Introduction
In early 2024, the project consultants, Kittelson & Associates, developed and released the project’s existing conditions technical analysis that includes information on biking and walking demand and activity levels in Palo Alto, a Bicycle Level of Traffic Stress analysis, a safety and collision analysis, and a barriers analysis, among other topics. Below is a summary of the analysis and the corresponding map exhibits.
Email transportation@cityofpaloalto.org with “BPTP Update” in the subject line with questions or comments about this information.
Bicycle Level of Traffic Stress (LTS)
Bicycle level of traffic stress (LTS) is a rating given to a road segment or crossing indicating the traffic stress it imposes on bicyclists. Levels of traffic stress range from 1 to 4 with LTS 1 indicating low stress facility and LTS 4 indicating a high stress facility. The segment analysis considers roadway functional classification, vehicle volume, posted or prevailing vehicle speeds, number of vehicle lanes, the presence of on-street parking, and vehicle parking and bicycle lane widths. The crossing analysis considers the right-turn lane configuration and length, bike lane approach, vehicle turning speeds, and the presence of a median refuge. The draft Bicycle LTS maps are included below.
As shown in the Bicycle LTS maps (Attachments A, B, and C), the most stressful segments for bicyclists are located on El Camino Real, Alma Street, Oregon Expressway, San Antonio Road, and Foothill Expressway. Many streets with existing bicycle facilities were classified as low-stress, LTS 1 or LTS 2. Approximately 68% of street miles in Palo Alto are LTS 1 or LTS 2. This map illustrates how low stress streets in Palo Alto are often interrupted by high stress roadways and intersections.
Exhibits
Major Barriers
The analysis of major barriers examines linear barriers and barriers near major transit stations that require people to take detours and increase the length of walking and biking trips. The draft barriers maps are included below.
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US 101: The lack of crossing opportunities across US 101 results in noticeably longer walking trips, including some paths that are more than four times longer than the straight line crossing path. Of the existing crossing locations, the walking and bicycling bridges provide the highest level of separation from vehicles, while the Embarcadero Road and San Antonio Road crossings include vehicle-oriented facilities such as channelized free highway on- and off-ramps. The most significant gap occurs between the two walking and bicycling bridges, limiting access to the Adobe Creek Loop Trail. Barriers Map - US 101 (Draft) [PDF](PDF, 1009KB)
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Oregon Expressway: The Oregon Expressway does not create significantly longer pedestrian crossing paths as crossings with curb ramps, crosswalks, and traffic signals are generally located every quarter mile. Barriers Map - Oregon Expressway (Draft) [PDF](PDF, 1MB)
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Barron Creek: While some paths across Barron Creek are longer than the straight long crossing distance, they are usually less than double that distance due to the availability of closely-spaced crossing facilities. Crossing opportunities are generally located every 1,100 feet north of Waverly Street, and every 300 feet south of Waverly Street and sidewalks are provided on streets crossing the creek. Barriers Map - Barron Creek (Draft) [PDF](PDF, 987KB)
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Matadero Creek: Lack of crossing opportunities of Matadero Creek result in increased travel distances of up to 1.75 times, especially to cross the canal west of Bryant Street. The presence of the rail line along the southern tip of the canal’s above-ground alignment further increases the out of distance travel in that area. Barriers Map - Matadero Creek (Draft) [PDF](PDF, 1005KB)
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Adobe Creek: The lack of crossing opportunities of Adobe Creek, especially to the south, results in out-of-distance travel of approximately two times the trip length. Opportunities to cross Adobe Creek include Louis Road, Middlefield Road, Charleston Road, Alma Street, and El Camino Real (all of which include sidewalks). There are also two walking- and bicycling-only connections: a walkway connecting the Miller Avenue cul-de-sac to Wilkie Way, and the Los Altos-Palo Alto Bike Path (connecting Los Altos Avenue to Arastradero Road). The greatest out of direction travel occurs in the area between the Los Altos-Palo Alto Bike Path and the Foothill Expressway, where the creek runs between the Alta Mesa Memorial Park and a residential neighborhood. Barriers Map - Adobe Creek (Draft) [PDF](PDF, 1MB)
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Rail: There is substantial variation in crossing opportunities along the length of the rail line. The longest distances are near Seale Avenue, Colorado Avenue, El Dorado Avenue, Loma Verde Avenue, and El Verano Avenue. There is an approximately 0.65-mile gap between the Churchill Avenue and California Avenue crossings with a midpoint at Seale Avenue. Peers Park is located between these two crossing locations on the west side of the railroad tracks, across the tracks from residential neighborhoods. The Churchill Avenue crossing is at grade. The California Avenue crossing is a grade-separated undercrossing that is not yet ADA compliant, and bicyclists must dismount to navigate the steep undercrossing if others are present in the tunnel. There is an approximately 1.3-mile gap between the California Avenue and Meadow Drive crossings (note, while the Oregon Expressway crosses the tracks, sidewalks are not provided). The Meadow Drive crossing is at grade. Barriers Map - Rail Corridor (Draft) [PDF](PDF, 1MB)
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Palo Alto Station, Palo Alto Transit Center, and El Camino Real/Embarcadero Road: Primary barriers include the presence of several channelized turn lanes, a number of intersections missing crosswalk markings, and there is a gap in the sidewalk network along Palo Alto Avenue east of El Camino Real.
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California Avenue Station, and El Camino Real/California Avenue: Primary barriers include missing crosswalk markings and presence of a channelized right-turn lane at the intersection of El Camino Real and Page Mill Road.
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San Antonio Station and El Camino Real/Charleston Road: The primary barrier in this area is a lack of sidewalks on a portion of San Antonio Road and on residential streets.
Barriers Map - Transit Station Areas (Draft) [PDF](PDF, 2MB)
Safety and Collisions
A high-level review of ten years of collision data was conducted to identify a general trend in the number and severity of pedestrian and bicycle collisions. The most recent five years of collision data was conducted to identify patterns or trends based on temporal characteristics, lighting conditions, location characteristics (intersection versus segment), primary collision factors, age, and gender. These collision profiles provide a better understanding of the common risks, and where and how efforts should be focused to most effectively make streets safer for people walking and biking.
Based on the ten most recent years (2012-2022) of collision data, there has been a general decrease in the total number of pedestrian and bicycle involved collisions.
Exhibit: Bicycle Collisions (2012-2022)
Exhibit: Pedestrian Collisions (2012-2022)
Throughout the five years (2018-2022) under more detailed review, a total of 104 pedestrian and 257 bicycle collisions were reported in the city of Palo Alto, with three collisions involving both pedestrians and bicyclists. Around 12%, or 12, of the pedestrian collisions resulted in a fatality (3 collisions) or severe injury (9 collisions). Around 5%, or 13, of the bicycle collisions resulted in a fatality (one collision) or severe injury (12 collisions). Collision maps are included below.
Pedestrian-involved collisions tended to be more severe during dark conditions. Around 29% (30 collisions) of the injury pedestrian collisions and almost half (6 collisions) of the fatal and severe injury pedestrian collisions occurred at night. Although the majority of nighttime pedestrian-involved collisions take place in areas with streetlights, the effectiveness of this lighting is inconsistent. Often, streetlights may not be bright enough or may be spaced too far apart. This issue particularly affects pedestrians and those on sidewalks, as streetlights are often designed primarily with vehicles in travel lanes in mind.
The most frequent type of bicycle collision that occurred in Palo Alto within the five year study period are broadside collisions, constituting 61% (156 collisions), followed by sideswipe collisions at 13% (34 collisions). Considering fatal and severe injury bicycle collisions, broadside collisions make up 54% (7 collisions), while head-on and hit object collisions comprise 15% (2 collisions) each. The fatal and severe injury bicyclist-involved collisions predominantly occurred in areas where streetlights were absent.
Exhibits
Activity and Demand
Replica (Big-Data provider) uses a comprehensive modeling technique that simulates the movements of residents, visitors, and commercial vehicles based on a synthetic population. This synthetic population is statistically representative of our community and constructed from a blend of mobile location data, consumer/resident data, built environment data, economic activity data and, when available, bike and pedestrian counts.
Replica uses cell phone telemetry data to determine the relative popularity of points of interest. However, it's important to note that this data isn't utilized to determine the mode of transportation for a trip. This is because the GPS-derived speed of a device lacks the precision necessary to differentiate between modes such as bus trips and biking trips. Instead, the determination of a trip’s mode is based on factors such as the proximity between the origin and destination, the availability of roadways suitable for bicycles and pedestrians, as well as household and commute characteristics. These variables collectively influence the mode choice.
Replica's methodology allows us to explore mobility patterns with a granularity previously unattainable, offering detailed insights into how, when, and why different population segments navigate our city. Such detailed modeling can uncover latent needs and opportunities for infrastructure improvements that might not be evident from traditional data sources alone.
The Spring 2023 data from Replica includes approximately 91,800 biking trips by 58,200 riders and 142,000 walking trips by 96,900 pedestrians originating within two miles of city limits. The dataset is a complete trip and population table for a typical weekday and typical weekend day for the selected season and region. Model inputs include American Community Survey 5-year estimates, TIGER/Line data, LEHD Origin-Destination Employment Statistics Data, and ACS Public Use Microdata Sample (PUMS), the Census Transportation Planning Products Program (CTPP) as well as data from the National Center for Education Statistics, US Department of Education, building data and proprietary parcel data and points of interest data.
- Biking Activity: Based on Replica data, the highest percentage of biking trips was associated with schools and colleges (17%), followed by shopping (11%) and work (8%) related trips. With only 7% of the population, Hispanics and Latinos represent 20% of the total bike trips. With about 15% of the population, people age 18-34 made almost 45% of the total bike trips. The highest percentage of trips in the morning occurs at 7 a.m., constituting around 11% of the overall bike trips. Over 59% of trips take place between 12 noon and 9 p.m., with the peak time observed at 3 p.m., representing 13% of the total bike trips. The average bike trip is 14.2 minutes, and the median travel time is 10 minutes. The average bike trip length is 2.5 miles, and 56% of trips are less than 2 miles in length, 23% are between 2 and 4 miles, and 20% are over 2 miles. The highest number of bicyclists travel to or from Stanford University.
- Walking Activity: Based on Replica data, the highest percentage of walking trips were associated with shopping (31%), work (9%), and restaurant (9%) related trips. With only 7% of the population, Hispanic and Latino represent 20% of the total walking trips. With about 15% of the population, people age 18-34 made almost 37% of the total walk trips. The peak time for pedestrian trips occurs between 3 and 5 p.m. Most walking trips are under 5 minutes with a mean of 11 minutes and median of 7 minutes. Most walking trips (56%) are under 0.5-mile, and 96% of trips are under 2 miles. The highest number of pedestrians travel to or from Stanford University with other walking hubs in downtown, Barron Park, and Adobe Meadow/Meadow Park.
E-bikes and Shared Micromobility
Electrification of the transport system has expanded in various ways with the development of electric bicycles (e-bikes) (which now out-sell electric cars in the USA) and e-scooters. The widespread use of internet-connected mobile phones has also allowed shared mobility to take off with bike, e-bike, and e-scooter sharing systems being implemented in cities around the world.
Electric Bicycles: The State of California Department of Motor Vehicles (DMV) defines e-bikes as “a bicycle equipped with fully operable pedals and an electric motor of less than 750 watts.” Within this definition, the DMV has established three classes of e-bikes.
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Class 1: A low speed pedal-assisted electric bicycle equipped with a motor which provides assistance only when the rider is pedaling and ceases to provide assistance when a speed of 20 mph is reached.
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Class 2: A low speed throttle-assisted electric bicycle equipped with a motor used exclusively to propel the bicycle and NOT capable of providing assistance when a speed of 20 mph is reached.
With e-bikes allowing people to travel further by bicycle, e-bikes can contribute to mode shifts and decongestion if they are replacing trips that would otherwise be made by personal automobile. Although research has found decongestion benefits to be marginal compared to the health benefits, these benefits are still relevant in the grand scheme of the transportation landscape. Studies have shown that e-bike riders travel further and cycle more often with one study from 2020 finding that after purchasing an e-bike, riders increased their total bicycle usage from 1.3 miles to 5.7 miles per day and that their share of all trips made by bike increased from 17 per cent to 49 percent. Although the benefits of e-bikes far outweigh the disbenefits, there are some challenges that must be addressed. E-bikes can allow users to travel at relatively high speeds which may present a safety risk to e-bike users and other active users (pedestrians, traditional cyclists) around them when there is a great speed differential, though the kinetic energy involved in a crash between an e-bike and pedestrian is significantly less than that involved in an automobile crash. While e-bikes are not drastically different than traditional bicycles, safely and effectively accommodating them in the transportation system requires careful thought. For example, to mitigate conflicts between modes, wider facilities should be implemented to ensure faster users can overtake slower ones and additional separation could be implemented to reduce the risk of crashes at conflict points. Design guidance developed for this BPTP Update will consider potential increases in e-bike usage.
Shared Micromobility: The United States Department of Transportation Federal Highway Administration (FHWA) defines micromobility as “any small, low-speed, human- or electric-powered transportation device, including bicycles, scooters, electric-assist bicycles, electric scooters (e-scooters), and other small, lightweight, wheeled conveyances”. Generally, micromobility vehicles (or devices) are expected to operate in the same road space as bicycles, using bike lanes and paths if available, otherwise sharing the roadway with motorists. While there is no California statewide law specifically permitting or prohibiting riding a bicycle on a sidewalk, the State DMV does not allow motorized scooters to be used on sidewalks and does not allow them to exceed 15 mph. E-scooter users under the age of 18 must wear a helmet and users must have a valid driver’s license.
Over the past decade, a variety of shared micromobility systems have emerged with the most common being shared e-scooters and e-bike share systems. While e-bikes and e-scooters are the most common form of micromobility, some niche forms are emerging including e-cargo bikes, mopeds, and neighborhood electric vehicles (NEVs), although these forms of mobility are yet to become widespread.
Advancements in technology have allowed many systems to now use a hybrid docked and dockless system based on geofencing. Municipalities and operators can now designate specific zones for parking shared micromobility vehicles, reducing the need for docking infrastructure while still allowing the municipality control over where vehicles can park.
The City of Palo Alto adopted a one-year bicycle and electric scooter sharing pilot program in March 2018 (CMR #8546) and developed permit guidelines for vendors to operate within the City of Palo Alto. The pilot program was extended by Council in 2019 (Resolution #9822) and subsequently in 2020 (Resolution #9882). The pilot program implementation was initially delayed due to staff resources and delayed further as a result of the COVID-19 pandemic. Staff recommended extending the pilot program from its expiration date of March 31, 2022 for an additional 18 months to test the concept of private bicycle and electric scooter sharing systems in Palo Alto. However, the extension has not been implemented and other shared micromobility partnerships have not been pursued since the 37-bike system run by Motivate was discontinued.
Bicycle Parking Inventory
Bicycle parking is an essential component of a complete bicycle network. To better understand the supply and demand for bicycle parking within the active downtown core of Palo Alto, a data collection effort was undertaken using the ESRI Survey123 application and tablets. The data collection was conducted on Thursday, December 14, 2023 from 10:00am to 4:00pm and the area included three parallel streets – University Avenue, Hamilton Avenue, Lytton Avenue – and cross streets between the Caltrain station and Middlefield Road. A total of 142 data points were collected. Each data point represents one bike parking location (e.g., a bike rack or bike corral). For each data point the following information was obtained:
- Location of bike parking (University Avenue, Parallel Street, or Cross Street)
- Latitude and longitude of each data point
- Total number of bike parking spaces
- Number of bike parking spaces per rack
- Number of occupied bike parking spaces
- Type of bike rack (Inverted U, Series Inverted U, Wave, Locker, Elevated or Other)
- The presence of a bike corral (Yes/No)
- Location of bike rack/corral (on the sidewalk or on the street)
- Condition of bike rack
- Classification of bike parking as short-term or long-term
- For short-term parking, proximity to the front entrance of the building it serves (within 50 feet)
- Whether the bike parking is covered (Yes/No)
- Security level of the bike parking, specifically if it's secured to the ground
- Presence of signage and/or wayfinding information at the parking location (optional)
- Additional notes on observations (optional)
- Photos for visual documentation
There are a total of 679 bike parking spaces in the survey area. University Avenue features 180 bike parking spaces at 61 bike parking locations, while Hamilton and Lytton Avenues combined offer 202 spaces at 43 locations, and the surrounding streets contribute an additional 297 spaces at 38 locations, including the Palo Alto Caltrain station. Approximately 90% of these spaces are located on the sidewalks and the remaining 10% are located on the street. There is a broad variety of bicycle rack types, with inverted U-racks (circular, rectangular) being predominant. Almost 9% of spaces are covered.
A higher utilization of bicycle parking was noted along University Avenue and near the Caltrain station. Spaces were generally available in the bike racks during the observation period (between 10 a.m. and 4 p.m. on December 14, 2023). People were observed to choose to lock bicycles to sign posts or trees, presumably desiring to park as close to their destination as possible. This was observed to occur even when space was available in a nearby rack.
Exhibit: Bike Parking Locations
Exhibit: Bike Parking Locations By Facility Type
Exhibit: Bike Parking Utilization
