What Types of Roads Are Most Commonly Flagged as High-Risk?

Discover which road types pose the greatest safety risks and why. We break down key risk factors, from design flaws to speed and pedestrian exposure.

City planners and transportation engineers increasingly rely on traffic safety data to pinpoint collision hotspots – the road segments most prone to crashes and severe injuries. These high-risk roads often exhibit certain telltale characteristics, and focusing on them can yield outsized safety improvements. In fact, studies show that a relatively small percentage of roadways typically account for a large share of serious collisions. Identifying such high-risk locations is a core aspect of urban road risk analysis and Vision Zero strategies aimed at eliminating traffic fatalities.

Modern analytics platforms enable cities to integrate data from crash reports, speed sensors, and roadway inventories into predictive road safety tools. For example, combining historical crash records, traffic volume, speeding patterns, and roadway characteristics can pinpoint high-risk hotspots across an entire road network. Using these insights, officials can proactively detect dangerous road segments before the next collision occurs and implement targeted interventions.

The following sections explore what criteria lead to a road being flagged as high-risk, the types of roads that frequently emerge in safety data, and how cities can act on these insights to reduce collision hotspots.

What Makes a Road High-Risk?

A road is typically flagged as “high-risk” when data indicates an elevated likelihood of crashes or severe outcomes relative to similar roads. Key factors that contribute to a road’s risk profile include:

Crash History:

Locations with a record of frequent crashes – especially serious or fatal crashes – are obvious red flags. Agencies often start by looking at road segments or intersections with unusually high crash rates. A long-term crash history remains the state-of-practice first filter for identifying high-risk sites.

Speeding Patterns:

Roads where vehicles consistently exceed the speed limit tend to see more severe crashes. High travel speeds both increase collision probability (due to longer stopping distances) and dramatically worsen injury severity. For instance, speed is a factor in roughly 27% of fatal collisions, and even a 5 mph reduction in impact speed can significantly improve a pedestrian’s chance of survival. Predictive road safety tools often monitor speeding data to flag corridors with chronic speeding issues as high-risk.

Roadway Geometry & Design:

Certain road designs inherently carry higher crash risk. Sharp horizontal curves, steep grades, inadequate banking (superelevation), or insufficient sight distance can all contribute to collisions. Narrow lane or shoulder widths and lack of a median or guardrails also elevate risk by leaving little room for error. 

Studies have found that limited clear zones (e.g. no shoulder), the presence of roadside obstacles (trees, poles, ditches), poor signage or markings, and other geometric factors correlate with higher crash rates. 

In other words, a winding two-lane road with blind curves and no shoulder will be riskier than a straight, well-marked road of the same traffic volume.

Land Use & Surroundings:

The context of a road – what’s around it – affects its risk level. Roads that pass through dense commercial or entertainment districts may see more crashes due to frequent turning movements, driveways, and distracted behavior. Corridors near schools, parks, or transit hubs have high pedestrian exposure, raising the risk of vehicle-pedestrian collisions if proper crosswalks and calming measures aren’t in place. Conversely, a highway through a rural open area might have fewer conflict points (intersections or crossings) but encourage higher speeds. Planners consider how land use (residential, rural, school zone, etc.) contributes to crash patterns on a road segment.

Traffic Volume & Mix:

All else being equal, a road carrying extremely high volumes of vehicles each day will experience more crashes simply due to exposure. High traffic volumes increase the interactions between road users, thus increasing opportunities for collisions. Planners normalize for exposure (e.g. crashes per million vehicle-miles traveled) to distinguish volume-related crash frequency from other risk factors. 

Additionally, the composition of traffic matters – roads that mix heavy trucks with pedestrians and cyclists, or those with complex vehicle movements (many turning vehicles, merging lanes, etc.), can be higher-risk. A robust crash risk index typically combines exposure metrics (traffic volume or VMT) with crash history and road features to fairly compare risk across roads.

Vulnerable Road User Exposure:

High-risk designations also account for the presence of pedestrians, bicyclists, and other vulnerable users. A street may not have many car-on-car crashes, but if it’s a busy pedestrian corridor with inadequate sidewalks or crossings, it is high-risk for walkers. Locations with frequent pedestrian injuries (e.g. crosswalks at multilane roads, or bus stops on high-speed arterials) will be flagged for safety improvements. Planners assess metrics like pedestrian volume, past pedestrian/bike crash history, and the availability of safe infrastructure (crossing signals, bike lanes) to gauge this risk. Roads lacking such protections in areas of high foot traffic are strong candidates for intervention.

In summary, transportation agencies evaluate a combination of crash frequency, crash severity, and the underlying risk factors (speed, volume, geometry, etc.) that make future crashes more likely. 

As one study noted, a comprehensive risk score for a road segment often incorporates three dimensions: the road’s physical characteristics, its crash history, and the traffic exposure on that road. If a road checks multiple high-risk boxes – for example, a history of severe crashes and a design prone to speeding and heavy pedestrian use – it will rise to the top of the priority list for safety action.

Common Road Types Flagged in Safety Data

While any roadway can experience crashes, analysis of traffic safety data reveals that certain road types and locations are disproportionately represented in serious collisions. Below are some of the most common categories of roads that are frequently flagged as high-risk:

Urban Arterial Roads (Multilane Thoroughfares):

Major arterial roads in cities – typically large, multilane streets that carry high volumes of traffic through urban areas – consistently show up as high-risk in crash data. These roads often combine relatively high speed limits with frequent intersections, numerous driveways, and mixed traffic (cars, trucks, buses, pedestrians). 

According to national statistics, the most dangerous roadways are urban arterial roads, which include avenues and city highways that see heavy traffic. Urban arterials also tend to have the highest traffic volumes of any road type, which partly explains why they account for a high share of accidents. Unfortunately, many arterial corridors were designed to move vehicles efficiently but not necessarily to accommodate safe pedestrian crossings or bicycle travel – a recipe for collisions. 

Research shows that a far greater proportion of pedestrian fatalities occur on arterials (often at night) compared to local streets, reflecting the risks of higher speeds and wider roads in an urban context. City safety dashboards often highlight busy multi-lane arterials (especially those with speed limits above 35–40 mph) as collision hotspots in need of redesign or traffic calming.

Rural High-Speed Roads (Two-Lane Highways & Local Roads):

Outside urban centers, the high-risk roads that stand out are often two-lane rural highways, county roads, and local routes lacking safety features. The fatality rates on rural roads are significantly higher than on comparable urban roads. 

For example, the fatal crash rate on rural collectors and local roads is more than 1.5 times higher than that on urban collector/local roads. Several factors contribute to this disparity. The physical characteristics of many rural roads are suboptimal for safety – they may have no shoulders or limited clear zones, meaning there’s little room for error if a driver drifts out of the lane. 

Roadside hazards like trees or ditches are often closer to the pavement’s edge. Roadway departure crashes (vehicles running off the road) are common on these roads, in part due to the lack of recovery space. Behavioral factors in rural areas also elevate risk: drivers can travel at higher speeds due to low congestion, seat belt use is statistically lower, and incidences of impaired driving tend to be higher in rural communities. Combined with typically longer emergency response times in remote areas, the consequences of crashes on rural roads are often severe. 

Thus, state highway safety plans routinely flag rural two-lane corridors for safety upgrades (improved shoulders, rumble strips, better lighting, etc.) under programs like the High Risk Rural Roads initiative.

Dangerous Intersections and Junctions:

Intersections – where streams of traffic cross and turn – are a focal point for crash analysis. Conflict points at intersections create numerous opportunities for collisions, from rear-ends to T-bone (right-angle) crashes. It’s no surprise that a large fraction of urban crashes occur at intersections. Each year roughly one-quarter of U.S. traffic fatalities and about one-half of all traffic injuries are attributed to intersections. 

In fact, more than 50% of the combined total of fatal and injury crashes happen at or near intersection areas. Certain intersection configurations tend to be repeatedly flagged as high-risk: multi-lane signalized crossroads in busy urban corridors, high-speed rural intersections with only stop-sign control, and complex junctions or interchanges with confusing designs. Factors like limited sight lines (e.g. due to an obstructed view of oncoming traffic), lack of dedicated turn lanes or signals, and irregular intersection geometry can all increase crash likelihood. 

Data-driven safety studies often highlight a city’s “Top 10” high-crash intersections, which are then targeted for improvements such as adding turn arrows, converting to roundabouts, or enhancing lighting and signage. Because intersections concentrate so many injury crashes, making intersection safety a priority (through design and operational changes) can yield major reductions in citywide crash totals.

Pedestrian and Bicycle Crash Hotspots:

Lastly, roads or areas with high pedestrian and cyclist activity commonly rise to the top of high-risk rankings, especially in urban environments. These aren’t a separate functional class of road per se, but rather segments (often on arterials or collectors) that see frequent conflicts between vehicles and non-motorized users. 

Examples include: streets in downtown retail districts, roads around schools and universities, corridors with popular nightlife or sporting venues, and any location with heavy foot traffic but insufficient crossing infrastructure. 

Safety data might reveal, for instance, a corridor that has experienced multiple pedestrian injuries in crosswalks, or a stretch where bicyclists often crash when mixing with fast traffic. Those segments would be flagged for intervention. Nationally, pedestrian fatalities have been rising in recent years, with a majority occurring on busy urban roads (especially at night). When planners see clusters of pedestrian or bike crashes in the data, they classify that roadway as high-risk for vulnerable users. Countermeasures could then include lowering speed limits, installing better crosswalks (with refuges or signals), adding protected bike lanes, or increasing lighting. 

In sum, corridors that mix high vehicle speeds with significant pedestrian exposure (and lack adequate protections) are routinely identified as high-risk roads in need of safety enhancements.

Conclusion

At Urban SDK, we believe the path to safer streets begins with understanding where the risks truly are. By identifying road segments with poor design, high speeds, and vulnerable user exposure, cities can take focused, data-informed actions that save lives.

Our platform helps planners and public agencies detect these high-risk corridors early by combining crash history, traffic volume, speed data, and roadway context into clear, actionable insights. Rather than waiting for another accident, we enable proactive safety planning—turning high-risk roads into safer, smarter corridors for everyone.

As communities work toward Vision Zero, we’re here to provide the real-time analytics and predictive tools that help public leaders act with confidence. Because the future of traffic safety isn’t reactive—it’s informed, targeted, and powered by data. And we’re proud to help lead that future.