ABSTRACT
Traffic congestion not only causes significant losses to city economy, but also seriously affects the happiness index of urban residents. Different from the specific and detailed research perspective of traditional traffic congestion, this paper attempts to study urban traffic congestion from a relatively macro perspective. The real-time traffic data, building survey data, Gaode POI data, bus stops data, urban road, population data, DEM data are collected. The spatial heterogeneity law of urban traffic congestion and its influencing factors are analyzed by GIS. The analysis found that:(1) Traffic congestion in Chongqing is "heavy in the north and light in the south", and the business district has a relatively obvious impact on traffic congestion. (2) Population density and commercial POI have a great impact on traffic congestion. For every 0.1 percentage point increase in the proportion of commercial POI, the average traffic jam time increased by 0.09 hours. (3) The number of bus stops can significantly alleviate traffic congestion. For every additional bus station, the traffic congestion time in this area can be reduced by 0.05 hours. (4) Increasing road density cannot effectively solve the problem of traffic congestion, which once again proves the correctness of "down Law". (5) Within the community, increasing the diversity of land use cannot effectively relieve traffic congestion.
- Downs A. The Law of Peak-Hour Expressway Congestion[J]. Traffic, 1962, 33(3):347--362.Google Scholar
- Lee K, Anatolii P, Justin D, et al. Estimation of travel time from taxi GPS data[C]. 2017 IEEE Symposium Series on Computational Intelligence, Honolulu, 2017,1--6.Google Scholar
- David T, Robert W, Poole J. Traffic congestion in America's cities: How much and at what cost[J]. Highway Capacity, 2006.Google Scholar
- Chandler C, Hoel L A. Effects of light rail transit on traffic congestion[J]. Light Rail Transit Grade Crossings, 2004.Google Scholar
- Seik F T. An effective demand management instrument in urban transport: The area licensing scheme in Singapore[J]. Cities, 1997,14(3):155--164.Google ScholarCross Ref
- Fosgerau M, Palma A D. The dynamics of urban traffic congestion and the price of parking[J]. Journal of Public Economics, 2013, 105(4):106--115.Google ScholarCross Ref
- Chen L W, Chang CC, Cooperative traffic control with green wave coordination for multiple intersection based on the internet of vehicles[J].IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2017, 47(7):1321--1335.Google Scholar
- Xu X, Dou W, Zhang X, et al. A traffic hotline discovery method over cloud of things using big taxi GPS data[J]. Software Practice & Experience, 2017, 47(3):361--377.Google ScholarDigital Library
- Logi F, Ritchie S G. Development and evaluation of a knowledge-based system for traffic congestion management and control[J]. Transportation Research, 2001, 9(6):433--459.Google Scholar
- Chou L D, Li D C, Chao H W. Mitigate traffic congestion with virtual data sink based information dissemination in intelligent transportation system[C]. Third International Conference on Ubiquitous and Future Networks, IEEE, 2011:37--42.Google Scholar
- Endo Y, Toda H, Nishida K, et al. Deep feature extraction from trajectories for transportation mode estimation[J]. Springer International Publishing, 2016:54--66.Google ScholarDigital Library
- Zhang M, Yi C. Can transit oriented developments reduce Austin's traffic congestion[J]. Railroad Commuter Service, 2006.Google Scholar
- Kuznetsov AV, Avramenko AA. A macroscopic model of traffic jams in axons[J]. Mathematical Biosciences, 2009, 218(2):142--152.Google ScholarCross Ref
Index Terms
- Analysis of Spatial Heterogeneity and Influencing Factors of Urban Traffic Congestion Based on GIS
Recommendations
GIS-Based Spatial Distributions and Evolvement Analysis of Urban Affordable Housing: A Case Study
ESIAT '09: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02Foci of this paper are spatial distribution and evolvement of middle or low income families living in urban affordable housing. Base on Geographic Information System (GIS) this paper presents (1) a methodology using Kernel Density Estimation to study ...
A Review on Recent Traffic Congestion Relief Approaches
ICAIET '14: Proceedings of the 2014 4th International Conference on Artificial Intelligence with Applications in Engineering and TechnologyTraffic congestion is a global and crucial problem due to increase in demand and limited network transportation structure. Complex traffic structure, imbalanced traffic flow, and uncertain event like road accident are among of the identified factors ...
Study on Spatial Pattern of Rural Settlements in Wuling Mountainous Area Based on GIS
Rural settlement is a living space of various people in rural area and it is the carrier of rural population spatial distribution. Taking Pengshui County of Wuling Mountainous Area in China as an empirical research object, the spatial pattern of rural ...
Comments