Shanghai, a bustling metropolis, relies heavily on trains and cars for daily commutes, with trains being the most popular mode of transport. Despite the extensive public transport network, traffic inefficiencies and high CO2 emissions remain significant challenges.

Average Commute Times

The average commute involves a total time of 46.46 minutes, with significant time spent driving and walking.
  • Bus - Bus commuters spend an average of 38.75 minutes on the bus, with additional time walking and waiting.
  • Car - Car users experience a driving time of 42.25 minutes, covering a distance of 27.11 km.
  • Train - Train commuters spend about 36.45 minutes on the train, with additional time for walking and waiting.
  • Walking - Walking commutes average 15.65 minutes, with some time allocated to waiting and short bike rides.
Traffic Breakdown
Train
36%
Car
23%
Walking
20%
Bicycle
8%
Bus
5%
Home
5%
Motorcycle
2%
Tram
1%
Seasonal Trends

Traffic congestion tends to increase during the summer months due to higher tourist activity. Winter sees a slight decrease in public transport usage as residents prefer personal vehicles.

Commuter Pain Points

Long wait times for buses and trains during peak hours are a common complaint. Traffic jams are frequent, especially during rush hours, leading to increased travel times.

Best Travel Times

Early mornings before 7 AM and late evenings after 8 PM are the best times to avoid heavy traffic. Midday travel between 11 AM and 2 PM is also relatively smooth.

Event Impacts

Major public events, such as the Shanghai International Film Festival, significantly increase traffic congestion. Sporting events at large venues often lead to temporary road closures and detours.

Sustainability Efforts

Shanghai is investing in electric buses and expanding its metro network to reduce reliance on cars. The city promotes cycling by enhancing bike-sharing programs and developing dedicated bike lanes.

Ride-Sharing Impact

Ride-sharing services have eased some congestion by reducing the number of personal vehicles on the road. However, they also contribute to traffic during peak hours as drivers seek passengers.

Traffic Rankings

Shanghai ranks 2nd on the Traffic rankings in China. The Traffic Index for China combines user-contributed data on commute times, traffic dissatisfaction, CO2 emissions, and traffic system inefficiencies in China, to provide insights into overall traffic conditions.

Worst to BestUpdated: Dec, 2024

Traffic Data

The following traffic data has been gathered from 88 user contributions.
Overall average travel
Distance
10.0 miles
Walking
9.2 mins
Waiting
3.4 mins
Driving Car
10.1 mins
Bus / Trolley
3.2 mins
Bicycle
2.1 mins
Motorcycle
0.4 mins
Train
15.4 mins
Tram
0.5 mins
Other
2.1 mins
Total:
46.5 mins
Average when primarily using Bus
Distance
7.3 miles
Walking
11.0 mins
Waiting
13.0 mins
Bus / Trolley
38.8 mins
Total:
62.8 mins
Average when primarily using Car
Distance
16.8 miles
Walking
1.6 mins
Driving Car
42.3 mins
Total:
43.8 mins
Average when primarily using Train
Distance
11.2 miles
Walking
12.9 mins
Waiting
5.5 mins
Bus / Trolley
2.8 mins
Train
36.5 mins
Tram
1.0 mins
Other
1.9 mins
Total:
60.5 mins
Average when primarily using Walking
Distance
2.7 miles
Walking
15.6 mins
Waiting
2.8 mins
Bus / Trolley
1.8 mins
Bicycle
0.6 mins
Motorcycle
0.0 mins
Train
6.6 mins
Total:
27.4 mins
Shanghai Traffic

"Key Takeaways"

Trains are the most used mode of transport, but inefficiencies in the system lead to long commute times.

High CO2 emissions suggest a need for sustainable transportation solutions.

Key Indexes

Emissions

Shanghai's CO2 emissions index is notably high at 3237.62, indicating a significant environmental impact.

Efforts to reduce emissions could focus on increasing the efficiency of public transport and promoting cleaner energy sources.

Time

The time index of 46.46 suggests that commuters spend a substantial amount of time traveling daily.

Reducing wait times and improving traffic flow could help decrease overall commute times.

Inefficiency

The inefficiency index stands at 224.46, highlighting room for improvement in traffic management.

Addressing bottlenecks and optimizing traffic signals could enhance efficiency.