular coverage, direct communication with installed RSUs is the better option.
| Option | Type of Road Curves | Type of Communications |
|---|---|---|
| Option A | Regular | Network |
| Option B | Critical — high incident risk or poor/no cellular coverage | Direct & Network |
Physical architecture for the deployment option of network communications for regular road curves. Click the diagram to enlarge.
| Data Flow | Content | Standard |
|---|---|---|
| (1) Environmental and Speed Data | Environmental data can include current road conditions (e.g., surface and subsurface temperatures, moisture, icing, treatment status) and surface weather conditions (e.g., air temperature, wind speed, precipitation, visibility). Speed-related data can include measured speeds, displayed warning messages, and violation records. | Various Formats |
| (2) Third-Party Data | Real-time or near-real-time traffic incident alerts, traffic flow data, and road closures. | Vendor Specific |
| (3A) BSM Messages | Information that includes vehicle location, heading, speed, acceleration, brake status, etc. | SAE J2735 |
| (3B) Aggregated CV Data | Aggregated BSM messages in CSV files. | SAE J2735 |
| (4) Collected Traffic and Environmental Data | Data collected from various sources, including but not limited to environmental sensor data, traffic data from roadside sensors, CV data from CV application providers, and incident and traffic data from third-party applications. | Various Formats |
| (5A & 5B) Curve Speed Warning Messages | Traveler Information Messages (TIMs) or Road Safety Messages (RSMs) with information such as road curve geometry, location and extent of reduced-speed zones, posted speed limits, and their applicability (e.g., time of day, day of week, seasonality, and relevant vehicle types). | SAE J2735 for TIM, SAE J2945/4 for RSM |
Implementation Considerations
Network Communications vs. Direct Communications
Direct communications (PC5) are recommended in ARC-IT 9.3 as the deployment option for Curve Speed Warning (CSW) because of their low latency and high reliability, and this approach is also planned for the CV pilot in Caltrans District 12. However, installing RSUs is difficult to scale due to high installation and maintenance costs. For regular road curves with good cellular coverage, network communications (Uu) are more suitable, given the considerations below.
Typically 10–20 ms; can be < 10 ms under ideal conditions
Very high — designed for safety applications
300–1,000 meters, depending on power and environmental conditions
30–100+ ms for 4G, 10–20 ms for 5G, < 10 ms with MEC
Varies with network load and operator
Unlimited — depends on cellular coverage
The information in Curve Speed Warning messages (curve geometry, reduced-speed zones, posted speed limits, and their applicability) is for notification purposes and does not require drivers to take immediate action to avoid collisions. It also tolerates latency significantly higher than direct or network communications.
When network communications are selected for deployment, a longer warning zone ahead of the road curve can be configured during the geofencing step to compensate for potentially degraded performance due to cellular network instability. This also gives drivers enough time to prepare before entering the reduced-speed zones.
However, for critical road curves that pose a high risk of traffic accidents or have poor or no cellular coverage, direct communications become a more appropriate deployment solution.
Mobility and Safety Impacts
Vehicles often exceed the speed limit, even when driving through curves. The posted speed limits in the Curve Speed Warning messages may be lower than the original speed limit during extreme weather conditions or when incidents are ahead.
Having more vehicles comply with the posted speed limits will enhance safety at the road curve. However, mobility is expected to degrade, as slower vehicle speeds cause longer delays — the lower the posted speed limit, the longer the expected delay. Posted speed limits therefore need to be chosen carefully to balance safety improvements against mobility degradation.
CV Penetration Rates and Traffic Demand
When connected vehicles comply with posted speed limits, other vehicles behind them either reduce their speeds accordingly or change lanes to travel faster. The higher the penetration rate of connected vehicles, the greater the share of vehicles that slow down to comply. This also indicates that a 100% penetration rate of CVs is not necessary to ensure that all vehicles comply with posted speed limits.
Another factor that affects compliance is traffic demand. When demand is high at a road curve, a low penetration rate of CVs leads to a large percentage of vehicles complying, since it is not easy to switch lanes to gain faster speeds. When demand is low, it is easier for vehicles to switch lanes, so a higher CV penetration rate is needed to maintain a high compliance rate.
Simulation results from Caltrans Task 4081 ("Guidance on Roadside Unit Placement for Future Deployment of Connected and Automated Vehicles") showed that there is an "optimal" penetration rate of connected vehicles that can lower the average curve speed while keeping the increase in delay "acceptable." The optimal rate is closely tied to traffic demand rather than to the number of lanes or speed limits at curves. For more details, contact Caltrans DRISI for the final report on Task 4081.
| Traffic Demand | Optimal Rate |
|---|---|
| 100% of road capacity | 10% |
| 90% of capacity | 15% |
| 80% of capacity | 20% |
| 70% of capacity | 25% |
| 60% of capacity | 30% |
Advanced Traffic Detection Systems
For critical road curves, it is possible to install advanced traffic detection systems, such as AI-powered video or LiDAR detection systems, to further enhance safety at the curve. These systems can track vehicle trajectories in real time, identify safety hazards, and trigger the warning system to send out warning messages to alert approaching vehicles.
Specifications for Data Standards
For system interoperability, it is essential not only to standardize data flows among different system components but also to specify data attributes within the data standards.
For data flows with established data standards, it is crucial to specify which attributes are required, which are optional, and which are extended or added to meet the application's needs.
For vendor-specific data flows, it is essential to establish new data standards that all entities can agree to.
Testing & Performance Evaluation
Device / Component Level
For each device or component, test and verify: (i) whether the required data standards are correctly applied; (ii) whether data inputs can be read properly; (iii) whether it can perform the necessary functions; and (iv) whether it can produce outputs in the correct format with accurate information.
System Level
At the system level, end-to-end testing verifies that: (i) messages or data files are transmitted accurately between components or devices; (ii) all components and devices support the application — identifying current traffic and environmental conditions at the curve using data from various sources, determining posted speed limits, generating curve speed warning messages, and sending those messages to upstream connected vehicles.
Microsimulation (Pre-Deployment)
PATH has developed a V2X microsimulation platform capable of thoroughly evaluating the curve speed warning application across test networks with different speed limits, warning triggers (always broadcasting vs. detection of excessive speeds), CV penetration rates, communications settings (range, latency, packet loss) for direct and geofenced network communications, traffic demand levels, and driver reactions to the warning messages.
Before-and-After Analysis (Post-Deployment)
Once deployed, data collected from detectors, advanced sensors, connected vehicles, and third-party applications can support before-and-after analysis. The number of detected speed violations and reductions in crashes, injuries, and fatalities measure safety improvements, while section-based flow and speed data, delays, energy consumption, and travel times serve as mobility performance measures.