Safety and Security Issues with Non-motorized Transportation:

An Examination of Potential Planning, Design and Technology Solutions

Stephen T. VaughnUniversity of Illinois at ChicagoIGERT PresentationApril 30, 2009

Over 60% of all personal trips are 5 miles or less in trip length with 40% of those trips 2 miles or less. These are considered reasonable bicycling distance. (2001 NHTS)

14% of all personal trips are a ½ mile or less, which is considered reasonable walking distance. (2001 NHTS)

Percentage of Daily Personal Trips

A total of 65.1% of work trips are within walking/bicycling distance

Work 18.9% < 1 mile 24.0% 1 to 3 miles 22.2% 3 to 6 miles

A total of 43.7% of non-work trips are within walking or bicycling distance

Non-work 8.8% < 1 mile 15.0% 1 to 3 miles 19.9% 3 to 6 miles

Daily travel by Walking and Bicycling

http://www.bts.gov/publications/transportation_statistics_annual_report/

Walking and Bicycling as a share of all modes

http://www.bts.gov/publications/transportation_statistics_annual_report/

Is a sedentary lifestyle preferred to a physically active one?

Survey results find that 80% of the American public would like to walk more for exercise.

78% would like to walk more for fun 63% would like to walk more to stores and to run errands 38% would like to walk to work more 79% consider presence of sidewalks and walkable communities

when deciding where to live

National Highway Traffic Safety Administration “National Survey of Bicyclist and Pedestrian Attitudes and Behavior”

So why isn’t there more use of non-motorized transportation?

Survey on bicycling as a mode of travel

National Highway Traffic Safety Administration “National Survey of Bicyclist and Pedestrian Attitudes and Behavior”

More reasons for sedentary lifestyles?

Reasons youth are not walking or bicycling to school:School is too far away (66%)*No safe route-traffic (17%)*Fear of abduction (16%)

*Neighborhood crime (6%)Lack of convenience (15%)

Children don’t want to walk (6%)

39% of the results deal with SAFETY concerns

Illinois Department of Transportation Accident variables and description of crash data

Chicago Police Department Incident data such as gender of victim and criminal, type of

crime, etc.

UTC Spatial Decision Support System Environmental factors such as housing and transit quality,

census data, transportation accessibility

Physical Environment Factors

Functionality Safety Aesthetic Destination

•Crossing aids•Crossings•Lighting•Verge width•Surveillance

•Cleanliness•Sights •Garden maintenance•Parks•Pollution•Trees•Architecture•Street Maintenance

•Direct route•Gradient•Intersection design•Intersection distance•Kerb type•Other access points•Path continuity•Path design•Path location•Path maintenance•Path surface•Path width•Street design•Street type•Street width•Traffic control devices•Traffic speed•Traffic volume•Type of path•Vehicle parking

•Local facilities•Parks•Public transport•Services•Shops•Vehicle parking facilities•Bike parking facilities

Reference:Pikora, Giles-Corti, Bull, Jamrozik, Donovan (2003) Developing a framework for assessment of the environmental determinants of walking and cycling. Social Science and Medicine. pp. 1693-1703.

Traveler Safety and Security Issues

Roadway Network Functionality Number of street lanes Width of lanes Roadway average daily traffic Availability of bike lanes/paths Roadway speed limit Presence of signage Traffic control devices Presence of on-street parking Condition of pavement (CRS) Curb type Presence of sidewalks and

pavement Number of access points

Personal Safety and Security Weather Special Events Crosswalks Presence of pedestrian signals Speed of travel Street lighting Crime Incidences* Accident Hotspot

Identification*

Traveler Safety and Security IssuesTraveler Safety and Security Issues

Non-motorized transportationchoice

Roadway NetworkFunctionality

Personal Safety and Security

Risk Exposure Model

Risk Exposure Model

width of roadway

# of street lanes

ADTaccess points

traffic volume

bike lanes

signage

weather

curb type

sidewalks

neighborhood crime

on-street parking

street lighting

accident hotspot

special events

bike path

traffic control device

pavement

speed limit

cross walks

road surface condition

Traveler Information Network

Roadway Network Functionality

Personal Safety and Security

Information HUB(risk exposure model)

Traveler Preference

Transit StationsWebsite

PDA’s Cell Phones Bike Stations

(Real time info) (Real time info)(Static/Historical info) (Static/Historical info)

What is Historical (Static) and Real time information?

Historical (Static) Information Number of street lanes Width of lanes Roadway average daily traffic Availability of bike lanes/paths Roadway speed limit Presence of signage Traffic control devices Street lighting Presence of on-street parking Condition of pavement (CRS) Curb type Presence of sidewalks and pavement Number of access points Crime Incidences* Accident Hotspot Identification*

Real time information Weather Special Events Transit arrival/departure time Congestion instances Speed of travel Estimated time of arrival

What is traveler preference?

Aesthetic

Risk Tolerance

Destination

Safest Route

Traveler Prompt

Information HUB

What is Risk Tolerance?

Risk averse: traveler would prefer the safest route with less risk

exposure as possible and possibly the longest travel time.

Risk neutral: traveler is indifferent to route of travel

Risk seeking: traveler prefers the fastest route to their destination

Why are perceptions of crime important?

“fear and concern about crime are related to perceptions of uncivil behavior” (Lewis and Maxfield, 1980)

Crime Identification (Neighborhood Perception)

Crime type: manslaughterhomicidecriminal sexual assaultinvoluntary aggravated assaultaggravated batterysimple assaultsimple batteryoffense against family (kidnapping child abductions/stranger)

Accident Hotspot Identification

Accident Hotspot Identification

What is a hotspot?At certain sites, the level of risk will be higher than the general level of risk in surrounding areas. Crashes tend to be concentrated at these relatively high-risk locations. Locations that have an abnormally high number of crashes are called hotspots or black spots.

Accident Classifications

Type A: Incapacitating injury which prevents the injured person from walking, cycling or driving (broken limbs, skull, chest injuries)

Type B: Injuries that are visible to observers at the scene (lump on head, bruises, lacerations)

Type C: Injuries that are reported and claimed but not evident (momentary unconsciousness)

Fatalities

Property Damage Only

Example of Accident Hotspot Identification

Accidents in a roadway network

What is “Clustering”?

Assumes that road accidents are spatially dependent when occurring in similar areas or because of shared common causes

Implies a common causal factor

What mapping technologies are currently available for non-motorized transportation

routing and how good are they?

Current routing programs (walking) (tele-atlas 2009)

Current routing programs (by car) (tele-atlas 2009)

Current routing programs (Navteq 2009)

Other data needs…

Sidewalks and pavement information Construction updates (is this possible??) Crime data

Possible outcomes of research

Safest route based on risk tolerance Social networking Inclement Weather re-routing Special events re-routing Increased trip linking availability

Questions

Thank you….