Impact of Spatiotemporal Constraints on Active Travel

doi:10.12141/j.issn.1000-565X.230228

Abstract

Abstract:

As a self-driven travel mode, active travel or active mobility (AT or AM) plays a crucial role in alleviating urban traffic pressure and improving the temporal and spatial irrationality of urban traffic because of its small road occupation area, high mobility and good sustainability. The paper firstly studied the definition and connotation of active mobility. Secondly, starting from the spatiotemporal conditions affecting active mobility, it splited time and space into four types of constraints, namely, departure time, travel time, travel distance and built environment from the perspective of point and line, and expounded the characteristics of different types of spatiotemporal conditions in turn. It also analyzed the potential connection between active mobility and spatiotemporal constraints, and analyzed constraints influence on active mobility with single constraints and multiple spatiotemporal combinations as the entry point. Through summarization, it is found that the influence of spatiotemporal constraints on active mobility is more complicated than that in traditional cognition, and it is mainly a non-linear relationship and some of indexes have corresponding theoretical threshold. Finally, it put forward the shortcomings of the current theoretical research and the future research direction, which will provide a reference for the subsequent research. The purpose of this paper is to summarize the role of spatiotemporal constraints on active mobility, to show the specific change rule of movement travel under the role of different spatiotemporal constraints, aiming at changing the intrinsic thinking of travelers, improving the sharing rate of movement travel, and optimizing the travel structure of urban transportation.

Key words: urban traffic, spatiotemporal constraint, active mobility, spatiotemporal combination

CLC Number:

U491

YANG Yazao, WENG Tangzheng. Impact of Spatiotemporal Constraints on Active Travel[J]. Journal of South China University of Technology(Natural Science Edition), 2024, 52(2): 113-123.

Figures/Tables 9

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理论	模型	备选方式	城市	调查方法	文献
效用理论	二项 Logit模型	私家车、公共交通	武汉	RP调查、实地访谈	［22］
	交叉巢式 Logit模型	私家车、公共交通、自行车、步行	北京	RP调查	［23］
	离散-连续模型	私家车、公共交通、自行车、步行、其他交通	多伦多	抽样调查、旅行日记	［24］
前景理论	分段函数	私家车	台中	电话访谈	［20］
	动态流量分配模型	私家车（燃油、电动）、公共交通		实地实验	［25］
	混合 Logit模型	私家车、地铁、公交车	上海	实地访谈、 SP调查	［26］
效用理论 + 前景理论	自建模型	私家车、地铁、公交车	北京	仿真实验	［21］
效用理论 + 前景理论	基于前景理论构建的模型	私家车、公共交通	西安	仿真实验	［27］

国家/城市	备选方式	区间距离划分	文献
中国/北京	私家车、公共交通、自行车、步行	短距离：<5 km	［19］
中国/北京	私家车、公交车、地铁、共享/私人单车、步行	短距离：<5 km 中长距离：5~9 km	［35］
印度/特里凡特朗	私家车、公交车、出租车、电动三轮车、摩托车	短距离：0~5 km 中距离：5~10 km 长距离：11~20 km	［33］
瑞士/苏黎世	私家车、公共交通、（电动）自行车、步行、电动滑板车	短距离：<3 km	［36］
中国/西安	私家车、公交车、轨道交通、步行、非机动车	短距离：<8 km 中距离：8~15 km 长距离：>15 km	［37］
中国/太原	私家车、公交车、电动自行车、共享单车	短距离：<2 km 中距离：2~5 km 长距离：>5 km	［38］

约束类型	时间约束	空间约束	出行目的	调查方法	文献
能力	行程时间、活动时间	目的地、吸引力	购物	SP调查	［52］
能力	出发时间、活动时间	出行距离	通勤	实地访谈、旅行日记	［54］
耦合	出发时间、活动时间	出行距离	接送孩子	RP调查	［55］
耦合	出发时间	出行距离	接送孩子	RP调查	［56］
权利	出行时间、活动时间	出行距离、站点可达性	就诊	实地访谈、 SP调查	［53］

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